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78 changes: 78 additions & 0 deletions .github/workflows/ci.yml
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name: CI

on:
push:
branches: [main]
pull_request:

permissions:
contents: read

concurrency:
group: ci-${{ github.ref }}
cancel-in-progress: true

jobs:
python:
name: Python ${{ matrix.python }}
runs-on: ubuntu-latest
timeout-minutes: 20
strategy:
fail-fast: false
matrix:
python: ["3.11", "3.12"]
steps:
- uses: actions/checkout@v7.0.1

- uses: astral-sh/setup-uv@v10.3.3
with:
version: "0.13.6"
python-version: ${{ matrix.python }}

- name: Check the lockfile matches pyproject.toml
run: uv lock --check

# The locked Linux torch pulls about 3 GB of CUDA packages that a CI runner cannot use.
# Install the CPU build of torch, with every other package pinned to the version in uv.lock.
- name: Install locked versions (CPU torch)
run: |
uv export --frozen --no-hashes --no-emit-project -o "$RUNNER_TEMP/constraints.txt"
uv venv
uv pip install --torch-backend cpu -c "$RUNNER_TEMP/constraints.txt" -e . --group dev

# The rotation test writes rotation metadata with the ffmpeg CLI.
- name: Install ffmpeg
run: sudo apt-get update -q && sudo apt-get install -y -q ffmpeg

- name: Lint
run: |
uv run --no-sync ruff check src tests
uv run --no-sync ruff format --check src tests

- name: Test
run: uv run --no-sync pytest -q -rs

viewer-and-wheel:
name: Viewer and wheel
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- uses: actions/checkout@v7.0.1

- uses: actions/setup-node@v7.1.0
with:
node-version: 24
cache: npm
cache-dependency-path: web/package-lock.json

- uses: astral-sh/setup-uv@v10.3.3
with:
version: "0.13.6"

# Installs and type-checks the viewer, builds it and the wheel, and fails if the wheel lacks it.
- name: Build
run: ./scripts/build.sh

- name: Lint viewer
working-directory: web
run: npx oxlint src
2 changes: 2 additions & 0 deletions README.md
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@@ -1,5 +1,7 @@
# jepa-scope

[![CI](https://github.com/ryangswe/jepa-scope/actions/workflows/ci.yml/badge.svg)](https://github.com/ryangswe/jepa-scope/actions/workflows/ci.yml)

jepa-scope shows you what a JEPA video encoder sees. Point it at a video and it opens a local viewer
with the model's patch features drawn over the picture, plus a timeline of how surprised the model
was by each moment. It runs Meta's pre-trained V-JEPA 2 on a laptop, so you need no training run, no
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