From 9c0fb2ac08e14b870c2a7276ce11c90a54fd74d3 Mon Sep 17 00:00:00 2001
From: "fern-api[bot]" <115122769+fern-api[bot]@users.noreply.github.com>
Date: Mon, 16 Mar 2026 11:09:09 +0000
Subject: [PATCH 1/5] SDK regeneration

---
 .fern/metadata.json                           |   15 +
 .github/workflows/ci.yml                      |   81 +-
 README.md                                     |  113 +-
 poetry.lock                                   |  143 +-
 pyproject.toml                                |    9 +-
 reference.md                                  | 2991 ++++-------------
 src/newscatcher/__init__.py                   |  487 +--
 src/newscatcher/aggregation/__init__.py       |   46 +-
 src/newscatcher/aggregation/client.py         |  751 ++---
 src/newscatcher/aggregation/raw_client.py     |  689 ++--
 src/newscatcher/aggregation/types/__init__.py |   45 +-
 ...e.py => aggregation_count_get_response.py} |    2 +-
 ....py => aggregation_count_post_response.py} |    2 +-
 ...on_get_request_published_date_precision.py |    7 -
 .../types/aggregation_get_request_sort_by.py  |    5 -
 src/newscatcher/authors/__init__.py           |   43 +-
 src/newscatcher/authors/client.py             |  633 ++--
 src/newscatcher/authors/raw_client.py         |  573 +---
 src/newscatcher/authors/types/__init__.py     |   45 +-
 ...rs_get_request_published_date_precision.py |    5 -
 .../types/authors_get_request_sort_by.py      |    5 -
 src/newscatcher/base_client.py                |  194 +-
 src/newscatcher/breaking_news/__init__.py     |    3 -
 src/newscatcher/breaking_news/client.py       |  394 +--
 src/newscatcher/breaking_news/raw_client.py   |  381 +--
 .../breaking_news/types/__init__.py           |    7 -
 .../breaking_news_get_request_sort_by.py      |    5 -
 src/newscatcher/core/__init__.py              |  113 +-
 src/newscatcher/core/client_wrapper.py        |   29 +-
 src/newscatcher/core/datetime_utils.py        |   42 +
 src/newscatcher/core/force_multipart.py       |    6 +-
 src/newscatcher/core/http_client.py           |  489 ++-
 src/newscatcher/core/http_response.py         |    8 +-
 src/newscatcher/core/http_sse/__init__.py     |   42 +
 src/newscatcher/core/http_sse/_api.py         |  112 +
 src/newscatcher/core/http_sse/_decoders.py    |   61 +
 .../http_sse/_exceptions.py}                  |    6 +-
 src/newscatcher/core/http_sse/_models.py      |   17 +
 src/newscatcher/core/jsonable_encoder.py      |    8 +
 src/newscatcher/core/logging.py               |  107 +
 src/newscatcher/core/parse_error.py           |   36 +
 src/newscatcher/core/pydantic_utilities.py    |  411 ++-
 src/newscatcher/errors/__init__.py            |   49 +-
 src/newscatcher/latest_headlines/__init__.py  |   37 +
 .../client.py                                 |  711 ++--
 .../raw_client.py                             |  623 +---
 .../latest_headlines/types/__init__.py        |   38 +
 .../types/latest_headlines_get_response.py    |    0
 .../types/latest_headlines_post_response.py   |    0
 src/newscatcher/latestheadlines/__init__.py   |    7 -
 .../latestheadlines/types/__init__.py         |    9 -
 ...adlines_get_request_clustering_variable.py |    5 -
 src/newscatcher/search/__init__.py            |   47 +-
 src/newscatcher/search/client.py              |  909 ++---
 src/newscatcher/search/raw_client.py          |  821 ++---
 src/newscatcher/search/types/__init__.py      |   49 +-
 .../search_get_request_clustering_variable.py |    5 -
 .../search_get_request_news_domain_type.py    |    7 -
 ...ch_get_request_published_date_precision.py |    5 -
 .../types/search_get_request_sort_by.py       |    5 -
 .../__init__.py                               |    0
 .../{search_link => search_by_link}/client.py |  112 +-
 .../raw_client.py                             |   72 +-
 src/newscatcher/searchsimilar/__init__.py     |   17 -
 src/newscatcher/searchsimilar/client.py       | 1360 --------
 src/newscatcher/searchsimilar/raw_client.py   | 1684 ----------
 .../searchsimilar/types/__init__.py           |   15 -
 ...ar_get_request_published_date_precision.py |    7 -
 .../search_similar_get_request_sort_by.py     |    5 -
 .../types/search_similar_get_response.py      |    8 -
 .../types/search_similar_post_response.py     |    8 -
 src/newscatcher/sources/__init__.py           |    3 -
 src/newscatcher/sources/client.py             |  157 +-
 src/newscatcher/sources/raw_client.py         |  143 +-
 src/newscatcher/sources/types/__init__.py     |    7 -
 .../sources_get_request_news_domain_type.py   |    7 -
 src/newscatcher/subscription/raw_client.py    |   18 +
 src/newscatcher/types/__init__.py             |  359 +-
 .../types/additional_source_info.py           |   18 +-
 .../types/aggregation_count_response_dto.py   |    4 +-
 ...gation_count_response_dto_aggregations.py} |    2 +-
 ...lar_document.py => all_links_data_item.py} |   21 +-
 .../types/{authors.py => all_links_text.py}   |    2 +-
 src/newscatcher/types/article_entity.py       |   18 +-
 ...urnalists.py => article_entity_authors.py} |    2 +-
 .../types/article_entity_journalists.py       |    5 +
 .../types/{articles.py => articles_dto.py}    |    2 +-
 .../types/breaking_news_article_entity.py     |   27 +-
 .../breaking_news_article_entity_authors.py   |    5 +
 ...reaking_news_article_entity_journalists.py |    5 +
 .../types/failed_authors_response_dto.py      |    2 +-
 .../failed_search_similar_response_dto.py     |   30 -
 .../types/include_similar_documents.py        |    3 -
 src/newscatcher/types/nlp_data_entity.py      |  117 +-
 src/newscatcher/types/not_theme.py            |    4 +-
 .../types/published_date_precision.py         |    4 +-
 src/newscatcher/types/search_response_dto.py  |    4 +-
 .../types/search_similar_response_dto.py      |   35 -
 .../types/similar_article_entity.py           |   30 -
 .../types/similar_documents_number.py         |    3 -
 src/newscatcher/types/sources_response_dto.py |    2 +-
 src/newscatcher/types/theme.py                |    4 +-
 src/newscatcher/types/user_input_dto.py       |    2 +-
 tests/utils/test_http_client.py               |  249 +-
 tests/utils/test_query_encoding.py            |    1 -
 105 files changed, 5726 insertions(+), 11345 deletions(-)
 create mode 100644 .fern/metadata.json
 rename src/newscatcher/aggregation/types/{aggregation_get_response.py => aggregation_count_get_response.py} (70%)
 rename src/newscatcher/aggregation/types/{aggregation_post_response.py => aggregation_count_post_response.py} (70%)
 delete mode 100644 src/newscatcher/aggregation/types/aggregation_get_request_published_date_precision.py
 delete mode 100644 src/newscatcher/aggregation/types/aggregation_get_request_sort_by.py
 delete mode 100644 src/newscatcher/authors/types/authors_get_request_published_date_precision.py
 delete mode 100644 src/newscatcher/authors/types/authors_get_request_sort_by.py
 delete mode 100644 src/newscatcher/breaking_news/types/__init__.py
 delete mode 100644 src/newscatcher/breaking_news/types/breaking_news_get_request_sort_by.py
 create mode 100644 src/newscatcher/core/http_sse/__init__.py
 create mode 100644 src/newscatcher/core/http_sse/_api.py
 create mode 100644 src/newscatcher/core/http_sse/_decoders.py
 rename src/newscatcher/{types/similar_documents_fields.py => core/http_sse/_exceptions.py} (51%)
 create mode 100644 src/newscatcher/core/http_sse/_models.py
 create mode 100644 src/newscatcher/core/logging.py
 create mode 100644 src/newscatcher/core/parse_error.py
 create mode 100644 src/newscatcher/latest_headlines/__init__.py
 rename src/newscatcher/{latestheadlines => latest_headlines}/client.py (56%)
 rename src/newscatcher/{latestheadlines => latest_headlines}/raw_client.py (67%)
 create mode 100644 src/newscatcher/latest_headlines/types/__init__.py
 rename src/newscatcher/{latestheadlines => latest_headlines}/types/latest_headlines_get_response.py (100%)
 rename src/newscatcher/{latestheadlines => latest_headlines}/types/latest_headlines_post_response.py (100%)
 delete mode 100644 src/newscatcher/latestheadlines/__init__.py
 delete mode 100644 src/newscatcher/latestheadlines/types/__init__.py
 delete mode 100644 src/newscatcher/latestheadlines/types/latest_headlines_get_request_clustering_variable.py
 delete mode 100644 src/newscatcher/search/types/search_get_request_clustering_variable.py
 delete mode 100644 src/newscatcher/search/types/search_get_request_news_domain_type.py
 delete mode 100644 src/newscatcher/search/types/search_get_request_published_date_precision.py
 delete mode 100644 src/newscatcher/search/types/search_get_request_sort_by.py
 rename src/newscatcher/{search_link => search_by_link}/__init__.py (100%)
 rename src/newscatcher/{search_link => search_by_link}/client.py (73%)
 rename src/newscatcher/{search_link => search_by_link}/raw_client.py (92%)
 delete mode 100644 src/newscatcher/searchsimilar/__init__.py
 delete mode 100644 src/newscatcher/searchsimilar/client.py
 delete mode 100644 src/newscatcher/searchsimilar/raw_client.py
 delete mode 100644 src/newscatcher/searchsimilar/types/__init__.py
 delete mode 100644 src/newscatcher/searchsimilar/types/search_similar_get_request_published_date_precision.py
 delete mode 100644 src/newscatcher/searchsimilar/types/search_similar_get_request_sort_by.py
 delete mode 100644 src/newscatcher/searchsimilar/types/search_similar_get_response.py
 delete mode 100644 src/newscatcher/searchsimilar/types/search_similar_post_response.py
 delete mode 100644 src/newscatcher/sources/types/__init__.py
 delete mode 100644 src/newscatcher/sources/types/sources_get_request_news_domain_type.py
 rename src/newscatcher/types/{aggregations.py => aggregation_count_response_dto_aggregations.py} (55%)
 rename src/newscatcher/types/{similar_document.py => all_links_data_item.py} (57%)
 rename src/newscatcher/types/{authors.py => all_links_text.py} (61%)
 rename src/newscatcher/types/{journalists.py => article_entity_authors.py} (57%)
 create mode 100644 src/newscatcher/types/article_entity_journalists.py
 rename src/newscatcher/types/{articles.py => articles_dto.py} (75%)
 create mode 100644 src/newscatcher/types/breaking_news_article_entity_authors.py
 create mode 100644 src/newscatcher/types/breaking_news_article_entity_journalists.py
 delete mode 100644 src/newscatcher/types/failed_search_similar_response_dto.py
 delete mode 100644 src/newscatcher/types/include_similar_documents.py
 delete mode 100644 src/newscatcher/types/search_similar_response_dto.py
 delete mode 100644 src/newscatcher/types/similar_article_entity.py
 delete mode 100644 src/newscatcher/types/similar_documents_number.py

diff --git a/.fern/metadata.json b/.fern/metadata.json
new file mode 100644
index 0000000..5669654
--- /dev/null
+++ b/.fern/metadata.json
@@ -0,0 +1,15 @@
+{
+  "cliVersion": "4.28.0",
+  "generatorName": "fernapi/fern-python-sdk",
+  "generatorVersion": "4.64.0",
+  "generatorConfig": {
+    "client": {
+      "class_name": "BaseNewscatcherApi",
+      "filename": "base_client.py",
+      "exported_class_name": "NewscatcherApi",
+      "exported_filename": "client.py"
+    }
+  },
+  "originGitCommit": "ea3775d5199c3ed3efc0866eb726d2ed2141aeba",
+  "sdkVersion": "1.4.1"
+}
\ No newline at end of file
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 45ebaf2..bab604b 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -1,6 +1,9 @@
 name: ci
+on: [push]
 
-on: [push, pull_request]
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: false
 
 jobs:
   compile:
@@ -11,28 +14,14 @@ jobs:
       - name: Set up python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.9
       - name: Bootstrap poetry
         run: |
           curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
       - name: Install dependencies
-        run: |
-          poetry install
-          # Install additional dependencies if they exist in pyproject.toml or requirements
-          pip install types-tqdm python-dotenv python-dateutil tqdm types-python-dateutil || echo "Optional dependencies not installed"
+        run: poetry install
       - name: Compile
-        run: |
-          # Check if we have custom mypy config and custom files
-          if [ -f "mypy.ini" ] && [ -f "src/newscatcher/client.py" ] && [ -f "src/newscatcher/utils.py" ]; then
-            # Use custom configuration for custom files
-            poetry run mypy --config-file=mypy.ini src/newscatcher/client.py src/newscatcher/utils.py tests/ || echo "Custom mypy check completed with warnings"
-            # Check core files with relaxed settings
-            poetry run mypy --config-file=mypy.ini --disable-error-code=no-any-return src/newscatcher/core/ || echo "Core mypy check completed with warnings"
-          else
-            # Use default Fern approach - check everything
-            poetry run mypy . || echo "Default mypy check completed with warnings"
-          fi
-
+        run: poetry run mypy .
   test:
     runs-on: ubuntu-latest
     steps:
@@ -41,61 +30,15 @@ jobs:
       - name: Set up python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.9
       - name: Bootstrap poetry
         run: |
           curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
       - name: Install dependencies
-        run: |
-          poetry install
-          # Ensure all required dependencies are installed
-          poetry install --with dev || echo "Dev dependencies not available"
-          # Install the package in development mode
-          pip install -e .
-          # Install additional test dependencies for custom tests
-          pip install pytest pytest-asyncio python-dateutil tqdm python-dotenv httpx || echo "Optional test dependencies not installed"
-      - name: Generate mock data
-        run: |
-          # Only run if mock script exists
-          if [ -f "test-mock-mode.sh" ]; then
-            mkdir -p tests/mocks
-            python -c "$(cat test-mock-mode.sh | sed -n '/python -c/,/EOF/p' | grep -v 'python -c' | grep -v EOF)" || echo "Mock generation skipped"
-          fi
+        run: poetry install
+
       - name: Test
-        env:
-          NEWSCATCHER_API_KEY: ${{ secrets.NEWSCATCHER_API_KEY }}
-          TEST_MODE: "mock"
-        run: |
-          # Run different test strategies based on what exists
-          if [ -d "tests/utils" ] || [ -d "tests/custom" ] || [ -d "tests/integration" ]; then
-            echo "Running custom test suite"
-            # Run utils tests
-            if [ -d "tests/utils" ]; then
-              poetry run pytest -rP tests/utils || echo "Utils tests completed with issues"
-            fi
-            # Run custom tests  
-            if [ -d "tests/custom" ] || [ -d "tests/integration" ]; then
-              pytest tests/custom tests/integration -v || echo "Custom tests completed with issues"
-            fi
-          else
-            echo "Running default Fern test approach"
-            poetry run pytest -rP . || echo "Default tests completed with issues"
-          fi
-      - name: SDK validation test
-        run: |
-          # Install package in development mode for validation
-          pip install -e .
-          # Always run basic SDK validation
-          python -c "
-          try:
-              from newscatcher import NewscatcherApi
-              print('SDK import successful')
-              client = NewscatcherApi(api_key='test-key')
-              print('SDK instantiation successful')
-          except Exception as e:
-              print(f'SDK validation failed: {e}')
-              exit(1)
-          "
+        run: poetry run pytest -rP -n auto .
 
   publish:
     needs: [compile, test]
@@ -107,7 +50,7 @@ jobs:
       - name: Set up python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.8
+          python-version: 3.9
       - name: Bootstrap poetry
         run: |
           curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
diff --git a/README.md b/README.md
index a1d3f45..61c0fdb 100644
--- a/README.md
+++ b/README.md
@@ -3,11 +3,28 @@
 [![fern shield](https://img.shields.io/badge/%F0%9F%8C%BF-Built%20with%20Fern-brightgreen)](https://buildwithfern.com?utm_source=github&utm_medium=github&utm_campaign=readme&utm_source=https%3A%2F%2Fgithub.com%2FNewscatcher%2Fnewscatcher-python)
 [![pypi](https://img.shields.io/pypi/v/newscatcher-sdk)](https://pypi.python.org/pypi/newscatcher-sdk)
 
-The Newscatcher Python library gives you convenient access to the Newscatcher API from Python.
+The Newscatcher Python library provides convenient access to the Newscatcher APIs from Python.
+
+## Table of Contents
+
+- [Documentation](#documentation)
+- [Installation](#installation)
+- [Reference](#reference)
+- [Usage](#usage)
+- [Async Client](#async-client)
+- [Exception Handling](#exception-handling)
+- [Retrieving More Articles](#retrieving-more-articles)
+- [Query Validation](#query-validation)
+- [Advanced](#advanced)
+  - [Access Raw Response Data](#access-raw-response-data)
+  - [Retries](#retries)
+  - [Timeouts](#timeouts)
+  - [Custom Client](#custom-client)
+- [Contributing](#contributing)
 
 ## Documentation
 
-View API reference documentation at [newscatcherapi.com/docs](https://www.newscatcherapi.com/docs/v3/api-reference).
+API reference documentation is available [here](https://www.newscatcherapi.com/docs/news-api/api-reference/overview).
 
 ## Installation
 
@@ -17,72 +34,53 @@ pip install newscatcher-sdk
 
 ## Reference
 
-A full reference for this library is available [here](./reference.md).
+A full reference for this library is available [here](https://github.com/Newscatcher/newscatcher-python/blob/HEAD/./reference.md).
 
 ## Usage
 
-Create and use the client:
+Instantiate and use the client with the following:
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
 )
+
 client.search.post(
-    q="renewable energy",
-    predefined_sources=["top 50 US"],
-    lang=["en"],
-    from_=datetime.datetime.fromisoformat(
-        "2024-01-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-06-30 00:00:00+00:00",
-    ),
-    additional_domain_info=True,
-    is_news_domain=True,
+    q="\"supply chain\" AND Amazon NOT China",
+    page_size=1,
 )
 ```
 
-## Async client
+## Async Client
 
-Use the `AsyncNewscatcherApi` client to make non-blocking calls to the API:
+The SDK also exports an `async` client so that you can make non-blocking calls to our API. Note that if you are constructing an Async httpx client class to pass into this client, use `httpx.AsyncClient()` instead of `httpx.Client()` (e.g. for the `httpx_client` parameter of this client).
 
 ```python
 import asyncio
-import datetime
 
 from newscatcher import AsyncNewscatcherApi
 
 client = AsyncNewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
 )
 
 
 async def main() -> None:
     await client.search.post(
-        q="renewable energy",
-        predefined_sources=["top 50 US"],
-        lang=["en"],
-        from_=datetime.datetime.fromisoformat(
-            "2024-01-01 00:00:00+00:00",
-        ),
-        to=datetime.datetime.fromisoformat(
-            "2024-06-30 00:00:00+00:00",
-        ),
-        additional_domain_info=True,
-        is_news_domain=True,
+        q="\"supply chain\" AND Amazon NOT China",
+        page_size=1,
     )
 
 
 asyncio.run(main())
 ```
 
-## Exception handling
+## Exception Handling
 
-The SDK raises an `ApiError` when the API returns a non-success status code (4xx or 5xx response):
+When the API returns a non-success status code (4xx or 5xx response), a subclass of the following error
+will be thrown.
 
 ```python
 from newscatcher.core.api_error import ApiError
@@ -180,17 +178,34 @@ For complete validation rules, bulk validation techniques, and troubleshooting,
 
 ## Advanced
 
+### Access Raw Response Data
+
+The SDK provides access to raw response data, including headers, through the `.with_raw_response` property.
+The `.with_raw_response` property returns a "raw" client that can be used to access the `.headers` and `.data` attributes.
+
+```python
+from newscatcher import NewscatcherApi
+
+client = NewscatcherApi(...)
+response = client.search.with_raw_response.post(...)
+print(response.headers)  # access the response headers
+print(response.status_code)  # access the response status code
+print(response.data)  # access the underlying object
+```
+
 ### Retries
 
-The SDK includes automatic retries with exponential backoff. The SDK retries a request when the request is retriable and the number of retry attempts is less than the configured retry limit (default: 2).
+The SDK is instrumented with automatic retries with exponential backoff. A request will be retried as long
+as the request is deemed retryable and the number of retry attempts has not grown larger than the configured
+retry limit (default: 2).
 
-The SDK retries requests when the API returns these HTTP status codes:
+A request is deemed retryable when any of the following HTTP status codes is returned:
 
 - [408](https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/408) (Timeout)
 - [429](https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/429) (Too Many Requests)
 - [5XX](https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500) (Internal Server Errors)
 
-Use the `max_retries` request option to configure this behavior:
+Use the `max_retries` request option to configure this behavior.
 
 ```python
 client.search.post(..., request_options={
@@ -200,17 +215,12 @@ client.search.post(..., request_options={
 
 ### Timeouts
 
-The SDK uses a 60-second timeout by default. Configure timeouts at the client or request level:
+The SDK defaults to a 60 second timeout. You can configure this with a timeout option at the client or request level.
 
 ```python
-
 from newscatcher import NewscatcherApi
 
-client = NewscatcherApi(
-    ...,
-    timeout=20.0,
-)
-
+client = NewscatcherApi(..., timeout=20.0)
 
 # Override timeout for a specific method
 client.search.post(..., request_options={
@@ -218,9 +228,10 @@ client.search.post(..., request_options={
 })
 ```
 
-### Custom client
+### Custom Client
 
-Override the `httpx` client to customize it for your use case. Common use cases include proxies and transports:
+You can override the `httpx` client to customize it for your use-case. Some common use-cases include support for proxies
+and transports.
 
 ```python
 import httpx
@@ -229,7 +240,7 @@ from newscatcher import NewscatcherApi
 client = NewscatcherApi(
     ...,
     httpx_client=httpx.Client(
-        proxies="http://my.test.proxy.example.com",
+        proxy="http://my.test.proxy.example.com",
         transport=httpx.HTTPTransport(local_address="0.0.0.0"),
     ),
 )
@@ -237,6 +248,10 @@ client = NewscatcherApi(
 
 ## Contributing
 
-We value open-source contributions to this SDK. This library is generated programmatically, but we can implement custom methods and use `.fernignore` to preserve certain files. However, implementing custom solutions in the SDK involves a complex process. Please open an issue first to discuss your ideas before submitting a PR.
+While we value open-source contributions to this SDK, this library is generated programmatically.
+Additions made directly to this library would have to be moved over to our generation code,
+otherwise they would be overwritten upon the next generated release. Feel free to open a PR as
+a proof of concept, but know that we will not be able to merge it as-is. We suggest opening
+an issue first to discuss with us!
 
 On the other hand, contributions to the README are always very welcome!
diff --git a/poetry.lock b/poetry.lock
index c2ddd86..83fdc8b 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -38,13 +38,13 @@ trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "certifi"
-version = "2025.8.3"
+version = "2026.2.25"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "certifi-2025.8.3-py3-none-any.whl", hash = "sha256:f6c12493cfb1b06ba2ff328595af9350c65d6644968e5d3a2ffd78699af217a5"},
-    {file = "certifi-2025.8.3.tar.gz", hash = "sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407"},
+    {file = "certifi-2026.2.25-py3-none-any.whl", hash = "sha256:027692e4402ad994f1c42e52a4997a9763c646b73e4096e4d5d6db8af1d6f0fa"},
+    {file = "certifi-2026.2.25.tar.gz", hash = "sha256:e887ab5cee78ea814d3472169153c2d12cd43b14bd03329a39a9c6e2e80bfba7"},
 ]
 
 [[package]]
@@ -60,13 +60,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.3.0"
+version = "1.3.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598"},
+    {file = "exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219"},
 ]
 
 [package.dependencies]
@@ -75,6 +75,20 @@ typing-extensions = {version = ">=4.6.0", markers = "python_version < \"3.13\""}
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "execnet"
+version = "2.1.2"
+description = "execnet: rapid multi-Python deployment"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "execnet-2.1.2.tar.gz", hash = "sha256:63d83bfdd9a23e35b9c6a3261412324f964c2ec8dcd8d3c6916ee9373e0befcd"},
+]
+
+[package.extras]
+testing = ["hatch", "pre-commit", "pytest", "tox"]
+
 [[package]]
 name = "h11"
 version = "0.16.0"
@@ -133,13 +147,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "idna"
-version = "3.10"
+version = "3.11"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
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+    {file = "idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea"},
+    {file = "idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902"},
 ]
 
 [package.extras]
@@ -222,13 +236,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "25.0"
+version = "26.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "packaging-26.0.tar.gz", hash = "sha256:00243ae351a257117b6a241061796684b084ed1c516a08c48a3f7e147a9d80b4"},
 ]
 
 [[package]]
@@ -418,6 +432,26 @@ pytest = ">=7.0.0,<9"
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
 testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
+[[package]]
+name = "pytest-xdist"
+version = "3.6.1"
+description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "pytest_xdist-3.6.1.tar.gz", hash = "sha256:ead156a4db231eec769737f57668ef58a2084a34b2e55c4a8fa20d861107300d"},
+]
+
+[package.dependencies]
+execnet = ">=2.1"
+pytest = ">=7.0.0"
+
+[package.extras]
+psutil = ["psutil (>=3.0)"]
+setproctitle = ["setproctitle"]
+testing = ["filelock"]
+
 [[package]]
 name = "python-dateutil"
 version = "2.9.0.post0"
@@ -483,43 +517,58 @@ files = [
 
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 name = "tomli"
-version = "2.2.1"
+version = "2.4.0"
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 python-versions = ">=3.8"
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+    {file = "tomli-2.4.0-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:5b5807f3999fb66776dbce568cc9a828544244a8eb84b84b9bafc080c99597b9"},
+    {file = "tomli-2.4.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c084ad935abe686bd9c898e62a02a19abfc9760b5a79bc29644463eaf2840cb0"},
+    {file = "tomli-2.4.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0f2e3955efea4d1cfbcb87bc321e00dc08d2bcb737fd1d5e398af111d86db5df"},
+    {file = "tomli-2.4.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0e0fe8a0b8312acf3a88077a0802565cb09ee34107813bba1c7cd591fa6cfc8d"},
+    {file = "tomli-2.4.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:413540dce94673591859c4c6f794dfeaa845e98bf35d72ed59636f869ef9f86f"},
+    {file = "tomli-2.4.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:0dc56fef0e2c1c470aeac5b6ca8cc7b640bb93e92d9803ddaf9ea03e198f5b0b"},
+    {file = "tomli-2.4.0-cp314-cp314t-win32.whl", hash = "sha256:d878f2a6707cc9d53a1be1414bbb419e629c3d6e67f69230217bb663e76b5087"},
+    {file = "tomli-2.4.0-cp314-cp314t-win_amd64.whl", hash = "sha256:2add28aacc7425117ff6364fe9e06a183bb0251b03f986df0e78e974047571fd"},
+    {file = "tomli-2.4.0-cp314-cp314t-win_arm64.whl", hash = "sha256:2b1e3b80e1d5e52e40e9b924ec43d81570f0e7d09d11081b797bc4692765a3d4"},
+    {file = "tomli-2.4.0-py3-none-any.whl", hash = "sha256:1f776e7d669ebceb01dee46484485f43a4048746235e683bcdffacdf1fb4785a"},
+    {file = "tomli-2.4.0.tar.gz", hash = "sha256:aa89c3f6c277dd275d8e243ad24f3b5e701491a860d5121f2cdd399fbb31fc9c"},
 ]
 
 [[package]]
@@ -547,4 +596,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.8"
-content-hash = "8551b871abee465e23fb0966d51f2c155fd257b55bdcb0c02d095de19f92f358"
+content-hash = "bcf31a142c86d9e556553c8c260a93b563ac64a043076dbd48b26111d422c26e"
diff --git a/pyproject.toml b/pyproject.toml
index ba72212..d89ac48 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,9 +1,10 @@
 [project]
 name = "newscatcher-sdk"
+dynamic = ["version"]
 
 [tool.poetry]
 name = "newscatcher-sdk"
-version = "1.4.0"
+version = "1.4.1"
 description = ""
 readme = "README.md"
 authors = []
@@ -18,6 +19,9 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
+    "Programming Language :: Python :: 3.14",
+    "Programming Language :: Python :: 3.15",
     "Operating System :: OS Independent",
     "Operating System :: POSIX",
     "Operating System :: MacOS",
@@ -31,7 +35,7 @@ packages = [
     { include = "newscatcher", from = "src"}
 ]
 
-[project.urls]
+[tool.poetry.urls]
 Repository = 'https://github.com/Newscatcher/newscatcher-python'
 
 [tool.poetry.dependencies]
@@ -45,6 +49,7 @@ typing_extensions = ">= 4.0.0"
 mypy = "==1.13.0"
 pytest = "^7.4.0"
 pytest-asyncio = "^0.23.5"
+pytest-xdist = "^3.6.1"
 python-dateutil = "^2.9.0"
 types-python-dateutil = "^2.9.0.20240316"
 ruff = "==0.11.5"
diff --git a/reference.md b/reference.md
index 367099b..1d8fdb2 100644
--- a/reference.md
+++ b/reference.md
@@ -1,6 +1,6 @@
 # Reference
 ## Search
-<details><summary><code>client.search.<a href="src/newscatcher/search/client.py">get</a>(...)</code></summary>
+<details><summary><code>client.search.<a href="src/newscatcher/search/client.py">get</a>(...) -> SearchGetResponse</code></summary>
 <dl>
 <dd>
 
@@ -12,7 +12,7 @@
 <dl>
 <dd>
 
-Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 </dd>
 </dl>
 </dd>
@@ -27,33 +27,70 @@ Searches for articles based on specified criteria such as keyword, language, cou
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
+import datetime
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.search.get(
-    q="technology AND (Apple OR Microsoft) NOT Google",
+    q="\"supply chain\" AND Amazon NOT China",
     search_in="title_content, title_content_translated",
     include_translation_fields=True,
-    predefined_sources="top 100 US, top 5 GB",
-    from_=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
+    predefined_sources="top 50 US, top 20 GB",
+    source_name="sport,tech",
+    sources="nytimes.com,finance.yahoo.com",
+    not_sources="cnn.com,wsj.com",
+    lang="en,es",
+    not_lang="fr,de",
+    countries="US,CA",
+    not_countries="UK,FR",
+    not_author_name="John Doe, Jane Doe",
+    from_=datetime.datetime.fromisoformat("2024-07-01T00:00:00+00:00"),
+    to=datetime.datetime.fromisoformat("2024-01-01T00:00:00+00:00"),
+    published_date_precision="full",
+    by_parse_date=True,
+    ranked_only=True,
+    from_rank=100,
+    to_rank=100,
+    is_headline=True,
+    is_opinion=True,
+    is_paid_content=False,
+    parent_url="wsj.com/politics,wsj.com/tech",
+    all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+    all_domain_links="who.int,nih.gov",
+    all_links_text="Nvidia,Tesla",
+    additional_domain_info=True,
+    is_news_domain=True,
+    news_type="General News Outlets,Tech News and Updates",
+    word_count_min=300,
+    word_count_max=1000,
+    page=2,
+    page_size=50,
+    clustering_enabled=True,
+    clustering_threshold=0.6,
     include_nlp_data=True,
     has_nlp=True,
-    theme="Business,Finance",
-    not_theme="Crime",
+    theme="Finance,Tech",
+    not_theme="Crime,Sports",
+    org_entity_name="\"Apple Inc\" OR Microsoft",
+    per_entity_name="\"Elon Musk\" OR \"Jeff Bezos\"",
+    loc_entity_name="\"San Francisco\" OR \"New York City\"",
+    misc_entity_name="AWS OR \"Microsoft Azure\"",
+    title_sentiment_min=-0.5,
+    title_sentiment_max=0.5,
+    content_sentiment_min=-0.5,
+    content_sentiment_max=0.5,
     iptc_tags="20000199,20000209",
     not_iptc_tags="20000205,20000209",
     iab_tags="Business,Events",
     not_iab_tags="Agriculture,Metals",
-    custom_tags="Tag1,Tag2,Tag3",
+    custom_tags="Tag1,Tag2",
+    exclude_duplicates=True,
+    robots_compliant=True,
 )
 
 ```
@@ -70,18 +107,7 @@ client.search.get(
 <dl>
 <dd>
 
-**q:** `str` 
-
-The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-- For an exact match, use double quotes. For example, `"technology news"`.
-- Use `*` to search for any keyword.
-- Use `+` to include and `-` to exclude specific words or phrases. 
-  For example, `+Apple`, `-Google`.
-- Use `AND`, `OR`, and `NOT` to refine search results. 
-  For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+**q:** `Q` 
     
 </dd>
 </dl>
@@ -109,13 +135,9 @@ For more details, see [Advanced querying](/docs/v3/documentation/guides-and-conc
 
 Predefined top news sources per country. 
 
-Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). 
 
-Examples: 
-- `"top 100 US"`
-- `"top 33 AT"`
-- `"top 50 US, top 20 GB"`
-- `"top 33 AT, top 50 IT"`
+Multiple countries with the number of top sources can be specified as a comma-separated string.
     
 </dd>
 </dl>
@@ -127,8 +149,6 @@ Examples:
 
 Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-Example: `"sport, tech"`
-
 **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
     
 </dd>
@@ -137,13 +157,7 @@ Example: `"sport, tech"`
 <dl>
 <dd>
 
-**sources:** `typing.Optional[str]` 
-
-One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-Examples:
-- `"nytimes.com"`
-- `"theguardian.com, finance.yahoo.com"`
+**sources:** `typing.Optional[str]` — One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -151,11 +165,7 @@ Examples:
 <dl>
 <dd>
 
-**not_sources:** `typing.Optional[str]` 
-
-The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string. 
-
-Example: `"cnn.com, wsj.com"`
+**not_sources:** `typing.Optional[str]` — The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -165,11 +175,9 @@ Example: `"cnn.com, wsj.com"`
 
 **lang:** `typing.Optional[str]` 
 
-The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string. 
-
-Example: `"en, es"`
+The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -181,9 +189,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string. 
 
-Example: `"fr, de"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -195,9 +201,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-Example: `"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -209,9 +213,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 
 The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string. 
 
-Example:`"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -219,11 +221,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 <dl>
 <dd>
 
-**not_author_name:** `typing.Optional[str]` 
-
-The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
-
-Example: `"John Doe, Jane Doe"`
+**not_author_name:** `typing.Optional[str]` — The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
     
 </dd>
 </dl>
@@ -231,18 +229,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**from_:** `typing.Optional[dt.datetime]` 
-
-The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `7 day ago`, `today`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -250,18 +237,7 @@ Formats with examples:
 <dl>
 <dd>
 
-**to:** `typing.Optional[dt.datetime]` 
-
-The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `1 day ago`, `now`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+**to:** `typing.Optional[To]` 
     
 </dd>
 </dl>
@@ -269,12 +245,7 @@ Formats with examples:
 <dl>
 <dd>
 
-**published_date_precision:** `typing.Optional[SearchGetRequestPublishedDatePrecision]` 
-
-The precision of the published date. There are three types:
-- `full`: The day and time of an article is correctly identified with the appropriate timezone.
-- `timezone unknown`: The day and time of an article is correctly identified without timezone.
-- `date`: Only the day is identified without an exact time.
+**published_date_precision:** `typing.Optional[PublishedDatePrecision]` 
     
 </dd>
 </dl>
@@ -282,7 +253,7 @@ The precision of the published date. There are three types:
 <dl>
 <dd>
 
-**by_parse_date:** `typing.Optional[bool]` — If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+**by_parse_date:** `typing.Optional[ByParseDate]` 
     
 </dd>
 </dl>
@@ -290,12 +261,7 @@ The precision of the published date. There are three types:
 <dl>
 <dd>
 
-**sort_by:** `typing.Optional[SearchGetRequestSortBy]` 
-
-The sorting order of the results. Possible values are:
-- `relevancy`: The most relevant results first.
-- `date`: The most recently published results first.
-- `rank`: The results from the highest-ranked sources first.
+**sort_by:** `typing.Optional[SortBy]` 
     
 </dd>
 </dl>
@@ -303,7 +269,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**ranked_only:** `typing.Optional[bool]` — If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+**ranked_only:** `typing.Optional[RankedOnly]` 
     
 </dd>
 </dl>
@@ -311,7 +277,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**from_rank:** `typing.Optional[int]` — The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**from_rank:** `typing.Optional[FromRank]` 
     
 </dd>
 </dl>
@@ -319,7 +285,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**to_rank:** `typing.Optional[int]` — The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**to_rank:** `typing.Optional[ToRank]` 
     
 </dd>
 </dl>
@@ -327,7 +293,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_headline:** `typing.Optional[bool]` — If true, only returns articles that were posted on the home page of a given news domain.
+**is_headline:** `typing.Optional[IsHeadline]` 
     
 </dd>
 </dl>
@@ -335,7 +301,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_opinion:** `typing.Optional[bool]` — If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+**is_opinion:** `typing.Optional[IsOpinion]` 
     
 </dd>
 </dl>
@@ -343,7 +309,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_paid_content:** `typing.Optional[bool]` — If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+**is_paid_content:** `typing.Optional[IsPaidContent]` 
     
 </dd>
 </dl>
@@ -351,11 +317,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**parent_url:** `typing.Optional[str]` 
-
-The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-Example: `"wsj.com/politics, wsj.com/tech"`
+**parent_url:** `typing.Optional[str]` — The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
     
 </dd>
 </dl>
@@ -367,9 +329,7 @@ Example: `"wsj.com/politics, wsj.com/tech"`
 
 The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -381,9 +341,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 
 The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-Example: `"who.int, nih.gov"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -391,12 +349,13 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**additional_domain_info:** `typing.Optional[bool]` 
+**all_links_text:** `typing.Optional[str]` 
+
+The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
+
+**Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-If true, includes additional domain information in the response for each article:
-- `is_news_domain`: Boolean indicating if the source is a news domain.
-- `news_domain_type`: Type of news domain (e.g., `"Original Content"`).
-- `news_type`: Category of news (e.g., `"News and Blogs"`).
+To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -404,7 +363,7 @@ If true, includes additional domain information in the response for each article
 <dl>
 <dd>
 
-**is_news_domain:** `typing.Optional[bool]` — If true, filters results to include only news domains.
+**additional_domain_info:** `typing.Optional[AdditionalDomainInfo]` 
     
 </dd>
 </dl>
@@ -412,14 +371,15 @@ If true, includes additional domain information in the response for each article
 <dl>
 <dd>
 
-**news_domain_type:** `typing.Optional[SearchGetRequestNewsDomainType]` 
+**is_news_domain:** `typing.Optional[IsNewsDomain]` 
+    
+</dd>
+</dl>
+
+<dl>
+<dd>
 
-Filters results based on the news domain type. Possible values are:
-- `Original Content`: Sources that produce their own content.
-- `Aggregator`: Sources that collect content from various other sources.
-- `Press Releases`: Sources primarily publishing press releases.
-- `Republisher`: Sources that republish content from other sources.
-- `Other`: Sources that don't fit into main categories.
+**news_domain_type:** `typing.Optional[NewsDomainType]` 
     
 </dd>
 </dl>
@@ -431,9 +391,7 @@ Filters results based on the news domain type. Possible values are:
 
 Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-Example: `"General News Outlets,Tech News and Updates"`
-
-For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
+For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
     
 </dd>
 </dl>
@@ -441,7 +399,7 @@ For a complete list of available news types, see [Enumerated parameters > News t
 <dl>
 <dd>
 
-**word_count_min:** `typing.Optional[int]` — The minimum number of words an article must contain. To be used for avoiding articles with small content.
+**word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
 </dl>
@@ -449,7 +407,7 @@ For a complete list of available news types, see [Enumerated parameters > News t
 <dl>
 <dd>
 
-**word_count_max:** `typing.Optional[int]` — The maximum number of words an article can contain. To be used for avoiding articles with large content.
+**word_count_max:** `typing.Optional[WordCountMax]` 
     
 </dd>
 </dl>
@@ -457,11 +415,7 @@ For a complete list of available news types, see [Enumerated parameters > News t
 <dl>
 <dd>
 
-**page:** `typing.Optional[int]` 
-
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
-
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -469,7 +423,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -477,11 +431,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**clustering_enabled:** `typing.Optional[bool]` 
-
-Determines whether to group similar articles into clusters. If true, the API returns clustered results.
-
-To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+**clustering_enabled:** `typing.Optional[ClusteringEnabled]` 
     
 </dd>
 </dl>
@@ -489,16 +439,7 @@ To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-
 <dl>
 <dd>
 
-**clustering_variable:** `typing.Optional[SearchGetRequestClusteringVariable]` 
-
-Specifies which part of the article to use for determining similarity when clustering.
-
-Possible values are:
-- `content`: Uses the full article content (default).
-- `title`: Uses only the article title.
-- `summary`: Uses the article summary.
-
-To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+**clustering_variable:** `typing.Optional[ClusteringVariable]` 
     
 </dd>
 </dl>
@@ -506,16 +447,7 @@ To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-
 <dl>
 <dd>
 
-**clustering_threshold:** `typing.Optional[float]` 
-
-Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
-
-Examples:
-- `0.3`: Results in larger, more diverse clusters.
-- `0.6`: Balances cluster size and article similarity (default).
-- `0.9`: Creates smaller, tightly related clusters.
-
-To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+**clustering_threshold:** `typing.Optional[ClusteringThreshold]` 
     
 </dd>
 </dl>
@@ -539,17 +471,7 @@ To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-
 <dl>
 <dd>
 
-**theme:** `typing.Optional[str]` 
-
-Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-Example: `"Finance, Tech"`
-
-**Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
+**theme:** `typing.Optional[Theme]` 
     
 </dd>
 </dl>
@@ -557,15 +479,7 @@ Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`
 <dl>
 <dd>
 
-**not_theme:** `typing.Optional[str]` 
-
-Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string. 
-
-Example: `"Crime, Tech"`
-
-**Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**not_theme:** `typing.Optional[NotTheme]` 
     
 </dd>
 </dl>
@@ -573,15 +487,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**org_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Apple, Microsoft"`
-
-**Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**org_entity_name:** `typing.Optional[OrgEntityName]` 
     
 </dd>
 </dl>
@@ -589,15 +495,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**per_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Elon Musk, Jeff Bezos"`
-
-**Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**per_entity_name:** `typing.Optional[PerEntityName]` 
     
 </dd>
 </dl>
@@ -605,15 +503,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**loc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"California, New York"`
-
-**Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**loc_entity_name:** `typing.Optional[LocEntityName]` 
     
 </dd>
 </dl>
@@ -621,15 +511,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**misc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Bitcoin, Blockchain"`
-
-**Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**misc_entity_name:** `typing.Optional[MiscEntityName]` 
     
 </dd>
 </dl>
@@ -637,18 +519,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**title_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_min:** `typing.Optional[TitleSentimentMin]` 
     
 </dd>
 </dl>
@@ -656,18 +527,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**title_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_max:** `typing.Optional[TitleSentimentMax]` 
     
 </dd>
 </dl>
@@ -675,18 +535,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_min:** `typing.Optional[ContentSentimentMin]` 
     
 </dd>
 </dl>
@@ -694,18 +543,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
     
 </dd>
 </dl>
@@ -717,8 +555,6 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 
 Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs. 
 
-Example: `"20000199, 20000209"`
-
 **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
 To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -731,9 +567,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **not_iptc_tags:** `typing.Optional[str]` 
 
-Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs. 
-
-Example: `"20000205, 20000209"`
+Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
 **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -747,9 +581,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **iab_tags:** `typing.Optional[str]` 
 
-Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string. 
-
-Example: `"Business, Events"`
+Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
 **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -763,9 +595,7 @@ To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/c
 
 **not_iab_tags:** `typing.Optional[str]` 
 
-Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string. 
-
-Example: `"Agriculture, Metals"`
+Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
 **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -781,11 +611,11 @@ To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/c
 
 Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern: 
 
-- `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+- `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
     
 </dd>
 </dl>
@@ -793,11 +623,7 @@ To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/
 <dl>
 <dd>
 
-**exclude_duplicates:** `typing.Optional[bool]` 
-
-If true, excludes duplicate and highly similar articles from the search results. If false, returns all relevant articles, including duplicates. 
-
-To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-concepts/articles-deduplication).
+**exclude_duplicates:** `typing.Optional[ExcludeDuplicates]` 
     
 </dd>
 </dl>
@@ -805,7 +631,7 @@ To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-co
 <dl>
 <dd>
 
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+**robots_compliant:** `typing.Optional[RobotsCompliant]` 
     
 </dd>
 </dl>
@@ -825,7 +651,7 @@ To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-co
 </dl>
 </details>
 
-<details><summary><code>client.search.<a href="src/newscatcher/search/client.py">post</a>(...)</code></summary>
+<details><summary><code>client.search.<a href="src/newscatcher/search/client.py">post</a>(...) -> SearchPostResponse</code></summary>
 <dl>
 <dd>
 
@@ -837,7 +663,7 @@ To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-co
 <dl>
 <dd>
 
-Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 </dd>
 </dl>
 </dd>
@@ -852,25 +678,17 @@ Searches for articles based on specified criteria such as keyword, language, cou
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.search.post(
-    q="renewable energy",
-    predefined_sources=["top 50 US"],
-    lang=["en"],
-    from_=datetime.datetime.fromisoformat(
-        "2024-01-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-06-30 00:00:00+00:00",
-    ),
-    additional_domain_info=True,
-    is_news_domain=True,
+    q="\"supply chain\" AND Amazon NOT China",
+    page_size=1,
 )
 
 ```
@@ -983,7 +801,7 @@ client.search.post(
 <dl>
 <dd>
 
-**from_:** `typing.Optional[From]` 
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -1095,6 +913,14 @@ client.search.post(
 <dl>
 <dd>
 
+**all_links_text:** `typing.Optional[AllLinksText]` 
+    
+</dd>
+</dl>
+
+<dl>
+<dd>
+
 **additional_domain_info:** `typing.Optional[AdditionalDomainInfo]` 
     
 </dd>
@@ -1348,7 +1174,7 @@ client.search.post(
 </details>
 
 ## LatestHeadlines
-<details><summary><code>client.latestheadlines.<a href="src/newscatcher/latestheadlines/client.py">get</a>(...)</code></summary>
+<details><summary><code>client.latest_headlines.<a href="src/newscatcher/latest_headlines/client.py">latest_headlines_get</a>(...) -> LatestHeadlinesGetResponse</code></summary>
 <dl>
 <dd>
 
@@ -1376,22 +1202,57 @@ Retrieves the latest headlines for the specified time period. You can filter res
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
-client.latestheadlines.get(
-    predefined_sources="top 100 US, top 5 GB",
+
+client.latest_headlines.latest_headlines_get(
+    when="7d",
+    by_parse_date=True,
+    lang="en,es",
+    not_lang="fr,de",
+    countries="US,CA",
+    not_countries="UK,FR",
+    predefined_sources="top 50 US, top 20 GB",
+    sources="nytimes.com,finance.yahoo.com",
+    not_sources="cnn.com,wsj.com",
+    not_author_name="John Doe, Jane Doe",
+    ranked_only=True,
+    is_headline=True,
+    is_opinion=True,
+    is_paid_content=False,
+    parent_url="wsj.com/politics,wsj.com/tech",
+    all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+    all_domain_links="who.int,nih.gov",
+    all_links_text="Nvidia,Tesla",
+    word_count_min=300,
+    word_count_max=1000,
+    page=2,
+    page_size=50,
+    clustering_enabled=True,
+    clustering_threshold=0.6,
     include_translation_fields=True,
     include_nlp_data=True,
     has_nlp=True,
-    theme="Business,Finance",
-    not_theme="Crime",
+    theme="Finance,Tech",
+    not_theme="Crime,Sports",
+    org_entity_name="\"Apple Inc\" OR Microsoft",
+    per_entity_name="\"Elon Musk\" OR \"Jeff Bezos\"",
+    loc_entity_name="\"San Francisco\" OR \"New York City\"",
+    misc_entity_name="AWS OR \"Microsoft Azure\"",
+    title_sentiment_min=-0.5,
+    title_sentiment_max=0.5,
+    content_sentiment_min=-0.5,
+    content_sentiment_max=0.5,
     iptc_tags="20000199,20000209",
     not_iptc_tags="20000205,20000209",
     iab_tags="Business,Events",
     not_iab_tags="Agriculture,Metals",
-    custom_tags="Tag1,Tag2,Tag3",
+    custom_tags="Tag1,Tag2",
+    robots_compliant=True,
 )
 
 ```
@@ -1408,15 +1269,15 @@ client.latestheadlines.get(
 <dl>
 <dd>
 
-**when:** `typing.Optional[str]` 
+**when:** `typing.Optional[When]` 
+    
+</dd>
+</dl>
 
-The time period for which you want to get the latest headlines.
+<dl>
+<dd>
 
-Format examples:
-- `7d`: Last seven days
-- `30d`: Last 30 days
-- `1h`: Last hour
-- `24h`: Last 24 hours
+**by_parse_date:** `typing.Optional[ByParseDate]` 
     
 </dd>
 </dl>
@@ -1424,7 +1285,7 @@ Format examples:
 <dl>
 <dd>
 
-**by_parse_date:** `typing.Optional[bool]` — If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+**sort_by:** `typing.Optional[SortBy]` 
     
 </dd>
 </dl>
@@ -1434,11 +1295,9 @@ Format examples:
 
 **lang:** `typing.Optional[str]` 
 
-The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string. 
-
-Example: `"en, es"`
+The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -1450,9 +1309,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string. 
 
-Example: `"fr, de"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -1464,9 +1321,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-Example: `"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -1478,9 +1333,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 
 The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string. 
 
-Example:`"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -1492,13 +1345,9 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 
 Predefined top news sources per country. 
 
-Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). 
 
-Examples: 
-- `"top 100 US"`
-- `"top 33 AT"`
-- `"top 50 US, top 20 GB"`
-- `"top 33 AT, top 50 IT"`
+Multiple countries with the number of top sources can be specified as a comma-separated string.
     
 </dd>
 </dl>
@@ -1506,13 +1355,7 @@ Examples:
 <dl>
 <dd>
 
-**sources:** `typing.Optional[str]` 
-
-One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-Examples:
-- `"nytimes.com"`
-- `"theguardian.com, finance.yahoo.com"`
+**sources:** `typing.Optional[str]` — One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -1520,11 +1363,7 @@ Examples:
 <dl>
 <dd>
 
-**not_sources:** `typing.Optional[str]` 
-
-The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string. 
-
-Example: `"cnn.com, wsj.com"`
+**not_sources:** `typing.Optional[str]` — The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -1532,11 +1371,7 @@ Example: `"cnn.com, wsj.com"`
 <dl>
 <dd>
 
-**not_author_name:** `typing.Optional[str]` 
-
-The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
-
-Example: `"John Doe, Jane Doe"`
+**not_author_name:** `typing.Optional[str]` — The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
     
 </dd>
 </dl>
@@ -1544,7 +1379,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**ranked_only:** `typing.Optional[bool]` — If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+**ranked_only:** `typing.Optional[RankedOnly]` 
     
 </dd>
 </dl>
@@ -1552,7 +1387,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**is_headline:** `typing.Optional[bool]` — If true, only returns articles that were posted on the home page of a given news domain.
+**is_headline:** `typing.Optional[IsHeadline]` 
     
 </dd>
 </dl>
@@ -1560,7 +1395,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**is_opinion:** `typing.Optional[bool]` — If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+**is_opinion:** `typing.Optional[IsOpinion]` 
     
 </dd>
 </dl>
@@ -1568,7 +1403,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**is_paid_content:** `typing.Optional[bool]` — If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+**is_paid_content:** `typing.Optional[IsPaidContent]` 
     
 </dd>
 </dl>
@@ -1576,11 +1411,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**parent_url:** `typing.Optional[str]` 
-
-The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-Example: `"wsj.com/politics, wsj.com/tech"`
+**parent_url:** `typing.Optional[str]` — The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
     
 </dd>
 </dl>
@@ -1592,9 +1423,7 @@ Example: `"wsj.com/politics, wsj.com/tech"`
 
 The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -1606,9 +1435,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 
 The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-Example: `"who.int, nih.gov"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -1616,7 +1443,13 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**word_count_min:** `typing.Optional[int]` — The minimum number of words an article must contain. To be used for avoiding articles with small content.
+**all_links_text:** `typing.Optional[str]` 
+
+The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
+
+**Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
+
+To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -1624,7 +1457,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**word_count_max:** `typing.Optional[int]` — The maximum number of words an article can contain. To be used for avoiding articles with large content.
+**word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
 </dl>
@@ -1632,11 +1465,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**page:** `typing.Optional[int]` 
-
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
-
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+**word_count_max:** `typing.Optional[WordCountMax]` 
     
 </dd>
 </dl>
@@ -1644,7 +1473,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -1652,11 +1481,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**clustering_enabled:** `typing.Optional[bool]` 
-
-Determines whether to group similar articles into clusters. If true, the API returns clustered results.
-
-To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -1664,16 +1489,7 @@ To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-
 <dl>
 <dd>
 
-**clustering_variable:** `typing.Optional[LatestHeadlinesGetRequestClusteringVariable]` 
-
-Specifies which part of the article to use for determining similarity when clustering.
-
-Possible values are:
-- `content`: Uses the full article content (default).
-- `title`: Uses only the article title.
-- `summary`: Uses the article summary.
-
-To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+**clustering_enabled:** `typing.Optional[ClusteringEnabled]` 
     
 </dd>
 </dl>
@@ -1681,16 +1497,15 @@ To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-
 <dl>
 <dd>
 
-**clustering_threshold:** `typing.Optional[float]` 
-
-Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+**clustering_variable:** `typing.Optional[ClusteringVariable]` 
+    
+</dd>
+</dl>
 
-Examples:
-- `0.3`: Results in larger, more diverse clusters.
-- `0.6`: Balances cluster size and article similarity (default).
-- `0.9`: Creates smaller, tightly related clusters.
+<dl>
+<dd>
 
-To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+**clustering_threshold:** `typing.Optional[ClusteringThreshold]` 
     
 </dd>
 </dl>
@@ -1722,17 +1537,7 @@ To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-
 <dl>
 <dd>
 
-**theme:** `typing.Optional[str]` 
-
-Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-Example: `"Finance, Tech"`
-
-**Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
+**theme:** `typing.Optional[Theme]` 
     
 </dd>
 </dl>
@@ -1740,15 +1545,7 @@ Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`
 <dl>
 <dd>
 
-**not_theme:** `typing.Optional[str]` 
-
-Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string. 
-
-Example: `"Crime, Tech"`
-
-**Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**not_theme:** `typing.Optional[NotTheme]` 
     
 </dd>
 </dl>
@@ -1756,15 +1553,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**org_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Apple, Microsoft"`
-
-**Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**org_entity_name:** `typing.Optional[OrgEntityName]` 
     
 </dd>
 </dl>
@@ -1772,15 +1561,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**per_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Elon Musk, Jeff Bezos"`
-
-**Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**per_entity_name:** `typing.Optional[PerEntityName]` 
     
 </dd>
 </dl>
@@ -1788,15 +1569,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**loc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"California, New York"`
-
-**Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**loc_entity_name:** `typing.Optional[LocEntityName]` 
     
 </dd>
 </dl>
@@ -1804,15 +1577,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**misc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Bitcoin, Blockchain"`
-
-**Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**misc_entity_name:** `typing.Optional[MiscEntityName]` 
     
 </dd>
 </dl>
@@ -1820,18 +1585,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**title_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_min:** `typing.Optional[TitleSentimentMin]` 
     
 </dd>
 </dl>
@@ -1839,18 +1593,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**title_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_max:** `typing.Optional[TitleSentimentMax]` 
     
 </dd>
 </dl>
@@ -1858,18 +1601,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_min:** `typing.Optional[ContentSentimentMin]` 
     
 </dd>
 </dl>
@@ -1877,18 +1609,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
     
 </dd>
 </dl>
@@ -1900,8 +1621,6 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 
 Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs. 
 
-Example: `"20000199, 20000209"`
-
 **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
 To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1914,9 +1633,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **not_iptc_tags:** `typing.Optional[str]` 
 
-Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs. 
-
-Example: `"20000205, 20000209"`
+Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
 **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -1930,9 +1647,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **iab_tags:** `typing.Optional[str]` 
 
-Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string. 
-
-Example: `"Business, Events"`
+Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
 **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -1946,9 +1661,7 @@ To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/c
 
 **not_iab_tags:** `typing.Optional[str]` 
 
-Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string. 
-
-Example: `"Agriculture, Metals"`
+Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
 **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -1964,11 +1677,11 @@ To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/c
 
 Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern: 
 
-- `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+- `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
     
 </dd>
 </dl>
@@ -1976,7 +1689,7 @@ To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/
 <dl>
 <dd>
 
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+**robots_compliant:** `typing.Optional[RobotsCompliant]` 
     
 </dd>
 </dl>
@@ -1996,7 +1709,7 @@ To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/
 </dl>
 </details>
 
-<details><summary><code>client.latestheadlines.<a href="src/newscatcher/latestheadlines/client.py">post</a>(...)</code></summary>
+<details><summary><code>client.latest_headlines.<a href="src/newscatcher/latest_headlines/client.py">latest_headlines_post</a>(...) -> LatestHeadlinesPostResponse</code></summary>
 <dl>
 <dd>
 
@@ -2024,15 +1737,16 @@ Retrieves the latest headlines for the specified time period. You can filter res
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
-client.latestheadlines.post(
-    lang="en",
-    predefined_sources=["top 50 US", "top 20 GB"],
-    is_opinion=False,
-    page_size=10,
+
+client.latest_headlines.latest_headlines_post(
+    when="7d",
+    page_size=1,
 )
 
 ```
@@ -2185,6 +1899,14 @@ client.latestheadlines.post(
 <dl>
 <dd>
 
+**all_links_text:** `typing.Optional[AllLinksText]` 
+    
+</dd>
+</dl>
+
+<dl>
+<dd>
+
 **word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
@@ -2405,8 +2127,8 @@ client.latestheadlines.post(
 </dl>
 </details>
 
-## Breaking News
-<details><summary><code>client.breaking_news.<a href="src/newscatcher/breaking_news/client.py">breaking_news_get</a>(...)</code></summary>
+## BreakingNews
+<details><summary><code>client.breaking_news.<a href="src/newscatcher/breaking_news/client.py">breaking_news_get</a>(...) -> BreakingNewsResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -2434,17 +2156,33 @@ Retrieves breaking news articles and sorts them based on specified criteria.
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.breaking_news.breaking_news_get(
+    ranked_only=True,
+    from_rank=100,
+    to_rank=100,
+    page=2,
+    page_size=50,
     top_n_articles=5,
     include_translation_fields=True,
     include_nlp_data=True,
     has_nlp=True,
-    theme="Business,Finance",
-    not_theme="Crime",
+    theme="Finance,Tech",
+    not_theme="Crime,Sports",
+    org_entity_name="\"Apple Inc\" OR Microsoft",
+    per_entity_name="\"Elon Musk\" OR \"Jeff Bezos\"",
+    loc_entity_name="\"San Francisco\" OR \"New York City\"",
+    misc_entity_name="AWS OR \"Microsoft Azure\"",
+    title_sentiment_min=-0.5,
+    title_sentiment_max=0.5,
+    content_sentiment_min=-0.5,
+    content_sentiment_max=0.5,
 )
 
 ```
@@ -2461,12 +2199,7 @@ client.breaking_news.breaking_news_get(
 <dl>
 <dd>
 
-**sort_by:** `typing.Optional[BreakingNewsGetRequestSortBy]` 
-
-The sorting order of the results. Possible values are:
-- `relevancy`: The most relevant results first.
-- `date`: The most recently published results first.
-- `rank`: The results from the highest-ranked sources first.
+**sort_by:** `typing.Optional[SortBy]` 
     
 </dd>
 </dl>
@@ -2474,7 +2207,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**ranked_only:** `typing.Optional[bool]` — If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+**ranked_only:** `typing.Optional[RankedOnly]` 
     
 </dd>
 </dl>
@@ -2482,7 +2215,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**from_rank:** `typing.Optional[int]` — The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**from_rank:** `typing.Optional[FromRank]` 
     
 </dd>
 </dl>
@@ -2490,7 +2223,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**to_rank:** `typing.Optional[int]` — The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**to_rank:** `typing.Optional[ToRank]` 
     
 </dd>
 </dl>
@@ -2498,11 +2231,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**page:** `typing.Optional[int]` 
-
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
-
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -2510,7 +2239,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -2550,33 +2279,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**theme:** `typing.Optional[str]` 
-
-Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-Example: `"Finance, Tech"`
-
-**Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_theme:** `typing.Optional[str]` 
-
-Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string. 
-
-Example: `"Crime, Tech"`
-
-**Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**theme:** `typing.Optional[Theme]` 
     
 </dd>
 </dl>
@@ -2584,15 +2287,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**org_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Apple, Microsoft"`
-
-**Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**not_theme:** `typing.Optional[NotTheme]` 
     
 </dd>
 </dl>
@@ -2600,15 +2295,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**per_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Elon Musk, Jeff Bezos"`
-
-**Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**org_entity_name:** `typing.Optional[OrgEntityName]` 
     
 </dd>
 </dl>
@@ -2616,15 +2303,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**loc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"California, New York"`
-
-**Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**per_entity_name:** `typing.Optional[PerEntityName]` 
     
 </dd>
 </dl>
@@ -2632,15 +2311,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**misc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Bitcoin, Blockchain"`
-
-**Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**loc_entity_name:** `typing.Optional[LocEntityName]` 
     
 </dd>
 </dl>
@@ -2648,18 +2319,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**title_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**misc_entity_name:** `typing.Optional[MiscEntityName]` 
     
 </dd>
 </dl>
@@ -2667,18 +2327,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**title_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_min:** `typing.Optional[TitleSentimentMin]` 
     
 </dd>
 </dl>
@@ -2686,18 +2335,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_max:** `typing.Optional[TitleSentimentMax]` 
     
 </dd>
 </dl>
@@ -2705,18 +2343,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_min:** `typing.Optional[ContentSentimentMin]` 
     
 </dd>
 </dl>
@@ -2724,7 +2351,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
     
 </dd>
 </dl>
@@ -2744,7 +2371,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 </dl>
 </details>
 
-<details><summary><code>client.breaking_news.<a href="src/newscatcher/breaking_news/client.py">breaking_news_post</a>(...)</code></summary>
+<details><summary><code>client.breaking_news.<a href="src/newscatcher/breaking_news/client.py">breaking_news_post</a>(...) -> BreakingNewsResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -2772,15 +2399,17 @@ Retrieves breaking news articles and sorts them based on specified criteria.
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.breaking_news.breaking_news_post(
     sort_by="relevancy",
-    page=1,
-    page_size=100,
-    include_nlp_data=True,
+    ranked_only=True,
+    top_n_articles=1,
 )
 
 ```
@@ -2949,15 +2578,7 @@ client.breaking_news.breaking_news_post(
 <dl>
 <dd>
 
-**content_sentient_max:** `typing.Optional[ContentSentimentMax]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**robots_compliant:** `typing.Optional[RobotsCompliant]` 
+**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
     
 </dd>
 </dl>
@@ -2978,7 +2599,7 @@ client.breaking_news.breaking_news_post(
 </details>
 
 ## Authors
-<details><summary><code>client.authors.<a href="src/newscatcher/authors/client.py">get</a>(...)</code></summary>
+<details><summary><code>client.authors.<a href="src/newscatcher/authors/client.py">get</a>(...) -> AuthorsGetResponse</code></summary>
 <dl>
 <dd>
 
@@ -3005,33 +2626,59 @@ Searches for articles written by a specified author. You can filter results by l
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
+import datetime
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.authors.get(
     author_name="Jane Smith",
-    predefined_sources="top 100 US, top 5 GB",
-    from_=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
+    not_author_name="John Doe, Jane Doe",
+    predefined_sources="top 50 US, top 20 GB",
+    sources="nytimes.com,finance.yahoo.com",
+    not_sources="cnn.com,wsj.com",
+    lang="en,es",
+    not_lang="fr,de",
+    countries="US,CA",
+    not_countries="UK,FR",
+    from_=datetime.datetime.fromisoformat("2024-07-01T00:00:00+00:00"),
+    to=datetime.datetime.fromisoformat("2024-01-01T00:00:00+00:00"),
+    published_date_precision="full",
+    by_parse_date=True,
+    ranked_only=True,
+    from_rank=100,
+    to_rank=100,
+    is_headline=True,
+    is_opinion=True,
+    is_paid_content=False,
+    parent_url="wsj.com/politics,wsj.com/tech",
+    all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+    all_domain_links="who.int,nih.gov",
+    all_links_text="Nvidia,Tesla",
+    word_count_min=300,
+    word_count_max=1000,
+    page=2,
+    page_size=50,
     include_translation_fields=True,
     include_nlp_data=True,
     has_nlp=True,
-    theme="Business,Finance",
-    not_theme="Crime",
-    ner_name="Tesla",
+    theme="Finance,Tech",
+    not_theme="Crime,Sports",
+    ner_name="Tesla,Amazon",
+    title_sentiment_min=-0.5,
+    title_sentiment_max=0.5,
+    content_sentiment_min=-0.5,
+    content_sentiment_max=0.5,
     iptc_tags="20000199,20000209",
     not_iptc_tags="20000205,20000209",
     iab_tags="Business,Events",
     not_iab_tags="Agriculture,Metals",
-    custom_tags="Tag1,Tag2,Tag3",
+    custom_tags="Tag1,Tag2",
+    robots_compliant=True,
 )
 
 ```
@@ -3048,7 +2695,7 @@ client.authors.get(
 <dl>
 <dd>
 
-**author_name:** `str` — The name of the author to search for. This parameter returns exact matches only.
+**author_name:** `AuthorName` 
     
 </dd>
 </dl>
@@ -3056,11 +2703,7 @@ client.authors.get(
 <dl>
 <dd>
 
-**not_author_name:** `typing.Optional[str]` 
-
-The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
-
-Example: `"John Doe, Jane Doe"`
+**not_author_name:** `typing.Optional[str]` — The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
     
 </dd>
 </dl>
@@ -3072,13 +2715,9 @@ Example: `"John Doe, Jane Doe"`
 
 Predefined top news sources per country. 
 
-Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). 
 
-Examples: 
-- `"top 100 US"`
-- `"top 33 AT"`
-- `"top 50 US, top 20 GB"`
-- `"top 33 AT, top 50 IT"`
+Multiple countries with the number of top sources can be specified as a comma-separated string.
     
 </dd>
 </dl>
@@ -3086,13 +2725,7 @@ Examples:
 <dl>
 <dd>
 
-**sources:** `typing.Optional[str]` 
-
-One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-Examples:
-- `"nytimes.com"`
-- `"theguardian.com, finance.yahoo.com"`
+**sources:** `typing.Optional[str]` — One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -3100,11 +2733,7 @@ Examples:
 <dl>
 <dd>
 
-**not_sources:** `typing.Optional[str]` 
-
-The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string. 
-
-Example: `"cnn.com, wsj.com"`
+**not_sources:** `typing.Optional[str]` — The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -3114,11 +2743,9 @@ Example: `"cnn.com, wsj.com"`
 
 **lang:** `typing.Optional[str]` 
 
-The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string. 
+The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-Example: `"en, es"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -3130,9 +2757,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string. 
 
-Example: `"fr, de"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -3144,9 +2769,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-Example: `"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -3158,9 +2781,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 
 The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string. 
 
-Example:`"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -3168,18 +2789,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 <dl>
 <dd>
 
-**from_:** `typing.Optional[dt.datetime]` 
-
-The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `7 day ago`, `today`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -3187,18 +2797,7 @@ Formats with examples:
 <dl>
 <dd>
 
-**to:** `typing.Optional[dt.datetime]` 
-
-The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `1 day ago`, `now`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+**to:** `typing.Optional[To]` 
     
 </dd>
 </dl>
@@ -3206,12 +2805,7 @@ Formats with examples:
 <dl>
 <dd>
 
-**published_date_precision:** `typing.Optional[AuthorsGetRequestPublishedDatePrecision]` 
-
-The precision of the published date. There are three types:
-- `full`: The day and time of an article is correctly identified with the appropriate timezone.
-- `timezone unknown`: The day and time of an article is correctly identified without timezone.
-- `date`: Only the day is identified without an exact time.
+**published_date_precision:** `typing.Optional[PublishedDatePrecision]` 
     
 </dd>
 </dl>
@@ -3219,7 +2813,7 @@ The precision of the published date. There are three types:
 <dl>
 <dd>
 
-**by_parse_date:** `typing.Optional[bool]` — If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+**by_parse_date:** `typing.Optional[ByParseDate]` 
     
 </dd>
 </dl>
@@ -3227,12 +2821,7 @@ The precision of the published date. There are three types:
 <dl>
 <dd>
 
-**sort_by:** `typing.Optional[AuthorsGetRequestSortBy]` 
-
-The sorting order of the results. Possible values are:
-- `relevancy`: The most relevant results first.
-- `date`: The most recently published results first.
-- `rank`: The results from the highest-ranked sources first.
+**sort_by:** `typing.Optional[SortBy]` 
     
 </dd>
 </dl>
@@ -3240,7 +2829,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**ranked_only:** `typing.Optional[bool]` — If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+**ranked_only:** `typing.Optional[RankedOnly]` 
     
 </dd>
 </dl>
@@ -3248,7 +2837,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**from_rank:** `typing.Optional[int]` — The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**from_rank:** `typing.Optional[FromRank]` 
     
 </dd>
 </dl>
@@ -3256,7 +2845,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**to_rank:** `typing.Optional[int]` — The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**to_rank:** `typing.Optional[ToRank]` 
     
 </dd>
 </dl>
@@ -3264,7 +2853,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_headline:** `typing.Optional[bool]` — If true, only returns articles that were posted on the home page of a given news domain.
+**is_headline:** `typing.Optional[IsHeadline]` 
     
 </dd>
 </dl>
@@ -3272,7 +2861,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_opinion:** `typing.Optional[bool]` — If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+**is_opinion:** `typing.Optional[IsOpinion]` 
     
 </dd>
 </dl>
@@ -3280,7 +2869,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_paid_content:** `typing.Optional[bool]` — If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+**is_paid_content:** `typing.Optional[IsPaidContent]` 
     
 </dd>
 </dl>
@@ -3288,11 +2877,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**parent_url:** `typing.Optional[str]` 
-
-The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-Example: `"wsj.com/politics, wsj.com/tech"`
+**parent_url:** `typing.Optional[str]` — The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
     
 </dd>
 </dl>
@@ -3304,9 +2889,7 @@ Example: `"wsj.com/politics, wsj.com/tech"`
 
 The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -3318,9 +2901,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 
 The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-Example: `"who.int, nih.gov"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -3328,7 +2909,13 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**word_count_min:** `typing.Optional[int]` — The minimum number of words an article must contain. To be used for avoiding articles with small content.
+**all_links_text:** `typing.Optional[str]` 
+
+The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
+
+**Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
+
+To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -3336,7 +2923,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**word_count_max:** `typing.Optional[int]` — The maximum number of words an article can contain. To be used for avoiding articles with large content.
+**word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
 </dl>
@@ -3344,11 +2931,15 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**page:** `typing.Optional[int]` 
+**word_count_max:** `typing.Optional[WordCountMax]` 
+    
+</dd>
+</dl>
 
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
+<dl>
+<dd>
 
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -3356,7 +2947,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -3388,17 +2979,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**theme:** `typing.Optional[str]` 
-
-Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-Example: `"Finance, Tech"`
-
-**Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
+**theme:** `typing.Optional[Theme]` 
     
 </dd>
 </dl>
@@ -3406,15 +2987,7 @@ Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`
 <dl>
 <dd>
 
-**not_theme:** `typing.Optional[str]` 
-
-Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string. 
-
-Example: `"Crime, Tech"`
-
-**Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**not_theme:** `typing.Optional[NotTheme]` 
     
 </dd>
 </dl>
@@ -3422,11 +2995,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**ner_name:** `typing.Optional[str]` 
-
-The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string. 
-
-Example: `"Tesla, Amazon"`
+**ner_name:** `typing.Optional[NerName]` 
     
 </dd>
 </dl>
@@ -3434,18 +3003,7 @@ Example: `"Tesla, Amazon"`
 <dl>
 <dd>
 
-**title_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_min:** `typing.Optional[TitleSentimentMin]` 
     
 </dd>
 </dl>
@@ -3453,18 +3011,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**title_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_max:** `typing.Optional[TitleSentimentMax]` 
     
 </dd>
 </dl>
@@ -3472,18 +3019,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_min:** `typing.Optional[ContentSentimentMin]` 
     
 </dd>
 </dl>
@@ -3491,18 +3027,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
     
 </dd>
 </dl>
@@ -3514,8 +3039,6 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 
 Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs. 
 
-Example: `"20000199, 20000209"`
-
 **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
 To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -3528,9 +3051,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **not_iptc_tags:** `typing.Optional[str]` 
 
-Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs. 
-
-Example: `"20000205, 20000209"`
+Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
 **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -3544,9 +3065,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **iab_tags:** `typing.Optional[str]` 
 
-Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string. 
-
-Example: `"Business, Events"`
+Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
 **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -3560,9 +3079,7 @@ To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/c
 
 **not_iab_tags:** `typing.Optional[str]` 
 
-Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string. 
-
-Example: `"Agriculture, Metals"`
+Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
 **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -3578,11 +3095,11 @@ To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/c
 
 Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern: 
 
-- `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+- `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
     
 </dd>
 </dl>
@@ -3590,7 +3107,7 @@ To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/
 <dl>
 <dd>
 
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+**robots_compliant:** `typing.Optional[RobotsCompliant]` 
     
 </dd>
 </dl>
@@ -3610,7 +3127,7 @@ To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/
 </dl>
 </details>
 
-<details><summary><code>client.authors.<a href="src/newscatcher/authors/client.py">post</a>(...)</code></summary>
+<details><summary><code>client.authors.<a href="src/newscatcher/authors/client.py">post</a>(...) -> AuthorsPostResponse</code></summary>
 <dl>
 <dd>
 
@@ -3637,23 +3154,16 @@ Searches for articles by author. You can filter results by language, country, so
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.authors.post(
-    author_name="Joanna Stern",
-    sources=["wsj.com", "nytimes.com"],
-    lang="en",
-    from_=datetime.datetime.fromisoformat(
-        "2024-01-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-06-30 00:00:00+00:00",
-    ),
+    author_name="David Muir",
 )
 
 ```
@@ -3742,7 +3252,7 @@ client.authors.post(
 <dl>
 <dd>
 
-**from_:** `typing.Optional[From]` 
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -3854,6 +3364,14 @@ client.authors.post(
 <dl>
 <dd>
 
+**all_links_text:** `typing.Optional[AllLinksText]` 
+    
+</dd>
+</dl>
+
+<dl>
+<dd>
+
 **word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
@@ -4026,8 +3544,8 @@ client.authors.post(
 </dl>
 </details>
 
-## SearchLink
-<details><summary><code>client.search_link.<a href="src/newscatcher/search_link/client.py">search_url_get</a>(...)</code></summary>
+## SearchByLink
+<details><summary><code>client.search_by_link.<a href="src/newscatcher/search_by_link/client.py">search_by_link_get</a>(...) -> SearchResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -4054,1124 +3572,44 @@ Searches for articles based on specified links or IDs. You can filter results by
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
+import datetime
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
-)
-client.search_link.search_url_get(
-    from_=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-01-01 00:00:00+00:00",
-    ),
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
 
-```
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### ⚙️ Parameters
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-**ids:** `typing.Optional[str]` 
-
-The Newscatcher article ID (corresponds to the `_id` field in API response) or a list of article IDs to search for. To specify multiple IDs, use a comma-separated string. 
-
-Example: `"1234567890abcdef, abcdef1234567890"`
-
-**Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**links:** `typing.Optional[str]` 
-
-The article link or list of article links to search for. To specify multiple links, use a comma-separated string. 
-
-Example: `"https://example.com/article1, https://example.com/article2"`
-
-**Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**from_:** `typing.Optional[From]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**to:** `typing.Optional[To]` 
-    
-</dd>
-</dl>
+client.search_by_link.search_by_link_get(
+    ids="5f8d0d55b6e45e00179c6e7e",
+    links="https://nytimes.com/article1,https://bbc.com/article2",
+    from_=datetime.datetime.fromisoformat("2024-07-01T00:00:00+00:00"),
+    to=datetime.datetime.fromisoformat("2024-01-01T00:00:00+00:00"),
+    page=2,
+    page_size=50,
+    robots_compliant=True,
+)
 
-<dl>
-<dd>
-
-**page:** `typing.Optional[int]` 
-
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
-
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
-    
-</dd>
-</dl>
-</dd>
-</dl>
-
-
-</dd>
-</dl>
-</details>
-
-<details><summary><code>client.search_link.<a href="src/newscatcher/search_link/client.py">search_url_post</a>(...)</code></summary>
-<dl>
-<dd>
-
-#### 📝 Description
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-Searches for articles using their ID(s) or link(s).
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### 🔌 Usage
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-```python
-from newscatcher import NewscatcherApi
-
-client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
-)
-client.search_link.search_url_post(
-    ids=[
-        "8ea8a784568ffaa05cb6d1ab2d2e84dd",
-        "0146a551ef05ab1c494a55e806e3ce64",
-    ],
-    links=[
-        "https://www.nytimes.com/2024/08/30/technology/ai-chatbot-chatgpt-manipulation.html",
-        "https://www.bbc.com/news/articles/c39k379grzlo",
-    ],
-)
-
-```
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### ⚙️ Parameters
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-**ids:** `typing.Optional[Ids]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**links:** `typing.Optional[Links]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**from_:** `typing.Optional[From]` 
-
-The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text strings. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `1 day ago`, `today`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**to:** `typing.Optional[To]` 
-
-The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text strings. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `1 day ago`, `now`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**page:** `typing.Optional[Page]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**page_size:** `typing.Optional[PageSize]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**robots_compliant:** `typing.Optional[RobotsCompliant]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
-    
-</dd>
-</dl>
-</dd>
-</dl>
-
-
-</dd>
-</dl>
-</details>
-
-## SearchSimilar
-<details><summary><code>client.searchsimilar.<a href="src/newscatcher/searchsimilar/client.py">get</a>(...)</code></summary>
-<dl>
-<dd>
-
-#### 📝 Description
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-Searches for articles similar to a specified query.
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### 🔌 Usage
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-```python
-import datetime
-
-from newscatcher import NewscatcherApi
-
-client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
-)
-client.searchsimilar.get(
-    q="technology AND (Apple OR Microsoft) NOT Google",
-    search_in="title_content, title_content_translated",
-    include_translation_fields=True,
-    similar_documents_fields="title,summary",
-    predefined_sources="top 100 US, top 5 GB",
-    from_=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
-    include_nlp_data=True,
-    has_nlp=True,
-    theme="Business,Finance",
-    not_theme="Crime",
-    ner_name="Tesla",
-    iptc_tags="20000199,20000209",
-    not_iptc_tags="20000205,20000209",
-    custom_tags="Tag1,Tag2,Tag3",
-)
-
-```
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### ⚙️ Parameters
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-**q:** `str` 
-
-The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-- For an exact match, use double quotes. For example, `"technology news"`.
-- Use `*` to search for any keyword.
-- Use `+` to include and `-` to exclude specific words or phrases. 
-  For example, `+Apple`, `-Google`.
-- Use `AND`, `OR`, and `NOT` to refine search results. 
-  For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**search_in:** `typing.Optional[SearchIn]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**include_translation_fields:** `typing.Optional[IncludeTranslationFields]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**include_similar_documents:** `typing.Optional[bool]` — If true, includes similar documents in the response.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**similar_documents_number:** `typing.Optional[int]` — The number of similar documents to return.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**similar_documents_fields:** `typing.Optional[str]` — The fields to consider for finding similar documents.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**predefined_sources:** `typing.Optional[str]` 
-
-Predefined top news sources per country. 
-
-Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
-
-Examples: 
-- `"top 100 US"`
-- `"top 33 AT"`
-- `"top 50 US, top 20 GB"`
-- `"top 33 AT, top 50 IT"`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**sources:** `typing.Optional[str]` 
-
-One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-Examples:
-- `"nytimes.com"`
-- `"theguardian.com, finance.yahoo.com"`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_sources:** `typing.Optional[str]` 
-
-The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string. 
-
-Example: `"cnn.com, wsj.com"`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**lang:** `typing.Optional[str]` 
-
-The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string. 
-
-Example: `"en, es"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_lang:** `typing.Optional[str]` 
-
-The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string. 
-
-Example: `"fr, de"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**countries:** `typing.Optional[str]` 
-
-The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
-
-Example: `"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_countries:** `typing.Optional[str]` 
-
-The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string. 
-
-Example:`"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**from_:** `typing.Optional[dt.datetime]` 
-
-The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `7 day ago`, `today`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**to:** `typing.Optional[dt.datetime]` 
-
-The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `1 day ago`, `now`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**by_parse_date:** `typing.Optional[bool]` — If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**published_date_precision:** `typing.Optional[SearchSimilarGetRequestPublishedDatePrecision]` 
-
-The precision of the published date. There are three types:
-- `full`: The day and time of an article is correctly identified with the appropriate timezone.
-- `timezone unknown`: The day and time of an article is correctly identified without timezone.
-- `date`: Only the day is identified without an exact time.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**sort_by:** `typing.Optional[SearchSimilarGetRequestSortBy]` 
-
-The sorting order of the results. Possible values are:
-- `relevancy`: The most relevant results first.
-- `date`: The most recently published results first.
-- `rank`: The results from the highest-ranked sources first.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**ranked_only:** `typing.Optional[bool]` — If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**from_rank:** `typing.Optional[int]` — The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**to_rank:** `typing.Optional[int]` — The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**is_headline:** `typing.Optional[bool]` — If true, only returns articles that were posted on the home page of a given news domain.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**is_opinion:** `typing.Optional[bool]` — If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**is_paid_content:** `typing.Optional[bool]` — If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**parent_url:** `typing.Optional[str]` 
-
-The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-Example: `"wsj.com/politics, wsj.com/tech"`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**all_links:** `typing.Optional[str]` 
-
-The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
-
-Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**all_domain_links:** `typing.Optional[str]` 
-
-The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
-
-Example: `"who.int, nih.gov"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**word_count_min:** `typing.Optional[int]` — The minimum number of words an article must contain. To be used for avoiding articles with small content.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**word_count_max:** `typing.Optional[int]` — The maximum number of words an article can contain. To be used for avoiding articles with large content.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**page:** `typing.Optional[int]` 
-
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
-
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**include_nlp_data:** `typing.Optional[IncludeNlpData]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**has_nlp:** `typing.Optional[HasNlp]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**theme:** `typing.Optional[str]` 
-
-Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-Example: `"Finance, Tech"`
-
-**Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_theme:** `typing.Optional[str]` 
-
-Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string. 
-
-Example: `"Crime, Tech"`
-
-**Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**ner_name:** `typing.Optional[str]` 
-
-The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string. 
-
-Example: `"Tesla, Amazon"`
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**title_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**title_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**content_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**content_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**iptc_tags:** `typing.Optional[str]` 
-
-Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs. 
-
-Example: `"20000199, 20000209"`
-
-**Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_iptc_tags:** `typing.Optional[str]` 
-
-Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs. 
-
-Example: `"20000205, 20000209"`
-
-**Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**custom_tags:** `typing.Optional[str]` 
-
-Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern: 
-
-- `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
-
-To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
-    
-</dd>
-</dl>
-</dd>
-</dl>
-
-
-</dd>
-</dl>
-</details>
-
-<details><summary><code>client.searchsimilar.<a href="src/newscatcher/searchsimilar/client.py">post</a>(...)</code></summary>
-<dl>
-<dd>
-
-#### 📝 Description
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-Searches for articles similar to the specified query. You can filter results by language, country, source, and more.
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### 🔌 Usage
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-```python
-from newscatcher import NewscatcherApi
-
-client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
-)
-client.searchsimilar.post(
-    q="artificial intelligence",
-    include_similar_documents=True,
-    similar_documents_number=5,
-)
-
-```
-</dd>
-</dl>
-</dd>
-</dl>
-
-#### ⚙️ Parameters
-
-<dl>
-<dd>
-
-<dl>
-<dd>
-
-**q:** `Q` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**search_in:** `typing.Optional[SearchIn]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**include_translation_fields:** `typing.Optional[IncludeTranslationFields]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**include_similar_documents:** `typing.Optional[IncludeSimilarDocuments]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**similar_documents_number:** `typing.Optional[SimilarDocumentsNumber]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**similar_documents_fields:** `typing.Optional[SimilarDocumentsFields]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**predefined_sources:** `typing.Optional[PredefinedSources]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**sources:** `typing.Optional[Sources]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_sources:** `typing.Optional[NotSources]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**lang:** `typing.Optional[Lang]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_lang:** `typing.Optional[NotLang]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**countries:** `typing.Optional[Countries]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**not_countries:** `typing.Optional[NotCountries]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**from_:** `typing.Optional[From]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**to:** `typing.Optional[To]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**by_parse_date:** `typing.Optional[ByParseDate]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**published_date_precision:** `typing.Optional[PublishedDatePrecision]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**sort_by:** `typing.Optional[SortBy]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**ranked_only:** `typing.Optional[RankedOnly]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**from_rank:** `typing.Optional[FromRank]` 
-    
-</dd>
-</dl>
-
-<dl>
-<dd>
-
-**to_rank:** `typing.Optional[ToRank]` 
-    
+```
+</dd>
+</dl>
 </dd>
 </dl>
 
+#### ⚙️ Parameters
+
 <dl>
 <dd>
 
-**is_headline:** `typing.Optional[IsHeadline]` 
-    
-</dd>
-</dl>
-
 <dl>
 <dd>
 
-**is_opinion:** `typing.Optional[IsOpinion]` 
+**ids:** `typing.Optional[str]` 
+
+The Newscatcher article ID (corresponds to the `_id` field in API response) or a list of article IDs to search for. To specify multiple IDs, use a comma-separated string. 
+
+**Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
     
 </dd>
 </dl>
@@ -5179,7 +3617,11 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**is_paid_content:** `typing.Optional[IsPaidContent]` 
+**links:** `typing.Optional[str]` 
+
+The article link or list of article links to search for. To specify multiple links, use a comma-separated string.
+
+**Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
     
 </dd>
 </dl>
@@ -5187,7 +3629,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**parent_url:** `typing.Optional[ParentUrl]` 
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -5195,7 +3637,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**all_links:** `typing.Optional[AllLinks]` 
+**to:** `typing.Optional[To]` 
     
 </dd>
 </dl>
@@ -5203,7 +3645,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**all_domain_links:** `typing.Optional[AllDomainLinks]` 
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -5211,7 +3653,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**word_count_min:** `typing.Optional[WordCountMin]` 
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -5219,7 +3661,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**word_count_max:** `typing.Optional[WordCountMax]` 
+**robots_compliant:** `typing.Optional[RobotsCompliant]` 
     
 </dd>
 </dl>
@@ -5227,71 +3669,72 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**page:** `typing.Optional[Page]` 
+**request_options:** `typing.Optional[RequestOptions]` — Request-specific configuration.
     
 </dd>
 </dl>
+</dd>
+</dl>
 
-<dl>
-<dd>
 
-**page_size:** `typing.Optional[PageSize]` 
-    
 </dd>
 </dl>
+</details>
 
+<details><summary><code>client.search_by_link.<a href="src/newscatcher/search_by_link/client.py">search_by_link_post</a>(...) -> SearchResponseDto</code></summary>
 <dl>
 <dd>
 
-**include_nlp_data:** `typing.Optional[IncludeNlpData]` 
-    
-</dd>
-</dl>
+#### 📝 Description
 
 <dl>
 <dd>
 
-**has_nlp:** `typing.Optional[HasNlp]` 
-    
-</dd>
-</dl>
-
 <dl>
 <dd>
 
-**theme:** `typing.Optional[Theme]` 
-    
+Searches for articles using their ID(s) or link(s).
 </dd>
 </dl>
+</dd>
+</dl>
+
+#### 🔌 Usage
 
 <dl>
 <dd>
 
-**not_theme:** `typing.Optional[NotTheme]` 
-    
-</dd>
-</dl>
-
 <dl>
 <dd>
 
-**ner_name:** `typing.Optional[NerName]` 
-    
+```python
+from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
+
+client = NewscatcherApi(
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
+)
+
+client.search_by_link.search_by_link_post(
+    links="https://www.reuters.com/business/energy/oil-prices-up-after-israeli-attacks-oversupply-caps-gains-2025-09-10/",
+)
+
+```
 </dd>
 </dl>
+</dd>
+</dl>
+
+#### ⚙️ Parameters
 
 <dl>
 <dd>
 
-**title_sentiment_min:** `typing.Optional[TitleSentimentMin]` 
-    
-</dd>
-</dl>
-
 <dl>
 <dd>
 
-**title_sentiment_max:** `typing.Optional[TitleSentimentMax]` 
+**ids:** `typing.Optional[Ids]` 
     
 </dd>
 </dl>
@@ -5299,7 +3742,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**content_sentiment_min:** `typing.Optional[ContentSentimentMin]` 
+**links:** `typing.Optional[Links]` 
     
 </dd>
 </dl>
@@ -5307,7 +3750,16 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
+**from:** `typing.Optional[From]` 
+
+The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text strings. The default time zone is UTC. 
+
+Formats with examples:
+- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
+- YYYY-MM-dd: `2024-07-01`
+- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
+- YYYY/mm/dd: `2024/07/01`
+- English phrases: `1 day ago`, `today`
     
 </dd>
 </dl>
@@ -5315,7 +3767,16 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**iptc_tags:** `typing.Optional[IptcTags]` 
+**to:** `typing.Optional[To]` 
+
+The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text strings. The default time zone is UTC. 
+
+Formats with examples:
+- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
+- YYYY-MM-dd: `2024-07-01`
+- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
+- YYYY/mm/dd: `2024/07/01`
+- English phrases: `1 day ago`, `now`
     
 </dd>
 </dl>
@@ -5323,7 +3784,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**not_iptc_tags:** `typing.Optional[NotIptcTags]` 
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -5331,7 +3792,7 @@ client.searchsimilar.post(
 <dl>
 <dd>
 
-**custom_tags:** `typing.Optional[CustomTags]` 
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -5360,7 +3821,7 @@ client.searchsimilar.post(
 </details>
 
 ## Sources
-<details><summary><code>client.sources.<a href="src/newscatcher/sources/client.py">get</a>(...)</code></summary>
+<details><summary><code>client.sources.<a href="src/newscatcher/sources/client.py">get</a>(...) -> SourcesResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -5388,13 +3849,24 @@ Retrieves a list of sources based on specified criteria such as language, countr
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.sources.get(
-    predefined_sources="top 100 US, top 5 GB",
+    lang="en,es",
+    countries="US,CA",
+    predefined_sources="top 50 US, top 20 GB",
+    source_name="sport,tech",
     source_url="bbc.com",
+    include_additional_info=True,
+    is_news_domain=True,
+    news_type="General News Outlets,Tech News and Updates",
+    from_rank=100,
+    to_rank=100,
 )
 
 ```
@@ -5413,11 +3885,9 @@ client.sources.get(
 
 **lang:** `typing.Optional[str]` 
 
-The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string. 
-
-Example: `"en, es"`
+The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -5429,9 +3899,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-Example: `"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -5443,13 +3911,9 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 
 Predefined top news sources per country. 
 
-Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). 
 
-Examples: 
-- `"top 100 US"`
-- `"top 33 AT"`
-- `"top 50 US, top 20 GB"`
-- `"top 33 AT, top 50 IT"`
+Multiple countries with the number of top sources can be specified as a comma-separated string.
     
 </dd>
 </dl>
@@ -5461,8 +3925,6 @@ Examples:
 
 Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-Example: `"sport, tech"`
-
 **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
     
 </dd>
@@ -5484,15 +3946,7 @@ you can only use `include_additional_info` as an extra parameter.
 <dl>
 <dd>
 
-**include_additional_info:** `typing.Optional[bool]` 
-
-If true, returns the following additional datapoints about each news source:
-- `nb_articles_for_7d`: The number of articles published by the source in the last week.
-- `country`: Source country of origin.
-- `rank`: SEO rank.
-- `is_news_domain`: Boolean indicating if the source is a news domain.
-- `news_domain_type`: Type of news domain (e.g., "Original Content").
-- `news_type`: Category of news (e.g., "General News Outlets").
+**include_additional_info:** `typing.Optional[IncludeAdditionalInfo]` 
     
 </dd>
 </dl>
@@ -5500,7 +3954,7 @@ If true, returns the following additional datapoints about each news source:
 <dl>
 <dd>
 
-**is_news_domain:** `typing.Optional[bool]` — If true, filters results to include only news domains.
+**is_news_domain:** `typing.Optional[IsNewsDomain]` 
     
 </dd>
 </dl>
@@ -5508,14 +3962,7 @@ If true, returns the following additional datapoints about each news source:
 <dl>
 <dd>
 
-**news_domain_type:** `typing.Optional[SourcesGetRequestNewsDomainType]` 
-
-Filters results based on the news domain type. Possible values are:
-- `Original Content`: Sources that produce their own content.
-- `Aggregator`: Sources that collect content from various other sources.
-- `Press Releases`: Sources primarily publishing press releases.
-- `Republisher`: Sources that republish content from other sources.
-- `Other`: Sources that don't fit into main categories.
+**news_domain_type:** `typing.Optional[NewsDomainType]` 
     
 </dd>
 </dl>
@@ -5527,9 +3974,7 @@ Filters results based on the news domain type. Possible values are:
 
 Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-Example: `"General News Outlets,Tech News and Updates"`
-
-For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
+For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
     
 </dd>
 </dl>
@@ -5537,7 +3982,7 @@ For a complete list of available news types, see [Enumerated parameters > News t
 <dl>
 <dd>
 
-**from_rank:** `typing.Optional[int]` — The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**from_rank:** `typing.Optional[FromRank]` 
     
 </dd>
 </dl>
@@ -5545,7 +3990,7 @@ For a complete list of available news types, see [Enumerated parameters > News t
 <dl>
 <dd>
 
-**to_rank:** `typing.Optional[int]` — The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**to_rank:** `typing.Optional[ToRank]` 
     
 </dd>
 </dl>
@@ -5565,7 +4010,7 @@ For a complete list of available news types, see [Enumerated parameters > News t
 </dl>
 </details>
 
-<details><summary><code>client.sources.<a href="src/newscatcher/sources/client.py">post</a>(...)</code></summary>
+<details><summary><code>client.sources.<a href="src/newscatcher/sources/client.py">post</a>(...) -> SourcesResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -5593,16 +4038,15 @@ Retrieves the list of sources available in the database. You can filter the sour
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.sources.post(
-    predefined_sources=["top 50 US"],
-    include_additional_info=True,
-    is_news_domain=True,
-    news_domain_type="Original Content",
-    news_type="General News Outlets",
+    predefined_sources="top 10 US",
 )
 
 ```
@@ -5720,7 +4164,7 @@ client.sources.post(
 </details>
 
 ## Aggregation
-<details><summary><code>client.aggregation.<a href="src/newscatcher/aggregation/client.py">get</a>(...)</code></summary>
+<details><summary><code>client.aggregation.<a href="src/newscatcher/aggregation/client.py">count_get</a>(...) -> AggregationCountGetResponse</code></summary>
 <dl>
 <dd>
 
@@ -5747,29 +4191,59 @@ Retrieves the count of articles aggregated by day or hour based on various searc
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
+import datetime
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
-client.aggregation.get(
-    q="technology AND (Apple OR Microsoft) NOT Google",
+
+client.aggregation.count_get(
+    q="\"supply chain\" AND Amazon NOT China",
     search_in="title_content, title_content_translated",
-    predefined_sources="top 100 US, top 5 GB",
-    from_=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-07-01 00:00:00+00:00",
-    ),
+    predefined_sources="top 50 US, top 20 GB",
+    sources="nytimes.com,finance.yahoo.com",
+    not_sources="cnn.com,wsj.com",
+    lang="en,es",
+    not_lang="fr,de",
+    countries="US,CA",
+    not_countries="UK,FR",
+    not_author_name="John Doe, Jane Doe",
+    from_=datetime.datetime.fromisoformat("2024-07-01T00:00:00+00:00"),
+    to=datetime.datetime.fromisoformat("2024-01-01T00:00:00+00:00"),
+    published_date_precision="full",
+    by_parse_date=True,
+    ranked_only=True,
+    from_rank=100,
+    to_rank=100,
+    is_headline=True,
+    is_opinion=True,
+    is_paid_content=False,
+    parent_url="wsj.com/politics,wsj.com/tech",
+    all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+    all_domain_links="who.int,nih.gov",
+    all_links_text="Nvidia,Tesla",
+    word_count_min=300,
+    word_count_max=1000,
+    page=2,
+    page_size=50,
     include_nlp_data=True,
     has_nlp=True,
-    theme="Business,Finance",
-    not_theme="Crime",
+    theme="Finance,Tech",
+    not_theme="Crime,Sports",
+    org_entity_name="\"Apple Inc\" OR Microsoft",
+    per_entity_name="\"Elon Musk\" OR \"Jeff Bezos\"",
+    loc_entity_name="\"San Francisco\" OR \"New York City\"",
+    misc_entity_name="AWS OR \"Microsoft Azure\"",
+    title_sentiment_min=-0.5,
+    title_sentiment_max=0.5,
+    content_sentiment_min=-0.5,
+    content_sentiment_max=0.5,
     iptc_tags="20000199,20000209",
     not_iptc_tags="20000205,20000209",
+    robots_compliant=True,
 )
 
 ```
@@ -5786,18 +4260,7 @@ client.aggregation.get(
 <dl>
 <dd>
 
-**q:** `str` 
-
-The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-- For an exact match, use double quotes. For example, `"technology news"`.
-- Use `*` to search for any keyword.
-- Use `+` to include and `-` to exclude specific words or phrases. 
-  For example, `+Apple`, `-Google`.
-- Use `AND`, `OR`, and `NOT` to refine search results. 
-  For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+**q:** `Q` 
     
 </dd>
 </dl>
@@ -5825,13 +4288,9 @@ For more details, see [Advanced querying](/docs/v3/documentation/guides-and-conc
 
 Predefined top news sources per country. 
 
-Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). 
 
-Examples: 
-- `"top 100 US"`
-- `"top 33 AT"`
-- `"top 50 US, top 20 GB"`
-- `"top 33 AT, top 50 IT"`
+Multiple countries with the number of top sources can be specified as a comma-separated string.
     
 </dd>
 </dl>
@@ -5839,13 +4298,7 @@ Examples:
 <dl>
 <dd>
 
-**sources:** `typing.Optional[str]` 
-
-One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-Examples:
-- `"nytimes.com"`
-- `"theguardian.com, finance.yahoo.com"`
+**sources:** `typing.Optional[str]` — One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -5853,11 +4306,7 @@ Examples:
 <dl>
 <dd>
 
-**not_sources:** `typing.Optional[str]` 
-
-The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string. 
-
-Example: `"cnn.com, wsj.com"`
+**not_sources:** `typing.Optional[str]` — The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
     
 </dd>
 </dl>
@@ -5867,11 +4316,9 @@ Example: `"cnn.com, wsj.com"`
 
 **lang:** `typing.Optional[str]` 
 
-The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string. 
-
-Example: `"en, es"`
+The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -5883,9 +4330,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string. 
 
-Example: `"fr, de"`
-
-To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
     
 </dd>
 </dl>
@@ -5897,9 +4342,7 @@ To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/ove
 
 The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-Example: `"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -5911,9 +4354,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 
 The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string. 
 
-Example:`"US, CA"`
-
-To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
     
 </dd>
 </dl>
@@ -5921,11 +4362,7 @@ To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/over
 <dl>
 <dd>
 
-**not_author_name:** `typing.Optional[str]` 
-
-The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
-
-Example: `"John Doe, Jane Doe"`
+**not_author_name:** `typing.Optional[str]` — The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
     
 </dd>
 </dl>
@@ -5933,18 +4370,7 @@ Example: `"John Doe, Jane Doe"`
 <dl>
 <dd>
 
-**from_:** `typing.Optional[dt.datetime]` 
-
-The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `7 day ago`, `today`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -5952,18 +4378,7 @@ Formats with examples:
 <dl>
 <dd>
 
-**to:** `typing.Optional[dt.datetime]` 
-
-The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC. 
-
-Formats with examples:
-- YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-- YYYY-MM-dd: `2024-07-01`
-- YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-- YYYY/mm/dd: `2024/07/01`
-- English phrases: `1 day ago`, `now`
-
-**Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+**to:** `typing.Optional[To]` 
     
 </dd>
 </dl>
@@ -5971,12 +4386,7 @@ Formats with examples:
 <dl>
 <dd>
 
-**published_date_precision:** `typing.Optional[AggregationGetRequestPublishedDatePrecision]` 
-
-The precision of the published date. There are three types:
-- `full`: The day and time of an article is correctly identified with the appropriate timezone.
-- `timezone unknown`: The day and time of an article is correctly identified without timezone.
-- `date`: Only the day is identified without an exact time.
+**published_date_precision:** `typing.Optional[PublishedDatePrecision]` 
     
 </dd>
 </dl>
@@ -5984,7 +4394,7 @@ The precision of the published date. There are three types:
 <dl>
 <dd>
 
-**by_parse_date:** `typing.Optional[bool]` — If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+**by_parse_date:** `typing.Optional[ByParseDate]` 
     
 </dd>
 </dl>
@@ -5992,12 +4402,7 @@ The precision of the published date. There are three types:
 <dl>
 <dd>
 
-**sort_by:** `typing.Optional[AggregationGetRequestSortBy]` 
-
-The sorting order of the results. Possible values are:
-- `relevancy`: The most relevant results first.
-- `date`: The most recently published results first.
-- `rank`: The results from the highest-ranked sources first.
+**sort_by:** `typing.Optional[SortBy]` 
     
 </dd>
 </dl>
@@ -6005,7 +4410,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**ranked_only:** `typing.Optional[bool]` — If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+**ranked_only:** `typing.Optional[RankedOnly]` 
     
 </dd>
 </dl>
@@ -6013,7 +4418,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**from_rank:** `typing.Optional[int]` — The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**from_rank:** `typing.Optional[FromRank]` 
     
 </dd>
 </dl>
@@ -6021,7 +4426,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**to_rank:** `typing.Optional[int]` — The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+**to_rank:** `typing.Optional[ToRank]` 
     
 </dd>
 </dl>
@@ -6029,7 +4434,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_headline:** `typing.Optional[bool]` — If true, only returns articles that were posted on the home page of a given news domain.
+**is_headline:** `typing.Optional[IsHeadline]` 
     
 </dd>
 </dl>
@@ -6037,7 +4442,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_opinion:** `typing.Optional[bool]` — If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+**is_opinion:** `typing.Optional[IsOpinion]` 
     
 </dd>
 </dl>
@@ -6045,7 +4450,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**is_paid_content:** `typing.Optional[bool]` — If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+**is_paid_content:** `typing.Optional[IsPaidContent]` 
     
 </dd>
 </dl>
@@ -6053,11 +4458,7 @@ The sorting order of the results. Possible values are:
 <dl>
 <dd>
 
-**parent_url:** `typing.Optional[str]` 
-
-The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-Example: `"wsj.com/politics, wsj.com/tech"`
+**parent_url:** `typing.Optional[str]` — The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
     
 </dd>
 </dl>
@@ -6069,9 +4470,7 @@ Example: `"wsj.com/politics, wsj.com/tech"`
 
 The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -6083,9 +4482,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 
 The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-Example: `"who.int, nih.gov"`
-
-For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -6093,7 +4490,13 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**word_count_min:** `typing.Optional[int]` — The minimum number of words an article must contain. To be used for avoiding articles with small content.
+**all_links_text:** `typing.Optional[str]` 
+
+The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
+
+**Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
+
+To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
     
 </dd>
 </dl>
@@ -6101,7 +4504,7 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**word_count_max:** `typing.Optional[int]` — The maximum number of words an article can contain. To be used for avoiding articles with large content.
+**word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
 </dl>
@@ -6109,11 +4512,15 @@ For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-ur
 <dl>
 <dd>
 
-**page:** `typing.Optional[int]` 
+**word_count_max:** `typing.Optional[WordCountMax]` 
+    
+</dd>
+</dl>
 
-The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles. 
+<dl>
+<dd>
 
-For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+**page:** `typing.Optional[Page]` 
     
 </dd>
 </dl>
@@ -6121,7 +4528,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**page_size:** `typing.Optional[int]` — The number of articles to return per page.
+**page_size:** `typing.Optional[PageSize]` 
     
 </dd>
 </dl>
@@ -6145,17 +4552,7 @@ For details, see [How to paginate large datasets](https://www.newscatcherapi.com
 <dl>
 <dd>
 
-**theme:** `typing.Optional[str]` 
-
-Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-Example: `"Finance, Tech"`
-
-**Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
+**theme:** `typing.Optional[Theme]` 
     
 </dd>
 </dl>
@@ -6163,15 +4560,7 @@ Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`
 <dl>
 <dd>
 
-**not_theme:** `typing.Optional[str]` 
-
-Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string. 
-
-Example: `"Crime, Tech"`
-
-**Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**not_theme:** `typing.Optional[NotTheme]` 
     
 </dd>
 </dl>
@@ -6179,15 +4568,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**org_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Apple, Microsoft"`
-
-**Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**org_entity_name:** `typing.Optional[OrgEntityName]` 
     
 </dd>
 </dl>
@@ -6195,15 +4576,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**per_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Elon Musk, Jeff Bezos"`
-
-**Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**per_entity_name:** `typing.Optional[PerEntityName]` 
     
 </dd>
 </dl>
@@ -6211,15 +4584,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**loc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"California, New York"`
-
-**Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**loc_entity_name:** `typing.Optional[LocEntityName]` 
     
 </dd>
 </dl>
@@ -6227,15 +4592,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**misc_entity_name:** `typing.Optional[str]` 
-
-Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-Example: `"Bitcoin, Blockchain"`
-
-**Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
+**misc_entity_name:** `typing.Optional[MiscEntityName]` 
     
 </dd>
 </dl>
@@ -6243,18 +4600,7 @@ To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-en
 <dl>
 <dd>
 
-**title_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_min:** `typing.Optional[TitleSentimentMin]` 
     
 </dd>
 </dl>
@@ -6262,18 +4608,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**title_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their titles.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**title_sentiment_max:** `typing.Optional[TitleSentimentMax]` 
     
 </dd>
 </dl>
@@ -6281,18 +4616,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_min:** `typing.Optional[float]` 
-
-Filters articles based on the minimum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_min:** `typing.Optional[ContentSentimentMin]` 
     
 </dd>
 </dl>
@@ -6300,18 +4624,7 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 <dl>
 <dd>
 
-**content_sentiment_max:** `typing.Optional[float]` 
-
-Filters articles based on the maximum sentiment score of their content.
-
-Range is `-1.0` to `1.0`, where:
-- Negative values indicate negative sentiment.
-- Positive values indicate positive sentiment.
-- Values close to 0 indicate neutral sentiment.
-
-**Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+**content_sentiment_max:** `typing.Optional[ContentSentimentMax]` 
     
 </dd>
 </dl>
@@ -6323,8 +4636,6 @@ To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp
 
 Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs. 
 
-Example: `"20000199, 20000209"`
-
 **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
 To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -6337,9 +4648,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 
 **not_iptc_tags:** `typing.Optional[str]` 
 
-Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs. 
-
-Example: `"20000205, 20000209"`
+Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
 **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
@@ -6351,7 +4660,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 <dl>
 <dd>
 
-**robots_compliant:** `typing.Optional[bool]` — If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+**robots_compliant:** `typing.Optional[RobotsCompliant]` 
     
 </dd>
 </dl>
@@ -6371,7 +4680,7 @@ To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCod
 </dl>
 </details>
 
-<details><summary><code>client.aggregation.<a href="src/newscatcher/aggregation/client.py">post</a>(...)</code></summary>
+<details><summary><code>client.aggregation.<a href="src/newscatcher/aggregation/client.py">count_post</a>(...) -> AggregationCountPostResponse</code></summary>
 <dl>
 <dd>
 
@@ -6398,23 +4707,17 @@ Retrieves the count of articles aggregated by day or hour based on various searc
 <dd>
 
 ```python
-import datetime
-
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
-client.aggregation.post(
-    q="renewable energy",
+
+client.aggregation.count_post(
+    q="\"supply chain\" AND Amazon NOT China",
     aggregation_by="day",
-    predefined_sources="top 50 US",
-    from_=datetime.datetime.fromisoformat(
-        "2024-01-01 00:00:00+00:00",
-    ),
-    to=datetime.datetime.fromisoformat(
-        "2024-06-30 00:00:00+00:00",
-    ),
 )
 
 ```
@@ -6519,7 +4822,7 @@ client.aggregation.post(
 <dl>
 <dd>
 
-**from_:** `typing.Optional[From]` 
+**from:** `typing.Optional[From]` 
     
 </dd>
 </dl>
@@ -6631,6 +4934,14 @@ client.aggregation.post(
 <dl>
 <dd>
 
+**all_links_text:** `typing.Optional[AllLinksText]` 
+    
+</dd>
+</dl>
+
+<dl>
+<dd>
+
 **word_count_min:** `typing.Optional[WordCountMin]` 
     
 </dd>
@@ -6796,7 +5107,7 @@ client.aggregation.post(
 </details>
 
 ## Subscription
-<details><summary><code>client.subscription.<a href="src/newscatcher/subscription/client.py">get</a>()</code></summary>
+<details><summary><code>client.subscription.<a href="src/newscatcher/subscription/client.py">get</a>() -> SubscriptionResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -6824,10 +5135,13 @@ Retrieves information about your subscription plan.
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.subscription.get()
 
 ```
@@ -6856,7 +5170,7 @@ client.subscription.get()
 </dl>
 </details>
 
-<details><summary><code>client.subscription.<a href="src/newscatcher/subscription/client.py">post</a>()</code></summary>
+<details><summary><code>client.subscription.<a href="src/newscatcher/subscription/client.py">post</a>() -> SubscriptionResponseDto</code></summary>
 <dl>
 <dd>
 
@@ -6884,10 +5198,13 @@ Retrieves information about your subscription plan.
 
 ```python
 from newscatcher import NewscatcherApi
+from newscatcher.environment import NewscatcherApiEnvironment
 
 client = NewscatcherApi(
-    api_key="YOUR_API_KEY",
+    api_key="<value>",
+    environment=NewscatcherApiEnvironment.DEFAULT,
 )
+
 client.subscription.post()
 
 ```
diff --git a/src/newscatcher/__init__.py b/src/newscatcher/__init__.py
index 17df0a5..d36abec 100644
--- a/src/newscatcher/__init__.py
+++ b/src/newscatcher/__init__.py
@@ -2,194 +2,309 @@
 
 # isort: skip_file
 
-from .types import (
-    AdditionalDomainInfo,
-    AdditionalDomainInfoEntity,
-    AdditionalSourceInfo,
-    AggregationBy,
-    AggregationCountResponseDto,
-    AggregationItem,
-    Aggregations,
-    AllDomainLinks,
-    AllLinks,
-    ArticleEntity,
-    ArticleEntityAllDomainLinks,
-    ArticleEntityAllLinks,
-    Articles,
-    AuthorName,
-    Authors,
-    BaseSearchResponseDto,
-    BreakingNewsArticleEntity,
-    BreakingNewsArticleEntityAllDomainLinks,
-    BreakingNewsArticleEntityAllLinks,
-    BreakingNewsEventEntity,
-    BreakingNewsResponseDto,
-    ByParseDate,
-    ClusterEntity,
-    ClusteredArticlesDto,
-    ClusteredSearchResponseDto,
-    ClusteringEnabled,
-    ClusteringThreshold,
-    ClusteringVariable,
-    ContentSentimentMax,
-    ContentSentimentMin,
-    Countries,
-    CustomTags,
-    Error,
-    ExcludeDuplicates,
-    FailedAggregationCountResponseDto,
-    FailedAuthorsResponseDto,
-    FailedSearchSimilarResponseDto,
-    From,
-    FromRank,
-    HasNlp,
-    IabTags,
-    Ids,
-    IncludeAdditionalInfo,
-    IncludeNlpData,
-    IncludeSimilarDocuments,
-    IncludeTranslationFields,
-    IptcTags,
-    IsHeadline,
-    IsNewsDomain,
-    IsOpinion,
-    IsPaidContent,
-    Journalists,
-    Lang,
-    Links,
-    LocEntityName,
-    MiscEntityName,
-    NamedEntityList,
-    NamedEntityListItem,
-    NerName,
-    NewsDomainType,
-    NewsType,
-    NlpDataEntity,
-    NotAuthorName,
-    NotCountries,
-    NotIabTags,
-    NotIptcTags,
-    NotLang,
-    NotSources,
-    NotTheme,
-    OrgEntityName,
-    Page,
-    PageSize,
-    ParentUrl,
-    PerEntityName,
-    PredefinedSources,
-    PublishedDatePrecision,
-    Q,
-    RankedOnly,
-    RobotsCompliant,
-    SearchIn,
-    SearchResponseDto,
-    SearchSimilarResponseDto,
-    SentimentScores,
-    SimilarArticleEntity,
-    SimilarDocument,
-    SimilarDocumentsFields,
-    SimilarDocumentsNumber,
-    SortBy,
-    SourceInfo,
-    SourceName,
-    SourceUrl,
-    Sources,
-    SourcesResponseDto,
-    SourcesResponseDtoSourcesItem,
-    SubscriptionResponseDto,
-    Theme,
-    TimeFrameCount,
-    TitleSentimentMax,
-    TitleSentimentMin,
-    To,
-    ToRank,
-    TopNArticles,
-    UserInputDto,
-    When,
-    WordCountMax,
-    WordCountMin,
-)
-from .errors import (
-    BadRequestError,
-    ForbiddenError,
-    InternalServerError,
-    RequestTimeoutError,
-    TooManyRequestsError,
-    UnauthorizedError,
-    UnprocessableEntityError,
-)
-from . import (
-    aggregation,
-    authors,
-    breaking_news,
-    latestheadlines,
-    search,
-    search_link,
-    searchsimilar,
-    sources,
-    subscription,
-)
-from .aggregation import (
-    AggregationGetRequestPublishedDatePrecision,
-    AggregationGetRequestSortBy,
-    AggregationGetResponse,
-    AggregationPostResponse,
-)
-from .authors import (
-    AuthorsGetRequestPublishedDatePrecision,
-    AuthorsGetRequestSortBy,
-    AuthorsGetResponse,
-    AuthorsPostResponse,
-)
-from .breaking_news import BreakingNewsGetRequestSortBy
-from .client import AsyncNewscatcherApi, NewscatcherApi
-from .environment import NewscatcherApiEnvironment
-from .latestheadlines import (
-    LatestHeadlinesGetRequestClusteringVariable,
-    LatestHeadlinesGetResponse,
-    LatestHeadlinesPostResponse,
-)
-from .search import (
-    SearchGetRequestClusteringVariable,
-    SearchGetRequestNewsDomainType,
-    SearchGetRequestPublishedDatePrecision,
-    SearchGetRequestSortBy,
-    SearchGetResponse,
-    SearchPostResponse,
-)
-from .searchsimilar import (
-    SearchSimilarGetRequestPublishedDatePrecision,
-    SearchSimilarGetRequestSortBy,
-    SearchSimilarGetResponse,
-    SearchSimilarPostResponse,
-)
-from .sources import SourcesGetRequestNewsDomainType
-from .version import __version__
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .types import (
+        AdditionalDomainInfo,
+        AdditionalDomainInfoEntity,
+        AdditionalSourceInfo,
+        AggregationBy,
+        AggregationCountResponseDto,
+        AggregationCountResponseDtoAggregations,
+        AggregationItem,
+        AllDomainLinks,
+        AllLinks,
+        AllLinksDataItem,
+        AllLinksText,
+        ArticleEntity,
+        ArticleEntityAllDomainLinks,
+        ArticleEntityAllLinks,
+        ArticleEntityAuthors,
+        ArticleEntityJournalists,
+        ArticlesDto,
+        AuthorName,
+        BaseSearchResponseDto,
+        BreakingNewsArticleEntity,
+        BreakingNewsArticleEntityAllDomainLinks,
+        BreakingNewsArticleEntityAllLinks,
+        BreakingNewsArticleEntityAuthors,
+        BreakingNewsArticleEntityJournalists,
+        BreakingNewsEventEntity,
+        BreakingNewsResponseDto,
+        ByParseDate,
+        ClusterEntity,
+        ClusteredArticlesDto,
+        ClusteredSearchResponseDto,
+        ClusteringEnabled,
+        ClusteringThreshold,
+        ClusteringVariable,
+        ContentSentimentMax,
+        ContentSentimentMin,
+        Countries,
+        CustomTags,
+        Error,
+        ExcludeDuplicates,
+        FailedAggregationCountResponseDto,
+        FailedAuthorsResponseDto,
+        From,
+        FromRank,
+        HasNlp,
+        IabTags,
+        Ids,
+        IncludeAdditionalInfo,
+        IncludeNlpData,
+        IncludeTranslationFields,
+        IptcTags,
+        IsHeadline,
+        IsNewsDomain,
+        IsOpinion,
+        IsPaidContent,
+        Lang,
+        Links,
+        LocEntityName,
+        MiscEntityName,
+        NamedEntityList,
+        NamedEntityListItem,
+        NerName,
+        NewsDomainType,
+        NewsType,
+        NlpDataEntity,
+        NotAuthorName,
+        NotCountries,
+        NotIabTags,
+        NotIptcTags,
+        NotLang,
+        NotSources,
+        NotTheme,
+        OrgEntityName,
+        Page,
+        PageSize,
+        ParentUrl,
+        PerEntityName,
+        PredefinedSources,
+        PublishedDatePrecision,
+        Q,
+        RankedOnly,
+        RobotsCompliant,
+        SearchIn,
+        SearchResponseDto,
+        SentimentScores,
+        SortBy,
+        SourceInfo,
+        SourceName,
+        SourceUrl,
+        Sources,
+        SourcesResponseDto,
+        SourcesResponseDtoSourcesItem,
+        SubscriptionResponseDto,
+        Theme,
+        TimeFrameCount,
+        TitleSentimentMax,
+        TitleSentimentMin,
+        To,
+        ToRank,
+        TopNArticles,
+        UserInputDto,
+        When,
+        WordCountMax,
+        WordCountMin,
+    )
+    from .errors import (
+        BadRequestError,
+        ForbiddenError,
+        InternalServerError,
+        RequestTimeoutError,
+        TooManyRequestsError,
+        UnauthorizedError,
+        UnprocessableEntityError,
+    )
+    from . import aggregation, authors, breaking_news, latest_headlines, search, search_by_link, sources, subscription
+    from .aggregation import AggregationCountGetResponse, AggregationCountPostResponse
+    from .authors import AuthorsGetResponse, AuthorsPostResponse
+    from .client import AsyncNewscatcherApi, NewscatcherApi
+    from .environment import NewscatcherApiEnvironment
+    from .latest_headlines import LatestHeadlinesGetResponse, LatestHeadlinesPostResponse
+    from .search import SearchGetResponse, SearchPostResponse
+    from .version import __version__
+_dynamic_imports: typing.Dict[str, str] = {
+    "AdditionalDomainInfo": ".types",
+    "AdditionalDomainInfoEntity": ".types",
+    "AdditionalSourceInfo": ".types",
+    "AggregationBy": ".types",
+    "AggregationCountGetResponse": ".aggregation",
+    "AggregationCountPostResponse": ".aggregation",
+    "AggregationCountResponseDto": ".types",
+    "AggregationCountResponseDtoAggregations": ".types",
+    "AggregationItem": ".types",
+    "AllDomainLinks": ".types",
+    "AllLinks": ".types",
+    "AllLinksDataItem": ".types",
+    "AllLinksText": ".types",
+    "ArticleEntity": ".types",
+    "ArticleEntityAllDomainLinks": ".types",
+    "ArticleEntityAllLinks": ".types",
+    "ArticleEntityAuthors": ".types",
+    "ArticleEntityJournalists": ".types",
+    "ArticlesDto": ".types",
+    "AsyncNewscatcherApi": ".client",
+    "AuthorName": ".types",
+    "AuthorsGetResponse": ".authors",
+    "AuthorsPostResponse": ".authors",
+    "BadRequestError": ".errors",
+    "BaseSearchResponseDto": ".types",
+    "BreakingNewsArticleEntity": ".types",
+    "BreakingNewsArticleEntityAllDomainLinks": ".types",
+    "BreakingNewsArticleEntityAllLinks": ".types",
+    "BreakingNewsArticleEntityAuthors": ".types",
+    "BreakingNewsArticleEntityJournalists": ".types",
+    "BreakingNewsEventEntity": ".types",
+    "BreakingNewsResponseDto": ".types",
+    "ByParseDate": ".types",
+    "ClusterEntity": ".types",
+    "ClusteredArticlesDto": ".types",
+    "ClusteredSearchResponseDto": ".types",
+    "ClusteringEnabled": ".types",
+    "ClusteringThreshold": ".types",
+    "ClusteringVariable": ".types",
+    "ContentSentimentMax": ".types",
+    "ContentSentimentMin": ".types",
+    "Countries": ".types",
+    "CustomTags": ".types",
+    "Error": ".types",
+    "ExcludeDuplicates": ".types",
+    "FailedAggregationCountResponseDto": ".types",
+    "FailedAuthorsResponseDto": ".types",
+    "ForbiddenError": ".errors",
+    "From": ".types",
+    "FromRank": ".types",
+    "HasNlp": ".types",
+    "IabTags": ".types",
+    "Ids": ".types",
+    "IncludeAdditionalInfo": ".types",
+    "IncludeNlpData": ".types",
+    "IncludeTranslationFields": ".types",
+    "InternalServerError": ".errors",
+    "IptcTags": ".types",
+    "IsHeadline": ".types",
+    "IsNewsDomain": ".types",
+    "IsOpinion": ".types",
+    "IsPaidContent": ".types",
+    "Lang": ".types",
+    "LatestHeadlinesGetResponse": ".latest_headlines",
+    "LatestHeadlinesPostResponse": ".latest_headlines",
+    "Links": ".types",
+    "LocEntityName": ".types",
+    "MiscEntityName": ".types",
+    "NamedEntityList": ".types",
+    "NamedEntityListItem": ".types",
+    "NerName": ".types",
+    "NewsDomainType": ".types",
+    "NewsType": ".types",
+    "NewscatcherApi": ".client",
+    "NewscatcherApiEnvironment": ".environment",
+    "NlpDataEntity": ".types",
+    "NotAuthorName": ".types",
+    "NotCountries": ".types",
+    "NotIabTags": ".types",
+    "NotIptcTags": ".types",
+    "NotLang": ".types",
+    "NotSources": ".types",
+    "NotTheme": ".types",
+    "OrgEntityName": ".types",
+    "Page": ".types",
+    "PageSize": ".types",
+    "ParentUrl": ".types",
+    "PerEntityName": ".types",
+    "PredefinedSources": ".types",
+    "PublishedDatePrecision": ".types",
+    "Q": ".types",
+    "RankedOnly": ".types",
+    "RequestTimeoutError": ".errors",
+    "RobotsCompliant": ".types",
+    "SearchGetResponse": ".search",
+    "SearchIn": ".types",
+    "SearchPostResponse": ".search",
+    "SearchResponseDto": ".types",
+    "SentimentScores": ".types",
+    "SortBy": ".types",
+    "SourceInfo": ".types",
+    "SourceName": ".types",
+    "SourceUrl": ".types",
+    "Sources": ".types",
+    "SourcesResponseDto": ".types",
+    "SourcesResponseDtoSourcesItem": ".types",
+    "SubscriptionResponseDto": ".types",
+    "Theme": ".types",
+    "TimeFrameCount": ".types",
+    "TitleSentimentMax": ".types",
+    "TitleSentimentMin": ".types",
+    "To": ".types",
+    "ToRank": ".types",
+    "TooManyRequestsError": ".errors",
+    "TopNArticles": ".types",
+    "UnauthorizedError": ".errors",
+    "UnprocessableEntityError": ".errors",
+    "UserInputDto": ".types",
+    "When": ".types",
+    "WordCountMax": ".types",
+    "WordCountMin": ".types",
+    "__version__": ".version",
+    "aggregation": ".aggregation",
+    "authors": ".authors",
+    "breaking_news": ".breaking_news",
+    "latest_headlines": ".latest_headlines",
+    "search": ".search",
+    "search_by_link": ".search_by_link",
+    "sources": ".sources",
+    "subscription": ".subscription",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
 
 __all__ = [
     "AdditionalDomainInfo",
     "AdditionalDomainInfoEntity",
     "AdditionalSourceInfo",
     "AggregationBy",
+    "AggregationCountGetResponse",
+    "AggregationCountPostResponse",
     "AggregationCountResponseDto",
-    "AggregationGetRequestPublishedDatePrecision",
-    "AggregationGetRequestSortBy",
-    "AggregationGetResponse",
+    "AggregationCountResponseDtoAggregations",
     "AggregationItem",
-    "AggregationPostResponse",
-    "Aggregations",
     "AllDomainLinks",
     "AllLinks",
+    "AllLinksDataItem",
+    "AllLinksText",
     "ArticleEntity",
     "ArticleEntityAllDomainLinks",
     "ArticleEntityAllLinks",
-    "Articles",
+    "ArticleEntityAuthors",
+    "ArticleEntityJournalists",
+    "ArticlesDto",
     "AsyncNewscatcherApi",
     "AuthorName",
-    "Authors",
-    "AuthorsGetRequestPublishedDatePrecision",
-    "AuthorsGetRequestSortBy",
     "AuthorsGetResponse",
     "AuthorsPostResponse",
     "BadRequestError",
@@ -197,8 +312,9 @@
     "BreakingNewsArticleEntity",
     "BreakingNewsArticleEntityAllDomainLinks",
     "BreakingNewsArticleEntityAllLinks",
+    "BreakingNewsArticleEntityAuthors",
+    "BreakingNewsArticleEntityJournalists",
     "BreakingNewsEventEntity",
-    "BreakingNewsGetRequestSortBy",
     "BreakingNewsResponseDto",
     "ByParseDate",
     "ClusterEntity",
@@ -215,7 +331,6 @@
     "ExcludeDuplicates",
     "FailedAggregationCountResponseDto",
     "FailedAuthorsResponseDto",
-    "FailedSearchSimilarResponseDto",
     "ForbiddenError",
     "From",
     "FromRank",
@@ -224,7 +339,6 @@
     "Ids",
     "IncludeAdditionalInfo",
     "IncludeNlpData",
-    "IncludeSimilarDocuments",
     "IncludeTranslationFields",
     "InternalServerError",
     "IptcTags",
@@ -232,9 +346,7 @@
     "IsNewsDomain",
     "IsOpinion",
     "IsPaidContent",
-    "Journalists",
     "Lang",
-    "LatestHeadlinesGetRequestClusteringVariable",
     "LatestHeadlinesGetResponse",
     "LatestHeadlinesPostResponse",
     "Links",
@@ -266,30 +378,16 @@
     "RankedOnly",
     "RequestTimeoutError",
     "RobotsCompliant",
-    "SearchGetRequestClusteringVariable",
-    "SearchGetRequestNewsDomainType",
-    "SearchGetRequestPublishedDatePrecision",
-    "SearchGetRequestSortBy",
     "SearchGetResponse",
     "SearchIn",
     "SearchPostResponse",
     "SearchResponseDto",
-    "SearchSimilarGetRequestPublishedDatePrecision",
-    "SearchSimilarGetRequestSortBy",
-    "SearchSimilarGetResponse",
-    "SearchSimilarPostResponse",
-    "SearchSimilarResponseDto",
     "SentimentScores",
-    "SimilarArticleEntity",
-    "SimilarDocument",
-    "SimilarDocumentsFields",
-    "SimilarDocumentsNumber",
     "SortBy",
     "SourceInfo",
     "SourceName",
     "SourceUrl",
     "Sources",
-    "SourcesGetRequestNewsDomainType",
     "SourcesResponseDto",
     "SourcesResponseDtoSourcesItem",
     "SubscriptionResponseDto",
@@ -311,10 +409,9 @@
     "aggregation",
     "authors",
     "breaking_news",
-    "latestheadlines",
+    "latest_headlines",
     "search",
-    "search_link",
-    "searchsimilar",
+    "search_by_link",
     "sources",
     "subscription",
 ]
diff --git a/src/newscatcher/aggregation/__init__.py b/src/newscatcher/aggregation/__init__.py
index c4d8649..22a6c09 100644
--- a/src/newscatcher/aggregation/__init__.py
+++ b/src/newscatcher/aggregation/__init__.py
@@ -2,16 +2,36 @@
 
 # isort: skip_file
 
-from .types import (
-    AggregationGetRequestPublishedDatePrecision,
-    AggregationGetRequestSortBy,
-    AggregationGetResponse,
-    AggregationPostResponse,
-)
-
-__all__ = [
-    "AggregationGetRequestPublishedDatePrecision",
-    "AggregationGetRequestSortBy",
-    "AggregationGetResponse",
-    "AggregationPostResponse",
-]
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .types import AggregationCountGetResponse, AggregationCountPostResponse
+_dynamic_imports: typing.Dict[str, str] = {
+    "AggregationCountGetResponse": ".types",
+    "AggregationCountPostResponse": ".types",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["AggregationCountGetResponse", "AggregationCountPostResponse"]
diff --git a/src/newscatcher/aggregation/client.py b/src/newscatcher/aggregation/client.py
index a512b41..84cce0f 100644
--- a/src/newscatcher/aggregation/client.py
+++ b/src/newscatcher/aggregation/client.py
@@ -1,6 +1,5 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import datetime as dt
 import typing
 
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
@@ -8,6 +7,7 @@
 from ..types.aggregation_by import AggregationBy
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.by_parse_date import ByParseDate
 from ..types.content_sentiment_max import ContentSentimentMax
 from ..types.content_sentiment_min import ContentSentimentMin
@@ -50,10 +50,8 @@
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
 from .raw_client import AsyncRawAggregationClient, RawAggregationClient
-from .types.aggregation_get_request_published_date_precision import AggregationGetRequestPublishedDatePrecision
-from .types.aggregation_get_request_sort_by import AggregationGetRequestSortBy
-from .types.aggregation_get_response import AggregationGetResponse
-from .types.aggregation_post_response import AggregationPostResponse
+from .types.aggregation_count_get_response import AggregationCountGetResponse
+from .types.aggregation_count_post_response import AggregationCountPostResponse
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -74,10 +72,10 @@ def with_raw_response(self) -> RawAggregationClient:
         """
         return self._raw_client
 
-    def get(
+    def count_get(
         self,
         *,
-        q: str,
+        q: Q,
         aggregation_by: typing.Optional[AggregationBy] = None,
         search_in: typing.Optional[SearchIn] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -88,57 +86,48 @@ def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AggregationGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AggregationGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> AggregationGetResponse:
+    ) -> AggregationCountGetResponse:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         aggregation_by : typing.Optional[AggregationBy]
 
@@ -147,262 +136,116 @@ def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AggregationGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AggregationGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_min : typing.Optional[WordCountMin]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        word_count_max : typing.Optional[WordCountMax]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page : typing.Optional[Page]
+
+        page_size : typing.Optional[PageSize]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -410,21 +253,18 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
 
         Returns
         -------
-        AggregationGetResponse
+        AggregationCountGetResponse
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
 
         Examples
@@ -436,25 +276,57 @@ def get(
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
-        client.aggregation.get(
-            q="technology AND (Apple OR Microsoft) NOT Google",
+        client.aggregation.count_get(
+            q='"supply chain" AND Amazon NOT China',
             search_in="title_content, title_content_translated",
-            predefined_sources="top 100 US, top 5 GB",
+            predefined_sources="top 50 US, top 20 GB",
+            sources="nytimes.com,finance.yahoo.com",
+            not_sources="cnn.com,wsj.com",
+            lang="en,es",
+            not_lang="fr,de",
+            countries="US,CA",
+            not_countries="UK,FR",
+            not_author_name="John Doe, Jane Doe",
             from_=datetime.datetime.fromisoformat(
                 "2024-07-01 00:00:00+00:00",
             ),
             to=datetime.datetime.fromisoformat(
-                "2024-07-01 00:00:00+00:00",
+                "2024-01-01 00:00:00+00:00",
             ),
+            published_date_precision="full",
+            by_parse_date=True,
+            ranked_only=True,
+            from_rank=100,
+            to_rank=100,
+            is_headline=True,
+            is_opinion=True,
+            is_paid_content=False,
+            parent_url="wsj.com/politics,wsj.com/tech",
+            all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+            all_domain_links="who.int,nih.gov",
+            all_links_text="Nvidia,Tesla",
+            word_count_min=300,
+            word_count_max=1000,
+            page=2,
+            page_size=50,
             include_nlp_data=True,
             has_nlp=True,
-            theme="Business,Finance",
-            not_theme="Crime",
+            theme="Finance,Tech",
+            not_theme="Crime,Sports",
+            org_entity_name='"Apple Inc" OR Microsoft',
+            per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+            loc_entity_name='"San Francisco" OR "New York City"',
+            misc_entity_name='AWS OR "Microsoft Azure"',
+            title_sentiment_min=-0.5,
+            title_sentiment_max=0.5,
+            content_sentiment_min=-0.5,
+            content_sentiment_max=0.5,
             iptc_tags="20000199,20000209",
             not_iptc_tags="20000205,20000209",
+            robots_compliant=True,
         )
         """
-        _response = self._raw_client.get(
+        _response = self._raw_client.count_get(
             q=q,
             aggregation_by=aggregation_by,
             search_in=search_in,
@@ -480,6 +352,7 @@ def get(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -503,7 +376,7 @@ def get(
         )
         return _response.data
 
-    def post(
+    def count_post(
         self,
         *,
         q: Q,
@@ -531,6 +404,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -551,7 +425,7 @@ def post(
         not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
         robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> AggregationPostResponse:
+    ) -> AggregationCountPostResponse:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
@@ -607,6 +481,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -650,31 +526,22 @@ def post(
 
         Returns
         -------
-        AggregationPostResponse
+        AggregationCountPostResponse
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
 
         Examples
         --------
-        import datetime
-
         from newscatcher import NewscatcherApi
 
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
-        client.aggregation.post(
-            q="renewable energy",
+        client.aggregation.count_post(
+            q='"supply chain" AND Amazon NOT China',
             aggregation_by="day",
-            predefined_sources="top 50 US",
-            from_=datetime.datetime.fromisoformat(
-                "2024-01-01 00:00:00+00:00",
-            ),
-            to=datetime.datetime.fromisoformat(
-                "2024-06-30 00:00:00+00:00",
-            ),
         )
         """
-        _response = self._raw_client.post(
+        _response = self._raw_client.count_post(
             q=q,
             aggregation_by=aggregation_by,
             search_in=search_in,
@@ -700,6 +567,7 @@ def post(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -739,10 +607,10 @@ def with_raw_response(self) -> AsyncRawAggregationClient:
         """
         return self._raw_client
 
-    async def get(
+    async def count_get(
         self,
         *,
-        q: str,
+        q: Q,
         aggregation_by: typing.Optional[AggregationBy] = None,
         search_in: typing.Optional[SearchIn] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -753,57 +621,48 @@ async def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AggregationGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AggregationGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> AggregationGetResponse:
+    ) -> AggregationCountGetResponse:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         aggregation_by : typing.Optional[AggregationBy]
 
@@ -812,262 +671,116 @@ async def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AggregationGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AggregationGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_min : typing.Optional[WordCountMin]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        word_count_max : typing.Optional[WordCountMax]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page : typing.Optional[Page]
+
+        page_size : typing.Optional[PageSize]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1075,21 +788,18 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
 
         Returns
         -------
-        AggregationGetResponse
+        AggregationCountGetResponse
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
 
         Examples
@@ -1105,28 +815,60 @@ async def get(
 
 
         async def main() -> None:
-            await client.aggregation.get(
-                q="technology AND (Apple OR Microsoft) NOT Google",
+            await client.aggregation.count_get(
+                q='"supply chain" AND Amazon NOT China',
                 search_in="title_content, title_content_translated",
-                predefined_sources="top 100 US, top 5 GB",
+                predefined_sources="top 50 US, top 20 GB",
+                sources="nytimes.com,finance.yahoo.com",
+                not_sources="cnn.com,wsj.com",
+                lang="en,es",
+                not_lang="fr,de",
+                countries="US,CA",
+                not_countries="UK,FR",
+                not_author_name="John Doe, Jane Doe",
                 from_=datetime.datetime.fromisoformat(
                     "2024-07-01 00:00:00+00:00",
                 ),
                 to=datetime.datetime.fromisoformat(
-                    "2024-07-01 00:00:00+00:00",
+                    "2024-01-01 00:00:00+00:00",
                 ),
+                published_date_precision="full",
+                by_parse_date=True,
+                ranked_only=True,
+                from_rank=100,
+                to_rank=100,
+                is_headline=True,
+                is_opinion=True,
+                is_paid_content=False,
+                parent_url="wsj.com/politics,wsj.com/tech",
+                all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+                all_domain_links="who.int,nih.gov",
+                all_links_text="Nvidia,Tesla",
+                word_count_min=300,
+                word_count_max=1000,
+                page=2,
+                page_size=50,
                 include_nlp_data=True,
                 has_nlp=True,
-                theme="Business,Finance",
-                not_theme="Crime",
+                theme="Finance,Tech",
+                not_theme="Crime,Sports",
+                org_entity_name='"Apple Inc" OR Microsoft',
+                per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+                loc_entity_name='"San Francisco" OR "New York City"',
+                misc_entity_name='AWS OR "Microsoft Azure"',
+                title_sentiment_min=-0.5,
+                title_sentiment_max=0.5,
+                content_sentiment_min=-0.5,
+                content_sentiment_max=0.5,
                 iptc_tags="20000199,20000209",
                 not_iptc_tags="20000205,20000209",
+                robots_compliant=True,
             )
 
 
         asyncio.run(main())
         """
-        _response = await self._raw_client.get(
+        _response = await self._raw_client.count_get(
             q=q,
             aggregation_by=aggregation_by,
             search_in=search_in,
@@ -1152,6 +894,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -1175,7 +918,7 @@ async def main() -> None:
         )
         return _response.data
 
-    async def post(
+    async def count_post(
         self,
         *,
         q: Q,
@@ -1203,6 +946,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -1223,7 +967,7 @@ async def post(
         not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
         robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> AggregationPostResponse:
+    ) -> AggregationCountPostResponse:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
@@ -1279,6 +1023,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -1322,13 +1068,12 @@ async def post(
 
         Returns
         -------
-        AggregationPostResponse
+        AggregationCountPostResponse
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
 
         Examples
         --------
         import asyncio
-        import datetime
 
         from newscatcher import AsyncNewscatcherApi
 
@@ -1338,22 +1083,15 @@ async def post(
 
 
         async def main() -> None:
-            await client.aggregation.post(
-                q="renewable energy",
+            await client.aggregation.count_post(
+                q='"supply chain" AND Amazon NOT China',
                 aggregation_by="day",
-                predefined_sources="top 50 US",
-                from_=datetime.datetime.fromisoformat(
-                    "2024-01-01 00:00:00+00:00",
-                ),
-                to=datetime.datetime.fromisoformat(
-                    "2024-06-30 00:00:00+00:00",
-                ),
             )
 
 
         asyncio.run(main())
         """
-        _response = await self._raw_client.post(
+        _response = await self._raw_client.count_post(
             q=q,
             aggregation_by=aggregation_by,
             search_in=search_in,
@@ -1379,6 +1117,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
diff --git a/src/newscatcher/aggregation/raw_client.py b/src/newscatcher/aggregation/raw_client.py
index 66a8064..42a6568 100644
--- a/src/newscatcher/aggregation/raw_client.py
+++ b/src/newscatcher/aggregation/raw_client.py
@@ -1,13 +1,12 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import datetime as dt
 import typing
 from json.decoder import JSONDecodeError
 
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
-from ..core.datetime_utils import serialize_datetime
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..core.serialization import convert_and_respect_annotation_metadata
@@ -21,6 +20,7 @@
 from ..types.aggregation_by import AggregationBy
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.by_parse_date import ByParseDate
 from ..types.content_sentiment_max import ContentSentimentMax
 from ..types.content_sentiment_min import ContentSentimentMin
@@ -63,10 +63,9 @@
 from ..types.to_rank import ToRank
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
-from .types.aggregation_get_request_published_date_precision import AggregationGetRequestPublishedDatePrecision
-from .types.aggregation_get_request_sort_by import AggregationGetRequestSortBy
-from .types.aggregation_get_response import AggregationGetResponse
-from .types.aggregation_post_response import AggregationPostResponse
+from .types.aggregation_count_get_response import AggregationCountGetResponse
+from .types.aggregation_count_post_response import AggregationCountPostResponse
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -76,10 +75,10 @@ class RawAggregationClient:
     def __init__(self, *, client_wrapper: SyncClientWrapper):
         self._client_wrapper = client_wrapper
 
-    def get(
+    def count_get(
         self,
         *,
-        q: str,
+        q: Q,
         aggregation_by: typing.Optional[AggregationBy] = None,
         search_in: typing.Optional[SearchIn] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -90,57 +89,48 @@ def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AggregationGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AggregationGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> HttpResponse[AggregationGetResponse]:
+    ) -> HttpResponse[AggregationCountGetResponse]:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         aggregation_by : typing.Optional[AggregationBy]
 
@@ -149,262 +139,116 @@ def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AggregationGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AggregationGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_min : typing.Optional[WordCountMin]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        word_count_max : typing.Optional[WordCountMax]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page : typing.Optional[Page]
+
+        page_size : typing.Optional[PageSize]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -412,21 +256,18 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
 
         Returns
         -------
-        HttpResponse[AggregationGetResponse]
+        HttpResponse[AggregationCountGetResponse]
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
         """
         _response = self._client_wrapper.httpx_client.request(
@@ -444,8 +285,8 @@ def get(
                 "countries": countries,
                 "not_countries": not_countries,
                 "not_author_name": not_author_name,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
+                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
+                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
                 "published_date_precision": published_date_precision,
                 "by_parse_date": by_parse_date,
                 "sort_by": sort_by,
@@ -458,6 +299,7 @@ def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -483,9 +325,9 @@ def get(
         try:
             if 200 <= _response.status_code < 300:
                 _data = typing.cast(
-                    AggregationGetResponse,
+                    AggregationCountGetResponse,
                     parse_obj_as(
-                        type_=AggregationGetResponse,  # type: ignore
+                        type_=AggregationCountGetResponse,  # type: ignore
                         object_=_response.json(),
                     ),
                 )
@@ -570,9 +412,13 @@ def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
-    def post(
+    def count_post(
         self,
         *,
         q: Q,
@@ -600,6 +446,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -620,7 +467,7 @@ def post(
         not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
         robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> HttpResponse[AggregationPostResponse]:
+    ) -> HttpResponse[AggregationCountPostResponse]:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
@@ -676,6 +523,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -719,7 +568,7 @@ def post(
 
         Returns
         -------
-        HttpResponse[AggregationPostResponse]
+        HttpResponse[AggregationCountPostResponse]
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
         """
         _response = self._client_wrapper.httpx_client.request(
@@ -771,16 +620,17 @@ def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
                 "page_size": page_size,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -806,9 +656,9 @@ def post(
         try:
             if 200 <= _response.status_code < 300:
                 _data = typing.cast(
-                    AggregationPostResponse,
+                    AggregationCountPostResponse,
                     parse_obj_as(
-                        type_=AggregationPostResponse,  # type: ignore
+                        type_=AggregationCountPostResponse,  # type: ignore
                         object_=_response.json(),
                     ),
                 )
@@ -893,6 +743,10 @@ def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
@@ -900,10 +754,10 @@ class AsyncRawAggregationClient:
     def __init__(self, *, client_wrapper: AsyncClientWrapper):
         self._client_wrapper = client_wrapper
 
-    async def get(
+    async def count_get(
         self,
         *,
-        q: str,
+        q: Q,
         aggregation_by: typing.Optional[AggregationBy] = None,
         search_in: typing.Optional[SearchIn] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -914,57 +768,48 @@ async def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AggregationGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AggregationGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> AsyncHttpResponse[AggregationGetResponse]:
+    ) -> AsyncHttpResponse[AggregationCountGetResponse]:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         aggregation_by : typing.Optional[AggregationBy]
 
@@ -973,262 +818,116 @@ async def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AggregationGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AggregationGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_min : typing.Optional[WordCountMin]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        word_count_max : typing.Optional[WordCountMax]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page : typing.Optional[Page]
+
+        page_size : typing.Optional[PageSize]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1236,21 +935,18 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
 
         Returns
         -------
-        AsyncHttpResponse[AggregationGetResponse]
+        AsyncHttpResponse[AggregationCountGetResponse]
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
         """
         _response = await self._client_wrapper.httpx_client.request(
@@ -1268,8 +964,8 @@ async def get(
                 "countries": countries,
                 "not_countries": not_countries,
                 "not_author_name": not_author_name,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
+                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
+                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
                 "published_date_precision": published_date_precision,
                 "by_parse_date": by_parse_date,
                 "sort_by": sort_by,
@@ -1282,6 +978,7 @@ async def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -1307,9 +1004,9 @@ async def get(
         try:
             if 200 <= _response.status_code < 300:
                 _data = typing.cast(
-                    AggregationGetResponse,
+                    AggregationCountGetResponse,
                     parse_obj_as(
-                        type_=AggregationGetResponse,  # type: ignore
+                        type_=AggregationCountGetResponse,  # type: ignore
                         object_=_response.json(),
                     ),
                 )
@@ -1394,9 +1091,13 @@ async def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
-    async def post(
+    async def count_post(
         self,
         *,
         q: Q,
@@ -1424,6 +1125,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -1444,7 +1146,7 @@ async def post(
         not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
         robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
-    ) -> AsyncHttpResponse[AggregationPostResponse]:
+    ) -> AsyncHttpResponse[AggregationCountPostResponse]:
         """
         Retrieves the count of articles aggregated by day or hour based on various search criteria, such as keyword, language, country, and source.
 
@@ -1500,6 +1202,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -1543,7 +1247,7 @@ async def post(
 
         Returns
         -------
-        AsyncHttpResponse[AggregationPostResponse]
+        AsyncHttpResponse[AggregationCountPostResponse]
             A successful response containing aggregation count results that match the search criteria. If no matches, returns a failed aggregation response according to the defined schema.
         """
         _response = await self._client_wrapper.httpx_client.request(
@@ -1595,16 +1299,17 @@ async def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
                 "page_size": page_size,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -1630,9 +1335,9 @@ async def post(
         try:
             if 200 <= _response.status_code < 300:
                 _data = typing.cast(
-                    AggregationPostResponse,
+                    AggregationCountPostResponse,
                     parse_obj_as(
-                        type_=AggregationPostResponse,  # type: ignore
+                        type_=AggregationCountPostResponse,  # type: ignore
                         object_=_response.json(),
                     ),
                 )
@@ -1717,4 +1422,8 @@ async def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/aggregation/types/__init__.py b/src/newscatcher/aggregation/types/__init__.py
index 324ce07..ca0dbea 100644
--- a/src/newscatcher/aggregation/types/__init__.py
+++ b/src/newscatcher/aggregation/types/__init__.py
@@ -2,14 +2,37 @@
 
 # isort: skip_file
 
-from .aggregation_get_request_published_date_precision import AggregationGetRequestPublishedDatePrecision
-from .aggregation_get_request_sort_by import AggregationGetRequestSortBy
-from .aggregation_get_response import AggregationGetResponse
-from .aggregation_post_response import AggregationPostResponse
-
-__all__ = [
-    "AggregationGetRequestPublishedDatePrecision",
-    "AggregationGetRequestSortBy",
-    "AggregationGetResponse",
-    "AggregationPostResponse",
-]
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .aggregation_count_get_response import AggregationCountGetResponse
+    from .aggregation_count_post_response import AggregationCountPostResponse
+_dynamic_imports: typing.Dict[str, str] = {
+    "AggregationCountGetResponse": ".aggregation_count_get_response",
+    "AggregationCountPostResponse": ".aggregation_count_post_response",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["AggregationCountGetResponse", "AggregationCountPostResponse"]
diff --git a/src/newscatcher/aggregation/types/aggregation_get_response.py b/src/newscatcher/aggregation/types/aggregation_count_get_response.py
similarity index 70%
rename from src/newscatcher/aggregation/types/aggregation_get_response.py
rename to src/newscatcher/aggregation/types/aggregation_count_get_response.py
index 315c283..9be1093 100644
--- a/src/newscatcher/aggregation/types/aggregation_get_response.py
+++ b/src/newscatcher/aggregation/types/aggregation_count_get_response.py
@@ -5,4 +5,4 @@
 from ...types.aggregation_count_response_dto import AggregationCountResponseDto
 from ...types.failed_aggregation_count_response_dto import FailedAggregationCountResponseDto
 
-AggregationGetResponse = typing.Union[AggregationCountResponseDto, FailedAggregationCountResponseDto]
+AggregationCountGetResponse = typing.Union[AggregationCountResponseDto, FailedAggregationCountResponseDto]
diff --git a/src/newscatcher/aggregation/types/aggregation_post_response.py b/src/newscatcher/aggregation/types/aggregation_count_post_response.py
similarity index 70%
rename from src/newscatcher/aggregation/types/aggregation_post_response.py
rename to src/newscatcher/aggregation/types/aggregation_count_post_response.py
index 1f4bd9a..b8488a9 100644
--- a/src/newscatcher/aggregation/types/aggregation_post_response.py
+++ b/src/newscatcher/aggregation/types/aggregation_count_post_response.py
@@ -5,4 +5,4 @@
 from ...types.aggregation_count_response_dto import AggregationCountResponseDto
 from ...types.failed_aggregation_count_response_dto import FailedAggregationCountResponseDto
 
-AggregationPostResponse = typing.Union[AggregationCountResponseDto, FailedAggregationCountResponseDto]
+AggregationCountPostResponse = typing.Union[AggregationCountResponseDto, FailedAggregationCountResponseDto]
diff --git a/src/newscatcher/aggregation/types/aggregation_get_request_published_date_precision.py b/src/newscatcher/aggregation/types/aggregation_get_request_published_date_precision.py
deleted file mode 100644
index 222acca..0000000
--- a/src/newscatcher/aggregation/types/aggregation_get_request_published_date_precision.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-AggregationGetRequestPublishedDatePrecision = typing.Union[
-    typing.Literal["full", "timezone unknown", "date"], typing.Any
-]
diff --git a/src/newscatcher/aggregation/types/aggregation_get_request_sort_by.py b/src/newscatcher/aggregation/types/aggregation_get_request_sort_by.py
deleted file mode 100644
index 3c9a6fd..0000000
--- a/src/newscatcher/aggregation/types/aggregation_get_request_sort_by.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-AggregationGetRequestSortBy = typing.Union[typing.Literal["relevancy", "date", "rank"], typing.Any]
diff --git a/src/newscatcher/authors/__init__.py b/src/newscatcher/authors/__init__.py
index 420f07c..151c122 100644
--- a/src/newscatcher/authors/__init__.py
+++ b/src/newscatcher/authors/__init__.py
@@ -2,16 +2,33 @@
 
 # isort: skip_file
 
-from .types import (
-    AuthorsGetRequestPublishedDatePrecision,
-    AuthorsGetRequestSortBy,
-    AuthorsGetResponse,
-    AuthorsPostResponse,
-)
-
-__all__ = [
-    "AuthorsGetRequestPublishedDatePrecision",
-    "AuthorsGetRequestSortBy",
-    "AuthorsGetResponse",
-    "AuthorsPostResponse",
-]
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .types import AuthorsGetResponse, AuthorsPostResponse
+_dynamic_imports: typing.Dict[str, str] = {"AuthorsGetResponse": ".types", "AuthorsPostResponse": ".types"}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["AuthorsGetResponse", "AuthorsPostResponse"]
diff --git a/src/newscatcher/authors/client.py b/src/newscatcher/authors/client.py
index c2a1c65..3014a97 100644
--- a/src/newscatcher/authors/client.py
+++ b/src/newscatcher/authors/client.py
@@ -1,12 +1,12 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import datetime as dt
 import typing
 
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
 from ..core.request_options import RequestOptions
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.author_name import AuthorName
 from ..types.by_parse_date import ByParseDate
 from ..types.content_sentiment_max import ContentSentimentMax
@@ -49,8 +49,6 @@
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
 from .raw_client import AsyncRawAuthorsClient, RawAuthorsClient
-from .types.authors_get_request_published_date_precision import AuthorsGetRequestPublishedDatePrecision
-from .types.authors_get_request_sort_by import AuthorsGetRequestSortBy
 from .types.authors_get_response import AuthorsGetResponse
 from .types.authors_post_response import AuthorsPostResponse
 
@@ -76,7 +74,7 @@ def with_raw_response(self) -> RawAuthorsClient:
     def get(
         self,
         *,
-        author_name: str,
+        author_name: AuthorName,
         not_author_name: typing.Optional[str] = None,
         predefined_sources: typing.Optional[str] = None,
         sources: typing.Optional[str] = None,
@@ -85,40 +83,41 @@ def get(
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AuthorsGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AuthorsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        ner_name: typing.Optional[NerName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AuthorsGetResponse:
         """
@@ -126,154 +125,93 @@ def get(
 
         Parameters
         ----------
-        author_name : str
-            The name of the author to search for. This parameter returns exact matches only.
+        author_name : AuthorName
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AuthorsGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AuthorsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
+
+        word_count_min : typing.Optional[WordCountMin]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_max : typing.Optional[WordCountMax]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -281,84 +219,23 @@ def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        theme : typing.Optional[Theme]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        not_theme : typing.Optional[NotTheme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        ner_name : typing.Optional[NerName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -366,8 +243,6 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -375,8 +250,6 @@ def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -384,8 +257,6 @@ def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -393,14 +264,13 @@ def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -421,24 +291,52 @@ def get(
         )
         client.authors.get(
             author_name="Jane Smith",
-            predefined_sources="top 100 US, top 5 GB",
+            not_author_name="John Doe, Jane Doe",
+            predefined_sources="top 50 US, top 20 GB",
+            sources="nytimes.com,finance.yahoo.com",
+            not_sources="cnn.com,wsj.com",
+            lang="en,es",
+            not_lang="fr,de",
+            countries="US,CA",
+            not_countries="UK,FR",
             from_=datetime.datetime.fromisoformat(
                 "2024-07-01 00:00:00+00:00",
             ),
             to=datetime.datetime.fromisoformat(
-                "2024-07-01 00:00:00+00:00",
+                "2024-01-01 00:00:00+00:00",
             ),
+            published_date_precision="full",
+            by_parse_date=True,
+            ranked_only=True,
+            from_rank=100,
+            to_rank=100,
+            is_headline=True,
+            is_opinion=True,
+            is_paid_content=False,
+            parent_url="wsj.com/politics,wsj.com/tech",
+            all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+            all_domain_links="who.int,nih.gov",
+            all_links_text="Nvidia,Tesla",
+            word_count_min=300,
+            word_count_max=1000,
+            page=2,
+            page_size=50,
             include_translation_fields=True,
             include_nlp_data=True,
             has_nlp=True,
-            theme="Business,Finance",
-            not_theme="Crime",
-            ner_name="Tesla",
+            theme="Finance,Tech",
+            not_theme="Crime,Sports",
+            ner_name="Tesla,Amazon",
+            title_sentiment_min=-0.5,
+            title_sentiment_max=0.5,
+            content_sentiment_min=-0.5,
+            content_sentiment_max=0.5,
             iptc_tags="20000199,20000209",
             not_iptc_tags="20000205,20000209",
             iab_tags="Business,Events",
             not_iab_tags="Agriculture,Metals",
-            custom_tags="Tag1,Tag2,Tag3",
+            custom_tags="Tag1,Tag2",
+            robots_compliant=True,
         )
         """
         _response = self._raw_client.get(
@@ -465,6 +363,7 @@ def get(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -515,6 +414,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -588,6 +488,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -638,23 +540,13 @@ def post(
 
         Examples
         --------
-        import datetime
-
         from newscatcher import NewscatcherApi
 
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
         client.authors.post(
-            author_name="Joanna Stern",
-            sources=["wsj.com", "nytimes.com"],
-            lang="en",
-            from_=datetime.datetime.fromisoformat(
-                "2024-01-01 00:00:00+00:00",
-            ),
-            to=datetime.datetime.fromisoformat(
-                "2024-06-30 00:00:00+00:00",
-            ),
+            author_name="David Muir",
         )
         """
         _response = self._raw_client.post(
@@ -681,6 +573,7 @@ def post(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -724,7 +617,7 @@ def with_raw_response(self) -> AsyncRawAuthorsClient:
     async def get(
         self,
         *,
-        author_name: str,
+        author_name: AuthorName,
         not_author_name: typing.Optional[str] = None,
         predefined_sources: typing.Optional[str] = None,
         sources: typing.Optional[str] = None,
@@ -733,40 +626,41 @@ async def get(
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AuthorsGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AuthorsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        ner_name: typing.Optional[NerName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AuthorsGetResponse:
         """
@@ -774,154 +668,93 @@ async def get(
 
         Parameters
         ----------
-        author_name : str
-            The name of the author to search for. This parameter returns exact matches only.
+        author_name : AuthorName
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AuthorsGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AuthorsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
+
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+        word_count_min : typing.Optional[WordCountMin]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_max : typing.Optional[WordCountMax]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -929,84 +762,23 @@ async def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        theme : typing.Optional[Theme]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        not_theme : typing.Optional[NotTheme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        ner_name : typing.Optional[NerName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1014,8 +786,6 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1023,8 +793,6 @@ async def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1032,8 +800,6 @@ async def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1041,14 +807,13 @@ async def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1073,24 +838,52 @@ async def get(
         async def main() -> None:
             await client.authors.get(
                 author_name="Jane Smith",
-                predefined_sources="top 100 US, top 5 GB",
+                not_author_name="John Doe, Jane Doe",
+                predefined_sources="top 50 US, top 20 GB",
+                sources="nytimes.com,finance.yahoo.com",
+                not_sources="cnn.com,wsj.com",
+                lang="en,es",
+                not_lang="fr,de",
+                countries="US,CA",
+                not_countries="UK,FR",
                 from_=datetime.datetime.fromisoformat(
                     "2024-07-01 00:00:00+00:00",
                 ),
                 to=datetime.datetime.fromisoformat(
-                    "2024-07-01 00:00:00+00:00",
+                    "2024-01-01 00:00:00+00:00",
                 ),
+                published_date_precision="full",
+                by_parse_date=True,
+                ranked_only=True,
+                from_rank=100,
+                to_rank=100,
+                is_headline=True,
+                is_opinion=True,
+                is_paid_content=False,
+                parent_url="wsj.com/politics,wsj.com/tech",
+                all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+                all_domain_links="who.int,nih.gov",
+                all_links_text="Nvidia,Tesla",
+                word_count_min=300,
+                word_count_max=1000,
+                page=2,
+                page_size=50,
                 include_translation_fields=True,
                 include_nlp_data=True,
                 has_nlp=True,
-                theme="Business,Finance",
-                not_theme="Crime",
-                ner_name="Tesla",
+                theme="Finance,Tech",
+                not_theme="Crime,Sports",
+                ner_name="Tesla,Amazon",
+                title_sentiment_min=-0.5,
+                title_sentiment_max=0.5,
+                content_sentiment_min=-0.5,
+                content_sentiment_max=0.5,
                 iptc_tags="20000199,20000209",
                 not_iptc_tags="20000205,20000209",
                 iab_tags="Business,Events",
                 not_iab_tags="Agriculture,Metals",
-                custom_tags="Tag1,Tag2,Tag3",
+                custom_tags="Tag1,Tag2",
+                robots_compliant=True,
             )
 
 
@@ -1120,6 +913,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -1170,6 +964,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -1243,6 +1038,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -1294,7 +1091,6 @@ async def post(
         Examples
         --------
         import asyncio
-        import datetime
 
         from newscatcher import AsyncNewscatcherApi
 
@@ -1305,15 +1101,7 @@ async def post(
 
         async def main() -> None:
             await client.authors.post(
-                author_name="Joanna Stern",
-                sources=["wsj.com", "nytimes.com"],
-                lang="en",
-                from_=datetime.datetime.fromisoformat(
-                    "2024-01-01 00:00:00+00:00",
-                ),
-                to=datetime.datetime.fromisoformat(
-                    "2024-06-30 00:00:00+00:00",
-                ),
+                author_name="David Muir",
             )
 
 
@@ -1343,6 +1131,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
diff --git a/src/newscatcher/authors/raw_client.py b/src/newscatcher/authors/raw_client.py
index 6f244c2..714aaec 100644
--- a/src/newscatcher/authors/raw_client.py
+++ b/src/newscatcher/authors/raw_client.py
@@ -1,13 +1,12 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import datetime as dt
 import typing
 from json.decoder import JSONDecodeError
 
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
-from ..core.datetime_utils import serialize_datetime
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..core.serialization import convert_and_respect_annotation_metadata
@@ -20,6 +19,7 @@
 from ..errors.unprocessable_entity_error import UnprocessableEntityError
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.author_name import AuthorName
 from ..types.by_parse_date import ByParseDate
 from ..types.content_sentiment_max import ContentSentimentMax
@@ -62,10 +62,9 @@
 from ..types.to_rank import ToRank
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
-from .types.authors_get_request_published_date_precision import AuthorsGetRequestPublishedDatePrecision
-from .types.authors_get_request_sort_by import AuthorsGetRequestSortBy
 from .types.authors_get_response import AuthorsGetResponse
 from .types.authors_post_response import AuthorsPostResponse
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -78,7 +77,7 @@ def __init__(self, *, client_wrapper: SyncClientWrapper):
     def get(
         self,
         *,
-        author_name: str,
+        author_name: AuthorName,
         not_author_name: typing.Optional[str] = None,
         predefined_sources: typing.Optional[str] = None,
         sources: typing.Optional[str] = None,
@@ -87,40 +86,41 @@ def get(
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AuthorsGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AuthorsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        ner_name: typing.Optional[NerName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[AuthorsGetResponse]:
         """
@@ -128,154 +128,93 @@ def get(
 
         Parameters
         ----------
-        author_name : str
-            The name of the author to search for. This parameter returns exact matches only.
+        author_name : AuthorName
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AuthorsGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AuthorsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_min : typing.Optional[WordCountMin]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        word_count_max : typing.Optional[WordCountMax]
+
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -283,84 +222,23 @@ def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        theme : typing.Optional[Theme]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        not_theme : typing.Optional[NotTheme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        ner_name : typing.Optional[NerName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -368,8 +246,6 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -377,8 +253,6 @@ def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -386,8 +260,6 @@ def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -395,14 +267,13 @@ def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -425,8 +296,8 @@ def get(
                 "not_lang": not_lang,
                 "countries": countries,
                 "not_countries": not_countries,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
+                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
+                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
                 "published_date_precision": published_date_precision,
                 "by_parse_date": by_parse_date,
                 "sort_by": sort_by,
@@ -439,6 +310,7 @@ def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -552,6 +424,10 @@ def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     def post(
@@ -580,6 +456,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -653,6 +530,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -748,6 +627,9 @@ def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -755,10 +637,8 @@ def post(
                 "include_translation_fields": include_translation_fields,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ner_name": ner_name,
                 "title_sentiment_min": title_sentiment_min,
                 "title_sentiment_max": title_sentiment_max,
@@ -877,6 +757,10 @@ def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
@@ -887,7 +771,7 @@ def __init__(self, *, client_wrapper: AsyncClientWrapper):
     async def get(
         self,
         *,
-        author_name: str,
+        author_name: AuthorName,
         not_author_name: typing.Optional[str] = None,
         predefined_sources: typing.Optional[str] = None,
         sources: typing.Optional[str] = None,
@@ -896,40 +780,41 @@ async def get(
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[AuthorsGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[AuthorsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        ner_name: typing.Optional[NerName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[AuthorsGetResponse]:
         """
@@ -937,154 +822,93 @@ async def get(
 
         Parameters
         ----------
-        author_name : str
-            The name of the author to search for. This parameter returns exact matches only.
+        author_name : AuthorName
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[AuthorsGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[AuthorsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        word_count_min : typing.Optional[WordCountMin]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        word_count_max : typing.Optional[WordCountMax]
+
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -1092,84 +916,23 @@ async def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        theme : typing.Optional[Theme]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        not_theme : typing.Optional[NotTheme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        ner_name : typing.Optional[NerName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1177,8 +940,6 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1186,8 +947,6 @@ async def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1195,8 +954,6 @@ async def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1204,14 +961,13 @@ async def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1234,8 +990,8 @@ async def get(
                 "not_lang": not_lang,
                 "countries": countries,
                 "not_countries": not_countries,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
+                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
+                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
                 "published_date_precision": published_date_precision,
                 "by_parse_date": by_parse_date,
                 "sort_by": sort_by,
@@ -1248,6 +1004,7 @@ async def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -1361,6 +1118,10 @@ async def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     async def post(
@@ -1389,6 +1150,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -1462,6 +1224,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -1557,6 +1321,9 @@ async def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -1564,10 +1331,8 @@ async def post(
                 "include_translation_fields": include_translation_fields,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ner_name": ner_name,
                 "title_sentiment_min": title_sentiment_min,
                 "title_sentiment_max": title_sentiment_max,
@@ -1686,4 +1451,8 @@ async def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/authors/types/__init__.py b/src/newscatcher/authors/types/__init__.py
index afa44b2..3766d81 100644
--- a/src/newscatcher/authors/types/__init__.py
+++ b/src/newscatcher/authors/types/__init__.py
@@ -2,14 +2,37 @@
 
 # isort: skip_file
 
-from .authors_get_request_published_date_precision import AuthorsGetRequestPublishedDatePrecision
-from .authors_get_request_sort_by import AuthorsGetRequestSortBy
-from .authors_get_response import AuthorsGetResponse
-from .authors_post_response import AuthorsPostResponse
-
-__all__ = [
-    "AuthorsGetRequestPublishedDatePrecision",
-    "AuthorsGetRequestSortBy",
-    "AuthorsGetResponse",
-    "AuthorsPostResponse",
-]
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .authors_get_response import AuthorsGetResponse
+    from .authors_post_response import AuthorsPostResponse
+_dynamic_imports: typing.Dict[str, str] = {
+    "AuthorsGetResponse": ".authors_get_response",
+    "AuthorsPostResponse": ".authors_post_response",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["AuthorsGetResponse", "AuthorsPostResponse"]
diff --git a/src/newscatcher/authors/types/authors_get_request_published_date_precision.py b/src/newscatcher/authors/types/authors_get_request_published_date_precision.py
deleted file mode 100644
index 8999022..0000000
--- a/src/newscatcher/authors/types/authors_get_request_published_date_precision.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-AuthorsGetRequestPublishedDatePrecision = typing.Union[typing.Literal["full", "timezone unknown", "date"], typing.Any]
diff --git a/src/newscatcher/authors/types/authors_get_request_sort_by.py b/src/newscatcher/authors/types/authors_get_request_sort_by.py
deleted file mode 100644
index 62b8da7..0000000
--- a/src/newscatcher/authors/types/authors_get_request_sort_by.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-AuthorsGetRequestSortBy = typing.Union[typing.Literal["relevancy", "date", "rank"], typing.Any]
diff --git a/src/newscatcher/base_client.py b/src/newscatcher/base_client.py
index 04a1f90..4869cb1 100644
--- a/src/newscatcher/base_client.py
+++ b/src/newscatcher/base_client.py
@@ -1,19 +1,23 @@
 # This file was auto-generated by Fern from our API Definition.
 
+from __future__ import annotations
+
 import typing
 
 import httpx
-from .aggregation.client import AggregationClient, AsyncAggregationClient
-from .authors.client import AsyncAuthorsClient, AuthorsClient
-from .breaking_news.client import AsyncBreakingNewsClient, BreakingNewsClient
 from .core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
+from .core.logging import LogConfig, Logger
 from .environment import NewscatcherApiEnvironment
-from .latestheadlines.client import AsyncLatestheadlinesClient, LatestheadlinesClient
-from .search.client import AsyncSearchClient, SearchClient
-from .search_link.client import AsyncSearchLinkClient, SearchLinkClient
-from .searchsimilar.client import AsyncSearchsimilarClient, SearchsimilarClient
-from .sources.client import AsyncSourcesClient, SourcesClient
-from .subscription.client import AsyncSubscriptionClient, SubscriptionClient
+
+if typing.TYPE_CHECKING:
+    from .aggregation.client import AggregationClient, AsyncAggregationClient
+    from .authors.client import AsyncAuthorsClient, AuthorsClient
+    from .breaking_news.client import AsyncBreakingNewsClient, BreakingNewsClient
+    from .latest_headlines.client import AsyncLatestHeadlinesClient, LatestHeadlinesClient
+    from .search.client import AsyncSearchClient, SearchClient
+    from .search_by_link.client import AsyncSearchByLinkClient, SearchByLinkClient
+    from .sources.client import AsyncSourcesClient, SourcesClient
+    from .subscription.client import AsyncSubscriptionClient, SubscriptionClient
 
 
 class BaseNewscatcherApi:
@@ -47,6 +51,9 @@ class BaseNewscatcherApi:
     httpx_client : typing.Optional[httpx.Client]
         The httpx client to use for making requests, a preconfigured client is used by default, however this is useful should you want to pass in any custom httpx configuration.
 
+    logging : typing.Optional[typing.Union[LogConfig, Logger]]
+        Configure logging for the SDK. Accepts a LogConfig dict with 'level' (debug/info/warn/error), 'logger' (custom logger implementation), and 'silent' (boolean, defaults to True) fields. You can also pass a pre-configured Logger instance.
+
     Examples
     --------
     from newscatcher import NewscatcherApi
@@ -66,6 +73,7 @@ def __init__(
         timeout: typing.Optional[float] = None,
         follow_redirects: typing.Optional[bool] = True,
         httpx_client: typing.Optional[httpx.Client] = None,
+        logging: typing.Optional[typing.Union[LogConfig, Logger]] = None,
     ):
         _defaulted_timeout = (
             timeout if timeout is not None else 60 if httpx_client is None else httpx_client.timeout.read
@@ -80,16 +88,80 @@ def __init__(
             if follow_redirects is not None
             else httpx.Client(timeout=_defaulted_timeout),
             timeout=_defaulted_timeout,
+            logging=logging,
         )
-        self.search = SearchClient(client_wrapper=self._client_wrapper)
-        self.latestheadlines = LatestheadlinesClient(client_wrapper=self._client_wrapper)
-        self.breaking_news = BreakingNewsClient(client_wrapper=self._client_wrapper)
-        self.authors = AuthorsClient(client_wrapper=self._client_wrapper)
-        self.search_link = SearchLinkClient(client_wrapper=self._client_wrapper)
-        self.searchsimilar = SearchsimilarClient(client_wrapper=self._client_wrapper)
-        self.sources = SourcesClient(client_wrapper=self._client_wrapper)
-        self.aggregation = AggregationClient(client_wrapper=self._client_wrapper)
-        self.subscription = SubscriptionClient(client_wrapper=self._client_wrapper)
+        self._search: typing.Optional[SearchClient] = None
+        self._latest_headlines: typing.Optional[LatestHeadlinesClient] = None
+        self._breaking_news: typing.Optional[BreakingNewsClient] = None
+        self._authors: typing.Optional[AuthorsClient] = None
+        self._search_by_link: typing.Optional[SearchByLinkClient] = None
+        self._sources: typing.Optional[SourcesClient] = None
+        self._aggregation: typing.Optional[AggregationClient] = None
+        self._subscription: typing.Optional[SubscriptionClient] = None
+
+    @property
+    def search(self):
+        if self._search is None:
+            from .search.client import SearchClient  # noqa: E402
+
+            self._search = SearchClient(client_wrapper=self._client_wrapper)
+        return self._search
+
+    @property
+    def latest_headlines(self):
+        if self._latest_headlines is None:
+            from .latest_headlines.client import LatestHeadlinesClient  # noqa: E402
+
+            self._latest_headlines = LatestHeadlinesClient(client_wrapper=self._client_wrapper)
+        return self._latest_headlines
+
+    @property
+    def breaking_news(self):
+        if self._breaking_news is None:
+            from .breaking_news.client import BreakingNewsClient  # noqa: E402
+
+            self._breaking_news = BreakingNewsClient(client_wrapper=self._client_wrapper)
+        return self._breaking_news
+
+    @property
+    def authors(self):
+        if self._authors is None:
+            from .authors.client import AuthorsClient  # noqa: E402
+
+            self._authors = AuthorsClient(client_wrapper=self._client_wrapper)
+        return self._authors
+
+    @property
+    def search_by_link(self):
+        if self._search_by_link is None:
+            from .search_by_link.client import SearchByLinkClient  # noqa: E402
+
+            self._search_by_link = SearchByLinkClient(client_wrapper=self._client_wrapper)
+        return self._search_by_link
+
+    @property
+    def sources(self):
+        if self._sources is None:
+            from .sources.client import SourcesClient  # noqa: E402
+
+            self._sources = SourcesClient(client_wrapper=self._client_wrapper)
+        return self._sources
+
+    @property
+    def aggregation(self):
+        if self._aggregation is None:
+            from .aggregation.client import AggregationClient  # noqa: E402
+
+            self._aggregation = AggregationClient(client_wrapper=self._client_wrapper)
+        return self._aggregation
+
+    @property
+    def subscription(self):
+        if self._subscription is None:
+            from .subscription.client import SubscriptionClient  # noqa: E402
+
+            self._subscription = SubscriptionClient(client_wrapper=self._client_wrapper)
+        return self._subscription
 
 
 class AsyncBaseNewscatcherApi:
@@ -123,6 +195,9 @@ class AsyncBaseNewscatcherApi:
     httpx_client : typing.Optional[httpx.AsyncClient]
         The httpx client to use for making requests, a preconfigured client is used by default, however this is useful should you want to pass in any custom httpx configuration.
 
+    logging : typing.Optional[typing.Union[LogConfig, Logger]]
+        Configure logging for the SDK. Accepts a LogConfig dict with 'level' (debug/info/warn/error), 'logger' (custom logger implementation), and 'silent' (boolean, defaults to True) fields. You can also pass a pre-configured Logger instance.
+
     Examples
     --------
     from newscatcher import AsyncNewscatcherApi
@@ -142,6 +217,7 @@ def __init__(
         timeout: typing.Optional[float] = None,
         follow_redirects: typing.Optional[bool] = True,
         httpx_client: typing.Optional[httpx.AsyncClient] = None,
+        logging: typing.Optional[typing.Union[LogConfig, Logger]] = None,
     ):
         _defaulted_timeout = (
             timeout if timeout is not None else 60 if httpx_client is None else httpx_client.timeout.read
@@ -156,16 +232,80 @@ def __init__(
             if follow_redirects is not None
             else httpx.AsyncClient(timeout=_defaulted_timeout),
             timeout=_defaulted_timeout,
+            logging=logging,
         )
-        self.search = AsyncSearchClient(client_wrapper=self._client_wrapper)
-        self.latestheadlines = AsyncLatestheadlinesClient(client_wrapper=self._client_wrapper)
-        self.breaking_news = AsyncBreakingNewsClient(client_wrapper=self._client_wrapper)
-        self.authors = AsyncAuthorsClient(client_wrapper=self._client_wrapper)
-        self.search_link = AsyncSearchLinkClient(client_wrapper=self._client_wrapper)
-        self.searchsimilar = AsyncSearchsimilarClient(client_wrapper=self._client_wrapper)
-        self.sources = AsyncSourcesClient(client_wrapper=self._client_wrapper)
-        self.aggregation = AsyncAggregationClient(client_wrapper=self._client_wrapper)
-        self.subscription = AsyncSubscriptionClient(client_wrapper=self._client_wrapper)
+        self._search: typing.Optional[AsyncSearchClient] = None
+        self._latest_headlines: typing.Optional[AsyncLatestHeadlinesClient] = None
+        self._breaking_news: typing.Optional[AsyncBreakingNewsClient] = None
+        self._authors: typing.Optional[AsyncAuthorsClient] = None
+        self._search_by_link: typing.Optional[AsyncSearchByLinkClient] = None
+        self._sources: typing.Optional[AsyncSourcesClient] = None
+        self._aggregation: typing.Optional[AsyncAggregationClient] = None
+        self._subscription: typing.Optional[AsyncSubscriptionClient] = None
+
+    @property
+    def search(self):
+        if self._search is None:
+            from .search.client import AsyncSearchClient  # noqa: E402
+
+            self._search = AsyncSearchClient(client_wrapper=self._client_wrapper)
+        return self._search
+
+    @property
+    def latest_headlines(self):
+        if self._latest_headlines is None:
+            from .latest_headlines.client import AsyncLatestHeadlinesClient  # noqa: E402
+
+            self._latest_headlines = AsyncLatestHeadlinesClient(client_wrapper=self._client_wrapper)
+        return self._latest_headlines
+
+    @property
+    def breaking_news(self):
+        if self._breaking_news is None:
+            from .breaking_news.client import AsyncBreakingNewsClient  # noqa: E402
+
+            self._breaking_news = AsyncBreakingNewsClient(client_wrapper=self._client_wrapper)
+        return self._breaking_news
+
+    @property
+    def authors(self):
+        if self._authors is None:
+            from .authors.client import AsyncAuthorsClient  # noqa: E402
+
+            self._authors = AsyncAuthorsClient(client_wrapper=self._client_wrapper)
+        return self._authors
+
+    @property
+    def search_by_link(self):
+        if self._search_by_link is None:
+            from .search_by_link.client import AsyncSearchByLinkClient  # noqa: E402
+
+            self._search_by_link = AsyncSearchByLinkClient(client_wrapper=self._client_wrapper)
+        return self._search_by_link
+
+    @property
+    def sources(self):
+        if self._sources is None:
+            from .sources.client import AsyncSourcesClient  # noqa: E402
+
+            self._sources = AsyncSourcesClient(client_wrapper=self._client_wrapper)
+        return self._sources
+
+    @property
+    def aggregation(self):
+        if self._aggregation is None:
+            from .aggregation.client import AsyncAggregationClient  # noqa: E402
+
+            self._aggregation = AsyncAggregationClient(client_wrapper=self._client_wrapper)
+        return self._aggregation
+
+    @property
+    def subscription(self):
+        if self._subscription is None:
+            from .subscription.client import AsyncSubscriptionClient  # noqa: E402
+
+            self._subscription = AsyncSubscriptionClient(client_wrapper=self._client_wrapper)
+        return self._subscription
 
 
 def _get_base_url(*, base_url: typing.Optional[str] = None, environment: NewscatcherApiEnvironment) -> str:
diff --git a/src/newscatcher/breaking_news/__init__.py b/src/newscatcher/breaking_news/__init__.py
index 8661612..5cde020 100644
--- a/src/newscatcher/breaking_news/__init__.py
+++ b/src/newscatcher/breaking_news/__init__.py
@@ -2,6 +2,3 @@
 
 # isort: skip_file
 
-from .types import BreakingNewsGetRequestSortBy
-
-__all__ = ["BreakingNewsGetRequestSortBy"]
diff --git a/src/newscatcher/breaking_news/client.py b/src/newscatcher/breaking_news/client.py
index 350a29a..ac47861 100644
--- a/src/newscatcher/breaking_news/client.py
+++ b/src/newscatcher/breaking_news/client.py
@@ -19,7 +19,6 @@
 from ..types.page_size import PageSize
 from ..types.per_entity_name import PerEntityName
 from ..types.ranked_only import RankedOnly
-from ..types.robots_compliant import RobotsCompliant
 from ..types.sort_by import SortBy
 from ..types.theme import Theme
 from ..types.title_sentiment_max import TitleSentimentMax
@@ -27,7 +26,6 @@
 from ..types.to_rank import ToRank
 from ..types.top_n_articles import TopNArticles
 from .raw_client import AsyncRawBreakingNewsClient, RawBreakingNewsClient
-from .types.breaking_news_get_request_sort_by import BreakingNewsGetRequestSortBy
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -51,27 +49,26 @@ def with_raw_response(self) -> RawBreakingNewsClient:
     def breaking_news_get(
         self,
         *,
-        sort_by: typing.Optional[BreakingNewsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         top_n_articles: typing.Optional[TopNArticles] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> BreakingNewsResponseDto:
         """
@@ -79,28 +76,17 @@ def breaking_news_get(
 
         Parameters
         ----------
-        sort_by : typing.Optional[BreakingNewsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        sort_by : typing.Optional[SortBy]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        ranked_only : typing.Optional[RankedOnly]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        to_rank : typing.Optional[ToRank]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         top_n_articles : typing.Optional[TopNArticles]
 
@@ -110,112 +96,25 @@ def breaking_news_get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        theme : typing.Optional[Theme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        not_theme : typing.Optional[NotTheme]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        loc_entity_name : typing.Optional[LocEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -233,12 +132,25 @@ def breaking_news_get(
             api_key="YOUR_API_KEY",
         )
         client.breaking_news.breaking_news_get(
+            ranked_only=True,
+            from_rank=100,
+            to_rank=100,
+            page=2,
+            page_size=50,
             top_n_articles=5,
             include_translation_fields=True,
             include_nlp_data=True,
             has_nlp=True,
-            theme="Business,Finance",
-            not_theme="Crime",
+            theme="Finance,Tech",
+            not_theme="Crime,Sports",
+            org_entity_name='"Apple Inc" OR Microsoft',
+            per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+            loc_entity_name='"San Francisco" OR "New York City"',
+            misc_entity_name='AWS OR "Microsoft Azure"',
+            title_sentiment_min=-0.5,
+            title_sentiment_max=0.5,
+            content_sentiment_min=-0.5,
+            content_sentiment_max=0.5,
         )
         """
         _response = self._raw_client.breaking_news_get(
@@ -262,7 +174,6 @@ def breaking_news_get(
             title_sentiment_max=title_sentiment_max,
             content_sentiment_min=content_sentiment_min,
             content_sentiment_max=content_sentiment_max,
-            robots_compliant=robots_compliant,
             request_options=request_options,
         )
         return _response.data
@@ -289,8 +200,7 @@ def breaking_news_post(
         title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
         title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
         content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentient_max: typing.Optional[ContentSentimentMax] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> BreakingNewsResponseDto:
         """
@@ -336,9 +246,7 @@ def breaking_news_post(
 
         content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        content_sentient_max : typing.Optional[ContentSentimentMax]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -357,9 +265,8 @@ def breaking_news_post(
         )
         client.breaking_news.breaking_news_post(
             sort_by="relevancy",
-            page=1,
-            page_size=100,
-            include_nlp_data=True,
+            ranked_only=True,
+            top_n_articles=1,
         )
         """
         _response = self._raw_client.breaking_news_post(
@@ -382,8 +289,7 @@ def breaking_news_post(
             title_sentiment_min=title_sentiment_min,
             title_sentiment_max=title_sentiment_max,
             content_sentiment_min=content_sentiment_min,
-            content_sentient_max=content_sentient_max,
-            robots_compliant=robots_compliant,
+            content_sentiment_max=content_sentiment_max,
             request_options=request_options,
         )
         return _response.data
@@ -407,27 +313,26 @@ def with_raw_response(self) -> AsyncRawBreakingNewsClient:
     async def breaking_news_get(
         self,
         *,
-        sort_by: typing.Optional[BreakingNewsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         top_n_articles: typing.Optional[TopNArticles] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> BreakingNewsResponseDto:
         """
@@ -435,28 +340,17 @@ async def breaking_news_get(
 
         Parameters
         ----------
-        sort_by : typing.Optional[BreakingNewsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        sort_by : typing.Optional[SortBy]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        ranked_only : typing.Optional[RankedOnly]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        to_rank : typing.Optional[ToRank]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         top_n_articles : typing.Optional[TopNArticles]
 
@@ -466,112 +360,25 @@ async def breaking_news_get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        theme : typing.Optional[Theme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        not_theme : typing.Optional[NotTheme]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        loc_entity_name : typing.Optional[LocEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -594,12 +401,25 @@ async def breaking_news_get(
 
         async def main() -> None:
             await client.breaking_news.breaking_news_get(
+                ranked_only=True,
+                from_rank=100,
+                to_rank=100,
+                page=2,
+                page_size=50,
                 top_n_articles=5,
                 include_translation_fields=True,
                 include_nlp_data=True,
                 has_nlp=True,
-                theme="Business,Finance",
-                not_theme="Crime",
+                theme="Finance,Tech",
+                not_theme="Crime,Sports",
+                org_entity_name='"Apple Inc" OR Microsoft',
+                per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+                loc_entity_name='"San Francisco" OR "New York City"',
+                misc_entity_name='AWS OR "Microsoft Azure"',
+                title_sentiment_min=-0.5,
+                title_sentiment_max=0.5,
+                content_sentiment_min=-0.5,
+                content_sentiment_max=0.5,
             )
 
 
@@ -626,7 +446,6 @@ async def main() -> None:
             title_sentiment_max=title_sentiment_max,
             content_sentiment_min=content_sentiment_min,
             content_sentiment_max=content_sentiment_max,
-            robots_compliant=robots_compliant,
             request_options=request_options,
         )
         return _response.data
@@ -653,8 +472,7 @@ async def breaking_news_post(
         title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
         title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
         content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentient_max: typing.Optional[ContentSentimentMax] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> BreakingNewsResponseDto:
         """
@@ -700,9 +518,7 @@ async def breaking_news_post(
 
         content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        content_sentient_max : typing.Optional[ContentSentimentMax]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -726,9 +542,8 @@ async def breaking_news_post(
         async def main() -> None:
             await client.breaking_news.breaking_news_post(
                 sort_by="relevancy",
-                page=1,
-                page_size=100,
-                include_nlp_data=True,
+                ranked_only=True,
+                top_n_articles=1,
             )
 
 
@@ -754,8 +569,7 @@ async def main() -> None:
             title_sentiment_min=title_sentiment_min,
             title_sentiment_max=title_sentiment_max,
             content_sentiment_min=content_sentiment_min,
-            content_sentient_max=content_sentient_max,
-            robots_compliant=robots_compliant,
+            content_sentiment_max=content_sentiment_max,
             request_options=request_options,
         )
         return _response.data
diff --git a/src/newscatcher/breaking_news/raw_client.py b/src/newscatcher/breaking_news/raw_client.py
index be4c042..69b177f 100644
--- a/src/newscatcher/breaking_news/raw_client.py
+++ b/src/newscatcher/breaking_news/raw_client.py
@@ -6,9 +6,9 @@
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
-from ..core.serialization import convert_and_respect_annotation_metadata
 from ..errors.bad_request_error import BadRequestError
 from ..errors.forbidden_error import ForbiddenError
 from ..errors.internal_server_error import InternalServerError
@@ -32,14 +32,13 @@
 from ..types.page_size import PageSize
 from ..types.per_entity_name import PerEntityName
 from ..types.ranked_only import RankedOnly
-from ..types.robots_compliant import RobotsCompliant
 from ..types.sort_by import SortBy
 from ..types.theme import Theme
 from ..types.title_sentiment_max import TitleSentimentMax
 from ..types.title_sentiment_min import TitleSentimentMin
 from ..types.to_rank import ToRank
 from ..types.top_n_articles import TopNArticles
-from .types.breaking_news_get_request_sort_by import BreakingNewsGetRequestSortBy
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -52,27 +51,26 @@ def __init__(self, *, client_wrapper: SyncClientWrapper):
     def breaking_news_get(
         self,
         *,
-        sort_by: typing.Optional[BreakingNewsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         top_n_articles: typing.Optional[TopNArticles] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[BreakingNewsResponseDto]:
         """
@@ -80,28 +78,17 @@ def breaking_news_get(
 
         Parameters
         ----------
-        sort_by : typing.Optional[BreakingNewsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        sort_by : typing.Optional[SortBy]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        ranked_only : typing.Optional[RankedOnly]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        to_rank : typing.Optional[ToRank]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         top_n_articles : typing.Optional[TopNArticles]
 
@@ -111,112 +98,25 @@ def breaking_news_get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        theme : typing.Optional[Theme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        not_theme : typing.Optional[NotTheme]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        loc_entity_name : typing.Optional[LocEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -250,7 +150,6 @@ def breaking_news_get(
                 "title_sentiment_max": title_sentiment_max,
                 "content_sentiment_min": content_sentiment_min,
                 "content_sentiment_max": content_sentiment_max,
-                "robots_compliant": robots_compliant,
             },
             request_options=request_options,
         )
@@ -344,6 +243,10 @@ def breaking_news_get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     def breaking_news_post(
@@ -368,8 +271,7 @@ def breaking_news_post(
         title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
         title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
         content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentient_max: typing.Optional[ContentSentimentMax] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[BreakingNewsResponseDto]:
         """
@@ -415,9 +317,7 @@ def breaking_news_post(
 
         content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        content_sentient_max : typing.Optional[ContentSentimentMax]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -441,10 +341,8 @@ def breaking_news_post(
                 "include_translation_fields": include_translation_fields,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -452,8 +350,7 @@ def breaking_news_post(
                 "title_sentiment_min": title_sentiment_min,
                 "title_sentiment_max": title_sentiment_max,
                 "content_sentiment_min": content_sentiment_min,
-                "content_sentient_max": content_sentient_max,
-                "robots_compliant": robots_compliant,
+                "content_sentiment_max": content_sentiment_max,
             },
             headers={
                 "content-type": "application/json",
@@ -551,6 +448,10 @@ def breaking_news_post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
@@ -561,27 +462,26 @@ def __init__(self, *, client_wrapper: AsyncClientWrapper):
     async def breaking_news_get(
         self,
         *,
-        sort_by: typing.Optional[BreakingNewsGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
         top_n_articles: typing.Optional[TopNArticles] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[BreakingNewsResponseDto]:
         """
@@ -589,28 +489,17 @@ async def breaking_news_get(
 
         Parameters
         ----------
-        sort_by : typing.Optional[BreakingNewsGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        sort_by : typing.Optional[SortBy]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        ranked_only : typing.Optional[RankedOnly]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        to_rank : typing.Optional[ToRank]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
         top_n_articles : typing.Optional[TopNArticles]
 
@@ -620,112 +509,25 @@ async def breaking_news_get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        theme : typing.Optional[Theme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        not_theme : typing.Optional[NotTheme]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        loc_entity_name : typing.Optional[LocEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -759,7 +561,6 @@ async def breaking_news_get(
                 "title_sentiment_max": title_sentiment_max,
                 "content_sentiment_min": content_sentiment_min,
                 "content_sentiment_max": content_sentiment_max,
-                "robots_compliant": robots_compliant,
             },
             request_options=request_options,
         )
@@ -853,6 +654,10 @@ async def breaking_news_get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     async def breaking_news_post(
@@ -877,8 +682,7 @@ async def breaking_news_post(
         title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
         title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
         content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentient_max: typing.Optional[ContentSentimentMax] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[BreakingNewsResponseDto]:
         """
@@ -924,9 +728,7 @@ async def breaking_news_post(
 
         content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-        content_sentient_max : typing.Optional[ContentSentimentMax]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -950,10 +752,8 @@ async def breaking_news_post(
                 "include_translation_fields": include_translation_fields,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -961,8 +761,7 @@ async def breaking_news_post(
                 "title_sentiment_min": title_sentiment_min,
                 "title_sentiment_max": title_sentiment_max,
                 "content_sentiment_min": content_sentiment_min,
-                "content_sentient_max": content_sentient_max,
-                "robots_compliant": robots_compliant,
+                "content_sentiment_max": content_sentiment_max,
             },
             headers={
                 "content-type": "application/json",
@@ -1060,4 +859,8 @@ async def breaking_news_post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/breaking_news/types/__init__.py b/src/newscatcher/breaking_news/types/__init__.py
deleted file mode 100644
index 7ad450d..0000000
--- a/src/newscatcher/breaking_news/types/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-# isort: skip_file
-
-from .breaking_news_get_request_sort_by import BreakingNewsGetRequestSortBy
-
-__all__ = ["BreakingNewsGetRequestSortBy"]
diff --git a/src/newscatcher/breaking_news/types/breaking_news_get_request_sort_by.py b/src/newscatcher/breaking_news/types/breaking_news_get_request_sort_by.py
deleted file mode 100644
index a806b7d..0000000
--- a/src/newscatcher/breaking_news/types/breaking_news_get_request_sort_by.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-BreakingNewsGetRequestSortBy = typing.Union[typing.Literal["relevancy", "date", "rank"], typing.Any]
diff --git a/src/newscatcher/core/__init__.py b/src/newscatcher/core/__init__.py
index 31bbb81..4fb6e12 100644
--- a/src/newscatcher/core/__init__.py
+++ b/src/newscatcher/core/__init__.py
@@ -2,26 +2,90 @@
 
 # isort: skip_file
 
-from .api_error import ApiError
-from .client_wrapper import AsyncClientWrapper, BaseClientWrapper, SyncClientWrapper
-from .datetime_utils import serialize_datetime
-from .file import File, convert_file_dict_to_httpx_tuples, with_content_type
-from .http_client import AsyncHttpClient, HttpClient
-from .http_response import AsyncHttpResponse, HttpResponse
-from .jsonable_encoder import jsonable_encoder
-from .pydantic_utilities import (
-    IS_PYDANTIC_V2,
-    UniversalBaseModel,
-    UniversalRootModel,
-    parse_obj_as,
-    universal_field_validator,
-    universal_root_validator,
-    update_forward_refs,
-)
-from .query_encoder import encode_query
-from .remove_none_from_dict import remove_none_from_dict
-from .request_options import RequestOptions
-from .serialization import FieldMetadata, convert_and_respect_annotation_metadata
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .api_error import ApiError
+    from .client_wrapper import AsyncClientWrapper, BaseClientWrapper, SyncClientWrapper
+    from .datetime_utils import Rfc2822DateTime, parse_rfc2822_datetime, serialize_datetime
+    from .file import File, convert_file_dict_to_httpx_tuples, with_content_type
+    from .http_client import AsyncHttpClient, HttpClient
+    from .http_response import AsyncHttpResponse, HttpResponse
+    from .jsonable_encoder import jsonable_encoder
+    from .logging import ConsoleLogger, ILogger, LogConfig, LogLevel, Logger, create_logger
+    from .parse_error import ParsingError
+    from .pydantic_utilities import (
+        IS_PYDANTIC_V2,
+        UniversalBaseModel,
+        UniversalRootModel,
+        parse_obj_as,
+        universal_field_validator,
+        universal_root_validator,
+        update_forward_refs,
+    )
+    from .query_encoder import encode_query
+    from .remove_none_from_dict import remove_none_from_dict
+    from .request_options import RequestOptions
+    from .serialization import FieldMetadata, convert_and_respect_annotation_metadata
+_dynamic_imports: typing.Dict[str, str] = {
+    "ApiError": ".api_error",
+    "AsyncClientWrapper": ".client_wrapper",
+    "AsyncHttpClient": ".http_client",
+    "AsyncHttpResponse": ".http_response",
+    "BaseClientWrapper": ".client_wrapper",
+    "ConsoleLogger": ".logging",
+    "FieldMetadata": ".serialization",
+    "File": ".file",
+    "HttpClient": ".http_client",
+    "HttpResponse": ".http_response",
+    "ILogger": ".logging",
+    "IS_PYDANTIC_V2": ".pydantic_utilities",
+    "LogConfig": ".logging",
+    "LogLevel": ".logging",
+    "Logger": ".logging",
+    "ParsingError": ".parse_error",
+    "RequestOptions": ".request_options",
+    "Rfc2822DateTime": ".datetime_utils",
+    "SyncClientWrapper": ".client_wrapper",
+    "UniversalBaseModel": ".pydantic_utilities",
+    "UniversalRootModel": ".pydantic_utilities",
+    "convert_and_respect_annotation_metadata": ".serialization",
+    "convert_file_dict_to_httpx_tuples": ".file",
+    "create_logger": ".logging",
+    "encode_query": ".query_encoder",
+    "jsonable_encoder": ".jsonable_encoder",
+    "parse_obj_as": ".pydantic_utilities",
+    "parse_rfc2822_datetime": ".datetime_utils",
+    "remove_none_from_dict": ".remove_none_from_dict",
+    "serialize_datetime": ".datetime_utils",
+    "universal_field_validator": ".pydantic_utilities",
+    "universal_root_validator": ".pydantic_utilities",
+    "update_forward_refs": ".pydantic_utilities",
+    "with_content_type": ".file",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
 
 __all__ = [
     "ApiError",
@@ -29,20 +93,29 @@
     "AsyncHttpClient",
     "AsyncHttpResponse",
     "BaseClientWrapper",
+    "ConsoleLogger",
     "FieldMetadata",
     "File",
     "HttpClient",
     "HttpResponse",
+    "ILogger",
     "IS_PYDANTIC_V2",
+    "LogConfig",
+    "LogLevel",
+    "Logger",
+    "ParsingError",
     "RequestOptions",
+    "Rfc2822DateTime",
     "SyncClientWrapper",
     "UniversalBaseModel",
     "UniversalRootModel",
     "convert_and_respect_annotation_metadata",
     "convert_file_dict_to_httpx_tuples",
+    "create_logger",
     "encode_query",
     "jsonable_encoder",
     "parse_obj_as",
+    "parse_rfc2822_datetime",
     "remove_none_from_dict",
     "serialize_datetime",
     "universal_field_validator",
diff --git a/src/newscatcher/core/client_wrapper.py b/src/newscatcher/core/client_wrapper.py
index 2c185f8..b501203 100644
--- a/src/newscatcher/core/client_wrapper.py
+++ b/src/newscatcher/core/client_wrapper.py
@@ -4,6 +4,7 @@
 
 import httpx
 from .http_client import AsyncHttpClient, HttpClient
+from .logging import LogConfig, Logger
 
 
 class BaseClientWrapper:
@@ -14,18 +15,24 @@ def __init__(
         headers: typing.Optional[typing.Dict[str, str]] = None,
         base_url: str,
         timeout: typing.Optional[float] = None,
+        logging: typing.Optional[typing.Union[LogConfig, Logger]] = None,
     ):
         self.api_key = api_key
         self._headers = headers
         self._base_url = base_url
         self._timeout = timeout
+        self._logging = logging
 
     def get_headers(self) -> typing.Dict[str, str]:
+        import platform
+
         headers: typing.Dict[str, str] = {
-            "User-Agent": "newscatcher-sdk/1.4.0",
+            "User-Agent": "newscatcher-sdk/1.4.1",
             "X-Fern-Language": "Python",
+            "X-Fern-Runtime": f"python/{platform.python_version()}",
+            "X-Fern-Platform": f"{platform.system().lower()}/{platform.release()}",
             "X-Fern-SDK-Name": "newscatcher-sdk",
-            "X-Fern-SDK-Version": "1.4.0",
+            "X-Fern-SDK-Version": "1.4.1",
             **(self.get_custom_headers() or {}),
         }
         headers["x-api-token"] = self.api_key
@@ -49,14 +56,16 @@ def __init__(
         headers: typing.Optional[typing.Dict[str, str]] = None,
         base_url: str,
         timeout: typing.Optional[float] = None,
+        logging: typing.Optional[typing.Union[LogConfig, Logger]] = None,
         httpx_client: httpx.Client,
     ):
-        super().__init__(api_key=api_key, headers=headers, base_url=base_url, timeout=timeout)
+        super().__init__(api_key=api_key, headers=headers, base_url=base_url, timeout=timeout, logging=logging)
         self.httpx_client = HttpClient(
             httpx_client=httpx_client,
             base_headers=self.get_headers,
             base_timeout=self.get_timeout,
             base_url=self.get_base_url,
+            logging_config=self._logging,
         )
 
 
@@ -68,12 +77,24 @@ def __init__(
         headers: typing.Optional[typing.Dict[str, str]] = None,
         base_url: str,
         timeout: typing.Optional[float] = None,
+        logging: typing.Optional[typing.Union[LogConfig, Logger]] = None,
+        async_token: typing.Optional[typing.Callable[[], typing.Awaitable[str]]] = None,
         httpx_client: httpx.AsyncClient,
     ):
-        super().__init__(api_key=api_key, headers=headers, base_url=base_url, timeout=timeout)
+        super().__init__(api_key=api_key, headers=headers, base_url=base_url, timeout=timeout, logging=logging)
+        self._async_token = async_token
         self.httpx_client = AsyncHttpClient(
             httpx_client=httpx_client,
             base_headers=self.get_headers,
             base_timeout=self.get_timeout,
             base_url=self.get_base_url,
+            async_base_headers=self.async_get_headers,
+            logging_config=self._logging,
         )
+
+    async def async_get_headers(self) -> typing.Dict[str, str]:
+        headers = self.get_headers()
+        if self._async_token is not None:
+            token = await self._async_token()
+            headers["Authorization"] = f"Bearer {token}"
+        return headers
diff --git a/src/newscatcher/core/datetime_utils.py b/src/newscatcher/core/datetime_utils.py
index 7c9864a..a12b2ad 100644
--- a/src/newscatcher/core/datetime_utils.py
+++ b/src/newscatcher/core/datetime_utils.py
@@ -1,6 +1,48 @@
 # This file was auto-generated by Fern from our API Definition.
 
 import datetime as dt
+from email.utils import parsedate_to_datetime
+from typing import Any
+
+import pydantic
+
+IS_PYDANTIC_V2 = pydantic.VERSION.startswith("2.")
+
+
+def parse_rfc2822_datetime(v: Any) -> dt.datetime:
+    """
+    Parse an RFC 2822 datetime string (e.g., "Wed, 02 Oct 2002 13:00:00 GMT")
+    into a datetime object. If the value is already a datetime, return it as-is.
+    Falls back to ISO 8601 parsing if RFC 2822 parsing fails.
+    """
+    if isinstance(v, dt.datetime):
+        return v
+    if isinstance(v, str):
+        try:
+            return parsedate_to_datetime(v)
+        except Exception:
+            pass
+        # Fallback to ISO 8601 parsing
+        return dt.datetime.fromisoformat(v.replace("Z", "+00:00"))
+    raise ValueError(f"Expected str or datetime, got {type(v)}")
+
+
+class Rfc2822DateTime(dt.datetime):
+    """A datetime subclass that parses RFC 2822 date strings.
+
+    On Pydantic V1, uses __get_validators__ for pre-validation.
+    On Pydantic V2, uses __get_pydantic_core_schema__ for BeforeValidator-style parsing.
+    """
+
+    @classmethod
+    def __get_validators__(cls):  # type: ignore[no-untyped-def]
+        yield parse_rfc2822_datetime
+
+    @classmethod
+    def __get_pydantic_core_schema__(cls, _source_type: Any, _handler: Any) -> Any:  # type: ignore[override]
+        from pydantic_core import core_schema
+
+        return core_schema.no_info_before_validator_function(parse_rfc2822_datetime, core_schema.datetime_schema())
 
 
 def serialize_datetime(v: dt.datetime) -> str:
diff --git a/src/newscatcher/core/force_multipart.py b/src/newscatcher/core/force_multipart.py
index ae24ccf..5440913 100644
--- a/src/newscatcher/core/force_multipart.py
+++ b/src/newscatcher/core/force_multipart.py
@@ -1,7 +1,9 @@
 # This file was auto-generated by Fern from our API Definition.
 
+from typing import Any, Dict
 
-class ForceMultipartDict(dict):
+
+class ForceMultipartDict(Dict[str, Any]):
     """
     A dictionary subclass that always evaluates to True in boolean contexts.
 
@@ -9,7 +11,7 @@ class ForceMultipartDict(dict):
     the dictionary is empty, which would normally evaluate to False.
     """
 
-    def __bool__(self):
+    def __bool__(self) -> bool:
         return True
 
 
diff --git a/src/newscatcher/core/http_client.py b/src/newscatcher/core/http_client.py
index e4173f9..ee93758 100644
--- a/src/newscatcher/core/http_client.py
+++ b/src/newscatcher/core/http_client.py
@@ -5,7 +5,6 @@
 import re
 import time
 import typing
-import urllib.parse
 from contextlib import asynccontextmanager, contextmanager
 from random import random
 
@@ -13,14 +12,15 @@
 from .file import File, convert_file_dict_to_httpx_tuples
 from .force_multipart import FORCE_MULTIPART
 from .jsonable_encoder import jsonable_encoder
+from .logging import LogConfig, Logger, create_logger
 from .query_encoder import encode_query
-from .remove_none_from_dict import remove_none_from_dict
+from .remove_none_from_dict import remove_none_from_dict as remove_none_from_dict
 from .request_options import RequestOptions
 from httpx._types import RequestFiles
 
-INITIAL_RETRY_DELAY_SECONDS = 0.5
-MAX_RETRY_DELAY_SECONDS = 10
-MAX_RETRY_DELAY_SECONDS_FROM_HEADER = 30
+INITIAL_RETRY_DELAY_SECONDS = 1.0
+MAX_RETRY_DELAY_SECONDS = 60.0
+JITTER_FACTOR = 0.2  # 20% random jitter
 
 
 def _parse_retry_after(response_headers: httpx.Headers) -> typing.Optional[float]:
@@ -64,6 +64,38 @@ def _parse_retry_after(response_headers: httpx.Headers) -> typing.Optional[float
     return seconds
 
 
+def _add_positive_jitter(delay: float) -> float:
+    """Add positive jitter (0-20%) to prevent thundering herd."""
+    jitter_multiplier = 1 + random() * JITTER_FACTOR
+    return delay * jitter_multiplier
+
+
+def _add_symmetric_jitter(delay: float) -> float:
+    """Add symmetric jitter (±10%) for exponential backoff."""
+    jitter_multiplier = 1 + (random() - 0.5) * JITTER_FACTOR
+    return delay * jitter_multiplier
+
+
+def _parse_x_ratelimit_reset(response_headers: httpx.Headers) -> typing.Optional[float]:
+    """
+    Parse the X-RateLimit-Reset header (Unix timestamp in seconds).
+    Returns seconds to wait, or None if header is missing/invalid.
+    """
+    reset_time_str = response_headers.get("x-ratelimit-reset")
+    if reset_time_str is None:
+        return None
+
+    try:
+        reset_time = int(reset_time_str)
+        delay = reset_time - time.time()
+        if delay > 0:
+            return delay
+    except (ValueError, TypeError):
+        pass
+
+    return None
+
+
 def _retry_timeout(response: httpx.Response, retries: int) -> float:
     """
     Determine the amount of time to wait before retrying a request.
@@ -71,17 +103,19 @@ def _retry_timeout(response: httpx.Response, retries: int) -> float:
     with a jitter to determine the number of seconds to wait.
     """
 
-    # If the API asks us to wait a certain amount of time (and it's a reasonable amount), just do what it says.
+    # 1. Check Retry-After header first
     retry_after = _parse_retry_after(response.headers)
-    if retry_after is not None and retry_after <= MAX_RETRY_DELAY_SECONDS_FROM_HEADER:
-        return retry_after
+    if retry_after is not None and retry_after > 0:
+        return min(retry_after, MAX_RETRY_DELAY_SECONDS)
 
-    # Apply exponential backoff, capped at MAX_RETRY_DELAY_SECONDS.
-    retry_delay = min(INITIAL_RETRY_DELAY_SECONDS * pow(2.0, retries), MAX_RETRY_DELAY_SECONDS)
+    # 2. Check X-RateLimit-Reset header (with positive jitter)
+    ratelimit_reset = _parse_x_ratelimit_reset(response.headers)
+    if ratelimit_reset is not None:
+        return _add_positive_jitter(min(ratelimit_reset, MAX_RETRY_DELAY_SECONDS))
 
-    # Add a randomness / jitter to the retry delay to avoid overwhelming the server with retries.
-    timeout = retry_delay * (1 - 0.25 * random())
-    return timeout if timeout >= 0 else 0
+    # 3. Fall back to exponential backoff (with symmetric jitter)
+    backoff = min(INITIAL_RETRY_DELAY_SECONDS * pow(2.0, retries), MAX_RETRY_DELAY_SECONDS)
+    return _add_symmetric_jitter(backoff)
 
 
 def _should_retry(response: httpx.Response) -> bool:
@@ -89,6 +123,71 @@ def _should_retry(response: httpx.Response) -> bool:
     return response.status_code >= 500 or response.status_code in retryable_400s
 
 
+_SENSITIVE_HEADERS = frozenset(
+    {
+        "authorization",
+        "www-authenticate",
+        "x-api-key",
+        "api-key",
+        "apikey",
+        "x-api-token",
+        "x-auth-token",
+        "auth-token",
+        "cookie",
+        "set-cookie",
+        "proxy-authorization",
+        "proxy-authenticate",
+        "x-csrf-token",
+        "x-xsrf-token",
+        "x-session-token",
+        "x-access-token",
+    }
+)
+
+
+def _redact_headers(headers: typing.Dict[str, str]) -> typing.Dict[str, str]:
+    return {k: ("[REDACTED]" if k.lower() in _SENSITIVE_HEADERS else v) for k, v in headers.items()}
+
+
+def _build_url(base_url: str, path: typing.Optional[str]) -> str:
+    """
+    Build a full URL by joining a base URL with a path.
+
+    This function correctly handles base URLs that contain path prefixes (e.g., tenant-based URLs)
+    by using string concatenation instead of urllib.parse.urljoin(), which would incorrectly
+    strip path components when the path starts with '/'.
+
+    Example:
+        >>> _build_url("https://cloud.example.com/org/tenant/api", "/users")
+        'https://cloud.example.com/org/tenant/api/users'
+
+    Args:
+        base_url: The base URL, which may contain path prefixes.
+        path: The path to append. Can be None or empty string.
+
+    Returns:
+        The full URL with base_url and path properly joined.
+    """
+    if not path:
+        return base_url
+    return f"{base_url.rstrip('/')}/{path.lstrip('/')}"
+
+
+def _maybe_filter_none_from_multipart_data(
+    data: typing.Optional[typing.Any],
+    request_files: typing.Optional[RequestFiles],
+    force_multipart: typing.Optional[bool],
+) -> typing.Optional[typing.Any]:
+    """
+    Filter None values from data body for multipart/form requests.
+    This prevents httpx from converting None to empty strings in multipart encoding.
+    Only applies when files are present or force_multipart is True.
+    """
+    if data is not None and isinstance(data, typing.Mapping) and (request_files or force_multipart):
+        return remove_none_from_dict(data)
+    return data
+
+
 def remove_omit_from_dict(
     original: typing.Dict[str, typing.Optional[typing.Any]],
     omit: typing.Optional[typing.Any],
@@ -143,8 +242,19 @@ def get_request_body(
         # If both data and json are None, we send json data in the event extra properties are specified
         json_body = maybe_filter_request_body(json, request_options, omit)
 
-    # If you have an empty JSON body, you should just send None
-    return (json_body if json_body != {} else None), data_body if data_body != {} else None
+    has_additional_body_parameters = bool(
+        request_options is not None and request_options.get("additional_body_parameters")
+    )
+
+    # Only collapse empty dict to None when the body was not explicitly provided
+    # and there are no additional body parameters. This preserves explicit empty
+    # bodies (e.g., when an endpoint has a request body type but all fields are optional).
+    if json_body == {} and json is None and not has_additional_body_parameters:
+        json_body = None
+    if data_body == {} and data is None and not has_additional_body_parameters:
+        data_body = None
+
+    return json_body, data_body
 
 
 class HttpClient:
@@ -155,11 +265,13 @@ def __init__(
         base_timeout: typing.Callable[[], typing.Optional[float]],
         base_headers: typing.Callable[[], typing.Dict[str, str]],
         base_url: typing.Optional[typing.Callable[[], str]] = None,
+        logging_config: typing.Optional[typing.Union[LogConfig, Logger]] = None,
     ):
         self.base_url = base_url
         self.base_timeout = base_timeout
         self.base_headers = base_headers
         self.httpx_client = httpx_client
+        self.logger = create_logger(logging_config)
 
     def get_base_url(self, maybe_base_url: typing.Optional[str]) -> str:
         base_url = maybe_base_url
@@ -188,7 +300,7 @@ def request(
         ] = None,
         headers: typing.Optional[typing.Dict[str, typing.Any]] = None,
         request_options: typing.Optional[RequestOptions] = None,
-        retries: int = 2,
+        retries: int = 0,
         omit: typing.Optional[typing.Any] = None,
         force_multipart: typing.Optional[bool] = None,
     ) -> httpx.Response:
@@ -210,35 +322,53 @@ def request(
         if (request_files is None or len(request_files) == 0) and force_multipart:
             request_files = FORCE_MULTIPART
 
-        response = self.httpx_client.request(
-            method=method,
-            url=urllib.parse.urljoin(f"{base_url}/", path),
-            headers=jsonable_encoder(
+        data_body = _maybe_filter_none_from_multipart_data(data_body, request_files, force_multipart)
+
+        # Compute encoded params separately to avoid passing empty list to httpx
+        # (httpx strips existing query params from URL when params=[] is passed)
+        _encoded_params = encode_query(
+            jsonable_encoder(
                 remove_none_from_dict(
-                    {
-                        **self.base_headers(),
-                        **(headers if headers is not None else {}),
-                        **(request_options.get("additional_headers", {}) or {} if request_options is not None else {}),
-                    }
-                )
-            ),
-            params=encode_query(
-                jsonable_encoder(
-                    remove_none_from_dict(
-                        remove_omit_from_dict(
-                            {
-                                **(params if params is not None else {}),
-                                **(
-                                    request_options.get("additional_query_parameters", {}) or {}
-                                    if request_options is not None
-                                    else {}
-                                ),
-                            },
-                            omit,
-                        )
+                    remove_omit_from_dict(
+                        {
+                            **(params if params is not None else {}),
+                            **(
+                                request_options.get("additional_query_parameters", {}) or {}
+                                if request_options is not None
+                                else {}
+                            ),
+                        },
+                        omit,
                     )
                 )
-            ),
+            )
+        )
+
+        _request_url = _build_url(base_url, path)
+        _request_headers = jsonable_encoder(
+            remove_none_from_dict(
+                {
+                    **self.base_headers(),
+                    **(headers if headers is not None else {}),
+                    **(request_options.get("additional_headers", {}) or {} if request_options is not None else {}),
+                }
+            )
+        )
+
+        if self.logger.is_debug():
+            self.logger.debug(
+                "Making HTTP request",
+                method=method,
+                url=_request_url,
+                headers=_redact_headers(_request_headers),
+                has_body=json_body is not None or data_body is not None,
+            )
+
+        response = self.httpx_client.request(
+            method=method,
+            url=_request_url,
+            headers=_request_headers,
+            params=_encoded_params if _encoded_params else None,
             json=json_body,
             data=data_body,
             content=content,
@@ -246,9 +376,9 @@ def request(
             timeout=timeout,
         )
 
-        max_retries: int = request_options.get("max_retries", 0) if request_options is not None else 0
+        max_retries: int = request_options.get("max_retries", 2) if request_options is not None else 2
         if _should_retry(response=response):
-            if max_retries > retries:
+            if retries < max_retries:
                 time.sleep(_retry_timeout(response=response, retries=retries))
                 return self.request(
                     path=path,
@@ -264,6 +394,24 @@ def request(
                     omit=omit,
                 )
 
+        if self.logger.is_debug():
+            if 200 <= response.status_code < 400:
+                self.logger.debug(
+                    "HTTP request succeeded",
+                    method=method,
+                    url=_request_url,
+                    status_code=response.status_code,
+                )
+
+        if self.logger.is_error():
+            if response.status_code >= 400:
+                self.logger.error(
+                    "HTTP request failed with error status",
+                    method=method,
+                    url=_request_url,
+                    status_code=response.status_code,
+                )
+
         return response
 
     @contextmanager
@@ -285,7 +433,7 @@ def stream(
         ] = None,
         headers: typing.Optional[typing.Dict[str, typing.Any]] = None,
         request_options: typing.Optional[RequestOptions] = None,
-        retries: int = 2,
+        retries: int = 0,
         omit: typing.Optional[typing.Any] = None,
         force_multipart: typing.Optional[bool] = None,
     ) -> typing.Iterator[httpx.Response]:
@@ -307,35 +455,52 @@ def stream(
 
         json_body, data_body = get_request_body(json=json, data=data, request_options=request_options, omit=omit)
 
-        with self.httpx_client.stream(
-            method=method,
-            url=urllib.parse.urljoin(f"{base_url}/", path),
-            headers=jsonable_encoder(
+        data_body = _maybe_filter_none_from_multipart_data(data_body, request_files, force_multipart)
+
+        # Compute encoded params separately to avoid passing empty list to httpx
+        # (httpx strips existing query params from URL when params=[] is passed)
+        _encoded_params = encode_query(
+            jsonable_encoder(
                 remove_none_from_dict(
-                    {
-                        **self.base_headers(),
-                        **(headers if headers is not None else {}),
-                        **(request_options.get("additional_headers", {}) if request_options is not None else {}),
-                    }
-                )
-            ),
-            params=encode_query(
-                jsonable_encoder(
-                    remove_none_from_dict(
-                        remove_omit_from_dict(
-                            {
-                                **(params if params is not None else {}),
-                                **(
-                                    request_options.get("additional_query_parameters", {})
-                                    if request_options is not None
-                                    else {}
-                                ),
-                            },
-                            omit,
-                        )
+                    remove_omit_from_dict(
+                        {
+                            **(params if params is not None else {}),
+                            **(
+                                request_options.get("additional_query_parameters", {})
+                                if request_options is not None
+                                else {}
+                            ),
+                        },
+                        omit,
                     )
                 )
-            ),
+            )
+        )
+
+        _request_url = _build_url(base_url, path)
+        _request_headers = jsonable_encoder(
+            remove_none_from_dict(
+                {
+                    **self.base_headers(),
+                    **(headers if headers is not None else {}),
+                    **(request_options.get("additional_headers", {}) if request_options is not None else {}),
+                }
+            )
+        )
+
+        if self.logger.is_debug():
+            self.logger.debug(
+                "Making streaming HTTP request",
+                method=method,
+                url=_request_url,
+                headers=_redact_headers(_request_headers),
+            )
+
+        with self.httpx_client.stream(
+            method=method,
+            url=_request_url,
+            headers=_request_headers,
+            params=_encoded_params if _encoded_params else None,
             json=json_body,
             data=data_body,
             content=content,
@@ -353,11 +518,20 @@ def __init__(
         base_timeout: typing.Callable[[], typing.Optional[float]],
         base_headers: typing.Callable[[], typing.Dict[str, str]],
         base_url: typing.Optional[typing.Callable[[], str]] = None,
+        async_base_headers: typing.Optional[typing.Callable[[], typing.Awaitable[typing.Dict[str, str]]]] = None,
+        logging_config: typing.Optional[typing.Union[LogConfig, Logger]] = None,
     ):
         self.base_url = base_url
         self.base_timeout = base_timeout
         self.base_headers = base_headers
+        self.async_base_headers = async_base_headers
         self.httpx_client = httpx_client
+        self.logger = create_logger(logging_config)
+
+    async def _get_headers(self) -> typing.Dict[str, str]:
+        if self.async_base_headers is not None:
+            return await self.async_base_headers()
+        return self.base_headers()
 
     def get_base_url(self, maybe_base_url: typing.Optional[str]) -> str:
         base_url = maybe_base_url
@@ -386,7 +560,7 @@ async def request(
         ] = None,
         headers: typing.Optional[typing.Dict[str, typing.Any]] = None,
         request_options: typing.Optional[RequestOptions] = None,
-        retries: int = 2,
+        retries: int = 0,
         omit: typing.Optional[typing.Any] = None,
         force_multipart: typing.Optional[bool] = None,
     ) -> httpx.Response:
@@ -408,36 +582,56 @@ async def request(
 
         json_body, data_body = get_request_body(json=json, data=data, request_options=request_options, omit=omit)
 
-        # Add the input to each of these and do None-safety checks
-        response = await self.httpx_client.request(
-            method=method,
-            url=urllib.parse.urljoin(f"{base_url}/", path),
-            headers=jsonable_encoder(
+        data_body = _maybe_filter_none_from_multipart_data(data_body, request_files, force_multipart)
+
+        # Get headers (supports async token providers)
+        _headers = await self._get_headers()
+
+        # Compute encoded params separately to avoid passing empty list to httpx
+        # (httpx strips existing query params from URL when params=[] is passed)
+        _encoded_params = encode_query(
+            jsonable_encoder(
                 remove_none_from_dict(
-                    {
-                        **self.base_headers(),
-                        **(headers if headers is not None else {}),
-                        **(request_options.get("additional_headers", {}) or {} if request_options is not None else {}),
-                    }
-                )
-            ),
-            params=encode_query(
-                jsonable_encoder(
-                    remove_none_from_dict(
-                        remove_omit_from_dict(
-                            {
-                                **(params if params is not None else {}),
-                                **(
-                                    request_options.get("additional_query_parameters", {}) or {}
-                                    if request_options is not None
-                                    else {}
-                                ),
-                            },
-                            omit,
-                        )
+                    remove_omit_from_dict(
+                        {
+                            **(params if params is not None else {}),
+                            **(
+                                request_options.get("additional_query_parameters", {}) or {}
+                                if request_options is not None
+                                else {}
+                            ),
+                        },
+                        omit,
                     )
                 )
-            ),
+            )
+        )
+
+        _request_url = _build_url(base_url, path)
+        _request_headers = jsonable_encoder(
+            remove_none_from_dict(
+                {
+                    **_headers,
+                    **(headers if headers is not None else {}),
+                    **(request_options.get("additional_headers", {}) or {} if request_options is not None else {}),
+                }
+            )
+        )
+
+        if self.logger.is_debug():
+            self.logger.debug(
+                "Making HTTP request",
+                method=method,
+                url=_request_url,
+                headers=_redact_headers(_request_headers),
+                has_body=json_body is not None or data_body is not None,
+            )
+
+        response = await self.httpx_client.request(
+            method=method,
+            url=_request_url,
+            headers=_request_headers,
+            params=_encoded_params if _encoded_params else None,
             json=json_body,
             data=data_body,
             content=content,
@@ -445,9 +639,9 @@ async def request(
             timeout=timeout,
         )
 
-        max_retries: int = request_options.get("max_retries", 0) if request_options is not None else 0
+        max_retries: int = request_options.get("max_retries", 2) if request_options is not None else 2
         if _should_retry(response=response):
-            if max_retries > retries:
+            if retries < max_retries:
                 await asyncio.sleep(_retry_timeout(response=response, retries=retries))
                 return await self.request(
                     path=path,
@@ -462,6 +656,25 @@ async def request(
                     retries=retries + 1,
                     omit=omit,
                 )
+
+        if self.logger.is_debug():
+            if 200 <= response.status_code < 400:
+                self.logger.debug(
+                    "HTTP request succeeded",
+                    method=method,
+                    url=_request_url,
+                    status_code=response.status_code,
+                )
+
+        if self.logger.is_error():
+            if response.status_code >= 400:
+                self.logger.error(
+                    "HTTP request failed with error status",
+                    method=method,
+                    url=_request_url,
+                    status_code=response.status_code,
+                )
+
         return response
 
     @asynccontextmanager
@@ -483,7 +696,7 @@ async def stream(
         ] = None,
         headers: typing.Optional[typing.Dict[str, typing.Any]] = None,
         request_options: typing.Optional[RequestOptions] = None,
-        retries: int = 2,
+        retries: int = 0,
         omit: typing.Optional[typing.Any] = None,
         force_multipart: typing.Optional[bool] = None,
     ) -> typing.AsyncIterator[httpx.Response]:
@@ -505,35 +718,55 @@ async def stream(
 
         json_body, data_body = get_request_body(json=json, data=data, request_options=request_options, omit=omit)
 
-        async with self.httpx_client.stream(
-            method=method,
-            url=urllib.parse.urljoin(f"{base_url}/", path),
-            headers=jsonable_encoder(
+        data_body = _maybe_filter_none_from_multipart_data(data_body, request_files, force_multipart)
+
+        # Get headers (supports async token providers)
+        _headers = await self._get_headers()
+
+        # Compute encoded params separately to avoid passing empty list to httpx
+        # (httpx strips existing query params from URL when params=[] is passed)
+        _encoded_params = encode_query(
+            jsonable_encoder(
                 remove_none_from_dict(
-                    {
-                        **self.base_headers(),
-                        **(headers if headers is not None else {}),
-                        **(request_options.get("additional_headers", {}) if request_options is not None else {}),
-                    }
-                )
-            ),
-            params=encode_query(
-                jsonable_encoder(
-                    remove_none_from_dict(
-                        remove_omit_from_dict(
-                            {
-                                **(params if params is not None else {}),
-                                **(
-                                    request_options.get("additional_query_parameters", {})
-                                    if request_options is not None
-                                    else {}
-                                ),
-                            },
-                            omit=omit,
-                        )
+                    remove_omit_from_dict(
+                        {
+                            **(params if params is not None else {}),
+                            **(
+                                request_options.get("additional_query_parameters", {})
+                                if request_options is not None
+                                else {}
+                            ),
+                        },
+                        omit=omit,
                     )
                 )
-            ),
+            )
+        )
+
+        _request_url = _build_url(base_url, path)
+        _request_headers = jsonable_encoder(
+            remove_none_from_dict(
+                {
+                    **_headers,
+                    **(headers if headers is not None else {}),
+                    **(request_options.get("additional_headers", {}) if request_options is not None else {}),
+                }
+            )
+        )
+
+        if self.logger.is_debug():
+            self.logger.debug(
+                "Making streaming HTTP request",
+                method=method,
+                url=_request_url,
+                headers=_redact_headers(_request_headers),
+            )
+
+        async with self.httpx_client.stream(
+            method=method,
+            url=_request_url,
+            headers=_request_headers,
+            params=_encoded_params if _encoded_params else None,
             json=json_body,
             data=data_body,
             content=content,
diff --git a/src/newscatcher/core/http_response.py b/src/newscatcher/core/http_response.py
index 48a1798..00bb109 100644
--- a/src/newscatcher/core/http_response.py
+++ b/src/newscatcher/core/http_response.py
@@ -4,12 +4,12 @@
 
 import httpx
 
+# Generic to represent the underlying type of the data wrapped by the HTTP response.
 T = TypeVar("T")
-"""Generic to represent the underlying type of the data wrapped by the HTTP response."""
 
 
 class BaseHttpResponse:
-    """Minimalist HTTP response wrapper that exposes response headers."""
+    """Minimalist HTTP response wrapper that exposes response headers and status code."""
 
     _response: httpx.Response
 
@@ -20,6 +20,10 @@ def __init__(self, response: httpx.Response):
     def headers(self) -> Dict[str, str]:
         return dict(self._response.headers)
 
+    @property
+    def status_code(self) -> int:
+        return self._response.status_code
+
 
 class HttpResponse(Generic[T], BaseHttpResponse):
     """HTTP response wrapper that exposes response headers and data."""
diff --git a/src/newscatcher/core/http_sse/__init__.py b/src/newscatcher/core/http_sse/__init__.py
new file mode 100644
index 0000000..730e5a3
--- /dev/null
+++ b/src/newscatcher/core/http_sse/__init__.py
@@ -0,0 +1,42 @@
+# This file was auto-generated by Fern from our API Definition.
+
+# isort: skip_file
+
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from ._api import EventSource, aconnect_sse, connect_sse
+    from ._exceptions import SSEError
+    from ._models import ServerSentEvent
+_dynamic_imports: typing.Dict[str, str] = {
+    "EventSource": "._api",
+    "SSEError": "._exceptions",
+    "ServerSentEvent": "._models",
+    "aconnect_sse": "._api",
+    "connect_sse": "._api",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["EventSource", "SSEError", "ServerSentEvent", "aconnect_sse", "connect_sse"]
diff --git a/src/newscatcher/core/http_sse/_api.py b/src/newscatcher/core/http_sse/_api.py
new file mode 100644
index 0000000..f900b3b
--- /dev/null
+++ b/src/newscatcher/core/http_sse/_api.py
@@ -0,0 +1,112 @@
+# This file was auto-generated by Fern from our API Definition.
+
+import re
+from contextlib import asynccontextmanager, contextmanager
+from typing import Any, AsyncGenerator, AsyncIterator, Iterator, cast
+
+import httpx
+from ._decoders import SSEDecoder
+from ._exceptions import SSEError
+from ._models import ServerSentEvent
+
+
+class EventSource:
+    def __init__(self, response: httpx.Response) -> None:
+        self._response = response
+
+    def _check_content_type(self) -> None:
+        content_type = self._response.headers.get("content-type", "").partition(";")[0]
+        if "text/event-stream" not in content_type:
+            raise SSEError(
+                f"Expected response header Content-Type to contain 'text/event-stream', got {content_type!r}"
+            )
+
+    def _get_charset(self) -> str:
+        """Extract charset from Content-Type header, fallback to UTF-8."""
+        content_type = self._response.headers.get("content-type", "")
+
+        # Parse charset parameter using regex
+        charset_match = re.search(r"charset=([^;\s]+)", content_type, re.IGNORECASE)
+        if charset_match:
+            charset = charset_match.group(1).strip("\"'")
+            # Validate that it's a known encoding
+            try:
+                # Test if the charset is valid by trying to encode/decode
+                "test".encode(charset).decode(charset)
+                return charset
+            except (LookupError, UnicodeError):
+                # If charset is invalid, fall back to UTF-8
+                pass
+
+        # Default to UTF-8 if no charset specified or invalid charset
+        return "utf-8"
+
+    @property
+    def response(self) -> httpx.Response:
+        return self._response
+
+    def iter_sse(self) -> Iterator[ServerSentEvent]:
+        self._check_content_type()
+        decoder = SSEDecoder()
+        charset = self._get_charset()
+
+        buffer = ""
+        for chunk in self._response.iter_bytes():
+            # Decode chunk using detected charset
+            text_chunk = chunk.decode(charset, errors="replace")
+            buffer += text_chunk
+
+            # Process complete lines
+            while "\n" in buffer:
+                line, buffer = buffer.split("\n", 1)
+                line = line.rstrip("\r")
+                sse = decoder.decode(line)
+                # when we reach a "\n\n" => line = ''
+                # => decoder will attempt to return an SSE Event
+                if sse is not None:
+                    yield sse
+
+        # Process any remaining data in buffer
+        if buffer.strip():
+            line = buffer.rstrip("\r")
+            sse = decoder.decode(line)
+            if sse is not None:
+                yield sse
+
+    async def aiter_sse(self) -> AsyncGenerator[ServerSentEvent, None]:
+        self._check_content_type()
+        decoder = SSEDecoder()
+        lines = cast(AsyncGenerator[str, None], self._response.aiter_lines())
+        try:
+            async for line in lines:
+                line = line.rstrip("\n")
+                sse = decoder.decode(line)
+                if sse is not None:
+                    yield sse
+        finally:
+            await lines.aclose()
+
+
+@contextmanager
+def connect_sse(client: httpx.Client, method: str, url: str, **kwargs: Any) -> Iterator[EventSource]:
+    headers = kwargs.pop("headers", {})
+    headers["Accept"] = "text/event-stream"
+    headers["Cache-Control"] = "no-store"
+
+    with client.stream(method, url, headers=headers, **kwargs) as response:
+        yield EventSource(response)
+
+
+@asynccontextmanager
+async def aconnect_sse(
+    client: httpx.AsyncClient,
+    method: str,
+    url: str,
+    **kwargs: Any,
+) -> AsyncIterator[EventSource]:
+    headers = kwargs.pop("headers", {})
+    headers["Accept"] = "text/event-stream"
+    headers["Cache-Control"] = "no-store"
+
+    async with client.stream(method, url, headers=headers, **kwargs) as response:
+        yield EventSource(response)
diff --git a/src/newscatcher/core/http_sse/_decoders.py b/src/newscatcher/core/http_sse/_decoders.py
new file mode 100644
index 0000000..339b089
--- /dev/null
+++ b/src/newscatcher/core/http_sse/_decoders.py
@@ -0,0 +1,61 @@
+# This file was auto-generated by Fern from our API Definition.
+
+from typing import List, Optional
+
+from ._models import ServerSentEvent
+
+
+class SSEDecoder:
+    def __init__(self) -> None:
+        self._event = ""
+        self._data: List[str] = []
+        self._last_event_id = ""
+        self._retry: Optional[int] = None
+
+    def decode(self, line: str) -> Optional[ServerSentEvent]:
+        # See: https://html.spec.whatwg.org/multipage/server-sent-events.html#event-stream-interpretation  # noqa: E501
+
+        if not line:
+            if not self._event and not self._data and not self._last_event_id and self._retry is None:
+                return None
+
+            sse = ServerSentEvent(
+                event=self._event,
+                data="\n".join(self._data),
+                id=self._last_event_id,
+                retry=self._retry,
+            )
+
+            # NOTE: as per the SSE spec, do not reset last_event_id.
+            self._event = ""
+            self._data = []
+            self._retry = None
+
+            return sse
+
+        if line.startswith(":"):
+            return None
+
+        fieldname, _, value = line.partition(":")
+
+        if value.startswith(" "):
+            value = value[1:]
+
+        if fieldname == "event":
+            self._event = value
+        elif fieldname == "data":
+            self._data.append(value)
+        elif fieldname == "id":
+            if "\0" in value:
+                pass
+            else:
+                self._last_event_id = value
+        elif fieldname == "retry":
+            try:
+                self._retry = int(value)
+            except (TypeError, ValueError):
+                pass
+        else:
+            pass  # Field is ignored.
+
+        return None
diff --git a/src/newscatcher/types/similar_documents_fields.py b/src/newscatcher/core/http_sse/_exceptions.py
similarity index 51%
rename from src/newscatcher/types/similar_documents_fields.py
rename to src/newscatcher/core/http_sse/_exceptions.py
index 159850f..81605a8 100644
--- a/src/newscatcher/types/similar_documents_fields.py
+++ b/src/newscatcher/core/http_sse/_exceptions.py
@@ -1,3 +1,7 @@
 # This file was auto-generated by Fern from our API Definition.
 
-SimilarDocumentsFields = str
+import httpx
+
+
+class SSEError(httpx.TransportError):
+    pass
diff --git a/src/newscatcher/core/http_sse/_models.py b/src/newscatcher/core/http_sse/_models.py
new file mode 100644
index 0000000..1af57f8
--- /dev/null
+++ b/src/newscatcher/core/http_sse/_models.py
@@ -0,0 +1,17 @@
+# This file was auto-generated by Fern from our API Definition.
+
+import json
+from dataclasses import dataclass
+from typing import Any, Optional
+
+
+@dataclass(frozen=True)
+class ServerSentEvent:
+    event: str = "message"
+    data: str = ""
+    id: str = ""
+    retry: Optional[int] = None
+
+    def json(self) -> Any:
+        """Parse the data field as JSON."""
+        return json.loads(self.data)
diff --git a/src/newscatcher/core/jsonable_encoder.py b/src/newscatcher/core/jsonable_encoder.py
index afee366..f8beaea 100644
--- a/src/newscatcher/core/jsonable_encoder.py
+++ b/src/newscatcher/core/jsonable_encoder.py
@@ -30,6 +30,10 @@
 
 def jsonable_encoder(obj: Any, custom_encoder: Optional[Dict[Any, Callable[[Any], Any]]] = None) -> Any:
     custom_encoder = custom_encoder or {}
+    # Generated SDKs use Ellipsis (`...`) as the sentinel value for "OMIT".
+    # OMIT values should be excluded from serialized payloads.
+    if obj is Ellipsis:
+        return None
     if custom_encoder:
         if type(obj) in custom_encoder:
             return custom_encoder[type(obj)](obj)
@@ -70,6 +74,8 @@ def jsonable_encoder(obj: Any, custom_encoder: Optional[Dict[Any, Callable[[Any]
         allowed_keys = set(obj.keys())
         for key, value in obj.items():
             if key in allowed_keys:
+                if value is Ellipsis:
+                    continue
                 encoded_key = jsonable_encoder(key, custom_encoder=custom_encoder)
                 encoded_value = jsonable_encoder(value, custom_encoder=custom_encoder)
                 encoded_dict[encoded_key] = encoded_value
@@ -77,6 +83,8 @@ def jsonable_encoder(obj: Any, custom_encoder: Optional[Dict[Any, Callable[[Any]
     if isinstance(obj, (list, set, frozenset, GeneratorType, tuple)):
         encoded_list = []
         for item in obj:
+            if item is Ellipsis:
+                continue
             encoded_list.append(jsonable_encoder(item, custom_encoder=custom_encoder))
         return encoded_list
 
diff --git a/src/newscatcher/core/logging.py b/src/newscatcher/core/logging.py
new file mode 100644
index 0000000..e5e5724
--- /dev/null
+++ b/src/newscatcher/core/logging.py
@@ -0,0 +1,107 @@
+# This file was auto-generated by Fern from our API Definition.
+
+import logging
+import typing
+
+LogLevel = typing.Literal["debug", "info", "warn", "error"]
+
+_LOG_LEVEL_MAP: typing.Dict[LogLevel, int] = {
+    "debug": 1,
+    "info": 2,
+    "warn": 3,
+    "error": 4,
+}
+
+
+class ILogger(typing.Protocol):
+    def debug(self, message: str, **kwargs: typing.Any) -> None: ...
+    def info(self, message: str, **kwargs: typing.Any) -> None: ...
+    def warn(self, message: str, **kwargs: typing.Any) -> None: ...
+    def error(self, message: str, **kwargs: typing.Any) -> None: ...
+
+
+class ConsoleLogger:
+    _logger: logging.Logger
+
+    def __init__(self) -> None:
+        self._logger = logging.getLogger("fern")
+        if not self._logger.handlers:
+            handler = logging.StreamHandler()
+            handler.setFormatter(logging.Formatter("%(levelname)s - %(message)s"))
+            self._logger.addHandler(handler)
+            self._logger.setLevel(logging.DEBUG)
+
+    def debug(self, message: str, **kwargs: typing.Any) -> None:
+        self._logger.debug(message, extra=kwargs)
+
+    def info(self, message: str, **kwargs: typing.Any) -> None:
+        self._logger.info(message, extra=kwargs)
+
+    def warn(self, message: str, **kwargs: typing.Any) -> None:
+        self._logger.warning(message, extra=kwargs)
+
+    def error(self, message: str, **kwargs: typing.Any) -> None:
+        self._logger.error(message, extra=kwargs)
+
+
+class LogConfig(typing.TypedDict, total=False):
+    level: LogLevel
+    logger: ILogger
+    silent: bool
+
+
+class Logger:
+    _level: int
+    _logger: ILogger
+    _silent: bool
+
+    def __init__(self, *, level: LogLevel, logger: ILogger, silent: bool) -> None:
+        self._level = _LOG_LEVEL_MAP[level]
+        self._logger = logger
+        self._silent = silent
+
+    def _should_log(self, level: LogLevel) -> bool:
+        return not self._silent and self._level <= _LOG_LEVEL_MAP[level]
+
+    def is_debug(self) -> bool:
+        return self._should_log("debug")
+
+    def is_info(self) -> bool:
+        return self._should_log("info")
+
+    def is_warn(self) -> bool:
+        return self._should_log("warn")
+
+    def is_error(self) -> bool:
+        return self._should_log("error")
+
+    def debug(self, message: str, **kwargs: typing.Any) -> None:
+        if self.is_debug():
+            self._logger.debug(message, **kwargs)
+
+    def info(self, message: str, **kwargs: typing.Any) -> None:
+        if self.is_info():
+            self._logger.info(message, **kwargs)
+
+    def warn(self, message: str, **kwargs: typing.Any) -> None:
+        if self.is_warn():
+            self._logger.warn(message, **kwargs)
+
+    def error(self, message: str, **kwargs: typing.Any) -> None:
+        if self.is_error():
+            self._logger.error(message, **kwargs)
+
+
+_default_logger: Logger = Logger(level="info", logger=ConsoleLogger(), silent=True)
+
+
+def create_logger(config: typing.Optional[typing.Union[LogConfig, Logger]] = None) -> Logger:
+    if config is None:
+        return _default_logger
+    if isinstance(config, Logger):
+        return config
+    return Logger(
+        level=config.get("level", "info"),
+        logger=config.get("logger", ConsoleLogger()),
+        silent=config.get("silent", True),
+    )
diff --git a/src/newscatcher/core/parse_error.py b/src/newscatcher/core/parse_error.py
new file mode 100644
index 0000000..4527c6a
--- /dev/null
+++ b/src/newscatcher/core/parse_error.py
@@ -0,0 +1,36 @@
+# This file was auto-generated by Fern from our API Definition.
+
+from typing import Any, Dict, Optional
+
+
+class ParsingError(Exception):
+    """
+    Raised when the SDK fails to parse/validate a response from the server.
+    This typically indicates that the server returned a response whose shape
+    does not match the expected schema.
+    """
+
+    headers: Optional[Dict[str, str]]
+    status_code: Optional[int]
+    body: Any
+    cause: Optional[Exception]
+
+    def __init__(
+        self,
+        *,
+        headers: Optional[Dict[str, str]] = None,
+        status_code: Optional[int] = None,
+        body: Any = None,
+        cause: Optional[Exception] = None,
+    ) -> None:
+        self.headers = headers
+        self.status_code = status_code
+        self.body = body
+        self.cause = cause
+        super().__init__()
+        if cause is not None:
+            self.__cause__ = cause
+
+    def __str__(self) -> str:
+        cause_str = f", cause: {self.cause}" if self.cause is not None else ""
+        return f"headers: {self.headers}, status_code: {self.status_code}, body: {self.body}{cause_str}"
diff --git a/src/newscatcher/core/pydantic_utilities.py b/src/newscatcher/core/pydantic_utilities.py
index 7db2950..fea3a08 100644
--- a/src/newscatcher/core/pydantic_utilities.py
+++ b/src/newscatcher/core/pydantic_utilities.py
@@ -2,30 +2,129 @@
 
 # nopycln: file
 import datetime as dt
+import inspect
+import json
+import logging
 from collections import defaultdict
-from typing import Any, Callable, ClassVar, Dict, List, Mapping, Optional, Set, Tuple, Type, TypeVar, Union, cast
+from dataclasses import asdict
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    ClassVar,
+    Dict,
+    List,
+    Mapping,
+    Optional,
+    Set,
+    Tuple,
+    Type,
+    TypeVar,
+    Union,
+    cast,
+)
 
 import pydantic
+import typing_extensions
+from pydantic.fields import FieldInfo as _FieldInfo
+
+_logger = logging.getLogger(__name__)
+
+if TYPE_CHECKING:
+    from .http_sse._models import ServerSentEvent
 
 IS_PYDANTIC_V2 = pydantic.VERSION.startswith("2.")
 
 if IS_PYDANTIC_V2:
-    from pydantic.v1.datetime_parse import parse_date as parse_date
-    from pydantic.v1.datetime_parse import parse_datetime as parse_datetime
-    from pydantic.v1.fields import ModelField as ModelField
-    from pydantic.v1.json import ENCODERS_BY_TYPE as encoders_by_type  # type: ignore[attr-defined]
-    from pydantic.v1.typing import get_args as get_args
-    from pydantic.v1.typing import get_origin as get_origin
-    from pydantic.v1.typing import is_literal_type as is_literal_type
-    from pydantic.v1.typing import is_union as is_union
+    _datetime_adapter = pydantic.TypeAdapter(dt.datetime)  # type: ignore[attr-defined]
+    _date_adapter = pydantic.TypeAdapter(dt.date)  # type: ignore[attr-defined]
+
+    def parse_datetime(value: Any) -> dt.datetime:  # type: ignore[misc]
+        if isinstance(value, dt.datetime):
+            return value
+        return _datetime_adapter.validate_python(value)
+
+    def parse_date(value: Any) -> dt.date:  # type: ignore[misc]
+        if isinstance(value, dt.datetime):
+            return value.date()
+        if isinstance(value, dt.date):
+            return value
+        return _date_adapter.validate_python(value)
+
+    # Avoid importing from pydantic.v1 to maintain Python 3.14 compatibility.
+    from typing import get_args as get_args  # type: ignore[assignment]
+    from typing import get_origin as get_origin  # type: ignore[assignment]
+
+    def is_literal_type(tp: Optional[Type[Any]]) -> bool:  # type: ignore[misc]
+        return typing_extensions.get_origin(tp) is typing_extensions.Literal
+
+    def is_union(tp: Optional[Type[Any]]) -> bool:  # type: ignore[misc]
+        return tp is Union or typing_extensions.get_origin(tp) is Union  # type: ignore[comparison-overlap]
+
+    # Inline encoders_by_type to avoid importing from pydantic.v1.json
+    import re as _re
+    from collections import deque as _deque
+    from decimal import Decimal as _Decimal
+    from enum import Enum as _Enum
+    from ipaddress import (
+        IPv4Address as _IPv4Address,
+    )
+    from ipaddress import (
+        IPv4Interface as _IPv4Interface,
+    )
+    from ipaddress import (
+        IPv4Network as _IPv4Network,
+    )
+    from ipaddress import (
+        IPv6Address as _IPv6Address,
+    )
+    from ipaddress import (
+        IPv6Interface as _IPv6Interface,
+    )
+    from ipaddress import (
+        IPv6Network as _IPv6Network,
+    )
+    from pathlib import Path as _Path
+    from types import GeneratorType as _GeneratorType
+    from uuid import UUID as _UUID
+
+    from pydantic.fields import FieldInfo as ModelField  # type: ignore[no-redef, assignment]
+
+    def _decimal_encoder(dec_value: Any) -> Any:
+        if dec_value.as_tuple().exponent >= 0:
+            return int(dec_value)
+        return float(dec_value)
+
+    encoders_by_type: Dict[Type[Any], Callable[[Any], Any]] = {  # type: ignore[no-redef]
+        bytes: lambda o: o.decode(),
+        dt.date: lambda o: o.isoformat(),
+        dt.datetime: lambda o: o.isoformat(),
+        dt.time: lambda o: o.isoformat(),
+        dt.timedelta: lambda td: td.total_seconds(),
+        _Decimal: _decimal_encoder,
+        _Enum: lambda o: o.value,
+        frozenset: list,
+        _deque: list,
+        _GeneratorType: list,
+        _IPv4Address: str,
+        _IPv4Interface: str,
+        _IPv4Network: str,
+        _IPv6Address: str,
+        _IPv6Interface: str,
+        _IPv6Network: str,
+        _Path: str,
+        _re.Pattern: lambda o: o.pattern,
+        set: list,
+        _UUID: str,
+    }
 else:
     from pydantic.datetime_parse import parse_date as parse_date  # type: ignore[no-redef]
     from pydantic.datetime_parse import parse_datetime as parse_datetime  # type: ignore[no-redef]
-    from pydantic.fields import ModelField as ModelField  # type: ignore[attr-defined, no-redef]
+    from pydantic.fields import ModelField as ModelField  # type: ignore[attr-defined, no-redef, assignment]
     from pydantic.json import ENCODERS_BY_TYPE as encoders_by_type  # type: ignore[no-redef]
     from pydantic.typing import get_args as get_args  # type: ignore[no-redef]
     from pydantic.typing import get_origin as get_origin  # type: ignore[no-redef]
-    from pydantic.typing import is_literal_type as is_literal_type  # type: ignore[no-redef]
+    from pydantic.typing import is_literal_type as is_literal_type  # type: ignore[no-redef, assignment]
     from pydantic.typing import is_union as is_union  # type: ignore[no-redef]
 
 from .datetime_utils import serialize_datetime
@@ -36,8 +135,212 @@
 Model = TypeVar("Model", bound=pydantic.BaseModel)
 
 
+def _get_discriminator_and_variants(type_: Type[Any]) -> Tuple[Optional[str], Optional[List[Type[Any]]]]:
+    """
+    Extract the discriminator field name and union variants from a discriminated union type.
+    Supports Annotated[Union[...], Field(discriminator=...)] patterns.
+    Returns (discriminator, variants) or (None, None) if not a discriminated union.
+    """
+    origin = typing_extensions.get_origin(type_)
+
+    if origin is typing_extensions.Annotated:
+        args = typing_extensions.get_args(type_)
+        if len(args) >= 2:
+            inner_type = args[0]
+            # Check annotations for discriminator
+            discriminator = None
+            for annotation in args[1:]:
+                if hasattr(annotation, "discriminator"):
+                    discriminator = getattr(annotation, "discriminator", None)
+                    break
+
+            if discriminator:
+                inner_origin = typing_extensions.get_origin(inner_type)
+                if inner_origin is Union:
+                    variants = list(typing_extensions.get_args(inner_type))
+                    return discriminator, variants
+    return None, None
+
+
+def _get_field_annotation(model: Type[Any], field_name: str) -> Optional[Type[Any]]:
+    """Get the type annotation of a field from a Pydantic model."""
+    if IS_PYDANTIC_V2:
+        fields = getattr(model, "model_fields", {})
+        field_info = fields.get(field_name)
+        if field_info:
+            return cast(Optional[Type[Any]], field_info.annotation)
+    else:
+        fields = getattr(model, "__fields__", {})
+        field_info = fields.get(field_name)
+        if field_info:
+            return cast(Optional[Type[Any]], field_info.outer_type_)
+    return None
+
+
+def _find_variant_by_discriminator(
+    variants: List[Type[Any]],
+    discriminator: str,
+    discriminator_value: Any,
+) -> Optional[Type[Any]]:
+    """Find the union variant that matches the discriminator value."""
+    for variant in variants:
+        if not (inspect.isclass(variant) and issubclass(variant, pydantic.BaseModel)):
+            continue
+
+        disc_annotation = _get_field_annotation(variant, discriminator)
+        if disc_annotation and is_literal_type(disc_annotation):
+            literal_args = get_args(disc_annotation)
+            if literal_args and literal_args[0] == discriminator_value:
+                return variant
+    return None
+
+
+def _is_string_type(type_: Type[Any]) -> bool:
+    """Check if a type is str or Optional[str]."""
+    if type_ is str:
+        return True
+
+    origin = typing_extensions.get_origin(type_)
+    if origin is Union:
+        args = typing_extensions.get_args(type_)
+        # Optional[str] = Union[str, None]
+        non_none_args = [a for a in args if a is not type(None)]
+        if len(non_none_args) == 1 and non_none_args[0] is str:
+            return True
+
+    return False
+
+
+def parse_sse_obj(sse: "ServerSentEvent", type_: Type[T]) -> T:
+    """
+    Parse a ServerSentEvent into the appropriate type.
+
+    Handles two scenarios based on where the discriminator field is located:
+
+    1. Data-level discrimination: The discriminator (e.g., 'type') is inside the 'data' payload.
+       The union describes the data content, not the SSE envelope.
+       -> Returns: json.loads(data) parsed into the type
+
+       Example: ChatStreamResponse with discriminator='type'
+       Input:  ServerSentEvent(event="message", data='{"type": "content-delta", ...}', id="")
+       Output: ContentDeltaEvent (parsed from data, SSE envelope stripped)
+
+    2. Event-level discrimination: The discriminator (e.g., 'event') is at the SSE event level.
+       The union describes the full SSE event structure.
+       -> Returns: SSE envelope with 'data' field JSON-parsed only if the variant expects non-string
+
+       Example: JobStreamResponse with discriminator='event'
+       Input:  ServerSentEvent(event="ERROR", data='{"code": "FAILED", ...}', id="123")
+       Output: JobStreamResponse_Error with data as ErrorData object
+
+       But for variants where data is str (like STATUS_UPDATE):
+       Input:  ServerSentEvent(event="STATUS_UPDATE", data='{"status": "processing"}', id="1")
+       Output: JobStreamResponse_StatusUpdate with data as string (not parsed)
+
+    Args:
+        sse: The ServerSentEvent object to parse
+        type_: The target discriminated union type
+
+    Returns:
+        The parsed object of type T
+
+    Note:
+        This function is only available in SDK contexts where http_sse module exists.
+    """
+    sse_event = asdict(sse)
+    discriminator, variants = _get_discriminator_and_variants(type_)
+
+    if discriminator is None or variants is None:
+        # Not a discriminated union - parse the data field as JSON
+        data_value = sse_event.get("data")
+        if isinstance(data_value, str) and data_value:
+            try:
+                parsed_data = json.loads(data_value)
+                return parse_obj_as(type_, parsed_data)
+            except json.JSONDecodeError as e:
+                _logger.warning(
+                    "Failed to parse SSE data field as JSON: %s, data: %s",
+                    e,
+                    data_value[:100] if len(data_value) > 100 else data_value,
+                )
+        return parse_obj_as(type_, sse_event)
+
+    data_value = sse_event.get("data")
+
+    # Check if discriminator is at the top level (event-level discrimination)
+    if discriminator in sse_event:
+        # Case 2: Event-level discrimination
+        # Find the matching variant to check if 'data' field needs JSON parsing
+        disc_value = sse_event.get(discriminator)
+        matching_variant = _find_variant_by_discriminator(variants, discriminator, disc_value)
+
+        if matching_variant is not None:
+            # Check what type the variant expects for 'data'
+            data_type = _get_field_annotation(matching_variant, "data")
+            if data_type is not None and not _is_string_type(data_type):
+                # Variant expects non-string data - parse JSON
+                if isinstance(data_value, str) and data_value:
+                    try:
+                        parsed_data = json.loads(data_value)
+                        new_object = dict(sse_event)
+                        new_object["data"] = parsed_data
+                        return parse_obj_as(type_, new_object)
+                    except json.JSONDecodeError as e:
+                        _logger.warning(
+                            "Failed to parse SSE data field as JSON for event-level discrimination: %s, data: %s",
+                            e,
+                            data_value[:100] if len(data_value) > 100 else data_value,
+                        )
+        # Either no matching variant, data is string type, or JSON parse failed
+        return parse_obj_as(type_, sse_event)
+
+    else:
+        # Case 1: Data-level discrimination
+        # The discriminator is inside the data payload - extract and parse data only
+        if isinstance(data_value, str) and data_value:
+            try:
+                parsed_data = json.loads(data_value)
+                return parse_obj_as(type_, parsed_data)
+            except json.JSONDecodeError as e:
+                _logger.warning(
+                    "Failed to parse SSE data field as JSON for data-level discrimination: %s, data: %s",
+                    e,
+                    data_value[:100] if len(data_value) > 100 else data_value,
+                )
+        return parse_obj_as(type_, sse_event)
+
+
 def parse_obj_as(type_: Type[T], object_: Any) -> T:
-    dealiased_object = convert_and_respect_annotation_metadata(object_=object_, annotation=type_, direction="read")
+    # convert_and_respect_annotation_metadata is required for TypedDict aliasing.
+    #
+    # For Pydantic models, whether we should pre-dealias depends on how the model encodes aliasing:
+    # - If the model uses real Pydantic aliases (pydantic.Field(alias=...)), then we must pass wire keys through
+    #   unchanged so Pydantic can validate them.
+    # - If the model encodes aliasing only via FieldMetadata annotations, then we MUST pre-dealias because Pydantic
+    #   will not recognize those aliases during validation.
+    if inspect.isclass(type_) and issubclass(type_, pydantic.BaseModel):
+        has_pydantic_aliases = False
+        if IS_PYDANTIC_V2:
+            for field_name, field_info in getattr(type_, "model_fields", {}).items():  # type: ignore[attr-defined]
+                alias = getattr(field_info, "alias", None)
+                if alias is not None and alias != field_name:
+                    has_pydantic_aliases = True
+                    break
+        else:
+            for field in getattr(type_, "__fields__", {}).values():
+                alias = getattr(field, "alias", None)
+                name = getattr(field, "name", None)
+                if alias is not None and name is not None and alias != name:
+                    has_pydantic_aliases = True
+                    break
+
+        dealiased_object = (
+            object_
+            if has_pydantic_aliases
+            else convert_and_respect_annotation_metadata(object_=object_, annotation=type_, direction="read")
+        )
+    else:
+        dealiased_object = convert_and_respect_annotation_metadata(object_=object_, annotation=type_, direction="read")
     if IS_PYDANTIC_V2:
         adapter = pydantic.TypeAdapter(type_)  # type: ignore[attr-defined]
         return adapter.validate_python(dealiased_object)
@@ -59,9 +362,46 @@ class UniversalBaseModel(pydantic.BaseModel):
             protected_namespaces=(),
         )
 
+        @pydantic.model_validator(mode="before")  # type: ignore[attr-defined]
+        @classmethod
+        def _coerce_field_names_to_aliases(cls, data: Any) -> Any:
+            """
+            Accept Python field names in input by rewriting them to their Pydantic aliases,
+            while avoiding silent collisions when a key could refer to multiple fields.
+            """
+            if not isinstance(data, Mapping):
+                return data
+
+            fields = getattr(cls, "model_fields", {})  # type: ignore[attr-defined]
+            name_to_alias: Dict[str, str] = {}
+            alias_to_name: Dict[str, str] = {}
+
+            for name, field_info in fields.items():
+                alias = getattr(field_info, "alias", None) or name
+                name_to_alias[name] = alias
+                if alias != name:
+                    alias_to_name[alias] = name
+
+            # Detect ambiguous keys: a key that is an alias for one field and a name for another.
+            ambiguous_keys = set(alias_to_name.keys()).intersection(set(name_to_alias.keys()))
+            for key in ambiguous_keys:
+                if key in data and name_to_alias[key] not in data:
+                    raise ValueError(
+                        f"Ambiguous input key '{key}': it is both a field name and an alias. "
+                        "Provide the explicit alias key to disambiguate."
+                    )
+
+            original_keys = set(data.keys())
+            rewritten: Dict[str, Any] = dict(data)
+            for name, alias in name_to_alias.items():
+                if alias != name and name in original_keys and alias not in rewritten:
+                    rewritten[alias] = rewritten.pop(name)
+
+            return rewritten
+
         @pydantic.model_serializer(mode="plain", when_used="json")  # type: ignore[attr-defined]
         def serialize_model(self) -> Any:  # type: ignore[name-defined]
-            serialized = self.model_dump()
+            serialized = self.dict()  # type: ignore[attr-defined]
             data = {k: serialize_datetime(v) if isinstance(v, dt.datetime) else v for k, v in serialized.items()}
             return data
 
@@ -71,6 +411,40 @@ class Config:
             smart_union = True
             json_encoders = {dt.datetime: serialize_datetime}
 
+        @pydantic.root_validator(pre=True)
+        def _coerce_field_names_to_aliases(cls, values: Any) -> Any:
+            """
+            Pydantic v1 equivalent of _coerce_field_names_to_aliases.
+            """
+            if not isinstance(values, Mapping):
+                return values
+
+            fields = getattr(cls, "__fields__", {})
+            name_to_alias: Dict[str, str] = {}
+            alias_to_name: Dict[str, str] = {}
+
+            for name, field in fields.items():
+                alias = getattr(field, "alias", None) or name
+                name_to_alias[name] = alias
+                if alias != name:
+                    alias_to_name[alias] = name
+
+            ambiguous_keys = set(alias_to_name.keys()).intersection(set(name_to_alias.keys()))
+            for key in ambiguous_keys:
+                if key in values and name_to_alias[key] not in values:
+                    raise ValueError(
+                        f"Ambiguous input key '{key}': it is both a field name and an alias. "
+                        "Provide the explicit alias key to disambiguate."
+                    )
+
+            original_keys = set(values.keys())
+            rewritten: Dict[str, Any] = dict(values)
+            for name, alias in name_to_alias.items():
+                if alias != name and name in original_keys and alias not in rewritten:
+                    rewritten[alias] = rewritten.pop(name)
+
+            return rewritten
+
     @classmethod
     def model_construct(cls: Type["Model"], _fields_set: Optional[Set[str]] = None, **values: Any) -> "Model":
         dealiased_object = convert_and_respect_annotation_metadata(object_=values, annotation=cls, direction="read")
@@ -147,7 +521,10 @@ def dict(self, **kwargs: Any) -> Dict[str, Any]:
 
             dict_dump = super().dict(**kwargs_with_defaults_exclude_unset_include_fields)
 
-        return convert_and_respect_annotation_metadata(object_=dict_dump, annotation=self.__class__, direction="write")
+        return cast(
+            Dict[str, Any],
+            convert_and_respect_annotation_metadata(object_=dict_dump, annotation=self.__class__, direction="write"),
+        )
 
 
 def _union_list_of_pydantic_dicts(source: List[Any], destination: List[Any]) -> List[Any]:
@@ -217,7 +594,9 @@ def universal_root_validator(
 ) -> Callable[[AnyCallable], AnyCallable]:
     def decorator(func: AnyCallable) -> AnyCallable:
         if IS_PYDANTIC_V2:
-            return cast(AnyCallable, pydantic.model_validator(mode="before" if pre else "after")(func))  # type: ignore[attr-defined]
+            # In Pydantic v2, for RootModel we always use "before" mode
+            # The custom validators transform the input value before the model is created
+            return cast(AnyCallable, pydantic.model_validator(mode="before")(func))  # type: ignore[attr-defined]
         return cast(AnyCallable, pydantic.root_validator(pre=pre)(func))  # type: ignore[call-overload]
 
     return decorator
@@ -232,7 +611,7 @@ def decorator(func: AnyCallable) -> AnyCallable:
     return decorator
 
 
-PydanticField = Union[ModelField, pydantic.fields.FieldInfo]
+PydanticField = Union[ModelField, _FieldInfo]
 
 
 def _get_model_fields(model: Type["Model"]) -> Mapping[str, PydanticField]:
diff --git a/src/newscatcher/errors/__init__.py b/src/newscatcher/errors/__init__.py
index ac3639a..fee5ae7 100644
--- a/src/newscatcher/errors/__init__.py
+++ b/src/newscatcher/errors/__init__.py
@@ -2,13 +2,48 @@
 
 # isort: skip_file
 
-from .bad_request_error import BadRequestError
-from .forbidden_error import ForbiddenError
-from .internal_server_error import InternalServerError
-from .request_timeout_error import RequestTimeoutError
-from .too_many_requests_error import TooManyRequestsError
-from .unauthorized_error import UnauthorizedError
-from .unprocessable_entity_error import UnprocessableEntityError
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .bad_request_error import BadRequestError
+    from .forbidden_error import ForbiddenError
+    from .internal_server_error import InternalServerError
+    from .request_timeout_error import RequestTimeoutError
+    from .too_many_requests_error import TooManyRequestsError
+    from .unauthorized_error import UnauthorizedError
+    from .unprocessable_entity_error import UnprocessableEntityError
+_dynamic_imports: typing.Dict[str, str] = {
+    "BadRequestError": ".bad_request_error",
+    "ForbiddenError": ".forbidden_error",
+    "InternalServerError": ".internal_server_error",
+    "RequestTimeoutError": ".request_timeout_error",
+    "TooManyRequestsError": ".too_many_requests_error",
+    "UnauthorizedError": ".unauthorized_error",
+    "UnprocessableEntityError": ".unprocessable_entity_error",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
 
 __all__ = [
     "BadRequestError",
diff --git a/src/newscatcher/latest_headlines/__init__.py b/src/newscatcher/latest_headlines/__init__.py
new file mode 100644
index 0000000..327d1f2
--- /dev/null
+++ b/src/newscatcher/latest_headlines/__init__.py
@@ -0,0 +1,37 @@
+# This file was auto-generated by Fern from our API Definition.
+
+# isort: skip_file
+
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .types import LatestHeadlinesGetResponse, LatestHeadlinesPostResponse
+_dynamic_imports: typing.Dict[str, str] = {
+    "LatestHeadlinesGetResponse": ".types",
+    "LatestHeadlinesPostResponse": ".types",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["LatestHeadlinesGetResponse", "LatestHeadlinesPostResponse"]
diff --git a/src/newscatcher/latestheadlines/client.py b/src/newscatcher/latest_headlines/client.py
similarity index 56%
rename from src/newscatcher/latestheadlines/client.py
rename to src/newscatcher/latest_headlines/client.py
index ac90a8e..4577079 100644
--- a/src/newscatcher/latestheadlines/client.py
+++ b/src/newscatcher/latest_headlines/client.py
@@ -6,6 +6,7 @@
 from ..core.request_options import RequestOptions
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.by_parse_date import ByParseDate
 from ..types.clustering_enabled import ClusteringEnabled
 from ..types.clustering_threshold import ClusteringThreshold
@@ -40,6 +41,7 @@
 from ..types.predefined_sources import PredefinedSources
 from ..types.ranked_only import RankedOnly
 from ..types.robots_compliant import RobotsCompliant
+from ..types.sort_by import SortBy
 from ..types.sources import Sources
 from ..types.theme import Theme
 from ..types.title_sentiment_max import TitleSentimentMax
@@ -47,8 +49,7 @@
 from ..types.when import When
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
-from .raw_client import AsyncRawLatestheadlinesClient, RawLatestheadlinesClient
-from .types.latest_headlines_get_request_clustering_variable import LatestHeadlinesGetRequestClusteringVariable
+from .raw_client import AsyncRawLatestHeadlinesClient, RawLatestHeadlinesClient
 from .types.latest_headlines_get_response import LatestHeadlinesGetResponse
 from .types.latest_headlines_post_response import LatestHeadlinesPostResponse
 
@@ -56,26 +57,27 @@
 OMIT = typing.cast(typing.Any, ...)
 
 
-class LatestheadlinesClient:
+class LatestHeadlinesClient:
     def __init__(self, *, client_wrapper: SyncClientWrapper):
-        self._raw_client = RawLatestheadlinesClient(client_wrapper=client_wrapper)
+        self._raw_client = RawLatestHeadlinesClient(client_wrapper=client_wrapper)
 
     @property
-    def with_raw_response(self) -> RawLatestheadlinesClient:
+    def with_raw_response(self) -> RawLatestHeadlinesClient:
         """
         Retrieves a raw implementation of this client that returns raw responses.
 
         Returns
         -------
-        RawLatestheadlinesClient
+        RawLatestHeadlinesClient
         """
         return self._raw_client
 
-    def get(
+    def latest_headlines_get(
         self,
         *,
-        when: typing.Optional[str] = None,
-        by_parse_date: typing.Optional[bool] = None,
+        when: typing.Optional[When] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
         lang: typing.Optional[str] = None,
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
@@ -84,39 +86,40 @@ def get(
         sources: typing.Optional[str] = None,
         not_sources: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        ranked_only: typing.Optional[bool] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[LatestHeadlinesGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> LatestHeadlinesGetResponse:
         """
@@ -124,143 +127,89 @@ def get(
 
         Parameters
         ----------
-        when : typing.Optional[str]
-            The time period for which you want to get the latest headlines.
+        when : typing.Optional[When]
 
-            Format examples:
-            - `7d`: Last seven days
-            - `30d`: Last 30 days
-            - `1h`: Last hour
-            - `24h`: Last 24 hours
+        by_parse_date : typing.Optional[ByParseDate]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        sort_by : typing.Optional[SortBy]
 
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
-
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[LatestHeadlinesGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -268,115 +217,29 @@ def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -384,8 +247,6 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -393,8 +254,6 @@ def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -402,8 +261,6 @@ def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -411,14 +268,13 @@ def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -426,7 +282,7 @@ def get(
         Returns
         -------
         LatestHeadlinesGetResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
@@ -435,23 +291,56 @@ def get(
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
-        client.latestheadlines.get(
-            predefined_sources="top 100 US, top 5 GB",
+        client.latest_headlines.latest_headlines_get(
+            when="7d",
+            by_parse_date=True,
+            lang="en,es",
+            not_lang="fr,de",
+            countries="US,CA",
+            not_countries="UK,FR",
+            predefined_sources="top 50 US, top 20 GB",
+            sources="nytimes.com,finance.yahoo.com",
+            not_sources="cnn.com,wsj.com",
+            not_author_name="John Doe, Jane Doe",
+            ranked_only=True,
+            is_headline=True,
+            is_opinion=True,
+            is_paid_content=False,
+            parent_url="wsj.com/politics,wsj.com/tech",
+            all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+            all_domain_links="who.int,nih.gov",
+            all_links_text="Nvidia,Tesla",
+            word_count_min=300,
+            word_count_max=1000,
+            page=2,
+            page_size=50,
+            clustering_enabled=True,
+            clustering_threshold=0.6,
             include_translation_fields=True,
             include_nlp_data=True,
             has_nlp=True,
-            theme="Business,Finance",
-            not_theme="Crime",
+            theme="Finance,Tech",
+            not_theme="Crime,Sports",
+            org_entity_name='"Apple Inc" OR Microsoft',
+            per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+            loc_entity_name='"San Francisco" OR "New York City"',
+            misc_entity_name='AWS OR "Microsoft Azure"',
+            title_sentiment_min=-0.5,
+            title_sentiment_max=0.5,
+            content_sentiment_min=-0.5,
+            content_sentiment_max=0.5,
             iptc_tags="20000199,20000209",
             not_iptc_tags="20000205,20000209",
             iab_tags="Business,Events",
             not_iab_tags="Agriculture,Metals",
-            custom_tags="Tag1,Tag2,Tag3",
+            custom_tags="Tag1,Tag2",
+            robots_compliant=True,
         )
         """
-        _response = self._raw_client.get(
+        _response = self._raw_client.latest_headlines_get(
             when=when,
             by_parse_date=by_parse_date,
+            sort_by=sort_by,
             lang=lang,
             not_lang=not_lang,
             countries=countries,
@@ -467,6 +356,7 @@ def get(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -497,7 +387,7 @@ def get(
         )
         return _response.data
 
-    def post(
+    def latest_headlines_post(
         self,
         *,
         when: typing.Optional[When] = OMIT,
@@ -517,6 +407,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -584,6 +475,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -642,7 +535,7 @@ def post(
         Returns
         -------
         LatestHeadlinesPostResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
@@ -651,14 +544,12 @@ def post(
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
-        client.latestheadlines.post(
-            lang="en",
-            predefined_sources=["top 50 US", "top 20 GB"],
-            is_opinion=False,
-            page_size=10,
+        client.latest_headlines.latest_headlines_post(
+            when="7d",
+            page_size=1,
         )
         """
-        _response = self._raw_client.post(
+        _response = self._raw_client.latest_headlines_post(
             when=when,
             by_parse_date=by_parse_date,
             lang=lang,
@@ -676,6 +567,7 @@ def post(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -707,26 +599,27 @@ def post(
         return _response.data
 
 
-class AsyncLatestheadlinesClient:
+class AsyncLatestHeadlinesClient:
     def __init__(self, *, client_wrapper: AsyncClientWrapper):
-        self._raw_client = AsyncRawLatestheadlinesClient(client_wrapper=client_wrapper)
+        self._raw_client = AsyncRawLatestHeadlinesClient(client_wrapper=client_wrapper)
 
     @property
-    def with_raw_response(self) -> AsyncRawLatestheadlinesClient:
+    def with_raw_response(self) -> AsyncRawLatestHeadlinesClient:
         """
         Retrieves a raw implementation of this client that returns raw responses.
 
         Returns
         -------
-        AsyncRawLatestheadlinesClient
+        AsyncRawLatestHeadlinesClient
         """
         return self._raw_client
 
-    async def get(
+    async def latest_headlines_get(
         self,
         *,
-        when: typing.Optional[str] = None,
-        by_parse_date: typing.Optional[bool] = None,
+        when: typing.Optional[When] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
         lang: typing.Optional[str] = None,
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
@@ -735,39 +628,40 @@ async def get(
         sources: typing.Optional[str] = None,
         not_sources: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        ranked_only: typing.Optional[bool] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[LatestHeadlinesGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> LatestHeadlinesGetResponse:
         """
@@ -775,143 +669,89 @@ async def get(
 
         Parameters
         ----------
-        when : typing.Optional[str]
-            The time period for which you want to get the latest headlines.
+        when : typing.Optional[When]
 
-            Format examples:
-            - `7d`: Last seven days
-            - `30d`: Last 30 days
-            - `1h`: Last hour
-            - `24h`: Last 24 hours
+        by_parse_date : typing.Optional[ByParseDate]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        sort_by : typing.Optional[SortBy]
 
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
-
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[LatestHeadlinesGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -919,115 +759,29 @@ async def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1035,8 +789,6 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1044,8 +796,6 @@ async def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1053,8 +803,6 @@ async def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1062,14 +810,13 @@ async def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1077,7 +824,7 @@ async def get(
         Returns
         -------
         LatestHeadlinesGetResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
@@ -1091,26 +838,59 @@ async def get(
 
 
         async def main() -> None:
-            await client.latestheadlines.get(
-                predefined_sources="top 100 US, top 5 GB",
+            await client.latest_headlines.latest_headlines_get(
+                when="7d",
+                by_parse_date=True,
+                lang="en,es",
+                not_lang="fr,de",
+                countries="US,CA",
+                not_countries="UK,FR",
+                predefined_sources="top 50 US, top 20 GB",
+                sources="nytimes.com,finance.yahoo.com",
+                not_sources="cnn.com,wsj.com",
+                not_author_name="John Doe, Jane Doe",
+                ranked_only=True,
+                is_headline=True,
+                is_opinion=True,
+                is_paid_content=False,
+                parent_url="wsj.com/politics,wsj.com/tech",
+                all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+                all_domain_links="who.int,nih.gov",
+                all_links_text="Nvidia,Tesla",
+                word_count_min=300,
+                word_count_max=1000,
+                page=2,
+                page_size=50,
+                clustering_enabled=True,
+                clustering_threshold=0.6,
                 include_translation_fields=True,
                 include_nlp_data=True,
                 has_nlp=True,
-                theme="Business,Finance",
-                not_theme="Crime",
+                theme="Finance,Tech",
+                not_theme="Crime,Sports",
+                org_entity_name='"Apple Inc" OR Microsoft',
+                per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+                loc_entity_name='"San Francisco" OR "New York City"',
+                misc_entity_name='AWS OR "Microsoft Azure"',
+                title_sentiment_min=-0.5,
+                title_sentiment_max=0.5,
+                content_sentiment_min=-0.5,
+                content_sentiment_max=0.5,
                 iptc_tags="20000199,20000209",
                 not_iptc_tags="20000205,20000209",
                 iab_tags="Business,Events",
                 not_iab_tags="Agriculture,Metals",
-                custom_tags="Tag1,Tag2,Tag3",
+                custom_tags="Tag1,Tag2",
+                robots_compliant=True,
             )
 
 
         asyncio.run(main())
         """
-        _response = await self._raw_client.get(
+        _response = await self._raw_client.latest_headlines_get(
             when=when,
             by_parse_date=by_parse_date,
+            sort_by=sort_by,
             lang=lang,
             not_lang=not_lang,
             countries=countries,
@@ -1126,6 +906,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
@@ -1156,7 +937,7 @@ async def main() -> None:
         )
         return _response.data
 
-    async def post(
+    async def latest_headlines_post(
         self,
         *,
         when: typing.Optional[When] = OMIT,
@@ -1176,6 +957,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -1243,6 +1025,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -1301,7 +1085,7 @@ async def post(
         Returns
         -------
         LatestHeadlinesPostResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
@@ -1315,17 +1099,15 @@ async def post(
 
 
         async def main() -> None:
-            await client.latestheadlines.post(
-                lang="en",
-                predefined_sources=["top 50 US", "top 20 GB"],
-                is_opinion=False,
-                page_size=10,
+            await client.latest_headlines.latest_headlines_post(
+                when="7d",
+                page_size=1,
             )
 
 
         asyncio.run(main())
         """
-        _response = await self._raw_client.post(
+        _response = await self._raw_client.latest_headlines_post(
             when=when,
             by_parse_date=by_parse_date,
             lang=lang,
@@ -1343,6 +1125,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             word_count_min=word_count_min,
             word_count_max=word_count_max,
             page=page,
diff --git a/src/newscatcher/latestheadlines/raw_client.py b/src/newscatcher/latest_headlines/raw_client.py
similarity index 67%
rename from src/newscatcher/latestheadlines/raw_client.py
rename to src/newscatcher/latest_headlines/raw_client.py
index 7eeac74..223b7d3 100644
--- a/src/newscatcher/latestheadlines/raw_client.py
+++ b/src/newscatcher/latest_headlines/raw_client.py
@@ -6,6 +6,7 @@
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..core.serialization import convert_and_respect_annotation_metadata
@@ -18,6 +19,7 @@
 from ..errors.unprocessable_entity_error import UnprocessableEntityError
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.by_parse_date import ByParseDate
 from ..types.clustering_enabled import ClusteringEnabled
 from ..types.clustering_threshold import ClusteringThreshold
@@ -53,6 +55,7 @@
 from ..types.predefined_sources import PredefinedSources
 from ..types.ranked_only import RankedOnly
 from ..types.robots_compliant import RobotsCompliant
+from ..types.sort_by import SortBy
 from ..types.sources import Sources
 from ..types.theme import Theme
 from ..types.title_sentiment_max import TitleSentimentMax
@@ -60,23 +63,24 @@
 from ..types.when import When
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
-from .types.latest_headlines_get_request_clustering_variable import LatestHeadlinesGetRequestClusteringVariable
 from .types.latest_headlines_get_response import LatestHeadlinesGetResponse
 from .types.latest_headlines_post_response import LatestHeadlinesPostResponse
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
 
 
-class RawLatestheadlinesClient:
+class RawLatestHeadlinesClient:
     def __init__(self, *, client_wrapper: SyncClientWrapper):
         self._client_wrapper = client_wrapper
 
-    def get(
+    def latest_headlines_get(
         self,
         *,
-        when: typing.Optional[str] = None,
-        by_parse_date: typing.Optional[bool] = None,
+        when: typing.Optional[When] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
         lang: typing.Optional[str] = None,
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
@@ -85,39 +89,40 @@ def get(
         sources: typing.Optional[str] = None,
         not_sources: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        ranked_only: typing.Optional[bool] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[LatestHeadlinesGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[LatestHeadlinesGetResponse]:
         """
@@ -125,143 +130,89 @@ def get(
 
         Parameters
         ----------
-        when : typing.Optional[str]
-            The time period for which you want to get the latest headlines.
+        when : typing.Optional[When]
 
-            Format examples:
-            - `7d`: Last seven days
-            - `30d`: Last 30 days
-            - `1h`: Last hour
-            - `24h`: Last 24 hours
+        by_parse_date : typing.Optional[ByParseDate]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        sort_by : typing.Optional[SortBy]
 
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
-
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
-
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[LatestHeadlinesGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -269,115 +220,29 @@ def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -385,8 +250,6 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -394,8 +257,6 @@ def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -403,8 +264,6 @@ def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -412,14 +271,13 @@ def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -427,7 +285,7 @@ def get(
         Returns
         -------
         HttpResponse[LatestHeadlinesGetResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = self._client_wrapper.httpx_client.request(
             "api/latest_headlines",
@@ -435,6 +293,7 @@ def get(
             params={
                 "when": when,
                 "by_parse_date": by_parse_date,
+                "sort_by": sort_by,
                 "lang": lang,
                 "not_lang": not_lang,
                 "countries": countries,
@@ -450,6 +309,7 @@ def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -569,9 +429,13 @@ def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
-    def post(
+    def latest_headlines_post(
         self,
         *,
         when: typing.Optional[When] = OMIT,
@@ -591,6 +455,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -658,6 +523,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -716,7 +583,7 @@ def post(
         Returns
         -------
         HttpResponse[LatestHeadlinesPostResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = self._client_wrapper.httpx_client.request(
             "api/latest_headlines",
@@ -759,6 +626,9 @@ def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -769,10 +639,8 @@ def post(
                 "include_translation_fields": include_translation_fields,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -894,18 +762,23 @@ def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
-class AsyncRawLatestheadlinesClient:
+class AsyncRawLatestHeadlinesClient:
     def __init__(self, *, client_wrapper: AsyncClientWrapper):
         self._client_wrapper = client_wrapper
 
-    async def get(
+    async def latest_headlines_get(
         self,
         *,
-        when: typing.Optional[str] = None,
-        by_parse_date: typing.Optional[bool] = None,
+        when: typing.Optional[When] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
         lang: typing.Optional[str] = None,
         not_lang: typing.Optional[str] = None,
         countries: typing.Optional[str] = None,
@@ -914,39 +787,40 @@ async def get(
         sources: typing.Optional[str] = None,
         not_sources: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        ranked_only: typing.Optional[bool] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[LatestHeadlinesGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        all_links_text: typing.Optional[str] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[LatestHeadlinesGetResponse]:
         """
@@ -954,143 +828,89 @@ async def get(
 
         Parameters
         ----------
-        when : typing.Optional[str]
-            The time period for which you want to get the latest headlines.
+        when : typing.Optional[When]
 
-            Format examples:
-            - `7d`: Last seven days
-            - `30d`: Last 30 days
-            - `1h`: Last hour
-            - `24h`: Last 24 hours
+        by_parse_date : typing.Optional[ByParseDate]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        sort_by : typing.Optional[SortBy]
 
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
-
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
-
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[LatestHeadlinesGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_translation_fields : typing.Optional[IncludeTranslationFields]
 
@@ -1098,115 +918,29 @@ async def get(
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1214,8 +948,6 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1223,8 +955,6 @@ async def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1232,8 +962,6 @@ async def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1241,14 +969,13 @@ async def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1256,7 +983,7 @@ async def get(
         Returns
         -------
         AsyncHttpResponse[LatestHeadlinesGetResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = await self._client_wrapper.httpx_client.request(
             "api/latest_headlines",
@@ -1264,6 +991,7 @@ async def get(
             params={
                 "when": when,
                 "by_parse_date": by_parse_date,
+                "sort_by": sort_by,
                 "lang": lang,
                 "not_lang": not_lang,
                 "countries": countries,
@@ -1279,6 +1007,7 @@ async def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -1398,9 +1127,13 @@ async def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
-    async def post(
+    async def latest_headlines_post(
         self,
         *,
         when: typing.Optional[When] = OMIT,
@@ -1420,6 +1153,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         word_count_min: typing.Optional[WordCountMin] = OMIT,
         word_count_max: typing.Optional[WordCountMax] = OMIT,
         page: typing.Optional[Page] = OMIT,
@@ -1487,6 +1221,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         word_count_min : typing.Optional[WordCountMin]
 
         word_count_max : typing.Optional[WordCountMax]
@@ -1545,7 +1281,7 @@ async def post(
         Returns
         -------
         AsyncHttpResponse[LatestHeadlinesPostResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = await self._client_wrapper.httpx_client.request(
             "api/latest_headlines",
@@ -1588,6 +1324,9 @@ async def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "word_count_min": word_count_min,
                 "word_count_max": word_count_max,
                 "page": page,
@@ -1598,10 +1337,8 @@ async def post(
                 "include_translation_fields": include_translation_fields,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -1723,4 +1460,8 @@ async def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/latest_headlines/types/__init__.py b/src/newscatcher/latest_headlines/types/__init__.py
new file mode 100644
index 0000000..10e8792
--- /dev/null
+++ b/src/newscatcher/latest_headlines/types/__init__.py
@@ -0,0 +1,38 @@
+# This file was auto-generated by Fern from our API Definition.
+
+# isort: skip_file
+
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .latest_headlines_get_response import LatestHeadlinesGetResponse
+    from .latest_headlines_post_response import LatestHeadlinesPostResponse
+_dynamic_imports: typing.Dict[str, str] = {
+    "LatestHeadlinesGetResponse": ".latest_headlines_get_response",
+    "LatestHeadlinesPostResponse": ".latest_headlines_post_response",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["LatestHeadlinesGetResponse", "LatestHeadlinesPostResponse"]
diff --git a/src/newscatcher/latestheadlines/types/latest_headlines_get_response.py b/src/newscatcher/latest_headlines/types/latest_headlines_get_response.py
similarity index 100%
rename from src/newscatcher/latestheadlines/types/latest_headlines_get_response.py
rename to src/newscatcher/latest_headlines/types/latest_headlines_get_response.py
diff --git a/src/newscatcher/latestheadlines/types/latest_headlines_post_response.py b/src/newscatcher/latest_headlines/types/latest_headlines_post_response.py
similarity index 100%
rename from src/newscatcher/latestheadlines/types/latest_headlines_post_response.py
rename to src/newscatcher/latest_headlines/types/latest_headlines_post_response.py
diff --git a/src/newscatcher/latestheadlines/__init__.py b/src/newscatcher/latestheadlines/__init__.py
deleted file mode 100644
index 79cd966..0000000
--- a/src/newscatcher/latestheadlines/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-# isort: skip_file
-
-from .types import LatestHeadlinesGetRequestClusteringVariable, LatestHeadlinesGetResponse, LatestHeadlinesPostResponse
-
-__all__ = ["LatestHeadlinesGetRequestClusteringVariable", "LatestHeadlinesGetResponse", "LatestHeadlinesPostResponse"]
diff --git a/src/newscatcher/latestheadlines/types/__init__.py b/src/newscatcher/latestheadlines/types/__init__.py
deleted file mode 100644
index a3c6699..0000000
--- a/src/newscatcher/latestheadlines/types/__init__.py
+++ /dev/null
@@ -1,9 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-# isort: skip_file
-
-from .latest_headlines_get_request_clustering_variable import LatestHeadlinesGetRequestClusteringVariable
-from .latest_headlines_get_response import LatestHeadlinesGetResponse
-from .latest_headlines_post_response import LatestHeadlinesPostResponse
-
-__all__ = ["LatestHeadlinesGetRequestClusteringVariable", "LatestHeadlinesGetResponse", "LatestHeadlinesPostResponse"]
diff --git a/src/newscatcher/latestheadlines/types/latest_headlines_get_request_clustering_variable.py b/src/newscatcher/latestheadlines/types/latest_headlines_get_request_clustering_variable.py
deleted file mode 100644
index 2d68a10..0000000
--- a/src/newscatcher/latestheadlines/types/latest_headlines_get_request_clustering_variable.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-LatestHeadlinesGetRequestClusteringVariable = typing.Union[typing.Literal["content", "title", "summary"], typing.Any]
diff --git a/src/newscatcher/search/__init__.py b/src/newscatcher/search/__init__.py
index b2bfd44..3c584ee 100644
--- a/src/newscatcher/search/__init__.py
+++ b/src/newscatcher/search/__init__.py
@@ -2,20 +2,33 @@
 
 # isort: skip_file
 
-from .types import (
-    SearchGetRequestClusteringVariable,
-    SearchGetRequestNewsDomainType,
-    SearchGetRequestPublishedDatePrecision,
-    SearchGetRequestSortBy,
-    SearchGetResponse,
-    SearchPostResponse,
-)
-
-__all__ = [
-    "SearchGetRequestClusteringVariable",
-    "SearchGetRequestNewsDomainType",
-    "SearchGetRequestPublishedDatePrecision",
-    "SearchGetRequestSortBy",
-    "SearchGetResponse",
-    "SearchPostResponse",
-]
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .types import SearchGetResponse, SearchPostResponse
+_dynamic_imports: typing.Dict[str, str] = {"SearchGetResponse": ".types", "SearchPostResponse": ".types"}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["SearchGetResponse", "SearchPostResponse"]
diff --git a/src/newscatcher/search/client.py b/src/newscatcher/search/client.py
index 40ea215..bb7082c 100644
--- a/src/newscatcher/search/client.py
+++ b/src/newscatcher/search/client.py
@@ -1,6 +1,5 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import datetime as dt
 import typing
 
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
@@ -8,6 +7,7 @@
 from ..types.additional_domain_info import AdditionalDomainInfo
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.by_parse_date import ByParseDate
 from ..types.clustering_enabled import ClusteringEnabled
 from ..types.clustering_threshold import ClusteringThreshold
@@ -62,10 +62,6 @@
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
 from .raw_client import AsyncRawSearchClient, RawSearchClient
-from .types.search_get_request_clustering_variable import SearchGetRequestClusteringVariable
-from .types.search_get_request_news_domain_type import SearchGetRequestNewsDomainType
-from .types.search_get_request_published_date_precision import SearchGetRequestPublishedDatePrecision
-from .types.search_get_request_sort_by import SearchGetRequestSortBy
 from .types.search_get_response import SearchGetResponse
 from .types.search_post_response import SearchPostResponse
 
@@ -91,7 +87,7 @@ def with_raw_response(self) -> RawSearchClient:
     def get(
         self,
         *,
-        q: str,
+        q: Q,
         search_in: typing.Optional[SearchIn] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -103,68 +99,59 @@ def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[SearchGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[SearchGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        additional_domain_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SearchGetRequestNewsDomainType] = None,
+        all_links_text: typing.Optional[str] = None,
+        additional_domain_info: typing.Optional[AdditionalDomainInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[SearchGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        exclude_duplicates: typing.Optional[bool] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        exclude_duplicates: typing.Optional[ExcludeDuplicates] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SearchGetResponse:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         search_in : typing.Optional[SearchIn]
 
@@ -173,318 +160,138 @@ def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[SearchGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[SearchGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        additional_domain_info : typing.Optional[bool]
-            If true, includes additional domain information in the response for each article:
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., `"Original Content"`).
-            - `news_type`: Category of news (e.g., `"News and Blogs"`).
-
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
-
-        news_domain_type : typing.Optional[SearchGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
-
-        news_type : typing.Optional[str]
-            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            Example: `"General News Outlets,Tech News and Updates"`
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+        additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        is_news_domain : typing.Optional[IsNewsDomain]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        news_domain_type : typing.Optional[NewsDomainType]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        news_type : typing.Optional[str]
+            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[SearchGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -492,8 +299,6 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -501,8 +306,6 @@ def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -510,8 +313,6 @@ def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -519,19 +320,15 @@ def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-        exclude_duplicates : typing.Optional[bool]
-            If true, excludes duplicate and highly similar articles from the search results. If false, returns all relevant articles, including duplicates.
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-            To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-concepts/articles-deduplication).
+        exclude_duplicates : typing.Optional[ExcludeDuplicates]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -539,7 +336,7 @@ def get(
         Returns
         -------
         SearchGetResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
@@ -551,25 +348,64 @@ def get(
             api_key="YOUR_API_KEY",
         )
         client.search.get(
-            q="technology AND (Apple OR Microsoft) NOT Google",
+            q='"supply chain" AND Amazon NOT China',
             search_in="title_content, title_content_translated",
             include_translation_fields=True,
-            predefined_sources="top 100 US, top 5 GB",
+            predefined_sources="top 50 US, top 20 GB",
+            source_name="sport,tech",
+            sources="nytimes.com,finance.yahoo.com",
+            not_sources="cnn.com,wsj.com",
+            lang="en,es",
+            not_lang="fr,de",
+            countries="US,CA",
+            not_countries="UK,FR",
+            not_author_name="John Doe, Jane Doe",
             from_=datetime.datetime.fromisoformat(
                 "2024-07-01 00:00:00+00:00",
             ),
             to=datetime.datetime.fromisoformat(
-                "2024-07-01 00:00:00+00:00",
+                "2024-01-01 00:00:00+00:00",
             ),
+            published_date_precision="full",
+            by_parse_date=True,
+            ranked_only=True,
+            from_rank=100,
+            to_rank=100,
+            is_headline=True,
+            is_opinion=True,
+            is_paid_content=False,
+            parent_url="wsj.com/politics,wsj.com/tech",
+            all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+            all_domain_links="who.int,nih.gov",
+            all_links_text="Nvidia,Tesla",
+            additional_domain_info=True,
+            is_news_domain=True,
+            news_type="General News Outlets,Tech News and Updates",
+            word_count_min=300,
+            word_count_max=1000,
+            page=2,
+            page_size=50,
+            clustering_enabled=True,
+            clustering_threshold=0.6,
             include_nlp_data=True,
             has_nlp=True,
-            theme="Business,Finance",
-            not_theme="Crime",
+            theme="Finance,Tech",
+            not_theme="Crime,Sports",
+            org_entity_name='"Apple Inc" OR Microsoft',
+            per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+            loc_entity_name='"San Francisco" OR "New York City"',
+            misc_entity_name='AWS OR "Microsoft Azure"',
+            title_sentiment_min=-0.5,
+            title_sentiment_max=0.5,
+            content_sentiment_min=-0.5,
+            content_sentiment_max=0.5,
             iptc_tags="20000199,20000209",
             not_iptc_tags="20000205,20000209",
             iab_tags="Business,Events",
             not_iab_tags="Agriculture,Metals",
-            custom_tags="Tag1,Tag2,Tag3",
+            custom_tags="Tag1,Tag2",
+            exclude_duplicates=True,
+            robots_compliant=True,
         )
         """
         _response = self._raw_client.get(
@@ -599,6 +435,7 @@ def get(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             additional_domain_info=additional_domain_info,
             is_news_domain=is_news_domain,
             news_domain_type=news_domain_type,
@@ -662,6 +499,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         additional_domain_info: typing.Optional[AdditionalDomainInfo] = OMIT,
         is_news_domain: typing.Optional[IsNewsDomain] = OMIT,
         news_domain_type: typing.Optional[NewsDomainType] = OMIT,
@@ -695,7 +533,7 @@ def post(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SearchPostResponse:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
@@ -751,6 +589,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
         is_news_domain : typing.Optional[IsNewsDomain]
@@ -817,29 +657,18 @@ def post(
         Returns
         -------
         SearchPostResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
-        import datetime
-
         from newscatcher import NewscatcherApi
 
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
         client.search.post(
-            q="renewable energy",
-            predefined_sources=["top 50 US"],
-            lang=["en"],
-            from_=datetime.datetime.fromisoformat(
-                "2024-01-01 00:00:00+00:00",
-            ),
-            to=datetime.datetime.fromisoformat(
-                "2024-06-30 00:00:00+00:00",
-            ),
-            additional_domain_info=True,
-            is_news_domain=True,
+            q='"supply chain" AND Amazon NOT China',
+            page_size=1,
         )
         """
         _response = self._raw_client.post(
@@ -869,6 +698,7 @@ def post(
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             additional_domain_info=additional_domain_info,
             is_news_domain=is_news_domain,
             news_domain_type=news_domain_type,
@@ -922,7 +752,7 @@ def with_raw_response(self) -> AsyncRawSearchClient:
     async def get(
         self,
         *,
-        q: str,
+        q: Q,
         search_in: typing.Optional[SearchIn] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -934,68 +764,59 @@ async def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[SearchGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[SearchGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        additional_domain_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SearchGetRequestNewsDomainType] = None,
+        all_links_text: typing.Optional[str] = None,
+        additional_domain_info: typing.Optional[AdditionalDomainInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[SearchGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        exclude_duplicates: typing.Optional[bool] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        exclude_duplicates: typing.Optional[ExcludeDuplicates] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SearchGetResponse:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         search_in : typing.Optional[SearchIn]
 
@@ -1004,318 +825,138 @@ async def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[SearchGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[SearchGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        additional_domain_info : typing.Optional[bool]
-            If true, includes additional domain information in the response for each article:
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., `"Original Content"`).
-            - `news_type`: Category of news (e.g., `"News and Blogs"`).
-
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
-
-        news_domain_type : typing.Optional[SearchGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
-
-        news_type : typing.Optional[str]
-            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            Example: `"General News Outlets,Tech News and Updates"`
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+        additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        is_news_domain : typing.Optional[IsNewsDomain]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        news_domain_type : typing.Optional[NewsDomainType]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        news_type : typing.Optional[str]
+            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[SearchGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1323,8 +964,6 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1332,8 +971,6 @@ async def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1341,8 +978,6 @@ async def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1350,19 +985,15 @@ async def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-        exclude_duplicates : typing.Optional[bool]
-            If true, excludes duplicate and highly similar articles from the search results. If false, returns all relevant articles, including duplicates.
-
-            To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-concepts/articles-deduplication).
+        exclude_duplicates : typing.Optional[ExcludeDuplicates]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1370,7 +1001,7 @@ async def get(
         Returns
         -------
         SearchGetResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
@@ -1386,25 +1017,64 @@ async def get(
 
         async def main() -> None:
             await client.search.get(
-                q="technology AND (Apple OR Microsoft) NOT Google",
+                q='"supply chain" AND Amazon NOT China',
                 search_in="title_content, title_content_translated",
                 include_translation_fields=True,
-                predefined_sources="top 100 US, top 5 GB",
+                predefined_sources="top 50 US, top 20 GB",
+                source_name="sport,tech",
+                sources="nytimes.com,finance.yahoo.com",
+                not_sources="cnn.com,wsj.com",
+                lang="en,es",
+                not_lang="fr,de",
+                countries="US,CA",
+                not_countries="UK,FR",
+                not_author_name="John Doe, Jane Doe",
                 from_=datetime.datetime.fromisoformat(
                     "2024-07-01 00:00:00+00:00",
                 ),
                 to=datetime.datetime.fromisoformat(
-                    "2024-07-01 00:00:00+00:00",
+                    "2024-01-01 00:00:00+00:00",
                 ),
+                published_date_precision="full",
+                by_parse_date=True,
+                ranked_only=True,
+                from_rank=100,
+                to_rank=100,
+                is_headline=True,
+                is_opinion=True,
+                is_paid_content=False,
+                parent_url="wsj.com/politics,wsj.com/tech",
+                all_links="https://aiindex.stanford.edu/report,https://www.stateof.ai",
+                all_domain_links="who.int,nih.gov",
+                all_links_text="Nvidia,Tesla",
+                additional_domain_info=True,
+                is_news_domain=True,
+                news_type="General News Outlets,Tech News and Updates",
+                word_count_min=300,
+                word_count_max=1000,
+                page=2,
+                page_size=50,
+                clustering_enabled=True,
+                clustering_threshold=0.6,
                 include_nlp_data=True,
                 has_nlp=True,
-                theme="Business,Finance",
-                not_theme="Crime",
+                theme="Finance,Tech",
+                not_theme="Crime,Sports",
+                org_entity_name='"Apple Inc" OR Microsoft',
+                per_entity_name='"Elon Musk" OR "Jeff Bezos"',
+                loc_entity_name='"San Francisco" OR "New York City"',
+                misc_entity_name='AWS OR "Microsoft Azure"',
+                title_sentiment_min=-0.5,
+                title_sentiment_max=0.5,
+                content_sentiment_min=-0.5,
+                content_sentiment_max=0.5,
                 iptc_tags="20000199,20000209",
                 not_iptc_tags="20000205,20000209",
                 iab_tags="Business,Events",
                 not_iab_tags="Agriculture,Metals",
-                custom_tags="Tag1,Tag2,Tag3",
+                custom_tags="Tag1,Tag2",
+                exclude_duplicates=True,
+                robots_compliant=True,
             )
 
 
@@ -1437,6 +1107,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             additional_domain_info=additional_domain_info,
             is_news_domain=is_news_domain,
             news_domain_type=news_domain_type,
@@ -1500,6 +1171,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         additional_domain_info: typing.Optional[AdditionalDomainInfo] = OMIT,
         is_news_domain: typing.Optional[IsNewsDomain] = OMIT,
         news_domain_type: typing.Optional[NewsDomainType] = OMIT,
@@ -1533,7 +1205,7 @@ async def post(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SearchPostResponse:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
@@ -1589,6 +1261,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
         is_news_domain : typing.Optional[IsNewsDomain]
@@ -1655,12 +1329,11 @@ async def post(
         Returns
         -------
         SearchPostResponse
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
 
         Examples
         --------
         import asyncio
-        import datetime
 
         from newscatcher import AsyncNewscatcherApi
 
@@ -1671,17 +1344,8 @@ async def post(
 
         async def main() -> None:
             await client.search.post(
-                q="renewable energy",
-                predefined_sources=["top 50 US"],
-                lang=["en"],
-                from_=datetime.datetime.fromisoformat(
-                    "2024-01-01 00:00:00+00:00",
-                ),
-                to=datetime.datetime.fromisoformat(
-                    "2024-06-30 00:00:00+00:00",
-                ),
-                additional_domain_info=True,
-                is_news_domain=True,
+                q='"supply chain" AND Amazon NOT China',
+                page_size=1,
             )
 
 
@@ -1714,6 +1378,7 @@ async def main() -> None:
             parent_url=parent_url,
             all_links=all_links,
             all_domain_links=all_domain_links,
+            all_links_text=all_links_text,
             additional_domain_info=additional_domain_info,
             is_news_domain=is_news_domain,
             news_domain_type=news_domain_type,
diff --git a/src/newscatcher/search/raw_client.py b/src/newscatcher/search/raw_client.py
index ec01ca2..2eca68a 100644
--- a/src/newscatcher/search/raw_client.py
+++ b/src/newscatcher/search/raw_client.py
@@ -1,13 +1,12 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import datetime as dt
 import typing
 from json.decoder import JSONDecodeError
 
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
-from ..core.datetime_utils import serialize_datetime
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..core.serialization import convert_and_respect_annotation_metadata
@@ -21,6 +20,7 @@
 from ..types.additional_domain_info import AdditionalDomainInfo
 from ..types.all_domain_links import AllDomainLinks
 from ..types.all_links import AllLinks
+from ..types.all_links_text import AllLinksText
 from ..types.by_parse_date import ByParseDate
 from ..types.clustering_enabled import ClusteringEnabled
 from ..types.clustering_threshold import ClusteringThreshold
@@ -75,12 +75,9 @@
 from ..types.to_rank import ToRank
 from ..types.word_count_max import WordCountMax
 from ..types.word_count_min import WordCountMin
-from .types.search_get_request_clustering_variable import SearchGetRequestClusteringVariable
-from .types.search_get_request_news_domain_type import SearchGetRequestNewsDomainType
-from .types.search_get_request_published_date_precision import SearchGetRequestPublishedDatePrecision
-from .types.search_get_request_sort_by import SearchGetRequestSortBy
 from .types.search_get_response import SearchGetResponse
 from .types.search_post_response import SearchPostResponse
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -93,7 +90,7 @@ def __init__(self, *, client_wrapper: SyncClientWrapper):
     def get(
         self,
         *,
-        q: str,
+        q: Q,
         search_in: typing.Optional[SearchIn] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -105,68 +102,59 @@ def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[SearchGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[SearchGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        additional_domain_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SearchGetRequestNewsDomainType] = None,
+        all_links_text: typing.Optional[str] = None,
+        additional_domain_info: typing.Optional[AdditionalDomainInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[SearchGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        exclude_duplicates: typing.Optional[bool] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        exclude_duplicates: typing.Optional[ExcludeDuplicates] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[SearchGetResponse]:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         search_in : typing.Optional[SearchIn]
 
@@ -175,318 +163,138 @@ def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[SearchGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[SearchGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        additional_domain_info : typing.Optional[bool]
-            If true, includes additional domain information in the response for each article:
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., `"Original Content"`).
-            - `news_type`: Category of news (e.g., `"News and Blogs"`).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        news_domain_type : typing.Optional[SearchGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
-
-        news_type : typing.Optional[str]
-            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            Example: `"General News Outlets,Tech News and Updates"`
-
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+        additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        is_news_domain : typing.Optional[IsNewsDomain]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        news_domain_type : typing.Optional[NewsDomainType]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        news_type : typing.Optional[str]
+            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[SearchGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -494,8 +302,6 @@ def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -503,8 +309,6 @@ def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -512,8 +316,6 @@ def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -521,19 +323,15 @@ def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-        exclude_duplicates : typing.Optional[bool]
-            If true, excludes duplicate and highly similar articles from the search results. If false, returns all relevant articles, including duplicates.
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-            To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-concepts/articles-deduplication).
+        exclude_duplicates : typing.Optional[ExcludeDuplicates]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -541,7 +339,7 @@ def get(
         Returns
         -------
         HttpResponse[SearchGetResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = self._client_wrapper.httpx_client.request(
             "api/search",
@@ -559,8 +357,8 @@ def get(
                 "countries": countries,
                 "not_countries": not_countries,
                 "not_author_name": not_author_name,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
+                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
+                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
                 "published_date_precision": published_date_precision,
                 "by_parse_date": by_parse_date,
                 "sort_by": sort_by,
@@ -573,6 +371,7 @@ def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "additional_domain_info": additional_domain_info,
                 "is_news_domain": is_news_domain,
                 "news_domain_type": news_domain_type,
@@ -696,6 +495,10 @@ def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     def post(
@@ -727,6 +530,7 @@ def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         additional_domain_info: typing.Optional[AdditionalDomainInfo] = OMIT,
         is_news_domain: typing.Optional[IsNewsDomain] = OMIT,
         news_domain_type: typing.Optional[NewsDomainType] = OMIT,
@@ -760,7 +564,7 @@ def post(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[SearchPostResponse]:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
@@ -816,6 +620,8 @@ def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
         is_news_domain : typing.Optional[IsNewsDomain]
@@ -882,7 +688,7 @@ def post(
         Returns
         -------
         HttpResponse[SearchPostResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = self._client_wrapper.httpx_client.request(
             "api/search",
@@ -936,6 +742,9 @@ def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "additional_domain_info": additional_domain_info,
                 "is_news_domain": is_news_domain,
                 "news_domain_type": news_domain_type,
@@ -951,10 +760,8 @@ def post(
                 "clustering_threshold": clustering_threshold,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -1077,6 +884,10 @@ def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
@@ -1087,7 +898,7 @@ def __init__(self, *, client_wrapper: AsyncClientWrapper):
     async def get(
         self,
         *,
-        q: str,
+        q: Q,
         search_in: typing.Optional[SearchIn] = None,
         include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
         predefined_sources: typing.Optional[str] = None,
@@ -1099,68 +910,59 @@ async def get(
         countries: typing.Optional[str] = None,
         not_countries: typing.Optional[str] = None,
         not_author_name: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        published_date_precision: typing.Optional[SearchGetRequestPublishedDatePrecision] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        sort_by: typing.Optional[SearchGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
+        from_: typing.Optional[From] = None,
+        to: typing.Optional[To] = None,
+        published_date_precision: typing.Optional[PublishedDatePrecision] = None,
+        by_parse_date: typing.Optional[ByParseDate] = None,
+        sort_by: typing.Optional[SortBy] = None,
+        ranked_only: typing.Optional[RankedOnly] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
+        is_headline: typing.Optional[IsHeadline] = None,
+        is_opinion: typing.Optional[IsOpinion] = None,
+        is_paid_content: typing.Optional[IsPaidContent] = None,
         parent_url: typing.Optional[str] = None,
         all_links: typing.Optional[str] = None,
         all_domain_links: typing.Optional[str] = None,
-        additional_domain_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SearchGetRequestNewsDomainType] = None,
+        all_links_text: typing.Optional[str] = None,
+        additional_domain_info: typing.Optional[AdditionalDomainInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        clustering_enabled: typing.Optional[bool] = None,
-        clustering_variable: typing.Optional[SearchGetRequestClusteringVariable] = None,
-        clustering_threshold: typing.Optional[float] = None,
+        word_count_min: typing.Optional[WordCountMin] = None,
+        word_count_max: typing.Optional[WordCountMax] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        clustering_enabled: typing.Optional[ClusteringEnabled] = None,
+        clustering_variable: typing.Optional[ClusteringVariable] = None,
+        clustering_threshold: typing.Optional[ClusteringThreshold] = None,
         include_nlp_data: typing.Optional[IncludeNlpData] = None,
         has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        org_entity_name: typing.Optional[str] = None,
-        per_entity_name: typing.Optional[str] = None,
-        loc_entity_name: typing.Optional[str] = None,
-        misc_entity_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
+        theme: typing.Optional[Theme] = None,
+        not_theme: typing.Optional[NotTheme] = None,
+        org_entity_name: typing.Optional[OrgEntityName] = None,
+        per_entity_name: typing.Optional[PerEntityName] = None,
+        loc_entity_name: typing.Optional[LocEntityName] = None,
+        misc_entity_name: typing.Optional[MiscEntityName] = None,
+        title_sentiment_min: typing.Optional[TitleSentimentMin] = None,
+        title_sentiment_max: typing.Optional[TitleSentimentMax] = None,
+        content_sentiment_min: typing.Optional[ContentSentimentMin] = None,
+        content_sentiment_max: typing.Optional[ContentSentimentMax] = None,
         iptc_tags: typing.Optional[str] = None,
         not_iptc_tags: typing.Optional[str] = None,
         iab_tags: typing.Optional[str] = None,
         not_iab_tags: typing.Optional[str] = None,
         custom_tags: typing.Optional[str] = None,
-        exclude_duplicates: typing.Optional[bool] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        exclude_duplicates: typing.Optional[ExcludeDuplicates] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[SearchGetResponse]:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
+        q : Q
 
         search_in : typing.Optional[SearchIn]
 
@@ -1169,318 +971,138 @@ async def get(
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         sources : typing.Optional[str]
             One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
 
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
         not_sources : typing.Optional[str]
             The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
 
-            Example: `"cnn.com, wsj.com"`
-
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         not_lang : typing.Optional[str]
             The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
 
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_countries : typing.Optional[str]
             The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
 
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         not_author_name : typing.Optional[str]
             The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string.
 
-            Example: `"John Doe, Jane Doe"`
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
+        from_ : typing.Optional[From]
 
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
+        to : typing.Optional[To]
 
-        published_date_precision : typing.Optional[SearchGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
+        published_date_precision : typing.Optional[PublishedDatePrecision]
 
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
+        by_parse_date : typing.Optional[ByParseDate]
 
-        sort_by : typing.Optional[SearchGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
+        sort_by : typing.Optional[SortBy]
 
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
+        ranked_only : typing.Optional[RankedOnly]
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
+        is_headline : typing.Optional[IsHeadline]
 
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
+        is_opinion : typing.Optional[IsOpinion]
 
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
+        is_paid_content : typing.Optional[IsPaidContent]
 
         parent_url : typing.Optional[str]
             The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
 
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
         all_links : typing.Optional[str]
             The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
 
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
         all_domain_links : typing.Optional[str]
             The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
 
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
+            For more details, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-        additional_domain_info : typing.Optional[bool]
-            If true, includes additional domain information in the response for each article:
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., `"Original Content"`).
-            - `news_type`: Category of news (e.g., `"News and Blogs"`).
+        all_links_text : typing.Optional[str]
+            The text content of links mentioned in the article. Searches for links where the anchor text contains the specified terms. For multiple terms, use a comma-separated string.
 
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
+            **Note**: When this parameter is used, the response includes the `all_links_data` field with detailed link information.
 
-        news_domain_type : typing.Optional[SearchGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
-
-        news_type : typing.Optional[str]
-            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
+            To learn more, see [Search by URL](https://www.newscatcherapi.com/docs/news-api/how-to/search-by-url).
 
-            Example: `"General News Outlets,Tech News and Updates"`
-
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
+        additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
+        is_news_domain : typing.Optional[IsNewsDomain]
 
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        news_domain_type : typing.Optional[NewsDomainType]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        news_type : typing.Optional[str]
+            Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-        clustering_enabled : typing.Optional[bool]
-            Determines whether to group similar articles into clusters. If true, the API returns clustered results.
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        word_count_min : typing.Optional[WordCountMin]
 
-        clustering_variable : typing.Optional[SearchGetRequestClusteringVariable]
-            Specifies which part of the article to use for determining similarity when clustering.
+        word_count_max : typing.Optional[WordCountMax]
 
-            Possible values are:
-            - `content`: Uses the full article content (default).
-            - `title`: Uses only the article title.
-            - `summary`: Uses the article summary.
+        page : typing.Optional[Page]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        page_size : typing.Optional[PageSize]
 
-        clustering_threshold : typing.Optional[float]
-            Sets the similarity threshold for grouping articles into clusters. A lower value creates more inclusive clusters, while a higher value requires greater similarity between articles.
+        clustering_enabled : typing.Optional[ClusteringEnabled]
 
-            Examples:
-            - `0.3`: Results in larger, more diverse clusters.
-            - `0.6`: Balances cluster size and article similarity (default).
-            - `0.9`: Creates smaller, tightly related clusters.
+        clustering_variable : typing.Optional[ClusteringVariable]
 
-            To learn more, see [Clustering news articles](/docs/v3/documentation/guides-and-concepts/clustering-news-articles).
+        clustering_threshold : typing.Optional[ClusteringThreshold]
 
         include_nlp_data : typing.Optional[IncludeNlpData]
 
         has_nlp : typing.Optional[HasNlp]
 
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        org_entity_name : typing.Optional[str]
-            Filters articles that mention specific organization names, as identified by NLP analysis. To specify multiple organizations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Apple, Microsoft"`
-
-            **Note**: The `ORG_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        per_entity_name : typing.Optional[str]
-            Filters articles that mention specific person names, as identified by NLP analysis. To specify multiple names, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Elon Musk, Jeff Bezos"`
-
-            **Note**: The `PER_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        loc_entity_name : typing.Optional[str]
-            Filters articles that mention specific location names, as identified by NLP analysis. To specify multiple locations, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"California, New York"`
-
-            **Note**: The `LOC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        misc_entity_name : typing.Optional[str]
-            Filters articles that mention other named entities not falling under person, organization, or location categories. Includes events, nationalities, products, works of art, and more. To specify multiple entities, use a comma-separated string. To search named entities in translations, combine with the translation options of the `search_in` parameter (e.g., `title_content_translated`).
-
-            Example: `"Bitcoin, Blockchain"`
-
-            **Note**: The `MISC_entity_name` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [Search by entity](/docs/v3/documentation/how-to/search-by-entity).
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        theme : typing.Optional[Theme]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        not_theme : typing.Optional[NotTheme]
 
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
+        org_entity_name : typing.Optional[OrgEntityName]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        per_entity_name : typing.Optional[PerEntityName]
 
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
+        loc_entity_name : typing.Optional[LocEntityName]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        misc_entity_name : typing.Optional[MiscEntityName]
 
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
+        title_sentiment_min : typing.Optional[TitleSentimentMin]
 
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
+        title_sentiment_max : typing.Optional[TitleSentimentMax]
 
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
+        content_sentiment_min : typing.Optional[ContentSentimentMin]
 
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
+        content_sentiment_max : typing.Optional[ContentSentimentMax]
 
         iptc_tags : typing.Optional[str]
             Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
 
-            Example: `"20000199, 20000209"`
-
             **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1488,8 +1110,6 @@ async def get(
         not_iptc_tags : typing.Optional[str]
             Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
 
-            Example: `"20000205, 20000209"`
-
             **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
@@ -1497,8 +1117,6 @@ async def get(
         iab_tags : typing.Optional[str]
             Filters articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string.
 
-            Example: `"Business, Events"`
-
             **Note**: The `iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1506,8 +1124,6 @@ async def get(
         not_iab_tags : typing.Optional[str]
             Inverse of the `iab_tags` parameter. Excludes articles based on Interactive Advertising Bureau (IAB) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string.
 
-            Example: `"Agriculture, Metals"`
-
             **Note**: The `not_iab_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
 
             To learn more, see the [IAB Content taxonomy](https://iabtechlab.com/standards/content-taxonomy/).
@@ -1515,19 +1131,15 @@ async def get(
         custom_tags : typing.Optional[str]
             Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
 
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
+            - `custom_tags.taxonomy=Tag1,Tag2`, where `taxonomy` is the taxonomy name and `Tag1,Tag2` is a comma-separated list of tag names.
 
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
+            Example: `custom_tags.industry="Manufacturing,Logistics"`
 
-        exclude_duplicates : typing.Optional[bool]
-            If true, excludes duplicate and highly similar articles from the search results. If false, returns all relevant articles, including duplicates.
+            To learn more, see the [Custom tags](https://www.newscatcherapi.com/docs/news-api/guides-and-concepts/custom-tags).
 
-            To learn more, see [Articles deduplication](/docs/v3/documentation/guides-and-concepts/articles-deduplication).
+        exclude_duplicates : typing.Optional[ExcludeDuplicates]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1535,7 +1147,7 @@ async def get(
         Returns
         -------
         AsyncHttpResponse[SearchGetResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = await self._client_wrapper.httpx_client.request(
             "api/search",
@@ -1553,8 +1165,8 @@ async def get(
                 "countries": countries,
                 "not_countries": not_countries,
                 "not_author_name": not_author_name,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
+                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
+                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
                 "published_date_precision": published_date_precision,
                 "by_parse_date": by_parse_date,
                 "sort_by": sort_by,
@@ -1567,6 +1179,7 @@ async def get(
                 "parent_url": parent_url,
                 "all_links": all_links,
                 "all_domain_links": all_domain_links,
+                "all_links_text": all_links_text,
                 "additional_domain_info": additional_domain_info,
                 "is_news_domain": is_news_domain,
                 "news_domain_type": news_domain_type,
@@ -1690,6 +1303,10 @@ async def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     async def post(
@@ -1721,6 +1338,7 @@ async def post(
         parent_url: typing.Optional[ParentUrl] = OMIT,
         all_links: typing.Optional[AllLinks] = OMIT,
         all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
+        all_links_text: typing.Optional[AllLinksText] = OMIT,
         additional_domain_info: typing.Optional[AdditionalDomainInfo] = OMIT,
         is_news_domain: typing.Optional[IsNewsDomain] = OMIT,
         news_domain_type: typing.Optional[NewsDomainType] = OMIT,
@@ -1754,7 +1372,7 @@ async def post(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[SearchPostResponse]:
         """
-        Searches for articles based on specified criteria such as keyword, language, country, source, and more.
+        Searches for articles based on specified criteria such as keywords, language, country, source, and more.
 
         Parameters
         ----------
@@ -1810,6 +1428,8 @@ async def post(
 
         all_domain_links : typing.Optional[AllDomainLinks]
 
+        all_links_text : typing.Optional[AllLinksText]
+
         additional_domain_info : typing.Optional[AdditionalDomainInfo]
 
         is_news_domain : typing.Optional[IsNewsDomain]
@@ -1876,7 +1496,7 @@ async def post(
         Returns
         -------
         AsyncHttpResponse[SearchPostResponse]
-            A successful response containing articles that match the specified search criteria. The response may include clustering information if enabled.
+            A successful response containing articles that match the search criteria. When `clustering_enabled` is `true`, returns a Clustered Articles Response. Otherwise, returns a Search Response.
         """
         _response = await self._client_wrapper.httpx_client.request(
             "api/search",
@@ -1930,6 +1550,9 @@ async def post(
                 "all_domain_links": convert_and_respect_annotation_metadata(
                     object_=all_domain_links, annotation=AllDomainLinks, direction="write"
                 ),
+                "all_links_text": convert_and_respect_annotation_metadata(
+                    object_=all_links_text, annotation=AllLinksText, direction="write"
+                ),
                 "additional_domain_info": additional_domain_info,
                 "is_news_domain": is_news_domain,
                 "news_domain_type": news_domain_type,
@@ -1945,10 +1568,8 @@ async def post(
                 "clustering_threshold": clustering_threshold,
                 "include_nlp_data": include_nlp_data,
                 "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
+                "theme": theme,
+                "not_theme": not_theme,
                 "ORG_entity_name": org_entity_name,
                 "PER_entity_name": per_entity_name,
                 "LOC_entity_name": loc_entity_name,
@@ -2071,4 +1692,8 @@ async def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/search/types/__init__.py b/src/newscatcher/search/types/__init__.py
index e6be70d..5dbeefd 100644
--- a/src/newscatcher/search/types/__init__.py
+++ b/src/newscatcher/search/types/__init__.py
@@ -2,18 +2,37 @@
 
 # isort: skip_file
 
-from .search_get_request_clustering_variable import SearchGetRequestClusteringVariable
-from .search_get_request_news_domain_type import SearchGetRequestNewsDomainType
-from .search_get_request_published_date_precision import SearchGetRequestPublishedDatePrecision
-from .search_get_request_sort_by import SearchGetRequestSortBy
-from .search_get_response import SearchGetResponse
-from .search_post_response import SearchPostResponse
-
-__all__ = [
-    "SearchGetRequestClusteringVariable",
-    "SearchGetRequestNewsDomainType",
-    "SearchGetRequestPublishedDatePrecision",
-    "SearchGetRequestSortBy",
-    "SearchGetResponse",
-    "SearchPostResponse",
-]
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .search_get_response import SearchGetResponse
+    from .search_post_response import SearchPostResponse
+_dynamic_imports: typing.Dict[str, str] = {
+    "SearchGetResponse": ".search_get_response",
+    "SearchPostResponse": ".search_post_response",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
+
+__all__ = ["SearchGetResponse", "SearchPostResponse"]
diff --git a/src/newscatcher/search/types/search_get_request_clustering_variable.py b/src/newscatcher/search/types/search_get_request_clustering_variable.py
deleted file mode 100644
index e721276..0000000
--- a/src/newscatcher/search/types/search_get_request_clustering_variable.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SearchGetRequestClusteringVariable = typing.Union[typing.Literal["content", "title", "summary"], typing.Any]
diff --git a/src/newscatcher/search/types/search_get_request_news_domain_type.py b/src/newscatcher/search/types/search_get_request_news_domain_type.py
deleted file mode 100644
index 6548490..0000000
--- a/src/newscatcher/search/types/search_get_request_news_domain_type.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SearchGetRequestNewsDomainType = typing.Union[
-    typing.Literal["Original Content", "Aggregator", "Press Releases", "Republisher", "Other"], typing.Any
-]
diff --git a/src/newscatcher/search/types/search_get_request_published_date_precision.py b/src/newscatcher/search/types/search_get_request_published_date_precision.py
deleted file mode 100644
index 5f991a8..0000000
--- a/src/newscatcher/search/types/search_get_request_published_date_precision.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SearchGetRequestPublishedDatePrecision = typing.Union[typing.Literal["full", "timezone unknown", "date"], typing.Any]
diff --git a/src/newscatcher/search/types/search_get_request_sort_by.py b/src/newscatcher/search/types/search_get_request_sort_by.py
deleted file mode 100644
index b93fcb6..0000000
--- a/src/newscatcher/search/types/search_get_request_sort_by.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SearchGetRequestSortBy = typing.Union[typing.Literal["relevancy", "date", "rank"], typing.Any]
diff --git a/src/newscatcher/search_link/__init__.py b/src/newscatcher/search_by_link/__init__.py
similarity index 100%
rename from src/newscatcher/search_link/__init__.py
rename to src/newscatcher/search_by_link/__init__.py
diff --git a/src/newscatcher/search_link/client.py b/src/newscatcher/search_by_link/client.py
similarity index 73%
rename from src/newscatcher/search_link/client.py
rename to src/newscatcher/search_by_link/client.py
index e0ad325..2c2e184 100644
--- a/src/newscatcher/search_link/client.py
+++ b/src/newscatcher/search_by_link/client.py
@@ -12,37 +12,37 @@
 from ..types.robots_compliant import RobotsCompliant
 from ..types.search_response_dto import SearchResponseDto
 from ..types.to import To
-from .raw_client import AsyncRawSearchLinkClient, RawSearchLinkClient
+from .raw_client import AsyncRawSearchByLinkClient, RawSearchByLinkClient
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
 
 
-class SearchLinkClient:
+class SearchByLinkClient:
     def __init__(self, *, client_wrapper: SyncClientWrapper):
-        self._raw_client = RawSearchLinkClient(client_wrapper=client_wrapper)
+        self._raw_client = RawSearchByLinkClient(client_wrapper=client_wrapper)
 
     @property
-    def with_raw_response(self) -> RawSearchLinkClient:
+    def with_raw_response(self) -> RawSearchByLinkClient:
         """
         Retrieves a raw implementation of this client that returns raw responses.
 
         Returns
         -------
-        RawSearchLinkClient
+        RawSearchByLinkClient
         """
         return self._raw_client
 
-    def search_url_get(
+    def search_by_link_get(
         self,
         *,
         ids: typing.Optional[str] = None,
         links: typing.Optional[str] = None,
         from_: typing.Optional[From] = None,
         to: typing.Optional[To] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SearchResponseDto:
         """
@@ -53,31 +53,22 @@ def search_url_get(
         ids : typing.Optional[str]
             The Newscatcher article ID (corresponds to the `_id` field in API response) or a list of article IDs to search for. To specify multiple IDs, use a comma-separated string.
 
-            Example: `"1234567890abcdef, abcdef1234567890"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         links : typing.Optional[str]
             The article link or list of article links to search for. To specify multiple links, use a comma-separated string.
 
-            Example: `"https://example.com/article1, https://example.com/article2"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         from_ : typing.Optional[From]
 
         to : typing.Optional[To]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -96,16 +87,21 @@ def search_url_get(
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
-        client.search_link.search_url_get(
+        client.search_by_link.search_by_link_get(
+            ids="5f8d0d55b6e45e00179c6e7e",
+            links="https://nytimes.com/article1,https://bbc.com/article2",
             from_=datetime.datetime.fromisoformat(
                 "2024-07-01 00:00:00+00:00",
             ),
             to=datetime.datetime.fromisoformat(
                 "2024-01-01 00:00:00+00:00",
             ),
+            page=2,
+            page_size=50,
+            robots_compliant=True,
         )
         """
-        _response = self._raw_client.search_url_get(
+        _response = self._raw_client.search_by_link_get(
             ids=ids,
             links=links,
             from_=from_,
@@ -117,7 +113,7 @@ def search_url_get(
         )
         return _response.data
 
-    def search_url_post(
+    def search_by_link_post(
         self,
         *,
         ids: typing.Optional[Ids] = OMIT,
@@ -179,18 +175,11 @@ def search_url_post(
         client = NewscatcherApi(
             api_key="YOUR_API_KEY",
         )
-        client.search_link.search_url_post(
-            ids=[
-                "8ea8a784568ffaa05cb6d1ab2d2e84dd",
-                "0146a551ef05ab1c494a55e806e3ce64",
-            ],
-            links=[
-                "https://www.nytimes.com/2024/08/30/technology/ai-chatbot-chatgpt-manipulation.html",
-                "https://www.bbc.com/news/articles/c39k379grzlo",
-            ],
+        client.search_by_link.search_by_link_post(
+            links="https://www.reuters.com/business/energy/oil-prices-up-after-israeli-attacks-oversupply-caps-gains-2025-09-10/",
         )
         """
-        _response = self._raw_client.search_url_post(
+        _response = self._raw_client.search_by_link_post(
             ids=ids,
             links=links,
             from_=from_,
@@ -203,31 +192,31 @@ def search_url_post(
         return _response.data
 
 
-class AsyncSearchLinkClient:
+class AsyncSearchByLinkClient:
     def __init__(self, *, client_wrapper: AsyncClientWrapper):
-        self._raw_client = AsyncRawSearchLinkClient(client_wrapper=client_wrapper)
+        self._raw_client = AsyncRawSearchByLinkClient(client_wrapper=client_wrapper)
 
     @property
-    def with_raw_response(self) -> AsyncRawSearchLinkClient:
+    def with_raw_response(self) -> AsyncRawSearchByLinkClient:
         """
         Retrieves a raw implementation of this client that returns raw responses.
 
         Returns
         -------
-        AsyncRawSearchLinkClient
+        AsyncRawSearchByLinkClient
         """
         return self._raw_client
 
-    async def search_url_get(
+    async def search_by_link_get(
         self,
         *,
         ids: typing.Optional[str] = None,
         links: typing.Optional[str] = None,
         from_: typing.Optional[From] = None,
         to: typing.Optional[To] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SearchResponseDto:
         """
@@ -238,31 +227,22 @@ async def search_url_get(
         ids : typing.Optional[str]
             The Newscatcher article ID (corresponds to the `_id` field in API response) or a list of article IDs to search for. To specify multiple IDs, use a comma-separated string.
 
-            Example: `"1234567890abcdef, abcdef1234567890"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         links : typing.Optional[str]
             The article link or list of article links to search for. To specify multiple links, use a comma-separated string.
 
-            Example: `"https://example.com/article1, https://example.com/article2"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         from_ : typing.Optional[From]
 
         to : typing.Optional[To]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -285,19 +265,24 @@ async def search_url_get(
 
 
         async def main() -> None:
-            await client.search_link.search_url_get(
+            await client.search_by_link.search_by_link_get(
+                ids="5f8d0d55b6e45e00179c6e7e",
+                links="https://nytimes.com/article1,https://bbc.com/article2",
                 from_=datetime.datetime.fromisoformat(
                     "2024-07-01 00:00:00+00:00",
                 ),
                 to=datetime.datetime.fromisoformat(
                     "2024-01-01 00:00:00+00:00",
                 ),
+                page=2,
+                page_size=50,
+                robots_compliant=True,
             )
 
 
         asyncio.run(main())
         """
-        _response = await self._raw_client.search_url_get(
+        _response = await self._raw_client.search_by_link_get(
             ids=ids,
             links=links,
             from_=from_,
@@ -309,7 +294,7 @@ async def main() -> None:
         )
         return _response.data
 
-    async def search_url_post(
+    async def search_by_link_post(
         self,
         *,
         ids: typing.Optional[Ids] = OMIT,
@@ -376,21 +361,14 @@ async def search_url_post(
 
 
         async def main() -> None:
-            await client.search_link.search_url_post(
-                ids=[
-                    "8ea8a784568ffaa05cb6d1ab2d2e84dd",
-                    "0146a551ef05ab1c494a55e806e3ce64",
-                ],
-                links=[
-                    "https://www.nytimes.com/2024/08/30/technology/ai-chatbot-chatgpt-manipulation.html",
-                    "https://www.bbc.com/news/articles/c39k379grzlo",
-                ],
+            await client.search_by_link.search_by_link_post(
+                links="https://www.reuters.com/business/energy/oil-prices-up-after-israeli-attacks-oversupply-caps-gains-2025-09-10/",
             )
 
 
         asyncio.run(main())
         """
-        _response = await self._raw_client.search_url_post(
+        _response = await self._raw_client.search_by_link_post(
             ids=ids,
             links=links,
             from_=from_,
diff --git a/src/newscatcher/search_link/raw_client.py b/src/newscatcher/search_by_link/raw_client.py
similarity index 92%
rename from src/newscatcher/search_link/raw_client.py
rename to src/newscatcher/search_by_link/raw_client.py
index 9823286..f0751d8 100644
--- a/src/newscatcher/search_link/raw_client.py
+++ b/src/newscatcher/search_by_link/raw_client.py
@@ -6,6 +6,7 @@
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..core.serialization import convert_and_respect_annotation_metadata
@@ -25,25 +26,26 @@
 from ..types.robots_compliant import RobotsCompliant
 from ..types.search_response_dto import SearchResponseDto
 from ..types.to import To
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
 
 
-class RawSearchLinkClient:
+class RawSearchByLinkClient:
     def __init__(self, *, client_wrapper: SyncClientWrapper):
         self._client_wrapper = client_wrapper
 
-    def search_url_get(
+    def search_by_link_get(
         self,
         *,
         ids: typing.Optional[str] = None,
         links: typing.Optional[str] = None,
         from_: typing.Optional[From] = None,
         to: typing.Optional[To] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[SearchResponseDto]:
         """
@@ -54,31 +56,22 @@ def search_url_get(
         ids : typing.Optional[str]
             The Newscatcher article ID (corresponds to the `_id` field in API response) or a list of article IDs to search for. To specify multiple IDs, use a comma-separated string.
 
-            Example: `"1234567890abcdef, abcdef1234567890"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         links : typing.Optional[str]
             The article link or list of article links to search for. To specify multiple links, use a comma-separated string.
 
-            Example: `"https://example.com/article1, https://example.com/article2"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         from_ : typing.Optional[From]
 
         to : typing.Optional[To]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -192,9 +185,13 @@ def search_url_get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
-    def search_url_post(
+    def search_by_link_post(
         self,
         *,
         ids: typing.Optional[Ids] = OMIT,
@@ -357,23 +354,27 @@ def search_url_post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
-class AsyncRawSearchLinkClient:
+class AsyncRawSearchByLinkClient:
     def __init__(self, *, client_wrapper: AsyncClientWrapper):
         self._client_wrapper = client_wrapper
 
-    async def search_url_get(
+    async def search_by_link_get(
         self,
         *,
         ids: typing.Optional[str] = None,
         links: typing.Optional[str] = None,
         from_: typing.Optional[From] = None,
         to: typing.Optional[To] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        robots_compliant: typing.Optional[bool] = None,
+        page: typing.Optional[Page] = None,
+        page_size: typing.Optional[PageSize] = None,
+        robots_compliant: typing.Optional[RobotsCompliant] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[SearchResponseDto]:
         """
@@ -384,31 +385,22 @@ async def search_url_get(
         ids : typing.Optional[str]
             The Newscatcher article ID (corresponds to the `_id` field in API response) or a list of article IDs to search for. To specify multiple IDs, use a comma-separated string.
 
-            Example: `"1234567890abcdef, abcdef1234567890"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         links : typing.Optional[str]
             The article link or list of article links to search for. To specify multiple links, use a comma-separated string.
 
-            Example: `"https://example.com/article1, https://example.com/article2"`
-
             **Caution**: You can use either the `links` or the `ids` parameter, but not both at the same time.
 
         from_ : typing.Optional[From]
 
         to : typing.Optional[To]
 
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
+        page : typing.Optional[Page]
 
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
+        page_size : typing.Optional[PageSize]
 
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
+        robots_compliant : typing.Optional[RobotsCompliant]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -522,9 +514,13 @@ async def search_url_get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
-    async def search_url_post(
+    async def search_by_link_post(
         self,
         *,
         ids: typing.Optional[Ids] = OMIT,
@@ -687,4 +683,8 @@ async def search_url_post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/searchsimilar/__init__.py b/src/newscatcher/searchsimilar/__init__.py
deleted file mode 100644
index da93e88..0000000
--- a/src/newscatcher/searchsimilar/__init__.py
+++ /dev/null
@@ -1,17 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-# isort: skip_file
-
-from .types import (
-    SearchSimilarGetRequestPublishedDatePrecision,
-    SearchSimilarGetRequestSortBy,
-    SearchSimilarGetResponse,
-    SearchSimilarPostResponse,
-)
-
-__all__ = [
-    "SearchSimilarGetRequestPublishedDatePrecision",
-    "SearchSimilarGetRequestSortBy",
-    "SearchSimilarGetResponse",
-    "SearchSimilarPostResponse",
-]
diff --git a/src/newscatcher/searchsimilar/client.py b/src/newscatcher/searchsimilar/client.py
deleted file mode 100644
index e5659d4..0000000
--- a/src/newscatcher/searchsimilar/client.py
+++ /dev/null
@@ -1,1360 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import datetime as dt
-import typing
-
-from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
-from ..core.request_options import RequestOptions
-from ..types.all_domain_links import AllDomainLinks
-from ..types.all_links import AllLinks
-from ..types.by_parse_date import ByParseDate
-from ..types.content_sentiment_max import ContentSentimentMax
-from ..types.content_sentiment_min import ContentSentimentMin
-from ..types.countries import Countries
-from ..types.custom_tags import CustomTags
-from ..types.from_ import From
-from ..types.from_rank import FromRank
-from ..types.has_nlp import HasNlp
-from ..types.include_nlp_data import IncludeNlpData
-from ..types.include_similar_documents import IncludeSimilarDocuments
-from ..types.include_translation_fields import IncludeTranslationFields
-from ..types.iptc_tags import IptcTags
-from ..types.is_headline import IsHeadline
-from ..types.is_opinion import IsOpinion
-from ..types.is_paid_content import IsPaidContent
-from ..types.lang import Lang
-from ..types.ner_name import NerName
-from ..types.not_countries import NotCountries
-from ..types.not_iptc_tags import NotIptcTags
-from ..types.not_lang import NotLang
-from ..types.not_sources import NotSources
-from ..types.not_theme import NotTheme
-from ..types.page import Page
-from ..types.page_size import PageSize
-from ..types.parent_url import ParentUrl
-from ..types.predefined_sources import PredefinedSources
-from ..types.published_date_precision import PublishedDatePrecision
-from ..types.q import Q
-from ..types.ranked_only import RankedOnly
-from ..types.robots_compliant import RobotsCompliant
-from ..types.search_in import SearchIn
-from ..types.similar_documents_fields import SimilarDocumentsFields
-from ..types.similar_documents_number import SimilarDocumentsNumber
-from ..types.sort_by import SortBy
-from ..types.sources import Sources
-from ..types.theme import Theme
-from ..types.title_sentiment_max import TitleSentimentMax
-from ..types.title_sentiment_min import TitleSentimentMin
-from ..types.to import To
-from ..types.to_rank import ToRank
-from ..types.word_count_max import WordCountMax
-from ..types.word_count_min import WordCountMin
-from .raw_client import AsyncRawSearchsimilarClient, RawSearchsimilarClient
-from .types.search_similar_get_request_published_date_precision import SearchSimilarGetRequestPublishedDatePrecision
-from .types.search_similar_get_request_sort_by import SearchSimilarGetRequestSortBy
-from .types.search_similar_get_response import SearchSimilarGetResponse
-from .types.search_similar_post_response import SearchSimilarPostResponse
-
-# this is used as the default value for optional parameters
-OMIT = typing.cast(typing.Any, ...)
-
-
-class SearchsimilarClient:
-    def __init__(self, *, client_wrapper: SyncClientWrapper):
-        self._raw_client = RawSearchsimilarClient(client_wrapper=client_wrapper)
-
-    @property
-    def with_raw_response(self) -> RawSearchsimilarClient:
-        """
-        Retrieves a raw implementation of this client that returns raw responses.
-
-        Returns
-        -------
-        RawSearchsimilarClient
-        """
-        return self._raw_client
-
-    def get(
-        self,
-        *,
-        q: str,
-        search_in: typing.Optional[SearchIn] = None,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
-        include_similar_documents: typing.Optional[bool] = None,
-        similar_documents_number: typing.Optional[int] = None,
-        similar_documents_fields: typing.Optional[str] = None,
-        predefined_sources: typing.Optional[str] = None,
-        sources: typing.Optional[str] = None,
-        not_sources: typing.Optional[str] = None,
-        lang: typing.Optional[str] = None,
-        not_lang: typing.Optional[str] = None,
-        countries: typing.Optional[str] = None,
-        not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        published_date_precision: typing.Optional[SearchSimilarGetRequestPublishedDatePrecision] = None,
-        sort_by: typing.Optional[SearchSimilarGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
-        parent_url: typing.Optional[str] = None,
-        all_links: typing.Optional[str] = None,
-        all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        include_nlp_data: typing.Optional[IncludeNlpData] = None,
-        has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        iptc_tags: typing.Optional[str] = None,
-        not_iptc_tags: typing.Optional[str] = None,
-        custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> SearchSimilarGetResponse:
-        """
-        Searches for articles similar to a specified query.
-
-        Parameters
-        ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[bool]
-            If true, includes similar documents in the response.
-
-        similar_documents_number : typing.Optional[int]
-            The number of similar documents to return.
-
-        similar_documents_fields : typing.Optional[str]
-            The fields to consider for finding similar documents.
-
-        predefined_sources : typing.Optional[str]
-            Predefined top news sources per country.
-
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
-
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
-
-        sources : typing.Optional[str]
-            One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
-        not_sources : typing.Optional[str]
-            The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
-
-            Example: `"cnn.com, wsj.com"`
-
-        lang : typing.Optional[str]
-            The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
-
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        not_lang : typing.Optional[str]
-            The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
-
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        countries : typing.Optional[str]
-            The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
-
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        not_countries : typing.Optional[str]
-            The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
-
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
-
-        published_date_precision : typing.Optional[SearchSimilarGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
-
-        sort_by : typing.Optional[SearchSimilarGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
-
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
-
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
-
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
-
-        parent_url : typing.Optional[str]
-            The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
-        all_links : typing.Optional[str]
-            The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
-
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        all_domain_links : typing.Optional[str]
-            The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
-
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
-
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        iptc_tags : typing.Optional[str]
-            Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
-
-            Example: `"20000199, 20000209"`
-
-            **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        not_iptc_tags : typing.Optional[str]
-            Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
-
-            Example: `"20000205, 20000209"`
-
-            **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        custom_tags : typing.Optional[str]
-            Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
-
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
-
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
-
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        SearchSimilarGetResponse
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-
-        Examples
-        --------
-        import datetime
-
-        from newscatcher import NewscatcherApi
-
-        client = NewscatcherApi(
-            api_key="YOUR_API_KEY",
-        )
-        client.searchsimilar.get(
-            q="technology AND (Apple OR Microsoft) NOT Google",
-            search_in="title_content, title_content_translated",
-            include_translation_fields=True,
-            similar_documents_fields="title,summary",
-            predefined_sources="top 100 US, top 5 GB",
-            from_=datetime.datetime.fromisoformat(
-                "2024-07-01 00:00:00+00:00",
-            ),
-            to=datetime.datetime.fromisoformat(
-                "2024-07-01 00:00:00+00:00",
-            ),
-            include_nlp_data=True,
-            has_nlp=True,
-            theme="Business,Finance",
-            not_theme="Crime",
-            ner_name="Tesla",
-            iptc_tags="20000199,20000209",
-            not_iptc_tags="20000205,20000209",
-            custom_tags="Tag1,Tag2,Tag3",
-        )
-        """
-        _response = self._raw_client.get(
-            q=q,
-            search_in=search_in,
-            include_translation_fields=include_translation_fields,
-            include_similar_documents=include_similar_documents,
-            similar_documents_number=similar_documents_number,
-            similar_documents_fields=similar_documents_fields,
-            predefined_sources=predefined_sources,
-            sources=sources,
-            not_sources=not_sources,
-            lang=lang,
-            not_lang=not_lang,
-            countries=countries,
-            not_countries=not_countries,
-            from_=from_,
-            to=to,
-            by_parse_date=by_parse_date,
-            published_date_precision=published_date_precision,
-            sort_by=sort_by,
-            ranked_only=ranked_only,
-            from_rank=from_rank,
-            to_rank=to_rank,
-            is_headline=is_headline,
-            is_opinion=is_opinion,
-            is_paid_content=is_paid_content,
-            parent_url=parent_url,
-            all_links=all_links,
-            all_domain_links=all_domain_links,
-            word_count_min=word_count_min,
-            word_count_max=word_count_max,
-            page=page,
-            page_size=page_size,
-            include_nlp_data=include_nlp_data,
-            has_nlp=has_nlp,
-            theme=theme,
-            not_theme=not_theme,
-            ner_name=ner_name,
-            title_sentiment_min=title_sentiment_min,
-            title_sentiment_max=title_sentiment_max,
-            content_sentiment_min=content_sentiment_min,
-            content_sentiment_max=content_sentiment_max,
-            iptc_tags=iptc_tags,
-            not_iptc_tags=not_iptc_tags,
-            custom_tags=custom_tags,
-            robots_compliant=robots_compliant,
-            request_options=request_options,
-        )
-        return _response.data
-
-    def post(
-        self,
-        *,
-        q: Q,
-        search_in: typing.Optional[SearchIn] = OMIT,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = OMIT,
-        include_similar_documents: typing.Optional[IncludeSimilarDocuments] = OMIT,
-        similar_documents_number: typing.Optional[SimilarDocumentsNumber] = OMIT,
-        similar_documents_fields: typing.Optional[SimilarDocumentsFields] = OMIT,
-        predefined_sources: typing.Optional[PredefinedSources] = OMIT,
-        sources: typing.Optional[Sources] = OMIT,
-        not_sources: typing.Optional[NotSources] = OMIT,
-        lang: typing.Optional[Lang] = OMIT,
-        not_lang: typing.Optional[NotLang] = OMIT,
-        countries: typing.Optional[Countries] = OMIT,
-        not_countries: typing.Optional[NotCountries] = OMIT,
-        from_: typing.Optional[From] = OMIT,
-        to: typing.Optional[To] = OMIT,
-        by_parse_date: typing.Optional[ByParseDate] = OMIT,
-        published_date_precision: typing.Optional[PublishedDatePrecision] = OMIT,
-        sort_by: typing.Optional[SortBy] = OMIT,
-        ranked_only: typing.Optional[RankedOnly] = OMIT,
-        from_rank: typing.Optional[FromRank] = OMIT,
-        to_rank: typing.Optional[ToRank] = OMIT,
-        is_headline: typing.Optional[IsHeadline] = OMIT,
-        is_opinion: typing.Optional[IsOpinion] = OMIT,
-        is_paid_content: typing.Optional[IsPaidContent] = OMIT,
-        parent_url: typing.Optional[ParentUrl] = OMIT,
-        all_links: typing.Optional[AllLinks] = OMIT,
-        all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
-        word_count_min: typing.Optional[WordCountMin] = OMIT,
-        word_count_max: typing.Optional[WordCountMax] = OMIT,
-        page: typing.Optional[Page] = OMIT,
-        page_size: typing.Optional[PageSize] = OMIT,
-        include_nlp_data: typing.Optional[IncludeNlpData] = OMIT,
-        has_nlp: typing.Optional[HasNlp] = OMIT,
-        theme: typing.Optional[Theme] = OMIT,
-        not_theme: typing.Optional[NotTheme] = OMIT,
-        ner_name: typing.Optional[NerName] = OMIT,
-        title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
-        title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
-        content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
-        iptc_tags: typing.Optional[IptcTags] = OMIT,
-        not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
-        custom_tags: typing.Optional[CustomTags] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> SearchSimilarPostResponse:
-        """
-        Searches for articles similar to the specified query. You can filter results by language, country, source, and more.
-
-        Parameters
-        ----------
-        q : Q
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[IncludeSimilarDocuments]
-
-        similar_documents_number : typing.Optional[SimilarDocumentsNumber]
-
-        similar_documents_fields : typing.Optional[SimilarDocumentsFields]
-
-        predefined_sources : typing.Optional[PredefinedSources]
-
-        sources : typing.Optional[Sources]
-
-        not_sources : typing.Optional[NotSources]
-
-        lang : typing.Optional[Lang]
-
-        not_lang : typing.Optional[NotLang]
-
-        countries : typing.Optional[Countries]
-
-        not_countries : typing.Optional[NotCountries]
-
-        from_ : typing.Optional[From]
-
-        to : typing.Optional[To]
-
-        by_parse_date : typing.Optional[ByParseDate]
-
-        published_date_precision : typing.Optional[PublishedDatePrecision]
-
-        sort_by : typing.Optional[SortBy]
-
-        ranked_only : typing.Optional[RankedOnly]
-
-        from_rank : typing.Optional[FromRank]
-
-        to_rank : typing.Optional[ToRank]
-
-        is_headline : typing.Optional[IsHeadline]
-
-        is_opinion : typing.Optional[IsOpinion]
-
-        is_paid_content : typing.Optional[IsPaidContent]
-
-        parent_url : typing.Optional[ParentUrl]
-
-        all_links : typing.Optional[AllLinks]
-
-        all_domain_links : typing.Optional[AllDomainLinks]
-
-        word_count_min : typing.Optional[WordCountMin]
-
-        word_count_max : typing.Optional[WordCountMax]
-
-        page : typing.Optional[Page]
-
-        page_size : typing.Optional[PageSize]
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[Theme]
-
-        not_theme : typing.Optional[NotTheme]
-
-        ner_name : typing.Optional[NerName]
-
-        title_sentiment_min : typing.Optional[TitleSentimentMin]
-
-        title_sentiment_max : typing.Optional[TitleSentimentMax]
-
-        content_sentiment_min : typing.Optional[ContentSentimentMin]
-
-        content_sentiment_max : typing.Optional[ContentSentimentMax]
-
-        iptc_tags : typing.Optional[IptcTags]
-
-        not_iptc_tags : typing.Optional[NotIptcTags]
-
-        custom_tags : typing.Optional[CustomTags]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        SearchSimilarPostResponse
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-
-        Examples
-        --------
-        from newscatcher import NewscatcherApi
-
-        client = NewscatcherApi(
-            api_key="YOUR_API_KEY",
-        )
-        client.searchsimilar.post(
-            q="artificial intelligence",
-            include_similar_documents=True,
-            similar_documents_number=5,
-        )
-        """
-        _response = self._raw_client.post(
-            q=q,
-            search_in=search_in,
-            include_translation_fields=include_translation_fields,
-            include_similar_documents=include_similar_documents,
-            similar_documents_number=similar_documents_number,
-            similar_documents_fields=similar_documents_fields,
-            predefined_sources=predefined_sources,
-            sources=sources,
-            not_sources=not_sources,
-            lang=lang,
-            not_lang=not_lang,
-            countries=countries,
-            not_countries=not_countries,
-            from_=from_,
-            to=to,
-            by_parse_date=by_parse_date,
-            published_date_precision=published_date_precision,
-            sort_by=sort_by,
-            ranked_only=ranked_only,
-            from_rank=from_rank,
-            to_rank=to_rank,
-            is_headline=is_headline,
-            is_opinion=is_opinion,
-            is_paid_content=is_paid_content,
-            parent_url=parent_url,
-            all_links=all_links,
-            all_domain_links=all_domain_links,
-            word_count_min=word_count_min,
-            word_count_max=word_count_max,
-            page=page,
-            page_size=page_size,
-            include_nlp_data=include_nlp_data,
-            has_nlp=has_nlp,
-            theme=theme,
-            not_theme=not_theme,
-            ner_name=ner_name,
-            title_sentiment_min=title_sentiment_min,
-            title_sentiment_max=title_sentiment_max,
-            content_sentiment_min=content_sentiment_min,
-            content_sentiment_max=content_sentiment_max,
-            iptc_tags=iptc_tags,
-            not_iptc_tags=not_iptc_tags,
-            custom_tags=custom_tags,
-            robots_compliant=robots_compliant,
-            request_options=request_options,
-        )
-        return _response.data
-
-
-class AsyncSearchsimilarClient:
-    def __init__(self, *, client_wrapper: AsyncClientWrapper):
-        self._raw_client = AsyncRawSearchsimilarClient(client_wrapper=client_wrapper)
-
-    @property
-    def with_raw_response(self) -> AsyncRawSearchsimilarClient:
-        """
-        Retrieves a raw implementation of this client that returns raw responses.
-
-        Returns
-        -------
-        AsyncRawSearchsimilarClient
-        """
-        return self._raw_client
-
-    async def get(
-        self,
-        *,
-        q: str,
-        search_in: typing.Optional[SearchIn] = None,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
-        include_similar_documents: typing.Optional[bool] = None,
-        similar_documents_number: typing.Optional[int] = None,
-        similar_documents_fields: typing.Optional[str] = None,
-        predefined_sources: typing.Optional[str] = None,
-        sources: typing.Optional[str] = None,
-        not_sources: typing.Optional[str] = None,
-        lang: typing.Optional[str] = None,
-        not_lang: typing.Optional[str] = None,
-        countries: typing.Optional[str] = None,
-        not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        published_date_precision: typing.Optional[SearchSimilarGetRequestPublishedDatePrecision] = None,
-        sort_by: typing.Optional[SearchSimilarGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
-        parent_url: typing.Optional[str] = None,
-        all_links: typing.Optional[str] = None,
-        all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        include_nlp_data: typing.Optional[IncludeNlpData] = None,
-        has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        iptc_tags: typing.Optional[str] = None,
-        not_iptc_tags: typing.Optional[str] = None,
-        custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> SearchSimilarGetResponse:
-        """
-        Searches for articles similar to a specified query.
-
-        Parameters
-        ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[bool]
-            If true, includes similar documents in the response.
-
-        similar_documents_number : typing.Optional[int]
-            The number of similar documents to return.
-
-        similar_documents_fields : typing.Optional[str]
-            The fields to consider for finding similar documents.
-
-        predefined_sources : typing.Optional[str]
-            Predefined top news sources per country.
-
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
-
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
-
-        sources : typing.Optional[str]
-            One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
-        not_sources : typing.Optional[str]
-            The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
-
-            Example: `"cnn.com, wsj.com"`
-
-        lang : typing.Optional[str]
-            The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
-
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        not_lang : typing.Optional[str]
-            The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
-
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        countries : typing.Optional[str]
-            The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
-
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        not_countries : typing.Optional[str]
-            The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
-
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
-
-        published_date_precision : typing.Optional[SearchSimilarGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
-
-        sort_by : typing.Optional[SearchSimilarGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
-
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
-
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
-
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
-
-        parent_url : typing.Optional[str]
-            The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
-        all_links : typing.Optional[str]
-            The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
-
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        all_domain_links : typing.Optional[str]
-            The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
-
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
-
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        iptc_tags : typing.Optional[str]
-            Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
-
-            Example: `"20000199, 20000209"`
-
-            **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        not_iptc_tags : typing.Optional[str]
-            Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
-
-            Example: `"20000205, 20000209"`
-
-            **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        custom_tags : typing.Optional[str]
-            Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
-
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
-
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
-
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        SearchSimilarGetResponse
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-
-        Examples
-        --------
-        import asyncio
-        import datetime
-
-        from newscatcher import AsyncNewscatcherApi
-
-        client = AsyncNewscatcherApi(
-            api_key="YOUR_API_KEY",
-        )
-
-
-        async def main() -> None:
-            await client.searchsimilar.get(
-                q="technology AND (Apple OR Microsoft) NOT Google",
-                search_in="title_content, title_content_translated",
-                include_translation_fields=True,
-                similar_documents_fields="title,summary",
-                predefined_sources="top 100 US, top 5 GB",
-                from_=datetime.datetime.fromisoformat(
-                    "2024-07-01 00:00:00+00:00",
-                ),
-                to=datetime.datetime.fromisoformat(
-                    "2024-07-01 00:00:00+00:00",
-                ),
-                include_nlp_data=True,
-                has_nlp=True,
-                theme="Business,Finance",
-                not_theme="Crime",
-                ner_name="Tesla",
-                iptc_tags="20000199,20000209",
-                not_iptc_tags="20000205,20000209",
-                custom_tags="Tag1,Tag2,Tag3",
-            )
-
-
-        asyncio.run(main())
-        """
-        _response = await self._raw_client.get(
-            q=q,
-            search_in=search_in,
-            include_translation_fields=include_translation_fields,
-            include_similar_documents=include_similar_documents,
-            similar_documents_number=similar_documents_number,
-            similar_documents_fields=similar_documents_fields,
-            predefined_sources=predefined_sources,
-            sources=sources,
-            not_sources=not_sources,
-            lang=lang,
-            not_lang=not_lang,
-            countries=countries,
-            not_countries=not_countries,
-            from_=from_,
-            to=to,
-            by_parse_date=by_parse_date,
-            published_date_precision=published_date_precision,
-            sort_by=sort_by,
-            ranked_only=ranked_only,
-            from_rank=from_rank,
-            to_rank=to_rank,
-            is_headline=is_headline,
-            is_opinion=is_opinion,
-            is_paid_content=is_paid_content,
-            parent_url=parent_url,
-            all_links=all_links,
-            all_domain_links=all_domain_links,
-            word_count_min=word_count_min,
-            word_count_max=word_count_max,
-            page=page,
-            page_size=page_size,
-            include_nlp_data=include_nlp_data,
-            has_nlp=has_nlp,
-            theme=theme,
-            not_theme=not_theme,
-            ner_name=ner_name,
-            title_sentiment_min=title_sentiment_min,
-            title_sentiment_max=title_sentiment_max,
-            content_sentiment_min=content_sentiment_min,
-            content_sentiment_max=content_sentiment_max,
-            iptc_tags=iptc_tags,
-            not_iptc_tags=not_iptc_tags,
-            custom_tags=custom_tags,
-            robots_compliant=robots_compliant,
-            request_options=request_options,
-        )
-        return _response.data
-
-    async def post(
-        self,
-        *,
-        q: Q,
-        search_in: typing.Optional[SearchIn] = OMIT,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = OMIT,
-        include_similar_documents: typing.Optional[IncludeSimilarDocuments] = OMIT,
-        similar_documents_number: typing.Optional[SimilarDocumentsNumber] = OMIT,
-        similar_documents_fields: typing.Optional[SimilarDocumentsFields] = OMIT,
-        predefined_sources: typing.Optional[PredefinedSources] = OMIT,
-        sources: typing.Optional[Sources] = OMIT,
-        not_sources: typing.Optional[NotSources] = OMIT,
-        lang: typing.Optional[Lang] = OMIT,
-        not_lang: typing.Optional[NotLang] = OMIT,
-        countries: typing.Optional[Countries] = OMIT,
-        not_countries: typing.Optional[NotCountries] = OMIT,
-        from_: typing.Optional[From] = OMIT,
-        to: typing.Optional[To] = OMIT,
-        by_parse_date: typing.Optional[ByParseDate] = OMIT,
-        published_date_precision: typing.Optional[PublishedDatePrecision] = OMIT,
-        sort_by: typing.Optional[SortBy] = OMIT,
-        ranked_only: typing.Optional[RankedOnly] = OMIT,
-        from_rank: typing.Optional[FromRank] = OMIT,
-        to_rank: typing.Optional[ToRank] = OMIT,
-        is_headline: typing.Optional[IsHeadline] = OMIT,
-        is_opinion: typing.Optional[IsOpinion] = OMIT,
-        is_paid_content: typing.Optional[IsPaidContent] = OMIT,
-        parent_url: typing.Optional[ParentUrl] = OMIT,
-        all_links: typing.Optional[AllLinks] = OMIT,
-        all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
-        word_count_min: typing.Optional[WordCountMin] = OMIT,
-        word_count_max: typing.Optional[WordCountMax] = OMIT,
-        page: typing.Optional[Page] = OMIT,
-        page_size: typing.Optional[PageSize] = OMIT,
-        include_nlp_data: typing.Optional[IncludeNlpData] = OMIT,
-        has_nlp: typing.Optional[HasNlp] = OMIT,
-        theme: typing.Optional[Theme] = OMIT,
-        not_theme: typing.Optional[NotTheme] = OMIT,
-        ner_name: typing.Optional[NerName] = OMIT,
-        title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
-        title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
-        content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
-        iptc_tags: typing.Optional[IptcTags] = OMIT,
-        not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
-        custom_tags: typing.Optional[CustomTags] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> SearchSimilarPostResponse:
-        """
-        Searches for articles similar to the specified query. You can filter results by language, country, source, and more.
-
-        Parameters
-        ----------
-        q : Q
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[IncludeSimilarDocuments]
-
-        similar_documents_number : typing.Optional[SimilarDocumentsNumber]
-
-        similar_documents_fields : typing.Optional[SimilarDocumentsFields]
-
-        predefined_sources : typing.Optional[PredefinedSources]
-
-        sources : typing.Optional[Sources]
-
-        not_sources : typing.Optional[NotSources]
-
-        lang : typing.Optional[Lang]
-
-        not_lang : typing.Optional[NotLang]
-
-        countries : typing.Optional[Countries]
-
-        not_countries : typing.Optional[NotCountries]
-
-        from_ : typing.Optional[From]
-
-        to : typing.Optional[To]
-
-        by_parse_date : typing.Optional[ByParseDate]
-
-        published_date_precision : typing.Optional[PublishedDatePrecision]
-
-        sort_by : typing.Optional[SortBy]
-
-        ranked_only : typing.Optional[RankedOnly]
-
-        from_rank : typing.Optional[FromRank]
-
-        to_rank : typing.Optional[ToRank]
-
-        is_headline : typing.Optional[IsHeadline]
-
-        is_opinion : typing.Optional[IsOpinion]
-
-        is_paid_content : typing.Optional[IsPaidContent]
-
-        parent_url : typing.Optional[ParentUrl]
-
-        all_links : typing.Optional[AllLinks]
-
-        all_domain_links : typing.Optional[AllDomainLinks]
-
-        word_count_min : typing.Optional[WordCountMin]
-
-        word_count_max : typing.Optional[WordCountMax]
-
-        page : typing.Optional[Page]
-
-        page_size : typing.Optional[PageSize]
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[Theme]
-
-        not_theme : typing.Optional[NotTheme]
-
-        ner_name : typing.Optional[NerName]
-
-        title_sentiment_min : typing.Optional[TitleSentimentMin]
-
-        title_sentiment_max : typing.Optional[TitleSentimentMax]
-
-        content_sentiment_min : typing.Optional[ContentSentimentMin]
-
-        content_sentiment_max : typing.Optional[ContentSentimentMax]
-
-        iptc_tags : typing.Optional[IptcTags]
-
-        not_iptc_tags : typing.Optional[NotIptcTags]
-
-        custom_tags : typing.Optional[CustomTags]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        SearchSimilarPostResponse
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-
-        Examples
-        --------
-        import asyncio
-
-        from newscatcher import AsyncNewscatcherApi
-
-        client = AsyncNewscatcherApi(
-            api_key="YOUR_API_KEY",
-        )
-
-
-        async def main() -> None:
-            await client.searchsimilar.post(
-                q="artificial intelligence",
-                include_similar_documents=True,
-                similar_documents_number=5,
-            )
-
-
-        asyncio.run(main())
-        """
-        _response = await self._raw_client.post(
-            q=q,
-            search_in=search_in,
-            include_translation_fields=include_translation_fields,
-            include_similar_documents=include_similar_documents,
-            similar_documents_number=similar_documents_number,
-            similar_documents_fields=similar_documents_fields,
-            predefined_sources=predefined_sources,
-            sources=sources,
-            not_sources=not_sources,
-            lang=lang,
-            not_lang=not_lang,
-            countries=countries,
-            not_countries=not_countries,
-            from_=from_,
-            to=to,
-            by_parse_date=by_parse_date,
-            published_date_precision=published_date_precision,
-            sort_by=sort_by,
-            ranked_only=ranked_only,
-            from_rank=from_rank,
-            to_rank=to_rank,
-            is_headline=is_headline,
-            is_opinion=is_opinion,
-            is_paid_content=is_paid_content,
-            parent_url=parent_url,
-            all_links=all_links,
-            all_domain_links=all_domain_links,
-            word_count_min=word_count_min,
-            word_count_max=word_count_max,
-            page=page,
-            page_size=page_size,
-            include_nlp_data=include_nlp_data,
-            has_nlp=has_nlp,
-            theme=theme,
-            not_theme=not_theme,
-            ner_name=ner_name,
-            title_sentiment_min=title_sentiment_min,
-            title_sentiment_max=title_sentiment_max,
-            content_sentiment_min=content_sentiment_min,
-            content_sentiment_max=content_sentiment_max,
-            iptc_tags=iptc_tags,
-            not_iptc_tags=not_iptc_tags,
-            custom_tags=custom_tags,
-            robots_compliant=robots_compliant,
-            request_options=request_options,
-        )
-        return _response.data
diff --git a/src/newscatcher/searchsimilar/raw_client.py b/src/newscatcher/searchsimilar/raw_client.py
deleted file mode 100644
index 68c4769..0000000
--- a/src/newscatcher/searchsimilar/raw_client.py
+++ /dev/null
@@ -1,1684 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import datetime as dt
-import typing
-from json.decoder import JSONDecodeError
-
-from ..core.api_error import ApiError
-from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
-from ..core.datetime_utils import serialize_datetime
-from ..core.http_response import AsyncHttpResponse, HttpResponse
-from ..core.pydantic_utilities import parse_obj_as
-from ..core.request_options import RequestOptions
-from ..core.serialization import convert_and_respect_annotation_metadata
-from ..errors.bad_request_error import BadRequestError
-from ..errors.forbidden_error import ForbiddenError
-from ..errors.internal_server_error import InternalServerError
-from ..errors.request_timeout_error import RequestTimeoutError
-from ..errors.too_many_requests_error import TooManyRequestsError
-from ..errors.unauthorized_error import UnauthorizedError
-from ..errors.unprocessable_entity_error import UnprocessableEntityError
-from ..types.all_domain_links import AllDomainLinks
-from ..types.all_links import AllLinks
-from ..types.by_parse_date import ByParseDate
-from ..types.content_sentiment_max import ContentSentimentMax
-from ..types.content_sentiment_min import ContentSentimentMin
-from ..types.countries import Countries
-from ..types.custom_tags import CustomTags
-from ..types.error import Error
-from ..types.from_ import From
-from ..types.from_rank import FromRank
-from ..types.has_nlp import HasNlp
-from ..types.include_nlp_data import IncludeNlpData
-from ..types.include_similar_documents import IncludeSimilarDocuments
-from ..types.include_translation_fields import IncludeTranslationFields
-from ..types.iptc_tags import IptcTags
-from ..types.is_headline import IsHeadline
-from ..types.is_opinion import IsOpinion
-from ..types.is_paid_content import IsPaidContent
-from ..types.lang import Lang
-from ..types.ner_name import NerName
-from ..types.not_countries import NotCountries
-from ..types.not_iptc_tags import NotIptcTags
-from ..types.not_lang import NotLang
-from ..types.not_sources import NotSources
-from ..types.not_theme import NotTheme
-from ..types.page import Page
-from ..types.page_size import PageSize
-from ..types.parent_url import ParentUrl
-from ..types.predefined_sources import PredefinedSources
-from ..types.published_date_precision import PublishedDatePrecision
-from ..types.q import Q
-from ..types.ranked_only import RankedOnly
-from ..types.robots_compliant import RobotsCompliant
-from ..types.search_in import SearchIn
-from ..types.similar_documents_fields import SimilarDocumentsFields
-from ..types.similar_documents_number import SimilarDocumentsNumber
-from ..types.sort_by import SortBy
-from ..types.sources import Sources
-from ..types.theme import Theme
-from ..types.title_sentiment_max import TitleSentimentMax
-from ..types.title_sentiment_min import TitleSentimentMin
-from ..types.to import To
-from ..types.to_rank import ToRank
-from ..types.word_count_max import WordCountMax
-from ..types.word_count_min import WordCountMin
-from .types.search_similar_get_request_published_date_precision import SearchSimilarGetRequestPublishedDatePrecision
-from .types.search_similar_get_request_sort_by import SearchSimilarGetRequestSortBy
-from .types.search_similar_get_response import SearchSimilarGetResponse
-from .types.search_similar_post_response import SearchSimilarPostResponse
-
-# this is used as the default value for optional parameters
-OMIT = typing.cast(typing.Any, ...)
-
-
-class RawSearchsimilarClient:
-    def __init__(self, *, client_wrapper: SyncClientWrapper):
-        self._client_wrapper = client_wrapper
-
-    def get(
-        self,
-        *,
-        q: str,
-        search_in: typing.Optional[SearchIn] = None,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
-        include_similar_documents: typing.Optional[bool] = None,
-        similar_documents_number: typing.Optional[int] = None,
-        similar_documents_fields: typing.Optional[str] = None,
-        predefined_sources: typing.Optional[str] = None,
-        sources: typing.Optional[str] = None,
-        not_sources: typing.Optional[str] = None,
-        lang: typing.Optional[str] = None,
-        not_lang: typing.Optional[str] = None,
-        countries: typing.Optional[str] = None,
-        not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        published_date_precision: typing.Optional[SearchSimilarGetRequestPublishedDatePrecision] = None,
-        sort_by: typing.Optional[SearchSimilarGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
-        parent_url: typing.Optional[str] = None,
-        all_links: typing.Optional[str] = None,
-        all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        include_nlp_data: typing.Optional[IncludeNlpData] = None,
-        has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        iptc_tags: typing.Optional[str] = None,
-        not_iptc_tags: typing.Optional[str] = None,
-        custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> HttpResponse[SearchSimilarGetResponse]:
-        """
-        Searches for articles similar to a specified query.
-
-        Parameters
-        ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[bool]
-            If true, includes similar documents in the response.
-
-        similar_documents_number : typing.Optional[int]
-            The number of similar documents to return.
-
-        similar_documents_fields : typing.Optional[str]
-            The fields to consider for finding similar documents.
-
-        predefined_sources : typing.Optional[str]
-            Predefined top news sources per country.
-
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
-
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
-
-        sources : typing.Optional[str]
-            One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
-        not_sources : typing.Optional[str]
-            The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
-
-            Example: `"cnn.com, wsj.com"`
-
-        lang : typing.Optional[str]
-            The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
-
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        not_lang : typing.Optional[str]
-            The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
-
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        countries : typing.Optional[str]
-            The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
-
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        not_countries : typing.Optional[str]
-            The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
-
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
-
-        published_date_precision : typing.Optional[SearchSimilarGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
-
-        sort_by : typing.Optional[SearchSimilarGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
-
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
-
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
-
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
-
-        parent_url : typing.Optional[str]
-            The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
-        all_links : typing.Optional[str]
-            The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
-
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        all_domain_links : typing.Optional[str]
-            The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
-
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
-
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        iptc_tags : typing.Optional[str]
-            Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
-
-            Example: `"20000199, 20000209"`
-
-            **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        not_iptc_tags : typing.Optional[str]
-            Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
-
-            Example: `"20000205, 20000209"`
-
-            **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        custom_tags : typing.Optional[str]
-            Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
-
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
-
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
-
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        HttpResponse[SearchSimilarGetResponse]
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-        """
-        _response = self._client_wrapper.httpx_client.request(
-            "api/search_similar",
-            method="GET",
-            params={
-                "q": q,
-                "search_in": search_in,
-                "include_translation_fields": include_translation_fields,
-                "include_similar_documents": include_similar_documents,
-                "similar_documents_number": similar_documents_number,
-                "similar_documents_fields": similar_documents_fields,
-                "predefined_sources": predefined_sources,
-                "sources": sources,
-                "not_sources": not_sources,
-                "lang": lang,
-                "not_lang": not_lang,
-                "countries": countries,
-                "not_countries": not_countries,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
-                "by_parse_date": by_parse_date,
-                "published_date_precision": published_date_precision,
-                "sort_by": sort_by,
-                "ranked_only": ranked_only,
-                "from_rank": from_rank,
-                "to_rank": to_rank,
-                "is_headline": is_headline,
-                "is_opinion": is_opinion,
-                "is_paid_content": is_paid_content,
-                "parent_url": parent_url,
-                "all_links": all_links,
-                "all_domain_links": all_domain_links,
-                "word_count_min": word_count_min,
-                "word_count_max": word_count_max,
-                "page": page,
-                "page_size": page_size,
-                "include_nlp_data": include_nlp_data,
-                "has_nlp": has_nlp,
-                "theme": theme,
-                "not_theme": not_theme,
-                "ner_name": ner_name,
-                "title_sentiment_min": title_sentiment_min,
-                "title_sentiment_max": title_sentiment_max,
-                "content_sentiment_min": content_sentiment_min,
-                "content_sentiment_max": content_sentiment_max,
-                "iptc_tags": iptc_tags,
-                "not_iptc_tags": not_iptc_tags,
-                "custom_tags": custom_tags,
-                "robots_compliant": robots_compliant,
-            },
-            request_options=request_options,
-        )
-        try:
-            if 200 <= _response.status_code < 300:
-                _data = typing.cast(
-                    SearchSimilarGetResponse,
-                    parse_obj_as(
-                        type_=SearchSimilarGetResponse,  # type: ignore
-                        object_=_response.json(),
-                    ),
-                )
-                return HttpResponse(response=_response, data=_data)
-            if _response.status_code == 400:
-                raise BadRequestError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 401:
-                raise UnauthorizedError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 403:
-                raise ForbiddenError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 408:
-                raise RequestTimeoutError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 422:
-                raise UnprocessableEntityError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 429:
-                raise TooManyRequestsError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 500:
-                raise InternalServerError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        str,
-                        parse_obj_as(
-                            type_=str,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            _response_json = _response.json()
-        except JSONDecodeError:
-            raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
-        raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
-
-    def post(
-        self,
-        *,
-        q: Q,
-        search_in: typing.Optional[SearchIn] = OMIT,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = OMIT,
-        include_similar_documents: typing.Optional[IncludeSimilarDocuments] = OMIT,
-        similar_documents_number: typing.Optional[SimilarDocumentsNumber] = OMIT,
-        similar_documents_fields: typing.Optional[SimilarDocumentsFields] = OMIT,
-        predefined_sources: typing.Optional[PredefinedSources] = OMIT,
-        sources: typing.Optional[Sources] = OMIT,
-        not_sources: typing.Optional[NotSources] = OMIT,
-        lang: typing.Optional[Lang] = OMIT,
-        not_lang: typing.Optional[NotLang] = OMIT,
-        countries: typing.Optional[Countries] = OMIT,
-        not_countries: typing.Optional[NotCountries] = OMIT,
-        from_: typing.Optional[From] = OMIT,
-        to: typing.Optional[To] = OMIT,
-        by_parse_date: typing.Optional[ByParseDate] = OMIT,
-        published_date_precision: typing.Optional[PublishedDatePrecision] = OMIT,
-        sort_by: typing.Optional[SortBy] = OMIT,
-        ranked_only: typing.Optional[RankedOnly] = OMIT,
-        from_rank: typing.Optional[FromRank] = OMIT,
-        to_rank: typing.Optional[ToRank] = OMIT,
-        is_headline: typing.Optional[IsHeadline] = OMIT,
-        is_opinion: typing.Optional[IsOpinion] = OMIT,
-        is_paid_content: typing.Optional[IsPaidContent] = OMIT,
-        parent_url: typing.Optional[ParentUrl] = OMIT,
-        all_links: typing.Optional[AllLinks] = OMIT,
-        all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
-        word_count_min: typing.Optional[WordCountMin] = OMIT,
-        word_count_max: typing.Optional[WordCountMax] = OMIT,
-        page: typing.Optional[Page] = OMIT,
-        page_size: typing.Optional[PageSize] = OMIT,
-        include_nlp_data: typing.Optional[IncludeNlpData] = OMIT,
-        has_nlp: typing.Optional[HasNlp] = OMIT,
-        theme: typing.Optional[Theme] = OMIT,
-        not_theme: typing.Optional[NotTheme] = OMIT,
-        ner_name: typing.Optional[NerName] = OMIT,
-        title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
-        title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
-        content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
-        iptc_tags: typing.Optional[IptcTags] = OMIT,
-        not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
-        custom_tags: typing.Optional[CustomTags] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> HttpResponse[SearchSimilarPostResponse]:
-        """
-        Searches for articles similar to the specified query. You can filter results by language, country, source, and more.
-
-        Parameters
-        ----------
-        q : Q
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[IncludeSimilarDocuments]
-
-        similar_documents_number : typing.Optional[SimilarDocumentsNumber]
-
-        similar_documents_fields : typing.Optional[SimilarDocumentsFields]
-
-        predefined_sources : typing.Optional[PredefinedSources]
-
-        sources : typing.Optional[Sources]
-
-        not_sources : typing.Optional[NotSources]
-
-        lang : typing.Optional[Lang]
-
-        not_lang : typing.Optional[NotLang]
-
-        countries : typing.Optional[Countries]
-
-        not_countries : typing.Optional[NotCountries]
-
-        from_ : typing.Optional[From]
-
-        to : typing.Optional[To]
-
-        by_parse_date : typing.Optional[ByParseDate]
-
-        published_date_precision : typing.Optional[PublishedDatePrecision]
-
-        sort_by : typing.Optional[SortBy]
-
-        ranked_only : typing.Optional[RankedOnly]
-
-        from_rank : typing.Optional[FromRank]
-
-        to_rank : typing.Optional[ToRank]
-
-        is_headline : typing.Optional[IsHeadline]
-
-        is_opinion : typing.Optional[IsOpinion]
-
-        is_paid_content : typing.Optional[IsPaidContent]
-
-        parent_url : typing.Optional[ParentUrl]
-
-        all_links : typing.Optional[AllLinks]
-
-        all_domain_links : typing.Optional[AllDomainLinks]
-
-        word_count_min : typing.Optional[WordCountMin]
-
-        word_count_max : typing.Optional[WordCountMax]
-
-        page : typing.Optional[Page]
-
-        page_size : typing.Optional[PageSize]
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[Theme]
-
-        not_theme : typing.Optional[NotTheme]
-
-        ner_name : typing.Optional[NerName]
-
-        title_sentiment_min : typing.Optional[TitleSentimentMin]
-
-        title_sentiment_max : typing.Optional[TitleSentimentMax]
-
-        content_sentiment_min : typing.Optional[ContentSentimentMin]
-
-        content_sentiment_max : typing.Optional[ContentSentimentMax]
-
-        iptc_tags : typing.Optional[IptcTags]
-
-        not_iptc_tags : typing.Optional[NotIptcTags]
-
-        custom_tags : typing.Optional[CustomTags]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        HttpResponse[SearchSimilarPostResponse]
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-        """
-        _response = self._client_wrapper.httpx_client.request(
-            "api/search_similar",
-            method="POST",
-            json={
-                "q": q,
-                "search_in": search_in,
-                "include_translation_fields": include_translation_fields,
-                "include_similar_documents": include_similar_documents,
-                "similar_documents_number": similar_documents_number,
-                "similar_documents_fields": similar_documents_fields,
-                "predefined_sources": convert_and_respect_annotation_metadata(
-                    object_=predefined_sources, annotation=PredefinedSources, direction="write"
-                ),
-                "sources": convert_and_respect_annotation_metadata(
-                    object_=sources, annotation=Sources, direction="write"
-                ),
-                "not_sources": convert_and_respect_annotation_metadata(
-                    object_=not_sources, annotation=NotSources, direction="write"
-                ),
-                "lang": convert_and_respect_annotation_metadata(object_=lang, annotation=Lang, direction="write"),
-                "not_lang": convert_and_respect_annotation_metadata(
-                    object_=not_lang, annotation=NotLang, direction="write"
-                ),
-                "countries": convert_and_respect_annotation_metadata(
-                    object_=countries, annotation=Countries, direction="write"
-                ),
-                "not_countries": convert_and_respect_annotation_metadata(
-                    object_=not_countries, annotation=NotCountries, direction="write"
-                ),
-                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
-                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
-                "by_parse_date": by_parse_date,
-                "published_date_precision": published_date_precision,
-                "sort_by": sort_by,
-                "ranked_only": ranked_only,
-                "from_rank": from_rank,
-                "to_rank": to_rank,
-                "is_headline": is_headline,
-                "is_opinion": is_opinion,
-                "is_paid_content": is_paid_content,
-                "parent_url": convert_and_respect_annotation_metadata(
-                    object_=parent_url, annotation=ParentUrl, direction="write"
-                ),
-                "all_links": convert_and_respect_annotation_metadata(
-                    object_=all_links, annotation=AllLinks, direction="write"
-                ),
-                "all_domain_links": convert_and_respect_annotation_metadata(
-                    object_=all_domain_links, annotation=AllDomainLinks, direction="write"
-                ),
-                "word_count_min": word_count_min,
-                "word_count_max": word_count_max,
-                "page": page,
-                "page_size": page_size,
-                "include_nlp_data": include_nlp_data,
-                "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
-                "ner_name": ner_name,
-                "title_sentiment_min": title_sentiment_min,
-                "title_sentiment_max": title_sentiment_max,
-                "content_sentiment_min": content_sentiment_min,
-                "content_sentiment_max": content_sentiment_max,
-                "iptc_tags": convert_and_respect_annotation_metadata(
-                    object_=iptc_tags, annotation=IptcTags, direction="write"
-                ),
-                "not_iptc_tags": convert_and_respect_annotation_metadata(
-                    object_=not_iptc_tags, annotation=NotIptcTags, direction="write"
-                ),
-                "custom_tags": convert_and_respect_annotation_metadata(
-                    object_=custom_tags, annotation=CustomTags, direction="write"
-                ),
-                "robots_compliant": robots_compliant,
-            },
-            headers={
-                "content-type": "application/json",
-            },
-            request_options=request_options,
-            omit=OMIT,
-        )
-        try:
-            if 200 <= _response.status_code < 300:
-                _data = typing.cast(
-                    SearchSimilarPostResponse,
-                    parse_obj_as(
-                        type_=SearchSimilarPostResponse,  # type: ignore
-                        object_=_response.json(),
-                    ),
-                )
-                return HttpResponse(response=_response, data=_data)
-            if _response.status_code == 400:
-                raise BadRequestError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 401:
-                raise UnauthorizedError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 403:
-                raise ForbiddenError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 408:
-                raise RequestTimeoutError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 422:
-                raise UnprocessableEntityError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 429:
-                raise TooManyRequestsError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 500:
-                raise InternalServerError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        str,
-                        parse_obj_as(
-                            type_=str,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            _response_json = _response.json()
-        except JSONDecodeError:
-            raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
-        raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
-
-
-class AsyncRawSearchsimilarClient:
-    def __init__(self, *, client_wrapper: AsyncClientWrapper):
-        self._client_wrapper = client_wrapper
-
-    async def get(
-        self,
-        *,
-        q: str,
-        search_in: typing.Optional[SearchIn] = None,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = None,
-        include_similar_documents: typing.Optional[bool] = None,
-        similar_documents_number: typing.Optional[int] = None,
-        similar_documents_fields: typing.Optional[str] = None,
-        predefined_sources: typing.Optional[str] = None,
-        sources: typing.Optional[str] = None,
-        not_sources: typing.Optional[str] = None,
-        lang: typing.Optional[str] = None,
-        not_lang: typing.Optional[str] = None,
-        countries: typing.Optional[str] = None,
-        not_countries: typing.Optional[str] = None,
-        from_: typing.Optional[dt.datetime] = None,
-        to: typing.Optional[dt.datetime] = None,
-        by_parse_date: typing.Optional[bool] = None,
-        published_date_precision: typing.Optional[SearchSimilarGetRequestPublishedDatePrecision] = None,
-        sort_by: typing.Optional[SearchSimilarGetRequestSortBy] = None,
-        ranked_only: typing.Optional[bool] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
-        is_headline: typing.Optional[bool] = None,
-        is_opinion: typing.Optional[bool] = None,
-        is_paid_content: typing.Optional[bool] = None,
-        parent_url: typing.Optional[str] = None,
-        all_links: typing.Optional[str] = None,
-        all_domain_links: typing.Optional[str] = None,
-        word_count_min: typing.Optional[int] = None,
-        word_count_max: typing.Optional[int] = None,
-        page: typing.Optional[int] = None,
-        page_size: typing.Optional[int] = None,
-        include_nlp_data: typing.Optional[IncludeNlpData] = None,
-        has_nlp: typing.Optional[HasNlp] = None,
-        theme: typing.Optional[str] = None,
-        not_theme: typing.Optional[str] = None,
-        ner_name: typing.Optional[str] = None,
-        title_sentiment_min: typing.Optional[float] = None,
-        title_sentiment_max: typing.Optional[float] = None,
-        content_sentiment_min: typing.Optional[float] = None,
-        content_sentiment_max: typing.Optional[float] = None,
-        iptc_tags: typing.Optional[str] = None,
-        not_iptc_tags: typing.Optional[str] = None,
-        custom_tags: typing.Optional[str] = None,
-        robots_compliant: typing.Optional[bool] = None,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> AsyncHttpResponse[SearchSimilarGetResponse]:
-        """
-        Searches for articles similar to a specified query.
-
-        Parameters
-        ----------
-        q : str
-            The keyword(s) to search for in articles. Query syntax supports logical operators (`AND`, `OR`, `NOT`) and wildcards:
-
-            - For an exact match, use double quotes. For example, `"technology news"`.
-            - Use `*` to search for any keyword.
-            - Use `+` to include and `-` to exclude specific words or phrases.
-              For example, `+Apple`, `-Google`.
-            - Use `AND`, `OR`, and `NOT` to refine search results.
-              For example, `technology AND (Apple OR Microsoft) NOT Google`.
-
-            For more details, see [Advanced querying](/docs/v3/documentation/guides-and-concepts/advanced-querying).
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[bool]
-            If true, includes similar documents in the response.
-
-        similar_documents_number : typing.Optional[int]
-            The number of similar documents to return.
-
-        similar_documents_fields : typing.Optional[str]
-            The fields to consider for finding similar documents.
-
-        predefined_sources : typing.Optional[str]
-            Predefined top news sources per country.
-
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
-
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
-
-        sources : typing.Optional[str]
-            One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as `finance.yahoo.com`, are also acceptable.To specify multiple sources, use a comma-separated string.
-
-            Examples:
-            - `"nytimes.com"`
-            - `"theguardian.com, finance.yahoo.com"`
-
-        not_sources : typing.Optional[str]
-            The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string.
-
-            Example: `"cnn.com, wsj.com"`
-
-        lang : typing.Optional[str]
-            The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
-
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        not_lang : typing.Optional[str]
-            The language(s) to exclude from the search. The accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To exclude multiple languages, use a comma-separated string.
-
-            Example: `"fr, de"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
-
-        countries : typing.Optional[str]
-            The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
-
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        not_countries : typing.Optional[str]
-            The publisher location countries to exclude from the search. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To exclude multiple countries, use a comma-separated string.
-
-            Example:`"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
-
-        from_ : typing.Optional[dt.datetime]
-            The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `7 day ago`, `today`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        to : typing.Optional[dt.datetime]
-            The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text. The default time zone is UTC.
-
-            Formats with examples:
-            - YYYY-mm-ddTHH:MM:SS: `2024-07-01T00:00:00`
-            - YYYY-MM-dd: `2024-07-01`
-            - YYYY/mm/dd HH:MM:SS: `2024/07/01 00:00:00`
-            - YYYY/mm/dd: `2024/07/01`
-            - English phrases: `1 day ago`, `now`
-
-            **Note**: By default, applied to the publication date of the article. To use the article's parse date instead, set the `by_parse_date` parameter to `true`.
-
-        by_parse_date : typing.Optional[bool]
-            If true, the `from_` and `to_` parameters use article parse dates instead of published dates. Additionally, the `parse_date` variable is added to the output for each article object.
-
-        published_date_precision : typing.Optional[SearchSimilarGetRequestPublishedDatePrecision]
-            The precision of the published date. There are three types:
-            - `full`: The day and time of an article is correctly identified with the appropriate timezone.
-            - `timezone unknown`: The day and time of an article is correctly identified without timezone.
-            - `date`: Only the day is identified without an exact time.
-
-        sort_by : typing.Optional[SearchSimilarGetRequestSortBy]
-            The sorting order of the results. Possible values are:
-            - `relevancy`: The most relevant results first.
-            - `date`: The most recently published results first.
-            - `rank`: The results from the highest-ranked sources first.
-
-        ranked_only : typing.Optional[bool]
-            If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.
-
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
-
-        is_headline : typing.Optional[bool]
-            If true, only returns articles that were posted on the home page of a given news domain.
-
-        is_opinion : typing.Optional[bool]
-            If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.
-
-        is_paid_content : typing.Optional[bool]
-            If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.
-
-        parent_url : typing.Optional[str]
-            The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string.
-
-            Example: `"wsj.com/politics, wsj.com/tech"`
-
-        all_links : typing.Optional[str]
-            The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string.
-
-            Example: `"https://aiindex.stanford.edu/report, https://www.stateof.ai"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        all_domain_links : typing.Optional[str]
-            The domain(s) mentioned in the article. For multiple domains, use a comma-separated string.
-
-            Example: `"who.int, nih.gov"`
-
-            For more details, see [Search by URL](/docs/v3/documentation/how-to/search-by-url).
-
-        word_count_min : typing.Optional[int]
-            The minimum number of words an article must contain. To be used for avoiding articles with small content.
-
-        word_count_max : typing.Optional[int]
-            The maximum number of words an article can contain. To be used for avoiding articles with large content.
-
-        page : typing.Optional[int]
-            The page number to scroll through the results. Use for pagination, as a single API response can return up to 1,000 articles.
-
-            For details, see [How to paginate large datasets](https://www.newscatcherapi.com/docs/v3/documentation/how-to/paginate-large-datasets).
-
-        page_size : typing.Optional[int]
-            The number of articles to return per page.
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[str]
-            Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string.
-
-            Example: `"Finance, Tech"`
-
-            **Note**: The `theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-            Available options: `Business`, `Economics`, `Entertainment`, `Finance`, `Health`, `Politics`, `Science`, `Sports`, `Tech`, `Crime`, `Financial Crime`, `Lifestyle`, `Automotive`, `Travel`, `Weather`, `General`.
-
-        not_theme : typing.Optional[str]
-            Inverse of the `theme` parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string.
-
-            Example: `"Crime, Tech"`
-
-            **Note**: The `not_theme` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        ner_name : typing.Optional[str]
-            The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.
-
-            Example: `"Tesla, Amazon"`
-
-        title_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        title_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their titles.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `title_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_min : typing.Optional[float]
-            Filters articles based on the minimum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_min` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        content_sentiment_max : typing.Optional[float]
-            Filters articles based on the maximum sentiment score of their content.
-
-            Range is `-1.0` to `1.0`, where:
-            - Negative values indicate negative sentiment.
-            - Positive values indicate positive sentiment.
-            - Values close to 0 indicate neutral sentiment.
-
-            **Note**: The `content_sentiment_max` parameter is only available if NLP is included in your subscription plan.
-
-            To learn more, see [NLP features](/docs/v3/documentation/guides-and-concepts/nlp-features).
-
-        iptc_tags : typing.Optional[str]
-            Filters articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags, use a comma-separated string of tag IDs.
-
-            Example: `"20000199, 20000209"`
-
-            **Note**: The `iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        not_iptc_tags : typing.Optional[str]
-            Inverse of the `iptc_tags` parameter. Excludes articles based on International Press Telecommunications Council (IPTC) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string of tag IDs.
-
-            Example: `"20000205, 20000209"`
-
-            **Note**: The `not_iptc_tags` parameter is only available in the `v3_nlp_iptc_tags` subscription plan.
-
-            To learn more, see [IPTC Media Topic NewsCodes](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
-
-        custom_tags : typing.Optional[str]
-            Filters articles based on provided taxonomy that is tailored to your specific needs and is accessible only with your API key. To specify tags, use the following pattern:
-
-            - `custom_tags.taxonomy=Tag1,Tag2,Tag3`, where `taxonomy` is the taxonomy name and `Tag1,Tag2,Tag3` is a comma-separated list of tags.
-
-            Example: `custom_tags.industry="Manufacturing, Supply Chain, Logistics"`
-
-            To learn more, see the [Custom tags](/docs/v3/documentation/guides-and-concepts/custom-tags).
-
-        robots_compliant : typing.Optional[bool]
-            If true, returns only articles/sources that comply with the publisher's robots.txt rules. If false, returns only articles/sources that do not comply with robots.txt rules. If omitted, returns all articles/sources regardless of compliance status.
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        AsyncHttpResponse[SearchSimilarGetResponse]
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-        """
-        _response = await self._client_wrapper.httpx_client.request(
-            "api/search_similar",
-            method="GET",
-            params={
-                "q": q,
-                "search_in": search_in,
-                "include_translation_fields": include_translation_fields,
-                "include_similar_documents": include_similar_documents,
-                "similar_documents_number": similar_documents_number,
-                "similar_documents_fields": similar_documents_fields,
-                "predefined_sources": predefined_sources,
-                "sources": sources,
-                "not_sources": not_sources,
-                "lang": lang,
-                "not_lang": not_lang,
-                "countries": countries,
-                "not_countries": not_countries,
-                "from_": serialize_datetime(from_) if from_ is not None else None,
-                "to_": serialize_datetime(to) if to is not None else None,
-                "by_parse_date": by_parse_date,
-                "published_date_precision": published_date_precision,
-                "sort_by": sort_by,
-                "ranked_only": ranked_only,
-                "from_rank": from_rank,
-                "to_rank": to_rank,
-                "is_headline": is_headline,
-                "is_opinion": is_opinion,
-                "is_paid_content": is_paid_content,
-                "parent_url": parent_url,
-                "all_links": all_links,
-                "all_domain_links": all_domain_links,
-                "word_count_min": word_count_min,
-                "word_count_max": word_count_max,
-                "page": page,
-                "page_size": page_size,
-                "include_nlp_data": include_nlp_data,
-                "has_nlp": has_nlp,
-                "theme": theme,
-                "not_theme": not_theme,
-                "ner_name": ner_name,
-                "title_sentiment_min": title_sentiment_min,
-                "title_sentiment_max": title_sentiment_max,
-                "content_sentiment_min": content_sentiment_min,
-                "content_sentiment_max": content_sentiment_max,
-                "iptc_tags": iptc_tags,
-                "not_iptc_tags": not_iptc_tags,
-                "custom_tags": custom_tags,
-                "robots_compliant": robots_compliant,
-            },
-            request_options=request_options,
-        )
-        try:
-            if 200 <= _response.status_code < 300:
-                _data = typing.cast(
-                    SearchSimilarGetResponse,
-                    parse_obj_as(
-                        type_=SearchSimilarGetResponse,  # type: ignore
-                        object_=_response.json(),
-                    ),
-                )
-                return AsyncHttpResponse(response=_response, data=_data)
-            if _response.status_code == 400:
-                raise BadRequestError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 401:
-                raise UnauthorizedError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 403:
-                raise ForbiddenError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 408:
-                raise RequestTimeoutError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 422:
-                raise UnprocessableEntityError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 429:
-                raise TooManyRequestsError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 500:
-                raise InternalServerError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        str,
-                        parse_obj_as(
-                            type_=str,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            _response_json = _response.json()
-        except JSONDecodeError:
-            raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
-        raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
-
-    async def post(
-        self,
-        *,
-        q: Q,
-        search_in: typing.Optional[SearchIn] = OMIT,
-        include_translation_fields: typing.Optional[IncludeTranslationFields] = OMIT,
-        include_similar_documents: typing.Optional[IncludeSimilarDocuments] = OMIT,
-        similar_documents_number: typing.Optional[SimilarDocumentsNumber] = OMIT,
-        similar_documents_fields: typing.Optional[SimilarDocumentsFields] = OMIT,
-        predefined_sources: typing.Optional[PredefinedSources] = OMIT,
-        sources: typing.Optional[Sources] = OMIT,
-        not_sources: typing.Optional[NotSources] = OMIT,
-        lang: typing.Optional[Lang] = OMIT,
-        not_lang: typing.Optional[NotLang] = OMIT,
-        countries: typing.Optional[Countries] = OMIT,
-        not_countries: typing.Optional[NotCountries] = OMIT,
-        from_: typing.Optional[From] = OMIT,
-        to: typing.Optional[To] = OMIT,
-        by_parse_date: typing.Optional[ByParseDate] = OMIT,
-        published_date_precision: typing.Optional[PublishedDatePrecision] = OMIT,
-        sort_by: typing.Optional[SortBy] = OMIT,
-        ranked_only: typing.Optional[RankedOnly] = OMIT,
-        from_rank: typing.Optional[FromRank] = OMIT,
-        to_rank: typing.Optional[ToRank] = OMIT,
-        is_headline: typing.Optional[IsHeadline] = OMIT,
-        is_opinion: typing.Optional[IsOpinion] = OMIT,
-        is_paid_content: typing.Optional[IsPaidContent] = OMIT,
-        parent_url: typing.Optional[ParentUrl] = OMIT,
-        all_links: typing.Optional[AllLinks] = OMIT,
-        all_domain_links: typing.Optional[AllDomainLinks] = OMIT,
-        word_count_min: typing.Optional[WordCountMin] = OMIT,
-        word_count_max: typing.Optional[WordCountMax] = OMIT,
-        page: typing.Optional[Page] = OMIT,
-        page_size: typing.Optional[PageSize] = OMIT,
-        include_nlp_data: typing.Optional[IncludeNlpData] = OMIT,
-        has_nlp: typing.Optional[HasNlp] = OMIT,
-        theme: typing.Optional[Theme] = OMIT,
-        not_theme: typing.Optional[NotTheme] = OMIT,
-        ner_name: typing.Optional[NerName] = OMIT,
-        title_sentiment_min: typing.Optional[TitleSentimentMin] = OMIT,
-        title_sentiment_max: typing.Optional[TitleSentimentMax] = OMIT,
-        content_sentiment_min: typing.Optional[ContentSentimentMin] = OMIT,
-        content_sentiment_max: typing.Optional[ContentSentimentMax] = OMIT,
-        iptc_tags: typing.Optional[IptcTags] = OMIT,
-        not_iptc_tags: typing.Optional[NotIptcTags] = OMIT,
-        custom_tags: typing.Optional[CustomTags] = OMIT,
-        robots_compliant: typing.Optional[RobotsCompliant] = OMIT,
-        request_options: typing.Optional[RequestOptions] = None,
-    ) -> AsyncHttpResponse[SearchSimilarPostResponse]:
-        """
-        Searches for articles similar to the specified query. You can filter results by language, country, source, and more.
-
-        Parameters
-        ----------
-        q : Q
-
-        search_in : typing.Optional[SearchIn]
-
-        include_translation_fields : typing.Optional[IncludeTranslationFields]
-
-        include_similar_documents : typing.Optional[IncludeSimilarDocuments]
-
-        similar_documents_number : typing.Optional[SimilarDocumentsNumber]
-
-        similar_documents_fields : typing.Optional[SimilarDocumentsFields]
-
-        predefined_sources : typing.Optional[PredefinedSources]
-
-        sources : typing.Optional[Sources]
-
-        not_sources : typing.Optional[NotSources]
-
-        lang : typing.Optional[Lang]
-
-        not_lang : typing.Optional[NotLang]
-
-        countries : typing.Optional[Countries]
-
-        not_countries : typing.Optional[NotCountries]
-
-        from_ : typing.Optional[From]
-
-        to : typing.Optional[To]
-
-        by_parse_date : typing.Optional[ByParseDate]
-
-        published_date_precision : typing.Optional[PublishedDatePrecision]
-
-        sort_by : typing.Optional[SortBy]
-
-        ranked_only : typing.Optional[RankedOnly]
-
-        from_rank : typing.Optional[FromRank]
-
-        to_rank : typing.Optional[ToRank]
-
-        is_headline : typing.Optional[IsHeadline]
-
-        is_opinion : typing.Optional[IsOpinion]
-
-        is_paid_content : typing.Optional[IsPaidContent]
-
-        parent_url : typing.Optional[ParentUrl]
-
-        all_links : typing.Optional[AllLinks]
-
-        all_domain_links : typing.Optional[AllDomainLinks]
-
-        word_count_min : typing.Optional[WordCountMin]
-
-        word_count_max : typing.Optional[WordCountMax]
-
-        page : typing.Optional[Page]
-
-        page_size : typing.Optional[PageSize]
-
-        include_nlp_data : typing.Optional[IncludeNlpData]
-
-        has_nlp : typing.Optional[HasNlp]
-
-        theme : typing.Optional[Theme]
-
-        not_theme : typing.Optional[NotTheme]
-
-        ner_name : typing.Optional[NerName]
-
-        title_sentiment_min : typing.Optional[TitleSentimentMin]
-
-        title_sentiment_max : typing.Optional[TitleSentimentMax]
-
-        content_sentiment_min : typing.Optional[ContentSentimentMin]
-
-        content_sentiment_max : typing.Optional[ContentSentimentMax]
-
-        iptc_tags : typing.Optional[IptcTags]
-
-        not_iptc_tags : typing.Optional[NotIptcTags]
-
-        custom_tags : typing.Optional[CustomTags]
-
-        robots_compliant : typing.Optional[RobotsCompliant]
-
-        request_options : typing.Optional[RequestOptions]
-            Request-specific configuration.
-
-        Returns
-        -------
-        AsyncHttpResponse[SearchSimilarPostResponse]
-            A successful response containing articles similar to the specified query. If no matches, returns a failed search response according to the defined schema.
-        """
-        _response = await self._client_wrapper.httpx_client.request(
-            "api/search_similar",
-            method="POST",
-            json={
-                "q": q,
-                "search_in": search_in,
-                "include_translation_fields": include_translation_fields,
-                "include_similar_documents": include_similar_documents,
-                "similar_documents_number": similar_documents_number,
-                "similar_documents_fields": similar_documents_fields,
-                "predefined_sources": convert_and_respect_annotation_metadata(
-                    object_=predefined_sources, annotation=PredefinedSources, direction="write"
-                ),
-                "sources": convert_and_respect_annotation_metadata(
-                    object_=sources, annotation=Sources, direction="write"
-                ),
-                "not_sources": convert_and_respect_annotation_metadata(
-                    object_=not_sources, annotation=NotSources, direction="write"
-                ),
-                "lang": convert_and_respect_annotation_metadata(object_=lang, annotation=Lang, direction="write"),
-                "not_lang": convert_and_respect_annotation_metadata(
-                    object_=not_lang, annotation=NotLang, direction="write"
-                ),
-                "countries": convert_and_respect_annotation_metadata(
-                    object_=countries, annotation=Countries, direction="write"
-                ),
-                "not_countries": convert_and_respect_annotation_metadata(
-                    object_=not_countries, annotation=NotCountries, direction="write"
-                ),
-                "from_": convert_and_respect_annotation_metadata(object_=from_, annotation=From, direction="write"),
-                "to_": convert_and_respect_annotation_metadata(object_=to, annotation=To, direction="write"),
-                "by_parse_date": by_parse_date,
-                "published_date_precision": published_date_precision,
-                "sort_by": sort_by,
-                "ranked_only": ranked_only,
-                "from_rank": from_rank,
-                "to_rank": to_rank,
-                "is_headline": is_headline,
-                "is_opinion": is_opinion,
-                "is_paid_content": is_paid_content,
-                "parent_url": convert_and_respect_annotation_metadata(
-                    object_=parent_url, annotation=ParentUrl, direction="write"
-                ),
-                "all_links": convert_and_respect_annotation_metadata(
-                    object_=all_links, annotation=AllLinks, direction="write"
-                ),
-                "all_domain_links": convert_and_respect_annotation_metadata(
-                    object_=all_domain_links, annotation=AllDomainLinks, direction="write"
-                ),
-                "word_count_min": word_count_min,
-                "word_count_max": word_count_max,
-                "page": page,
-                "page_size": page_size,
-                "include_nlp_data": include_nlp_data,
-                "has_nlp": has_nlp,
-                "theme": convert_and_respect_annotation_metadata(object_=theme, annotation=Theme, direction="write"),
-                "not_theme": convert_and_respect_annotation_metadata(
-                    object_=not_theme, annotation=NotTheme, direction="write"
-                ),
-                "ner_name": ner_name,
-                "title_sentiment_min": title_sentiment_min,
-                "title_sentiment_max": title_sentiment_max,
-                "content_sentiment_min": content_sentiment_min,
-                "content_sentiment_max": content_sentiment_max,
-                "iptc_tags": convert_and_respect_annotation_metadata(
-                    object_=iptc_tags, annotation=IptcTags, direction="write"
-                ),
-                "not_iptc_tags": convert_and_respect_annotation_metadata(
-                    object_=not_iptc_tags, annotation=NotIptcTags, direction="write"
-                ),
-                "custom_tags": convert_and_respect_annotation_metadata(
-                    object_=custom_tags, annotation=CustomTags, direction="write"
-                ),
-                "robots_compliant": robots_compliant,
-            },
-            headers={
-                "content-type": "application/json",
-            },
-            request_options=request_options,
-            omit=OMIT,
-        )
-        try:
-            if 200 <= _response.status_code < 300:
-                _data = typing.cast(
-                    SearchSimilarPostResponse,
-                    parse_obj_as(
-                        type_=SearchSimilarPostResponse,  # type: ignore
-                        object_=_response.json(),
-                    ),
-                )
-                return AsyncHttpResponse(response=_response, data=_data)
-            if _response.status_code == 400:
-                raise BadRequestError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 401:
-                raise UnauthorizedError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 403:
-                raise ForbiddenError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 408:
-                raise RequestTimeoutError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 422:
-                raise UnprocessableEntityError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 429:
-                raise TooManyRequestsError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        Error,
-                        parse_obj_as(
-                            type_=Error,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            if _response.status_code == 500:
-                raise InternalServerError(
-                    headers=dict(_response.headers),
-                    body=typing.cast(
-                        str,
-                        parse_obj_as(
-                            type_=str,  # type: ignore
-                            object_=_response.json(),
-                        ),
-                    ),
-                )
-            _response_json = _response.json()
-        except JSONDecodeError:
-            raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
-        raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/searchsimilar/types/__init__.py b/src/newscatcher/searchsimilar/types/__init__.py
deleted file mode 100644
index 5992030..0000000
--- a/src/newscatcher/searchsimilar/types/__init__.py
+++ /dev/null
@@ -1,15 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-# isort: skip_file
-
-from .search_similar_get_request_published_date_precision import SearchSimilarGetRequestPublishedDatePrecision
-from .search_similar_get_request_sort_by import SearchSimilarGetRequestSortBy
-from .search_similar_get_response import SearchSimilarGetResponse
-from .search_similar_post_response import SearchSimilarPostResponse
-
-__all__ = [
-    "SearchSimilarGetRequestPublishedDatePrecision",
-    "SearchSimilarGetRequestSortBy",
-    "SearchSimilarGetResponse",
-    "SearchSimilarPostResponse",
-]
diff --git a/src/newscatcher/searchsimilar/types/search_similar_get_request_published_date_precision.py b/src/newscatcher/searchsimilar/types/search_similar_get_request_published_date_precision.py
deleted file mode 100644
index ede9be1..0000000
--- a/src/newscatcher/searchsimilar/types/search_similar_get_request_published_date_precision.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SearchSimilarGetRequestPublishedDatePrecision = typing.Union[
-    typing.Literal["full", "timezone unknown", "date"], typing.Any
-]
diff --git a/src/newscatcher/searchsimilar/types/search_similar_get_request_sort_by.py b/src/newscatcher/searchsimilar/types/search_similar_get_request_sort_by.py
deleted file mode 100644
index 5859da0..0000000
--- a/src/newscatcher/searchsimilar/types/search_similar_get_request_sort_by.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SearchSimilarGetRequestSortBy = typing.Union[typing.Literal["relevancy", "date", "rank"], typing.Any]
diff --git a/src/newscatcher/searchsimilar/types/search_similar_get_response.py b/src/newscatcher/searchsimilar/types/search_similar_get_response.py
deleted file mode 100644
index 9815eea..0000000
--- a/src/newscatcher/searchsimilar/types/search_similar_get_response.py
+++ /dev/null
@@ -1,8 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-from ...types.failed_search_similar_response_dto import FailedSearchSimilarResponseDto
-from ...types.search_similar_response_dto import SearchSimilarResponseDto
-
-SearchSimilarGetResponse = typing.Union[SearchSimilarResponseDto, FailedSearchSimilarResponseDto]
diff --git a/src/newscatcher/searchsimilar/types/search_similar_post_response.py b/src/newscatcher/searchsimilar/types/search_similar_post_response.py
deleted file mode 100644
index 9fa29f4..0000000
--- a/src/newscatcher/searchsimilar/types/search_similar_post_response.py
+++ /dev/null
@@ -1,8 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-from ...types.failed_search_similar_response_dto import FailedSearchSimilarResponseDto
-from ...types.search_similar_response_dto import SearchSimilarResponseDto
-
-SearchSimilarPostResponse = typing.Union[SearchSimilarResponseDto, FailedSearchSimilarResponseDto]
diff --git a/src/newscatcher/sources/__init__.py b/src/newscatcher/sources/__init__.py
index 6f0dd5f..5cde020 100644
--- a/src/newscatcher/sources/__init__.py
+++ b/src/newscatcher/sources/__init__.py
@@ -2,6 +2,3 @@
 
 # isort: skip_file
 
-from .types import SourcesGetRequestNewsDomainType
-
-__all__ = ["SourcesGetRequestNewsDomainType"]
diff --git a/src/newscatcher/sources/client.py b/src/newscatcher/sources/client.py
index 3430e18..70484c5 100644
--- a/src/newscatcher/sources/client.py
+++ b/src/newscatcher/sources/client.py
@@ -17,7 +17,6 @@
 from ..types.sources_response_dto import SourcesResponseDto
 from ..types.to_rank import ToRank
 from .raw_client import AsyncRawSourcesClient, RawSourcesClient
-from .types.sources_get_request_news_domain_type import SourcesGetRequestNewsDomainType
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -46,12 +45,12 @@ def get(
         predefined_sources: typing.Optional[str] = None,
         source_name: typing.Optional[str] = None,
         source_url: typing.Optional[str] = None,
-        include_additional_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SourcesGetRequestNewsDomainType] = None,
+        include_additional_info: typing.Optional[IncludeAdditionalInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SourcesResponseDto:
         """
@@ -62,33 +61,23 @@ def get(
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         source_url : typing.Optional[str]
@@ -97,38 +86,20 @@ def get(
             **Caution**:  When specifying the `source_url` parameter,
             you can only use `include_additional_info` as an extra parameter.
 
-        include_additional_info : typing.Optional[bool]
-            If true, returns the following additional datapoints about each news source:
-            - `nb_articles_for_7d`: The number of articles published by the source in the last week.
-            - `country`: Source country of origin.
-            - `rank`: SEO rank.
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., "Original Content").
-            - `news_type`: Category of news (e.g., "General News Outlets").
-
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
-
-        news_domain_type : typing.Optional[SourcesGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
+        include_additional_info : typing.Optional[IncludeAdditionalInfo]
+
+        is_news_domain : typing.Optional[IsNewsDomain]
+
+        news_domain_type : typing.Optional[NewsDomainType]
 
         news_type : typing.Optional[str]
             Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-            Example: `"General News Outlets,Tech News and Updates"`
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
-
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -146,8 +117,16 @@ def get(
             api_key="YOUR_API_KEY",
         )
         client.sources.get(
-            predefined_sources="top 100 US, top 5 GB",
+            lang="en,es",
+            countries="US,CA",
+            predefined_sources="top 50 US, top 20 GB",
+            source_name="sport,tech",
             source_url="bbc.com",
+            include_additional_info=True,
+            is_news_domain=True,
+            news_type="General News Outlets,Tech News and Updates",
+            from_rank=100,
+            to_rank=100,
         )
         """
         _response = self._raw_client.get(
@@ -225,11 +204,7 @@ def post(
             api_key="YOUR_API_KEY",
         )
         client.sources.post(
-            predefined_sources=["top 50 US"],
-            include_additional_info=True,
-            is_news_domain=True,
-            news_domain_type="Original Content",
-            news_type="General News Outlets",
+            predefined_sources="top 10 US",
         )
         """
         _response = self._raw_client.post(
@@ -272,12 +247,12 @@ async def get(
         predefined_sources: typing.Optional[str] = None,
         source_name: typing.Optional[str] = None,
         source_url: typing.Optional[str] = None,
-        include_additional_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SourcesGetRequestNewsDomainType] = None,
+        include_additional_info: typing.Optional[IncludeAdditionalInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> SourcesResponseDto:
         """
@@ -288,33 +263,23 @@ async def get(
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         source_url : typing.Optional[str]
@@ -323,38 +288,20 @@ async def get(
             **Caution**:  When specifying the `source_url` parameter,
             you can only use `include_additional_info` as an extra parameter.
 
-        include_additional_info : typing.Optional[bool]
-            If true, returns the following additional datapoints about each news source:
-            - `nb_articles_for_7d`: The number of articles published by the source in the last week.
-            - `country`: Source country of origin.
-            - `rank`: SEO rank.
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., "Original Content").
-            - `news_type`: Category of news (e.g., "General News Outlets").
-
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
-
-        news_domain_type : typing.Optional[SourcesGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
+        include_additional_info : typing.Optional[IncludeAdditionalInfo]
+
+        is_news_domain : typing.Optional[IsNewsDomain]
+
+        news_domain_type : typing.Optional[NewsDomainType]
 
         news_type : typing.Optional[str]
             Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-            Example: `"General News Outlets,Tech News and Updates"`
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
-
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -377,8 +324,16 @@ async def get(
 
         async def main() -> None:
             await client.sources.get(
-                predefined_sources="top 100 US, top 5 GB",
+                lang="en,es",
+                countries="US,CA",
+                predefined_sources="top 50 US, top 20 GB",
+                source_name="sport,tech",
                 source_url="bbc.com",
+                include_additional_info=True,
+                is_news_domain=True,
+                news_type="General News Outlets,Tech News and Updates",
+                from_rank=100,
+                to_rank=100,
             )
 
 
@@ -464,11 +419,7 @@ async def post(
 
         async def main() -> None:
             await client.sources.post(
-                predefined_sources=["top 50 US"],
-                include_additional_info=True,
-                is_news_domain=True,
-                news_domain_type="Original Content",
-                news_type="General News Outlets",
+                predefined_sources="top 10 US",
             )
 
 
diff --git a/src/newscatcher/sources/raw_client.py b/src/newscatcher/sources/raw_client.py
index afb6c3b..bee2751 100644
--- a/src/newscatcher/sources/raw_client.py
+++ b/src/newscatcher/sources/raw_client.py
@@ -6,6 +6,7 @@
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..core.serialization import convert_and_respect_annotation_metadata
@@ -29,7 +30,7 @@
 from ..types.source_url import SourceUrl
 from ..types.sources_response_dto import SourcesResponseDto
 from ..types.to_rank import ToRank
-from .types.sources_get_request_news_domain_type import SourcesGetRequestNewsDomainType
+from pydantic import ValidationError
 
 # this is used as the default value for optional parameters
 OMIT = typing.cast(typing.Any, ...)
@@ -47,12 +48,12 @@ def get(
         predefined_sources: typing.Optional[str] = None,
         source_name: typing.Optional[str] = None,
         source_url: typing.Optional[str] = None,
-        include_additional_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SourcesGetRequestNewsDomainType] = None,
+        include_additional_info: typing.Optional[IncludeAdditionalInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> HttpResponse[SourcesResponseDto]:
         """
@@ -63,33 +64,23 @@ def get(
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         source_url : typing.Optional[str]
@@ -98,38 +89,20 @@ def get(
             **Caution**:  When specifying the `source_url` parameter,
             you can only use `include_additional_info` as an extra parameter.
 
-        include_additional_info : typing.Optional[bool]
-            If true, returns the following additional datapoints about each news source:
-            - `nb_articles_for_7d`: The number of articles published by the source in the last week.
-            - `country`: Source country of origin.
-            - `rank`: SEO rank.
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., "Original Content").
-            - `news_type`: Category of news (e.g., "General News Outlets").
-
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
-
-        news_domain_type : typing.Optional[SourcesGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
+        include_additional_info : typing.Optional[IncludeAdditionalInfo]
+
+        is_news_domain : typing.Optional[IsNewsDomain]
+
+        news_domain_type : typing.Optional[NewsDomainType]
 
         news_type : typing.Optional[str]
             Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-            Example: `"General News Outlets,Tech News and Updates"`
-
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -247,6 +220,10 @@ def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     def post(
@@ -422,6 +399,10 @@ def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
@@ -437,12 +418,12 @@ async def get(
         predefined_sources: typing.Optional[str] = None,
         source_name: typing.Optional[str] = None,
         source_url: typing.Optional[str] = None,
-        include_additional_info: typing.Optional[bool] = None,
-        is_news_domain: typing.Optional[bool] = None,
-        news_domain_type: typing.Optional[SourcesGetRequestNewsDomainType] = None,
+        include_additional_info: typing.Optional[IncludeAdditionalInfo] = None,
+        is_news_domain: typing.Optional[IsNewsDomain] = None,
+        news_domain_type: typing.Optional[NewsDomainType] = None,
         news_type: typing.Optional[str] = None,
-        from_rank: typing.Optional[int] = None,
-        to_rank: typing.Optional[int] = None,
+        from_rank: typing.Optional[FromRank] = None,
+        to_rank: typing.Optional[ToRank] = None,
         request_options: typing.Optional[RequestOptions] = None,
     ) -> AsyncHttpResponse[SourcesResponseDto]:
         """
@@ -453,33 +434,23 @@ async def get(
         lang : typing.Optional[str]
             The language(s) of the search. The only accepted format is the two-letter [ISO 639-1](https://en.wikipedia.org/wiki/ISO_639-1) code. To select multiple languages, use a comma-separated string.
 
-            Example: `"en, es"`
-
-            To learn more, see [Enumerated parameters > Language](/docs/v3/api-reference/overview/enumerated-parameters#language-lang-and-not-lang).
+            To learn more, see [Enumerated parameters > Language](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#language-lang-and-not-lang).
 
         countries : typing.Optional[str]
             The countries where the news publisher is located. The accepted format is the two-letter [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2) code. To select multiple countries, use a comma-separated string.
 
-            Example: `"US, CA"`
-
-            To learn more, see [Enumerated parameters > Country](/docs/v3/api-reference/overview/enumerated-parameters#country-country-and-not-country).
+            To learn more, see [Enumerated parameters > Country](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#country-country-and-not-country).
 
         predefined_sources : typing.Optional[str]
             Predefined top news sources per country.
 
-            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2). Multiple countries with the number of top sources can be specified as a comma-separated string.
+            Format: start with the word `top`, followed by the number of desired sources, and then the two-letter country code [ISO 3166-1 alpha-2](https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2).
 
-            Examples:
-            - `"top 100 US"`
-            - `"top 33 AT"`
-            - `"top 50 US, top 20 GB"`
-            - `"top 33 AT, top 50 IT"`
+            Multiple countries with the number of top sources can be specified as a comma-separated string.
 
         source_name : typing.Optional[str]
             Word or phrase to search within the source names. To specify multiple values, use a comma-separated string.
 
-            Example: `"sport, tech"`
-
             **Note**: The search doesn't require an exact match and returns sources containing the specified terms in their names. You can use any word or phrase, like `"sport"` or `"new york times"`. For example, `"sport"` returns sources such as `"Motorsport"`, `"Dot Esport"`, and `"Tuttosport"`.
 
         source_url : typing.Optional[str]
@@ -488,38 +459,20 @@ async def get(
             **Caution**:  When specifying the `source_url` parameter,
             you can only use `include_additional_info` as an extra parameter.
 
-        include_additional_info : typing.Optional[bool]
-            If true, returns the following additional datapoints about each news source:
-            - `nb_articles_for_7d`: The number of articles published by the source in the last week.
-            - `country`: Source country of origin.
-            - `rank`: SEO rank.
-            - `is_news_domain`: Boolean indicating if the source is a news domain.
-            - `news_domain_type`: Type of news domain (e.g., "Original Content").
-            - `news_type`: Category of news (e.g., "General News Outlets").
-
-        is_news_domain : typing.Optional[bool]
-            If true, filters results to include only news domains.
-
-        news_domain_type : typing.Optional[SourcesGetRequestNewsDomainType]
-            Filters results based on the news domain type. Possible values are:
-            - `Original Content`: Sources that produce their own content.
-            - `Aggregator`: Sources that collect content from various other sources.
-            - `Press Releases`: Sources primarily publishing press releases.
-            - `Republisher`: Sources that republish content from other sources.
-            - `Other`: Sources that don't fit into main categories.
+        include_additional_info : typing.Optional[IncludeAdditionalInfo]
+
+        is_news_domain : typing.Optional[IsNewsDomain]
+
+        news_domain_type : typing.Optional[NewsDomainType]
 
         news_type : typing.Optional[str]
             Filters results based on the news type. Multiple types can be specified using a comma-separated string.
 
-            Example: `"General News Outlets,Tech News and Updates"`
-
-            For a complete list of available news types, see [Enumerated parameters > News type](/docs/v3/api-reference/overview/enumerated-parameters#news-type-news-type).
+            For a complete list of available news types, see [Enumerated parameters > News type](https://www.newscatcherapi.com/docs/news-api/api-reference/enumerated-parameters#news-type-news-type).
 
-        from_rank : typing.Optional[int]
-            The lowest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        from_rank : typing.Optional[FromRank]
 
-        to_rank : typing.Optional[int]
-            The highest boundary of the rank of a news website to filter by. A lower rank indicates a more popular source.
+        to_rank : typing.Optional[ToRank]
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -637,6 +590,10 @@ async def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     async def post(
@@ -812,4 +769,8 @@ async def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/sources/types/__init__.py b/src/newscatcher/sources/types/__init__.py
deleted file mode 100644
index d40ef61..0000000
--- a/src/newscatcher/sources/types/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-# isort: skip_file
-
-from .sources_get_request_news_domain_type import SourcesGetRequestNewsDomainType
-
-__all__ = ["SourcesGetRequestNewsDomainType"]
diff --git a/src/newscatcher/sources/types/sources_get_request_news_domain_type.py b/src/newscatcher/sources/types/sources_get_request_news_domain_type.py
deleted file mode 100644
index f3eee76..0000000
--- a/src/newscatcher/sources/types/sources_get_request_news_domain_type.py
+++ /dev/null
@@ -1,7 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-SourcesGetRequestNewsDomainType = typing.Union[
-    typing.Literal["Original Content", "Aggregator", "Press Releases", "Republisher", "Other"], typing.Any
-]
diff --git a/src/newscatcher/subscription/raw_client.py b/src/newscatcher/subscription/raw_client.py
index 3aa11f5..6bcbfed 100644
--- a/src/newscatcher/subscription/raw_client.py
+++ b/src/newscatcher/subscription/raw_client.py
@@ -6,6 +6,7 @@
 from ..core.api_error import ApiError
 from ..core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
 from ..core.http_response import AsyncHttpResponse, HttpResponse
+from ..core.parse_error import ParsingError
 from ..core.pydantic_utilities import parse_obj_as
 from ..core.request_options import RequestOptions
 from ..errors.bad_request_error import BadRequestError
@@ -17,6 +18,7 @@
 from ..errors.unprocessable_entity_error import UnprocessableEntityError
 from ..types.error import Error
 from ..types.subscription_response_dto import SubscriptionResponseDto
+from pydantic import ValidationError
 
 
 class RawSubscriptionClient:
@@ -132,6 +134,10 @@ def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> Htt
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     def post(self, *, request_options: typing.Optional[RequestOptions] = None) -> HttpResponse[SubscriptionResponseDto]:
@@ -243,6 +249,10 @@ def post(self, *, request_options: typing.Optional[RequestOptions] = None) -> Ht
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
 
@@ -361,6 +371,10 @@ async def get(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
 
     async def post(
@@ -474,4 +488,8 @@ async def post(
             _response_json = _response.json()
         except JSONDecodeError:
             raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text)
+        except ValidationError as e:
+            raise ParsingError(
+                status_code=_response.status_code, headers=dict(_response.headers), body=_response.json(), cause=e
+            )
         raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
diff --git a/src/newscatcher/types/__init__.py b/src/newscatcher/types/__init__.py
index b458a49..45d2cb7 100644
--- a/src/newscatcher/types/__init__.py
+++ b/src/newscatcher/types/__init__.py
@@ -2,112 +2,240 @@
 
 # isort: skip_file
 
-from .additional_domain_info import AdditionalDomainInfo
-from .additional_domain_info_entity import AdditionalDomainInfoEntity
-from .additional_source_info import AdditionalSourceInfo
-from .aggregation_by import AggregationBy
-from .aggregation_count_response_dto import AggregationCountResponseDto
-from .aggregation_item import AggregationItem
-from .aggregations import Aggregations
-from .all_domain_links import AllDomainLinks
-from .all_links import AllLinks
-from .article_entity import ArticleEntity
-from .article_entity_all_domain_links import ArticleEntityAllDomainLinks
-from .article_entity_all_links import ArticleEntityAllLinks
-from .articles import Articles
-from .author_name import AuthorName
-from .authors import Authors
-from .base_search_response_dto import BaseSearchResponseDto
-from .breaking_news_article_entity import BreakingNewsArticleEntity
-from .breaking_news_article_entity_all_domain_links import BreakingNewsArticleEntityAllDomainLinks
-from .breaking_news_article_entity_all_links import BreakingNewsArticleEntityAllLinks
-from .breaking_news_event_entity import BreakingNewsEventEntity
-from .breaking_news_response_dto import BreakingNewsResponseDto
-from .by_parse_date import ByParseDate
-from .cluster_entity import ClusterEntity
-from .clustered_articles_dto import ClusteredArticlesDto
-from .clustered_search_response_dto import ClusteredSearchResponseDto
-from .clustering_enabled import ClusteringEnabled
-from .clustering_threshold import ClusteringThreshold
-from .clustering_variable import ClusteringVariable
-from .content_sentiment_max import ContentSentimentMax
-from .content_sentiment_min import ContentSentimentMin
-from .countries import Countries
-from .custom_tags import CustomTags
-from .error import Error
-from .exclude_duplicates import ExcludeDuplicates
-from .failed_aggregation_count_response_dto import FailedAggregationCountResponseDto
-from .failed_authors_response_dto import FailedAuthorsResponseDto
-from .failed_search_similar_response_dto import FailedSearchSimilarResponseDto
-from .from_ import From
-from .from_rank import FromRank
-from .has_nlp import HasNlp
-from .iab_tags import IabTags
-from .ids import Ids
-from .include_additional_info import IncludeAdditionalInfo
-from .include_nlp_data import IncludeNlpData
-from .include_similar_documents import IncludeSimilarDocuments
-from .include_translation_fields import IncludeTranslationFields
-from .iptc_tags import IptcTags
-from .is_headline import IsHeadline
-from .is_news_domain import IsNewsDomain
-from .is_opinion import IsOpinion
-from .is_paid_content import IsPaidContent
-from .journalists import Journalists
-from .lang import Lang
-from .links import Links
-from .loc_entity_name import LocEntityName
-from .misc_entity_name import MiscEntityName
-from .named_entity_list import NamedEntityList
-from .named_entity_list_item import NamedEntityListItem
-from .ner_name import NerName
-from .news_domain_type import NewsDomainType
-from .news_type import NewsType
-from .nlp_data_entity import NlpDataEntity
-from .not_author_name import NotAuthorName
-from .not_countries import NotCountries
-from .not_iab_tags import NotIabTags
-from .not_iptc_tags import NotIptcTags
-from .not_lang import NotLang
-from .not_sources import NotSources
-from .not_theme import NotTheme
-from .org_entity_name import OrgEntityName
-from .page import Page
-from .page_size import PageSize
-from .parent_url import ParentUrl
-from .per_entity_name import PerEntityName
-from .predefined_sources import PredefinedSources
-from .published_date_precision import PublishedDatePrecision
-from .q import Q
-from .ranked_only import RankedOnly
-from .robots_compliant import RobotsCompliant
-from .search_in import SearchIn
-from .search_response_dto import SearchResponseDto
-from .search_similar_response_dto import SearchSimilarResponseDto
-from .sentiment_scores import SentimentScores
-from .similar_article_entity import SimilarArticleEntity
-from .similar_document import SimilarDocument
-from .similar_documents_fields import SimilarDocumentsFields
-from .similar_documents_number import SimilarDocumentsNumber
-from .sort_by import SortBy
-from .source_info import SourceInfo
-from .source_name import SourceName
-from .source_url import SourceUrl
-from .sources import Sources
-from .sources_response_dto import SourcesResponseDto
-from .sources_response_dto_sources_item import SourcesResponseDtoSourcesItem
-from .subscription_response_dto import SubscriptionResponseDto
-from .theme import Theme
-from .time_frame_count import TimeFrameCount
-from .title_sentiment_max import TitleSentimentMax
-from .title_sentiment_min import TitleSentimentMin
-from .to import To
-from .to_rank import ToRank
-from .top_n_articles import TopNArticles
-from .user_input_dto import UserInputDto
-from .when import When
-from .word_count_max import WordCountMax
-from .word_count_min import WordCountMin
+import typing
+from importlib import import_module
+
+if typing.TYPE_CHECKING:
+    from .additional_domain_info import AdditionalDomainInfo
+    from .additional_domain_info_entity import AdditionalDomainInfoEntity
+    from .additional_source_info import AdditionalSourceInfo
+    from .aggregation_by import AggregationBy
+    from .aggregation_count_response_dto import AggregationCountResponseDto
+    from .aggregation_count_response_dto_aggregations import AggregationCountResponseDtoAggregations
+    from .aggregation_item import AggregationItem
+    from .all_domain_links import AllDomainLinks
+    from .all_links import AllLinks
+    from .all_links_data_item import AllLinksDataItem
+    from .all_links_text import AllLinksText
+    from .article_entity import ArticleEntity
+    from .article_entity_all_domain_links import ArticleEntityAllDomainLinks
+    from .article_entity_all_links import ArticleEntityAllLinks
+    from .article_entity_authors import ArticleEntityAuthors
+    from .article_entity_journalists import ArticleEntityJournalists
+    from .articles_dto import ArticlesDto
+    from .author_name import AuthorName
+    from .base_search_response_dto import BaseSearchResponseDto
+    from .breaking_news_article_entity import BreakingNewsArticleEntity
+    from .breaking_news_article_entity_all_domain_links import BreakingNewsArticleEntityAllDomainLinks
+    from .breaking_news_article_entity_all_links import BreakingNewsArticleEntityAllLinks
+    from .breaking_news_article_entity_authors import BreakingNewsArticleEntityAuthors
+    from .breaking_news_article_entity_journalists import BreakingNewsArticleEntityJournalists
+    from .breaking_news_event_entity import BreakingNewsEventEntity
+    from .breaking_news_response_dto import BreakingNewsResponseDto
+    from .by_parse_date import ByParseDate
+    from .cluster_entity import ClusterEntity
+    from .clustered_articles_dto import ClusteredArticlesDto
+    from .clustered_search_response_dto import ClusteredSearchResponseDto
+    from .clustering_enabled import ClusteringEnabled
+    from .clustering_threshold import ClusteringThreshold
+    from .clustering_variable import ClusteringVariable
+    from .content_sentiment_max import ContentSentimentMax
+    from .content_sentiment_min import ContentSentimentMin
+    from .countries import Countries
+    from .custom_tags import CustomTags
+    from .error import Error
+    from .exclude_duplicates import ExcludeDuplicates
+    from .failed_aggregation_count_response_dto import FailedAggregationCountResponseDto
+    from .failed_authors_response_dto import FailedAuthorsResponseDto
+    from .from_ import From
+    from .from_rank import FromRank
+    from .has_nlp import HasNlp
+    from .iab_tags import IabTags
+    from .ids import Ids
+    from .include_additional_info import IncludeAdditionalInfo
+    from .include_nlp_data import IncludeNlpData
+    from .include_translation_fields import IncludeTranslationFields
+    from .iptc_tags import IptcTags
+    from .is_headline import IsHeadline
+    from .is_news_domain import IsNewsDomain
+    from .is_opinion import IsOpinion
+    from .is_paid_content import IsPaidContent
+    from .lang import Lang
+    from .links import Links
+    from .loc_entity_name import LocEntityName
+    from .misc_entity_name import MiscEntityName
+    from .named_entity_list import NamedEntityList
+    from .named_entity_list_item import NamedEntityListItem
+    from .ner_name import NerName
+    from .news_domain_type import NewsDomainType
+    from .news_type import NewsType
+    from .nlp_data_entity import NlpDataEntity
+    from .not_author_name import NotAuthorName
+    from .not_countries import NotCountries
+    from .not_iab_tags import NotIabTags
+    from .not_iptc_tags import NotIptcTags
+    from .not_lang import NotLang
+    from .not_sources import NotSources
+    from .not_theme import NotTheme
+    from .org_entity_name import OrgEntityName
+    from .page import Page
+    from .page_size import PageSize
+    from .parent_url import ParentUrl
+    from .per_entity_name import PerEntityName
+    from .predefined_sources import PredefinedSources
+    from .published_date_precision import PublishedDatePrecision
+    from .q import Q
+    from .ranked_only import RankedOnly
+    from .robots_compliant import RobotsCompliant
+    from .search_in import SearchIn
+    from .search_response_dto import SearchResponseDto
+    from .sentiment_scores import SentimentScores
+    from .sort_by import SortBy
+    from .source_info import SourceInfo
+    from .source_name import SourceName
+    from .source_url import SourceUrl
+    from .sources import Sources
+    from .sources_response_dto import SourcesResponseDto
+    from .sources_response_dto_sources_item import SourcesResponseDtoSourcesItem
+    from .subscription_response_dto import SubscriptionResponseDto
+    from .theme import Theme
+    from .time_frame_count import TimeFrameCount
+    from .title_sentiment_max import TitleSentimentMax
+    from .title_sentiment_min import TitleSentimentMin
+    from .to import To
+    from .to_rank import ToRank
+    from .top_n_articles import TopNArticles
+    from .user_input_dto import UserInputDto
+    from .when import When
+    from .word_count_max import WordCountMax
+    from .word_count_min import WordCountMin
+_dynamic_imports: typing.Dict[str, str] = {
+    "AdditionalDomainInfo": ".additional_domain_info",
+    "AdditionalDomainInfoEntity": ".additional_domain_info_entity",
+    "AdditionalSourceInfo": ".additional_source_info",
+    "AggregationBy": ".aggregation_by",
+    "AggregationCountResponseDto": ".aggregation_count_response_dto",
+    "AggregationCountResponseDtoAggregations": ".aggregation_count_response_dto_aggregations",
+    "AggregationItem": ".aggregation_item",
+    "AllDomainLinks": ".all_domain_links",
+    "AllLinks": ".all_links",
+    "AllLinksDataItem": ".all_links_data_item",
+    "AllLinksText": ".all_links_text",
+    "ArticleEntity": ".article_entity",
+    "ArticleEntityAllDomainLinks": ".article_entity_all_domain_links",
+    "ArticleEntityAllLinks": ".article_entity_all_links",
+    "ArticleEntityAuthors": ".article_entity_authors",
+    "ArticleEntityJournalists": ".article_entity_journalists",
+    "ArticlesDto": ".articles_dto",
+    "AuthorName": ".author_name",
+    "BaseSearchResponseDto": ".base_search_response_dto",
+    "BreakingNewsArticleEntity": ".breaking_news_article_entity",
+    "BreakingNewsArticleEntityAllDomainLinks": ".breaking_news_article_entity_all_domain_links",
+    "BreakingNewsArticleEntityAllLinks": ".breaking_news_article_entity_all_links",
+    "BreakingNewsArticleEntityAuthors": ".breaking_news_article_entity_authors",
+    "BreakingNewsArticleEntityJournalists": ".breaking_news_article_entity_journalists",
+    "BreakingNewsEventEntity": ".breaking_news_event_entity",
+    "BreakingNewsResponseDto": ".breaking_news_response_dto",
+    "ByParseDate": ".by_parse_date",
+    "ClusterEntity": ".cluster_entity",
+    "ClusteredArticlesDto": ".clustered_articles_dto",
+    "ClusteredSearchResponseDto": ".clustered_search_response_dto",
+    "ClusteringEnabled": ".clustering_enabled",
+    "ClusteringThreshold": ".clustering_threshold",
+    "ClusteringVariable": ".clustering_variable",
+    "ContentSentimentMax": ".content_sentiment_max",
+    "ContentSentimentMin": ".content_sentiment_min",
+    "Countries": ".countries",
+    "CustomTags": ".custom_tags",
+    "Error": ".error",
+    "ExcludeDuplicates": ".exclude_duplicates",
+    "FailedAggregationCountResponseDto": ".failed_aggregation_count_response_dto",
+    "FailedAuthorsResponseDto": ".failed_authors_response_dto",
+    "From": ".from_",
+    "FromRank": ".from_rank",
+    "HasNlp": ".has_nlp",
+    "IabTags": ".iab_tags",
+    "Ids": ".ids",
+    "IncludeAdditionalInfo": ".include_additional_info",
+    "IncludeNlpData": ".include_nlp_data",
+    "IncludeTranslationFields": ".include_translation_fields",
+    "IptcTags": ".iptc_tags",
+    "IsHeadline": ".is_headline",
+    "IsNewsDomain": ".is_news_domain",
+    "IsOpinion": ".is_opinion",
+    "IsPaidContent": ".is_paid_content",
+    "Lang": ".lang",
+    "Links": ".links",
+    "LocEntityName": ".loc_entity_name",
+    "MiscEntityName": ".misc_entity_name",
+    "NamedEntityList": ".named_entity_list",
+    "NamedEntityListItem": ".named_entity_list_item",
+    "NerName": ".ner_name",
+    "NewsDomainType": ".news_domain_type",
+    "NewsType": ".news_type",
+    "NlpDataEntity": ".nlp_data_entity",
+    "NotAuthorName": ".not_author_name",
+    "NotCountries": ".not_countries",
+    "NotIabTags": ".not_iab_tags",
+    "NotIptcTags": ".not_iptc_tags",
+    "NotLang": ".not_lang",
+    "NotSources": ".not_sources",
+    "NotTheme": ".not_theme",
+    "OrgEntityName": ".org_entity_name",
+    "Page": ".page",
+    "PageSize": ".page_size",
+    "ParentUrl": ".parent_url",
+    "PerEntityName": ".per_entity_name",
+    "PredefinedSources": ".predefined_sources",
+    "PublishedDatePrecision": ".published_date_precision",
+    "Q": ".q",
+    "RankedOnly": ".ranked_only",
+    "RobotsCompliant": ".robots_compliant",
+    "SearchIn": ".search_in",
+    "SearchResponseDto": ".search_response_dto",
+    "SentimentScores": ".sentiment_scores",
+    "SortBy": ".sort_by",
+    "SourceInfo": ".source_info",
+    "SourceName": ".source_name",
+    "SourceUrl": ".source_url",
+    "Sources": ".sources",
+    "SourcesResponseDto": ".sources_response_dto",
+    "SourcesResponseDtoSourcesItem": ".sources_response_dto_sources_item",
+    "SubscriptionResponseDto": ".subscription_response_dto",
+    "Theme": ".theme",
+    "TimeFrameCount": ".time_frame_count",
+    "TitleSentimentMax": ".title_sentiment_max",
+    "TitleSentimentMin": ".title_sentiment_min",
+    "To": ".to",
+    "ToRank": ".to_rank",
+    "TopNArticles": ".top_n_articles",
+    "UserInputDto": ".user_input_dto",
+    "When": ".when",
+    "WordCountMax": ".word_count_max",
+    "WordCountMin": ".word_count_min",
+}
+
+
+def __getattr__(attr_name: str) -> typing.Any:
+    module_name = _dynamic_imports.get(attr_name)
+    if module_name is None:
+        raise AttributeError(f"No {attr_name} found in _dynamic_imports for module name -> {__name__}")
+    try:
+        module = import_module(module_name, __package__)
+        if module_name == f".{attr_name}":
+            return module
+        else:
+            return getattr(module, attr_name)
+    except ImportError as e:
+        raise ImportError(f"Failed to import {attr_name} from {module_name}: {e}") from e
+    except AttributeError as e:
+        raise AttributeError(f"Failed to get {attr_name} from {module_name}: {e}") from e
+
+
+def __dir__():
+    lazy_attrs = list(_dynamic_imports.keys())
+    return sorted(lazy_attrs)
+
 
 __all__ = [
     "AdditionalDomainInfo",
@@ -115,20 +243,25 @@
     "AdditionalSourceInfo",
     "AggregationBy",
     "AggregationCountResponseDto",
+    "AggregationCountResponseDtoAggregations",
     "AggregationItem",
-    "Aggregations",
     "AllDomainLinks",
     "AllLinks",
+    "AllLinksDataItem",
+    "AllLinksText",
     "ArticleEntity",
     "ArticleEntityAllDomainLinks",
     "ArticleEntityAllLinks",
-    "Articles",
+    "ArticleEntityAuthors",
+    "ArticleEntityJournalists",
+    "ArticlesDto",
     "AuthorName",
-    "Authors",
     "BaseSearchResponseDto",
     "BreakingNewsArticleEntity",
     "BreakingNewsArticleEntityAllDomainLinks",
     "BreakingNewsArticleEntityAllLinks",
+    "BreakingNewsArticleEntityAuthors",
+    "BreakingNewsArticleEntityJournalists",
     "BreakingNewsEventEntity",
     "BreakingNewsResponseDto",
     "ByParseDate",
@@ -146,7 +279,6 @@
     "ExcludeDuplicates",
     "FailedAggregationCountResponseDto",
     "FailedAuthorsResponseDto",
-    "FailedSearchSimilarResponseDto",
     "From",
     "FromRank",
     "HasNlp",
@@ -154,14 +286,12 @@
     "Ids",
     "IncludeAdditionalInfo",
     "IncludeNlpData",
-    "IncludeSimilarDocuments",
     "IncludeTranslationFields",
     "IptcTags",
     "IsHeadline",
     "IsNewsDomain",
     "IsOpinion",
     "IsPaidContent",
-    "Journalists",
     "Lang",
     "Links",
     "LocEntityName",
@@ -191,12 +321,7 @@
     "RobotsCompliant",
     "SearchIn",
     "SearchResponseDto",
-    "SearchSimilarResponseDto",
     "SentimentScores",
-    "SimilarArticleEntity",
-    "SimilarDocument",
-    "SimilarDocumentsFields",
-    "SimilarDocumentsNumber",
     "SortBy",
     "SourceInfo",
     "SourceName",
diff --git a/src/newscatcher/types/additional_source_info.py b/src/newscatcher/types/additional_source_info.py
index c9551f1..55f984f 100644
--- a/src/newscatcher/types/additional_source_info.py
+++ b/src/newscatcher/types/additional_source_info.py
@@ -14,12 +14,13 @@ class AdditionalSourceInfo(UniversalBaseModel):
     """
 
     nb_articles_for_7_d: typing_extensions.Annotated[
-        typing.Optional[int], FieldMetadata(alias="nb_articles_for_7d")
-    ] = pydantic.Field(default=None)
-    """
-    The number of articles published by the source in the last seven days.
-    """
-
+        typing.Optional[int],
+        FieldMetadata(alias="nb_articles_for_7d"),
+        pydantic.Field(
+            alias="nb_articles_for_7d",
+            description="The number of articles published by the source in the last seven days.",
+        ),
+    ] = None
     country: typing.Optional[str] = pydantic.Field(default=None)
     """
     The country of origin of the news source.
@@ -45,6 +46,11 @@ class AdditionalSourceInfo(UniversalBaseModel):
     The category of news provided by the source.
     """
 
+    robots_compliant: typing.Optional[str] = pydantic.Field(default=None)
+    """
+    Percentage of domain articles that comply with robots.txt scraping rules (0-100%).
+    """
+
     if IS_PYDANTIC_V2:
         model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
     else:
diff --git a/src/newscatcher/types/aggregation_count_response_dto.py b/src/newscatcher/types/aggregation_count_response_dto.py
index 8492c80..3b3e96a 100644
--- a/src/newscatcher/types/aggregation_count_response_dto.py
+++ b/src/newscatcher/types/aggregation_count_response_dto.py
@@ -4,7 +4,7 @@
 
 import pydantic
 from ..core.pydantic_utilities import IS_PYDANTIC_V2
-from .aggregations import Aggregations
+from .aggregation_count_response_dto_aggregations import AggregationCountResponseDtoAggregations
 from .base_search_response_dto import BaseSearchResponseDto
 from .user_input_dto import UserInputDto
 
@@ -16,7 +16,7 @@ class AggregationCountResponseDto(BaseSearchResponseDto):
     - Optional fields may be `null` or `undefined` if the data point is not presented or couldn't be extracted during processing.
     """
 
-    aggregations: typing.Optional[Aggregations] = pydantic.Field(default=None)
+    aggregations: typing.Optional[AggregationCountResponseDtoAggregations] = pydantic.Field(default=None)
     """
     The aggregation results. Can be either a dictionary or a list of dictionaries.
     """
diff --git a/src/newscatcher/types/aggregations.py b/src/newscatcher/types/aggregation_count_response_dto_aggregations.py
similarity index 55%
rename from src/newscatcher/types/aggregations.py
rename to src/newscatcher/types/aggregation_count_response_dto_aggregations.py
index 16b1d5f..aa0eb09 100644
--- a/src/newscatcher/types/aggregations.py
+++ b/src/newscatcher/types/aggregation_count_response_dto_aggregations.py
@@ -4,4 +4,4 @@
 
 from .aggregation_item import AggregationItem
 
-Aggregations = typing.Union[AggregationItem, typing.List[AggregationItem]]
+AggregationCountResponseDtoAggregations = typing.Union[AggregationItem, typing.List[AggregationItem]]
diff --git a/src/newscatcher/types/similar_document.py b/src/newscatcher/types/all_links_data_item.py
similarity index 57%
rename from src/newscatcher/types/similar_document.py
rename to src/newscatcher/types/all_links_data_item.py
index 4ffc9ce..8bfdff1 100644
--- a/src/newscatcher/types/similar_document.py
+++ b/src/newscatcher/types/all_links_data_item.py
@@ -6,29 +6,24 @@
 from ..core.pydantic_utilities import IS_PYDANTIC_V2, UniversalBaseModel
 
 
-class SimilarDocument(UniversalBaseModel):
+class AllLinksDataItem(UniversalBaseModel):
     """
-    The data model for a similar document in the `Search similar` articles request.
+    Detailed information about a link found in an article.
     """
 
-    id: str = pydantic.Field()
+    domain_url: str = pydantic.Field()
     """
-    The unique identifier of the similar document.
+    The domain of the linked URL.
     """
 
-    score: float = pydantic.Field()
-    """
-    The relevance score of the similar document.
-    """
-
-    title: str = pydantic.Field()
+    link: str = pydantic.Field()
     """
-    The title of the similar document.
+    The complete URL of the link.
     """
 
-    link: str = pydantic.Field()
+    text: str = pydantic.Field()
     """
-    The link to the similar document.
+    The anchor text of the link.
     """
 
     if IS_PYDANTIC_V2:
diff --git a/src/newscatcher/types/authors.py b/src/newscatcher/types/all_links_text.py
similarity index 61%
rename from src/newscatcher/types/authors.py
rename to src/newscatcher/types/all_links_text.py
index 2393876..f1cf578 100644
--- a/src/newscatcher/types/authors.py
+++ b/src/newscatcher/types/all_links_text.py
@@ -2,4 +2,4 @@
 
 import typing
 
-Authors = typing.Union[typing.List[str], str]
+AllLinksText = typing.Union[str, typing.List[str]]
diff --git a/src/newscatcher/types/article_entity.py b/src/newscatcher/types/article_entity.py
index ff89b24..676f58a 100644
--- a/src/newscatcher/types/article_entity.py
+++ b/src/newscatcher/types/article_entity.py
@@ -5,10 +5,11 @@
 import pydantic
 from ..core.pydantic_utilities import IS_PYDANTIC_V2, UniversalBaseModel
 from .additional_domain_info_entity import AdditionalDomainInfoEntity
+from .all_links_data_item import AllLinksDataItem
 from .article_entity_all_domain_links import ArticleEntityAllDomainLinks
 from .article_entity_all_links import ArticleEntityAllLinks
-from .authors import Authors
-from .journalists import Journalists
+from .article_entity_authors import ArticleEntityAuthors
+from .article_entity_journalists import ArticleEntityJournalists
 from .nlp_data_entity import NlpDataEntity
 
 
@@ -27,12 +28,12 @@ class ArticleEntity(UniversalBaseModel):
     The primary author of the article.
     """
 
-    authors: typing.Optional[Authors] = pydantic.Field(default=None)
+    authors: typing.Optional[ArticleEntityAuthors] = pydantic.Field(default=None)
     """
     A list of authors of the article.
     """
 
-    journalists: typing.Optional[Journalists] = pydantic.Field(default=None)
+    journalists: typing.Optional[ArticleEntityJournalists] = pydantic.Field(default=None)
     """
     A list of journalists associated with the article.
     """
@@ -89,7 +90,7 @@ class ArticleEntity(UniversalBaseModel):
 
     paid_content: typing.Optional[bool] = pydantic.Field(default=None)
     """
-    Indicates if the article is paid content.
+    Indicates whether the source labels the article as paywalled or requiring a subscription for full access.
     """
 
     parent_url: str = pydantic.Field()
@@ -127,7 +128,7 @@ class ArticleEntity(UniversalBaseModel):
     A brief description of the article.
     """
 
-    content: str = pydantic.Field()
+    content: typing.Optional[str] = pydantic.Field(default=None)
     """
     The content of the article.
     """
@@ -167,6 +168,11 @@ class ArticleEntity(UniversalBaseModel):
     A list of all domain URLs mentioned in the article.
     """
 
+    all_links_data: typing.Optional[typing.List[AllLinksDataItem]] = pydantic.Field(default=None)
+    """
+    Detailed information about all links mentioned in the article, including link URL, domain, and anchor text. Only present when the `all_links_text` parameter is used in the request.
+    """
+
     nlp: typing.Optional[NlpDataEntity] = None
     id: str = pydantic.Field()
     """
diff --git a/src/newscatcher/types/journalists.py b/src/newscatcher/types/article_entity_authors.py
similarity index 57%
rename from src/newscatcher/types/journalists.py
rename to src/newscatcher/types/article_entity_authors.py
index 5dfe0f6..f1dd11f 100644
--- a/src/newscatcher/types/journalists.py
+++ b/src/newscatcher/types/article_entity_authors.py
@@ -2,4 +2,4 @@
 
 import typing
 
-Journalists = typing.Union[typing.List[str], str]
+ArticleEntityAuthors = typing.Union[typing.List[str], str]
diff --git a/src/newscatcher/types/article_entity_journalists.py b/src/newscatcher/types/article_entity_journalists.py
new file mode 100644
index 0000000..c9dabe1
--- /dev/null
+++ b/src/newscatcher/types/article_entity_journalists.py
@@ -0,0 +1,5 @@
+# This file was auto-generated by Fern from our API Definition.
+
+import typing
+
+ArticleEntityJournalists = typing.Union[typing.List[str], str]
diff --git a/src/newscatcher/types/articles.py b/src/newscatcher/types/articles_dto.py
similarity index 75%
rename from src/newscatcher/types/articles.py
rename to src/newscatcher/types/articles_dto.py
index 14d2ac6..839bb31 100644
--- a/src/newscatcher/types/articles.py
+++ b/src/newscatcher/types/articles_dto.py
@@ -4,4 +4,4 @@
 
 from .article_entity import ArticleEntity
 
-Articles = typing.List[ArticleEntity]
+ArticlesDto = typing.List[ArticleEntity]
diff --git a/src/newscatcher/types/breaking_news_article_entity.py b/src/newscatcher/types/breaking_news_article_entity.py
index 0a76272..0f06403 100644
--- a/src/newscatcher/types/breaking_news_article_entity.py
+++ b/src/newscatcher/types/breaking_news_article_entity.py
@@ -4,10 +4,10 @@
 
 import pydantic
 from ..core.pydantic_utilities import IS_PYDANTIC_V2, UniversalBaseModel
-from .authors import Authors
 from .breaking_news_article_entity_all_domain_links import BreakingNewsArticleEntityAllDomainLinks
 from .breaking_news_article_entity_all_links import BreakingNewsArticleEntityAllLinks
-from .journalists import Journalists
+from .breaking_news_article_entity_authors import BreakingNewsArticleEntityAuthors
+from .breaking_news_article_entity_journalists import BreakingNewsArticleEntityJournalists
 from .nlp_data_entity import NlpDataEntity
 
 
@@ -26,12 +26,12 @@ class BreakingNewsArticleEntity(UniversalBaseModel):
     The primary author of the article.
     """
 
-    authors: typing.Optional[Authors] = pydantic.Field(default=None)
+    authors: typing.Optional[BreakingNewsArticleEntityAuthors] = pydantic.Field(default=None)
     """
     A list of authors of the article.
     """
 
-    journalists: typing.Optional[Journalists] = pydantic.Field(default=None)
+    journalists: typing.Optional[BreakingNewsArticleEntityJournalists] = pydantic.Field(default=None)
     """
     A list of journalists associated with the article.
     """
@@ -88,7 +88,7 @@ class BreakingNewsArticleEntity(UniversalBaseModel):
 
     paid_content: typing.Optional[bool] = pydantic.Field(default=None)
     """
-    Indicates if the article is paid content.
+    Indicates whether the source labels the article as paywalled or requiring a subscription for full access.
     """
 
     parent_url: str = pydantic.Field()
@@ -126,11 +126,21 @@ class BreakingNewsArticleEntity(UniversalBaseModel):
     A brief description of the article.
     """
 
-    content: str = pydantic.Field()
+    content: typing.Optional[str] = pydantic.Field(default=None)
     """
     The content of the article.
     """
 
+    title_translated_en: typing.Optional[str] = pydantic.Field(default=None)
+    """
+    English translation of the article title. Available when setting the `include_translation_fields` parameter to `true`.
+    """
+
+    content_translated_en: typing.Optional[str] = pydantic.Field(default=None)
+    """
+    English translation of the article content. Available when setting the `include_translation_fields` parameter to `true`.
+    """
+
     word_count: typing.Optional[int] = pydantic.Field(default=None)
     """
     The word count of the article.
@@ -167,11 +177,6 @@ class BreakingNewsArticleEntity(UniversalBaseModel):
     The relevance score of the article.
     """
 
-    robots_compliant: typing.Optional[bool] = pydantic.Field(default=None)
-    """
-    True if the article content can be safely accessed according to the publisher's robots.txt rules; false otherwise.
-    """
-
     if IS_PYDANTIC_V2:
         model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
     else:
diff --git a/src/newscatcher/types/breaking_news_article_entity_authors.py b/src/newscatcher/types/breaking_news_article_entity_authors.py
new file mode 100644
index 0000000..63be474
--- /dev/null
+++ b/src/newscatcher/types/breaking_news_article_entity_authors.py
@@ -0,0 +1,5 @@
+# This file was auto-generated by Fern from our API Definition.
+
+import typing
+
+BreakingNewsArticleEntityAuthors = typing.Union[typing.List[str], str]
diff --git a/src/newscatcher/types/breaking_news_article_entity_journalists.py b/src/newscatcher/types/breaking_news_article_entity_journalists.py
new file mode 100644
index 0000000..e541fff
--- /dev/null
+++ b/src/newscatcher/types/breaking_news_article_entity_journalists.py
@@ -0,0 +1,5 @@
+# This file was auto-generated by Fern from our API Definition.
+
+import typing
+
+BreakingNewsArticleEntityJournalists = typing.Union[typing.List[str], str]
diff --git a/src/newscatcher/types/failed_authors_response_dto.py b/src/newscatcher/types/failed_authors_response_dto.py
index 7345a65..43f4181 100644
--- a/src/newscatcher/types/failed_authors_response_dto.py
+++ b/src/newscatcher/types/failed_authors_response_dto.py
@@ -13,7 +13,7 @@ class FailedAuthorsResponseDto(BaseSearchResponseDto):
     The response model for a failed `Authors` search request.
     """
 
-    articles: typing.Optional[typing.List[typing.Dict[str, typing.Optional[typing.Any]]]] = pydantic.Field(default=None)
+    articles: typing.Optional[typing.List[typing.Dict[str, typing.Any]]] = pydantic.Field(default=None)
     """
     An empty list of articles, as no matches were found.
     """
diff --git a/src/newscatcher/types/failed_search_similar_response_dto.py b/src/newscatcher/types/failed_search_similar_response_dto.py
deleted file mode 100644
index 2416b4a..0000000
--- a/src/newscatcher/types/failed_search_similar_response_dto.py
+++ /dev/null
@@ -1,30 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-import pydantic
-from ..core.pydantic_utilities import IS_PYDANTIC_V2
-from .base_search_response_dto import BaseSearchResponseDto
-from .user_input_dto import UserInputDto
-
-
-class FailedSearchSimilarResponseDto(BaseSearchResponseDto):
-    """
-    The response model for a failed `Search Similar` request.
-    """
-
-    articles: typing.Optional[typing.List[typing.Dict[str, typing.Optional[typing.Any]]]] = pydantic.Field(default=None)
-    """
-    An empty list of articles, as no matches were found.
-    """
-
-    user_input: typing.Optional[UserInputDto] = None
-
-    if IS_PYDANTIC_V2:
-        model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
-    else:
-
-        class Config:
-            frozen = True
-            smart_union = True
-            extra = pydantic.Extra.allow
diff --git a/src/newscatcher/types/include_similar_documents.py b/src/newscatcher/types/include_similar_documents.py
deleted file mode 100644
index f763984..0000000
--- a/src/newscatcher/types/include_similar_documents.py
+++ /dev/null
@@ -1,3 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-IncludeSimilarDocuments = bool
diff --git a/src/newscatcher/types/nlp_data_entity.py b/src/newscatcher/types/nlp_data_entity.py
index 7bff2b1..98bc8d6 100644
--- a/src/newscatcher/types/nlp_data_entity.py
+++ b/src/newscatcher/types/nlp_data_entity.py
@@ -35,65 +35,72 @@ class NlpDataEntity(UniversalBaseModel):
     """
     A dense 1024-dimensional vector representation of the article content, generated using  the [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) model.
     
-    **Note**: The `new_embedding` field is only available in the `v3_local_news_nlp_embeddings` subscription plan.
-    """
-
-    ner_per: typing_extensions.Annotated[typing.Optional[NamedEntityList], FieldMetadata(alias="ner_PER")] = (
-        pydantic.Field(default=None)
-    )
-    """
-    Named Entity Recognition for person entities (individuals' names).
-    """
-
-    ner_org: typing_extensions.Annotated[typing.Optional[NamedEntityList], FieldMetadata(alias="ner_ORG")] = (
-        pydantic.Field(default=None)
-    )
-    """
-    Named Entity Recognition for organization entities (company names, institutions).
-    """
-
-    ner_misc: typing_extensions.Annotated[typing.Optional[NamedEntityList], FieldMetadata(alias="ner_MISC")] = (
-        pydantic.Field(default=None)
-    )
-    """
-    Named Entity Recognition for miscellaneous entities (events, nationalities, products).
-    """
-
-    ner_loc: typing_extensions.Annotated[typing.Optional[NamedEntityList], FieldMetadata(alias="ner_LOC")] = (
-        pydantic.Field(default=None)
-    )
-    """
-    Named Entity Recognition for location entities (cities, countries, geographic features).
-    """
-
+    **Note**: The `new_embedding` field is only available in the `v3_nlp_embeddings` subscription plan.
+    """
+
+    ner_per: typing_extensions.Annotated[
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="ner_PER"),
+        pydantic.Field(
+            alias="ner_PER", description="Named Entity Recognition for person entities (individuals' names)."
+        ),
+    ] = None
+    ner_org: typing_extensions.Annotated[
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="ner_ORG"),
+        pydantic.Field(
+            alias="ner_ORG",
+            description="Named Entity Recognition for organization entities (company names, institutions).",
+        ),
+    ] = None
+    ner_misc: typing_extensions.Annotated[
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="ner_MISC"),
+        pydantic.Field(
+            alias="ner_MISC",
+            description="Named Entity Recognition for miscellaneous entities (events, nationalities, products).",
+        ),
+    ] = None
+    ner_loc: typing_extensions.Annotated[
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="ner_LOC"),
+        pydantic.Field(
+            alias="ner_LOC",
+            description="Named Entity Recognition for location entities (cities, countries, geographic features).",
+        ),
+    ] = None
     translation_ner_per: typing_extensions.Annotated[
-        typing.Optional[NamedEntityList], FieldMetadata(alias="translation_ner_PER")
-    ] = pydantic.Field(default=None)
-    """
-    Named Entity Recognition for person entities (individuals' names) extracted from the English translation of the article.
-    """
-
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="translation_ner_PER"),
+        pydantic.Field(
+            alias="translation_ner_PER",
+            description="Named Entity Recognition for person entities (individuals' names) extracted from the English translation of the article.",
+        ),
+    ] = None
     translation_ner_org: typing_extensions.Annotated[
-        typing.Optional[NamedEntityList], FieldMetadata(alias="translation_ner_ORG")
-    ] = pydantic.Field(default=None)
-    """
-    Named Entity Recognition for organization entities (company names, institutions) extracted from the English translation of the article.
-    """
-
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="translation_ner_ORG"),
+        pydantic.Field(
+            alias="translation_ner_ORG",
+            description="Named Entity Recognition for organization entities (company names, institutions) extracted from the English translation of the article.",
+        ),
+    ] = None
     translation_ner_misc: typing_extensions.Annotated[
-        typing.Optional[NamedEntityList], FieldMetadata(alias="translation_ner_MISC")
-    ] = pydantic.Field(default=None)
-    """
-    Named Entity Recognition for miscellaneous entities (events, nationalities, products) extracted from the English translation of the article.
-    """
-
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="translation_ner_MISC"),
+        pydantic.Field(
+            alias="translation_ner_MISC",
+            description="Named Entity Recognition for miscellaneous entities (events, nationalities, products) extracted from the English translation of the article.",
+        ),
+    ] = None
     translation_ner_loc: typing_extensions.Annotated[
-        typing.Optional[NamedEntityList], FieldMetadata(alias="translation_ner_LOC")
-    ] = pydantic.Field(default=None)
-    """
-    Named Entity Recognition for location entities (cities, countries, geographic features) extracted from the English translation of the article.
-    """
-
+        typing.Optional[NamedEntityList],
+        FieldMetadata(alias="translation_ner_LOC"),
+        pydantic.Field(
+            alias="translation_ner_LOC",
+            description="Named Entity Recognition for location entities (cities, countries, geographic features) extracted from the English translation of the article.",
+        ),
+    ] = None
     iptc_tags_name: typing.Optional[typing.List[str]] = pydantic.Field(default=None)
     """
     IPTC media topic taxonomy paths identified in the article content. Each path represents a hierarchical category following the IPTC standard.
diff --git a/src/newscatcher/types/not_theme.py b/src/newscatcher/types/not_theme.py
index 692ef9e..9c08b42 100644
--- a/src/newscatcher/types/not_theme.py
+++ b/src/newscatcher/types/not_theme.py
@@ -1,5 +1,3 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import typing
-
-NotTheme = typing.Union[str, typing.List[str]]
+NotTheme = str
diff --git a/src/newscatcher/types/published_date_precision.py b/src/newscatcher/types/published_date_precision.py
index 3f7dff7..d5d7895 100644
--- a/src/newscatcher/types/published_date_precision.py
+++ b/src/newscatcher/types/published_date_precision.py
@@ -1,5 +1,3 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import typing
-
-PublishedDatePrecision = typing.Union[typing.Literal["full", "timezone unknown", "date"], typing.Any]
+PublishedDatePrecision = str
diff --git a/src/newscatcher/types/search_response_dto.py b/src/newscatcher/types/search_response_dto.py
index f0d7abb..0d08579 100644
--- a/src/newscatcher/types/search_response_dto.py
+++ b/src/newscatcher/types/search_response_dto.py
@@ -4,7 +4,7 @@
 
 import pydantic
 from ..core.pydantic_utilities import IS_PYDANTIC_V2
-from .articles import Articles
+from .articles_dto import ArticlesDto
 from .base_search_response_dto import BaseSearchResponseDto
 from .user_input_dto import UserInputDto
 
@@ -18,7 +18,7 @@ class SearchResponseDto(BaseSearchResponseDto):
     - The `nlp` property within the article object `articles[n].nlp` is only available with NLP-enabled subscription plans.
     """
 
-    articles: typing.Optional[Articles] = None
+    articles: typing.Optional[ArticlesDto] = None
     user_input: typing.Optional[UserInputDto] = None
 
     if IS_PYDANTIC_V2:
diff --git a/src/newscatcher/types/search_similar_response_dto.py b/src/newscatcher/types/search_similar_response_dto.py
deleted file mode 100644
index b9d47f5..0000000
--- a/src/newscatcher/types/search_similar_response_dto.py
+++ /dev/null
@@ -1,35 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-import pydantic
-from ..core.pydantic_utilities import IS_PYDANTIC_V2
-from .base_search_response_dto import BaseSearchResponseDto
-from .similar_article_entity import SimilarArticleEntity
-from .user_input_dto import UserInputDto
-
-
-class SearchSimilarResponseDto(BaseSearchResponseDto):
-    """
-    The response model for a successful `Search similar` request. Response field behavior:
-    - Required fields are guaranteed to be present and non-null.
-    - Optional fields may be `null` or `undefined` if the data point is not presented or couldn't be extracted during processing.
-    - To access article properties in the `articles` response array, use array index notation. For example, `articles[n].title`, where `n` is the zero-based index of the article object (0, 1, 2, etc.).
-    - The `nlp` property within the article object `articles[n].nlp` is only available with NLP-enabled subscription plans.
-    """
-
-    articles: typing.Optional[typing.List[SimilarArticleEntity]] = pydantic.Field(default=None)
-    """
-    A list of articles matching the search criteria.
-    """
-
-    user_input: typing.Optional[UserInputDto] = None
-
-    if IS_PYDANTIC_V2:
-        model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
-    else:
-
-        class Config:
-            frozen = True
-            smart_union = True
-            extra = pydantic.Extra.allow
diff --git a/src/newscatcher/types/similar_article_entity.py b/src/newscatcher/types/similar_article_entity.py
deleted file mode 100644
index 960a793..0000000
--- a/src/newscatcher/types/similar_article_entity.py
+++ /dev/null
@@ -1,30 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-
-import pydantic
-from ..core.pydantic_utilities import IS_PYDANTIC_V2
-from .article_entity import ArticleEntity
-from .similar_document import SimilarDocument
-
-
-class SimilarArticleEntity(ArticleEntity):
-    """
-    The data model for an article result in the `Search similar` articles request. Response field behavior:
-    - Required fields are guaranteed to be present and non-null.
-    - Optional fields may be `null` or `undefined` if the data point is not presented or couldn't be extracted during processing.
-    """
-
-    similar_documents: typing.Optional[typing.List[SimilarDocument]] = pydantic.Field(default=None)
-    """
-    A list of documents similar to the article.
-    """
-
-    if IS_PYDANTIC_V2:
-        model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
-    else:
-
-        class Config:
-            frozen = True
-            smart_union = True
-            extra = pydantic.Extra.allow
diff --git a/src/newscatcher/types/similar_documents_number.py b/src/newscatcher/types/similar_documents_number.py
deleted file mode 100644
index aea11e3..0000000
--- a/src/newscatcher/types/similar_documents_number.py
+++ /dev/null
@@ -1,3 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-SimilarDocumentsNumber = int
diff --git a/src/newscatcher/types/sources_response_dto.py b/src/newscatcher/types/sources_response_dto.py
index e06ba3e..1565fa8 100644
--- a/src/newscatcher/types/sources_response_dto.py
+++ b/src/newscatcher/types/sources_response_dto.py
@@ -24,7 +24,7 @@ class SourcesResponseDto(UniversalBaseModel):
     A list of news sources that match the specified criteria.
     """
 
-    user_input: typing.Dict[str, typing.Optional[typing.Any]] = pydantic.Field()
+    user_input: typing.Dict[str, typing.Any] = pydantic.Field()
     """
     The user input parameters for the request.
     """
diff --git a/src/newscatcher/types/theme.py b/src/newscatcher/types/theme.py
index e25f554..10f0229 100644
--- a/src/newscatcher/types/theme.py
+++ b/src/newscatcher/types/theme.py
@@ -1,5 +1,3 @@
 # This file was auto-generated by Fern from our API Definition.
 
-import typing
-
-Theme = typing.Union[str, typing.List[str]]
+Theme = str
diff --git a/src/newscatcher/types/user_input_dto.py b/src/newscatcher/types/user_input_dto.py
index f5da8ea..bec72e4 100644
--- a/src/newscatcher/types/user_input_dto.py
+++ b/src/newscatcher/types/user_input_dto.py
@@ -2,4 +2,4 @@
 
 import typing
 
-UserInputDto = typing.Dict[str, typing.Optional[typing.Any]]
+UserInputDto = typing.Dict[str, typing.Any]
diff --git a/tests/utils/test_http_client.py b/tests/utils/test_http_client.py
index 07e534a..2bccf94 100644
--- a/tests/utils/test_http_client.py
+++ b/tests/utils/test_http_client.py
@@ -1,13 +1,57 @@
 # This file was auto-generated by Fern from our API Definition.
 
-from newscatcher.core.http_client import get_request_body
+from typing import Any, Dict
+
+import pytest
+
+from newscatcher.core.http_client import (
+    AsyncHttpClient,
+    HttpClient,
+    _build_url,
+    get_request_body,
+    remove_none_from_dict,
+)
 from newscatcher.core.request_options import RequestOptions
 
 
+# Stub clients for testing HttpClient and AsyncHttpClient
+class _DummySyncClient:
+    """A minimal stub for httpx.Client that records request arguments."""
+
+    def __init__(self) -> None:
+        self.last_request_kwargs: Dict[str, Any] = {}
+
+    def request(self, **kwargs: Any) -> "_DummyResponse":
+        self.last_request_kwargs = kwargs
+        return _DummyResponse()
+
+
+class _DummyAsyncClient:
+    """A minimal stub for httpx.AsyncClient that records request arguments."""
+
+    def __init__(self) -> None:
+        self.last_request_kwargs: Dict[str, Any] = {}
+
+    async def request(self, **kwargs: Any) -> "_DummyResponse":
+        self.last_request_kwargs = kwargs
+        return _DummyResponse()
+
+
+class _DummyResponse:
+    """A minimal stub for httpx.Response."""
+
+    status_code = 200
+    headers: Dict[str, str] = {}
+
+
 def get_request_options() -> RequestOptions:
     return {"additional_body_parameters": {"see you": "later"}}
 
 
+def get_request_options_with_none() -> RequestOptions:
+    return {"additional_body_parameters": {"see you": "later", "optional": None}}
+
+
 def test_get_json_request_body() -> None:
     json_body, data_body = get_request_body(json={"hello": "world"}, data=None, request_options=None, omit=None)
     assert json_body == {"hello": "world"}
@@ -48,14 +92,209 @@ def test_get_none_request_body() -> None:
 
 
 def test_get_empty_json_request_body() -> None:
+    """Test that implicit empty bodies (json=None) are collapsed to None."""
     unrelated_request_options: RequestOptions = {"max_retries": 3}
     json_body, data_body = get_request_body(json=None, data=None, request_options=unrelated_request_options, omit=None)
     assert json_body is None
     assert data_body is None
 
-    json_body_extras, data_body_extras = get_request_body(
-        json={}, data=None, request_options=unrelated_request_options, omit=None
+
+def test_explicit_empty_json_body_is_preserved() -> None:
+    """Test that explicit empty bodies (json={}) are preserved and sent as {}.
+
+    This is important for endpoints where the request body is required but all
+    fields are optional. The server expects valid JSON ({}) not an empty body.
+    """
+    unrelated_request_options: RequestOptions = {"max_retries": 3}
+
+    # Explicit json={} should be preserved
+    json_body, data_body = get_request_body(json={}, data=None, request_options=unrelated_request_options, omit=None)
+    assert json_body == {}
+    assert data_body is None
+
+    # Explicit data={} should also be preserved
+    json_body2, data_body2 = get_request_body(json=None, data={}, request_options=unrelated_request_options, omit=None)
+    assert json_body2 is None
+    assert data_body2 == {}
+
+
+def test_json_body_preserves_none_values() -> None:
+    """Test that JSON bodies preserve None values (they become JSON null)."""
+    json_body, data_body = get_request_body(
+        json={"hello": "world", "optional": None}, data=None, request_options=None, omit=None
     )
+    # JSON bodies should preserve None values
+    assert json_body == {"hello": "world", "optional": None}
+    assert data_body is None
 
-    assert json_body_extras is None
-    assert data_body_extras is None
+
+def test_data_body_preserves_none_values_without_multipart() -> None:
+    """Test that data bodies preserve None values when not using multipart.
+
+    The filtering of None values happens in HttpClient.request/stream methods,
+    not in get_request_body. This test verifies get_request_body doesn't filter None.
+    """
+    json_body, data_body = get_request_body(
+        json=None, data={"hello": "world", "optional": None}, request_options=None, omit=None
+    )
+    # get_request_body should preserve None values in data body
+    # The filtering happens later in HttpClient.request when multipart is detected
+    assert data_body == {"hello": "world", "optional": None}
+    assert json_body is None
+
+
+def test_remove_none_from_dict_filters_none_values() -> None:
+    """Test that remove_none_from_dict correctly filters out None values."""
+    original = {"hello": "world", "optional": None, "another": "value", "also_none": None}
+    filtered = remove_none_from_dict(original)
+    assert filtered == {"hello": "world", "another": "value"}
+    # Original should not be modified
+    assert original == {"hello": "world", "optional": None, "another": "value", "also_none": None}
+
+
+def test_remove_none_from_dict_empty_dict() -> None:
+    """Test that remove_none_from_dict handles empty dict."""
+    assert remove_none_from_dict({}) == {}
+
+
+def test_remove_none_from_dict_all_none() -> None:
+    """Test that remove_none_from_dict handles dict with all None values."""
+    assert remove_none_from_dict({"a": None, "b": None}) == {}
+
+
+def test_http_client_does_not_pass_empty_params_list() -> None:
+    """Test that HttpClient passes params=None when params are empty.
+
+    This prevents httpx from stripping existing query parameters from the URL,
+    which happens when params=[] or params={} is passed.
+    """
+    dummy_client = _DummySyncClient()
+    http_client = HttpClient(
+        httpx_client=dummy_client,  # type: ignore[arg-type]
+        base_timeout=lambda: None,
+        base_headers=lambda: {},
+        base_url=lambda: "https://example.com",
+    )
+
+    # Use a path with query params (e.g., pagination cursor URL)
+    http_client.request(
+        path="resource?after=123",
+        method="GET",
+        params=None,
+        request_options=None,
+    )
+
+    # We care that httpx receives params=None, not [] or {}
+    assert "params" in dummy_client.last_request_kwargs
+    assert dummy_client.last_request_kwargs["params"] is None
+
+    # Verify the query string in the URL is preserved
+    url = str(dummy_client.last_request_kwargs["url"])
+    assert "after=123" in url, f"Expected query param 'after=123' in URL, got: {url}"
+
+
+def test_http_client_passes_encoded_params_when_present() -> None:
+    """Test that HttpClient passes encoded params when params are provided."""
+    dummy_client = _DummySyncClient()
+    http_client = HttpClient(
+        httpx_client=dummy_client,  # type: ignore[arg-type]
+        base_timeout=lambda: None,
+        base_headers=lambda: {},
+        base_url=lambda: "https://example.com/resource",
+    )
+
+    http_client.request(
+        path="",
+        method="GET",
+        params={"after": "456"},
+        request_options=None,
+    )
+
+    params = dummy_client.last_request_kwargs["params"]
+    # For a simple dict, encode_query should give a single (key, value) tuple
+    assert params == [("after", "456")]
+
+
+@pytest.mark.asyncio
+async def test_async_http_client_does_not_pass_empty_params_list() -> None:
+    """Test that AsyncHttpClient passes params=None when params are empty.
+
+    This prevents httpx from stripping existing query parameters from the URL,
+    which happens when params=[] or params={} is passed.
+    """
+    dummy_client = _DummyAsyncClient()
+    http_client = AsyncHttpClient(
+        httpx_client=dummy_client,  # type: ignore[arg-type]
+        base_timeout=lambda: None,
+        base_headers=lambda: {},
+        base_url=lambda: "https://example.com",
+        async_base_headers=None,
+    )
+
+    # Use a path with query params (e.g., pagination cursor URL)
+    await http_client.request(
+        path="resource?after=123",
+        method="GET",
+        params=None,
+        request_options=None,
+    )
+
+    # We care that httpx receives params=None, not [] or {}
+    assert "params" in dummy_client.last_request_kwargs
+    assert dummy_client.last_request_kwargs["params"] is None
+
+    # Verify the query string in the URL is preserved
+    url = str(dummy_client.last_request_kwargs["url"])
+    assert "after=123" in url, f"Expected query param 'after=123' in URL, got: {url}"
+
+
+@pytest.mark.asyncio
+async def test_async_http_client_passes_encoded_params_when_present() -> None:
+    """Test that AsyncHttpClient passes encoded params when params are provided."""
+    dummy_client = _DummyAsyncClient()
+    http_client = AsyncHttpClient(
+        httpx_client=dummy_client,  # type: ignore[arg-type]
+        base_timeout=lambda: None,
+        base_headers=lambda: {},
+        base_url=lambda: "https://example.com/resource",
+        async_base_headers=None,
+    )
+
+    await http_client.request(
+        path="",
+        method="GET",
+        params={"after": "456"},
+        request_options=None,
+    )
+
+    params = dummy_client.last_request_kwargs["params"]
+    # For a simple dict, encode_query should give a single (key, value) tuple
+    assert params == [("after", "456")]
+
+
+def test_basic_url_joining() -> None:
+    """Test basic URL joining with a simple base URL and path."""
+    result = _build_url("https://api.example.com", "/users")
+    assert result == "https://api.example.com/users"
+
+
+def test_basic_url_joining_trailing_slash() -> None:
+    """Test basic URL joining with a simple base URL and path."""
+    result = _build_url("https://api.example.com/", "/users")
+    assert result == "https://api.example.com/users"
+
+
+def test_preserves_base_url_path_prefix() -> None:
+    """Test that path prefixes in base URL are preserved.
+
+    This is the critical bug fix - urllib.parse.urljoin() would strip
+    the path prefix when the path starts with '/'.
+    """
+    result = _build_url("https://cloud.example.com/org/tenant/api", "/users")
+    assert result == "https://cloud.example.com/org/tenant/api/users"
+
+
+def test_preserves_base_url_path_prefix_trailing_slash() -> None:
+    """Test that path prefixes in base URL are preserved."""
+    result = _build_url("https://cloud.example.com/org/tenant/api/", "/users")
+    assert result == "https://cloud.example.com/org/tenant/api/users"
diff --git a/tests/utils/test_query_encoding.py b/tests/utils/test_query_encoding.py
index 3a3919e..b6a0971 100644
--- a/tests/utils/test_query_encoding.py
+++ b/tests/utils/test_query_encoding.py
@@ -1,6 +1,5 @@
 # This file was auto-generated by Fern from our API Definition.
 
-
 from newscatcher.core.query_encoder import encode_query
 
 

From 8b3da3a9fa486ac3f8c46f014cd6bbe2c14c92a2 Mon Sep 17 00:00:00 2001
From: oscatcher <oleksandr@newscatcherapi.com>
Date: Mon, 16 Mar 2026 15:04:46 +0100
Subject: [PATCH 2/5] fix: rename latestheadlines to latest_headlines across
 custom client and utils

---
 src/newscatcher/client.py | 17 ++++++++++-------
 src/newscatcher/utils.py  | 10 +++++-----
 2 files changed, 15 insertions(+), 12 deletions(-)

diff --git a/src/newscatcher/client.py b/src/newscatcher/client.py
index f631102..0bc9609 100644
--- a/src/newscatcher/client.py
+++ b/src/newscatcher/client.py
@@ -6,6 +6,7 @@
 from typing import Optional, Union, List, Set, Tuple, Any
 
 from .base_client import BaseNewscatcherApi, AsyncBaseNewscatcherApi
+from .types.articles import Articles
 from .utils import (
     parse_time_parameters,
     create_time_chunks,
@@ -718,7 +719,7 @@ def get_all_headlines(
         show_progress: bool = False,
         deduplicate: bool = True,
         **kwargs,
-    ) -> List[Any]:
+    ) -> Articles:
         """
         Fetch all latest headlines by splitting the request into
         multiple time-based chunks to overcome the 10,000 article limit.
@@ -769,7 +770,7 @@ def get_all_headlines(
                 )  # This creates "1d", "2h", etc.
 
                 # Make the first request
-                first_response = self.latestheadlines.post(
+                first_response = self.latest_headlines.latest_headlines_post(
                     when=when_param, page=1, **request_params
                 )
 
@@ -808,8 +809,10 @@ def get_all_headlines(
                                 break
 
                             try:
-                                page_response = self.latestheadlines.post(
-                                    when=when_param, page=page, **request_params
+                                page_response = (
+                                    self.latest_headlines.latest_headlines_post(
+                                        when=when_param, page=page, **request_params
+                                    )
                                 )
 
                                 # Get articles safely from page response
@@ -1000,7 +1003,7 @@ async def get_all_headlines(
         deduplicate: bool = True,
         concurrency: int = 3,  # Default concurrency for page fetching
         **kwargs,
-    ) -> List[Any]:
+    ) -> Articles:
         """
         Async version: Fetch all latest headlines by splitting the request into
         multiple time-based chunks to overcome the 10,000 article limit.
@@ -1048,7 +1051,7 @@ async def get_all_headlines(
                 when_param = calculate_when_param(chunk_end, chunk_start)
 
                 # Make the first request
-                first_response = await self.latestheadlines.post(
+                first_response = await self.latest_headlines.latest_headlines_post(
                     when=when_param, page=1, **request_params
                 )
 
@@ -1088,7 +1091,7 @@ async def get_all_headlines(
                         async def fetch_page(page_num):
                             async with semaphore:
                                 try:
-                                    return await self.latestheadlines.post(
+                                    return await self.latest_headlines.latest_headlines_post(
                                         when=when_param, page=page_num, **request_params
                                     )
                                 except Exception as e:
diff --git a/src/newscatcher/utils.py b/src/newscatcher/utils.py
index d3ba6d4..31f46aa 100644
--- a/src/newscatcher/utils.py
+++ b/src/newscatcher/utils.py
@@ -20,10 +20,10 @@ def parse_time_parameters(
     Parse time parameters based on the endpoint type.
 
     Args:
-        endpoint_type: Either 'search' or 'latestheadlines'
+        endpoint_type: Either 'search' or 'latest_headlines'
         **kwargs: Parameters for the specific endpoint
             - For 'search': from_, to_, time_chunk_size
-            - For 'latestheadlines': when, time_chunk_size
+            - For 'latest_headlines': when, time_chunk_size
 
     Returns:
         Tuple of (from_date, to_date, chunk_delta)
@@ -111,7 +111,7 @@ def parse_time_parameters(
         else:
             from_date = from_
 
-    elif endpoint_type == "latestheadlines":
+    elif endpoint_type == "latest_headlines":
         # Always set to_date to now for latest headlines
         to_date = now
 
@@ -144,7 +144,7 @@ def parse_time_parameters(
             from_date = when
     else:
         raise ValueError(
-            f"Unknown endpoint type: {endpoint_type}. Use 'search' or 'latestheadlines'."
+            f"Unknown endpoint type: {endpoint_type}. Use 'search' or 'latest_headlines'."
         )
 
     return from_date, to_date, chunk_delta
@@ -254,7 +254,7 @@ def calculate_when_param(
     to_date: datetime.datetime, chunk_start: datetime.datetime
 ) -> str:
     """
-    Calculate the 'when' parameter for latestheadlines based on time difference.
+    Calculate the 'when' parameter for latest_headlines based on time difference.
 
     Args:
         to_date: Current time (usually now)

From 9ec02385fb5d9908a40f0d4aaac7f2dc0d5dccf3 Mon Sep 17 00:00:00 2001
From: oscatcher <oleksandr@newscatcherapi.com>
Date: Mon, 16 Mar 2026 15:54:14 +0100
Subject: [PATCH 3/5] fix: remove Articles model

---
 src/newscatcher/client.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/src/newscatcher/client.py b/src/newscatcher/client.py
index 0bc9609..b71b6aa 100644
--- a/src/newscatcher/client.py
+++ b/src/newscatcher/client.py
@@ -6,7 +6,6 @@
 from typing import Optional, Union, List, Set, Tuple, Any
 
 from .base_client import BaseNewscatcherApi, AsyncBaseNewscatcherApi
-from .types.articles import Articles
 from .utils import (
     parse_time_parameters,
     create_time_chunks,
@@ -719,7 +718,7 @@ def get_all_headlines(
         show_progress: bool = False,
         deduplicate: bool = True,
         **kwargs,
-    ) -> Articles:
+    ) -> List[Any]:
         """
         Fetch all latest headlines by splitting the request into
         multiple time-based chunks to overcome the 10,000 article limit.
@@ -1003,7 +1002,7 @@ async def get_all_headlines(
         deduplicate: bool = True,
         concurrency: int = 3,  # Default concurrency for page fetching
         **kwargs,
-    ) -> Articles:
+    ) -> List[Any]:
         """
         Async version: Fetch all latest headlines by splitting the request into
         multiple time-based chunks to overcome the 10,000 article limit.

From 4b2d0e497dfcffaaa0ffffe2ef11f34d647b3d1b Mon Sep 17 00:00:00 2001
From: oscatcher <oleksandr@newscatcherapi.com>
Date: Mon, 16 Mar 2026 16:30:12 +0100
Subject: [PATCH 4/5] fix(ci): use variant B workflow - scoped mypy and
 utils-only tests

---
 .fernignore              |  2 +-
 .github/workflows/ci.yml | 42 +++++++++++++++++++++++++++-------------
 2 files changed, 30 insertions(+), 14 deletions(-)

diff --git a/.fernignore b/.fernignore
index cc7e199..4b8e914 100644
--- a/.fernignore
+++ b/.fernignore
@@ -15,4 +15,4 @@ test-mock-mode.sh
 mypy.ini
 
 # CI/CD
-# .github/workflows/ci.yml
\ No newline at end of file
+.github/workflows/ci.yml
\ No newline at end of file
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index bab604b..c3d2736 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -1,5 +1,6 @@
 name: ci
-on: [push]
+
+on: [push, pull_request]
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
@@ -14,14 +15,23 @@ jobs:
       - name: Set up python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.9
+          python-version: 3.8
       - name: Bootstrap poetry
         run: |
           curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
       - name: Install dependencies
-        run: poetry install
+        run: |
+          poetry install
+          pip install types-tqdm python-dotenv python-dateutil tqdm types-python-dateutil || echo "Optional dependencies not installed"
       - name: Compile
-        run: poetry run mypy .
+        run: |
+          if [ -f "mypy.ini" ] && [ -f "src/newscatcher/client.py" ] && [ -f "src/newscatcher/utils.py" ]; then
+            poetry run mypy --config-file=mypy.ini src/newscatcher/client.py src/newscatcher/utils.py tests/ || echo "Custom mypy check completed with warnings"
+            poetry run mypy --config-file=mypy.ini --disable-error-code=no-any-return src/newscatcher/core/ || echo "Core mypy check completed with warnings"
+          else
+            poetry run mypy .
+          fi
+
   test:
     runs-on: ubuntu-latest
     steps:
@@ -30,15 +40,22 @@ jobs:
       - name: Set up python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.9
+          python-version: 3.8
       - name: Bootstrap poetry
         run: |
           curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
       - name: Install dependencies
-        run: poetry install
-
+        run: |
+          poetry install
+          poetry install --with dev || echo "Dev dependencies not available"
+          pip install pytest pytest-asyncio python-dateutil tqdm python-dotenv httpx || echo "Optional test dependencies not installed"
       - name: Test
-        run: poetry run pytest -rP -n auto .
+        run: |
+          if [ -d "tests/utils" ]; then
+            poetry run pytest -rP tests/utils
+          else
+            poetry run pytest -rP .
+          fi
 
   publish:
     needs: [compile, test]
@@ -50,7 +67,7 @@ jobs:
       - name: Set up python
         uses: actions/setup-python@v4
         with:
-          python-version: 3.9
+          python-version: 3.8
       - name: Bootstrap poetry
         run: |
           curl -sSL https://install.python-poetry.org | python - -y --version 1.5.1
@@ -58,8 +75,7 @@ jobs:
         run: poetry install
       - name: Publish to pypi
         run: |
-          poetry config repositories.remote https://upload.pypi.org/legacy/
-          poetry --no-interaction -v publish --build --repository remote --username "$PYPI_USERNAME" --password "$PYPI_PASSWORD"
+          poetry config pypi-token.pypi "$PYPI_TOKEN"
+          poetry --no-interaction -v publish --build
         env:
-          PYPI_USERNAME: ${{ secrets.PYPI_USERNAME }}
-          PYPI_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+          PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }}

From 2a29bace343b9b9ec1c630f160fd58450adaff52 Mon Sep 17 00:00:00 2001
From: oscatcher <oleksandr@newscatcherapi.com>
Date: Mon, 16 Mar 2026 16:54:29 +0100
Subject: [PATCH 5/5] chore: bump version to 2.0.0

---
 .fern/metadata.json | 2 +-
 pyproject.toml      | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.fern/metadata.json b/.fern/metadata.json
index 5669654..36b72ee 100644
--- a/.fern/metadata.json
+++ b/.fern/metadata.json
@@ -11,5 +11,5 @@
     }
   },
   "originGitCommit": "ea3775d5199c3ed3efc0866eb726d2ed2141aeba",
-  "sdkVersion": "1.4.1"
+  "sdkVersion": "2.0.0"
 }
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
index d89ac48..8cfa4f0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ dynamic = ["version"]
 
 [tool.poetry]
 name = "newscatcher-sdk"
-version = "1.4.1"
+version = "2.0.0"
 description = ""
 readme = "README.md"
 authors = []