application-example.toml

### vanling Configuration
###
### THIS FILE IS GENERATED. CHANGES/CONTRIBUTIONS IN THE REPO WILL BE
### OVERWRITTEN!
###
### You should rename this file before configuring your server. Changes to
### documentation and defaults can be contributed in source code at
### src/config/mod.rs. This file is generated when building.
###
### Any values pre-populated are the default values for said config option.
###
### At the minimum, you MUST edit all the config options to your environment
### that say "YOU NEED TO EDIT THIS".
###

[global]

# Server hostname displayed to clients.
#
#server_name = "localhost.localdomain"

# Base data directory for model files. All model paths are relative to this.
#
#data_dir = "data"

# The default address (IPv4 or IPv6)  will listen on.
#
# If you are using Docker or a container NAT networking setup, this must
# be "0.0.0.0".
#
#
#address = "127.0.0.1"

# The port(s) will listen on.
#
# If you are using Docker, don't change this, you'll need to map an
# external port to this.
#
#port = 3000

# Database connection URL.
#
#database_url = "sqlite://db.sqlite?mode=rwc"

# Secret key for signing JWT access tokens.
#
#auth_access_token_secret = "QLjJTeVblAlM47de"

# Access token expiry duration in seconds.
#
#auth_access_token_expires_in = 28800

# Secret key for signing JWT refresh tokens.
#
#auth_refresh_token_secret = "N8lI0uitNzJl6vYK"

# Refresh token expiry duration in seconds.
#
#auth_refresh_token_expires_in = 15897600

# JWT audience claim.
#
#auth_audience = "audience"

# JWT issuer claim.
#
#auth_issuer = "issuer"

# OAuth 2.0 client ID.
#
#auth_client_id = "d1aicsr57dijo7h963ig"

# OAuth 2.0 client secret.
#
#auth_client_secret = "ujTgh2lEQYy0PXhK"

# Named rate-limit resources matched by regex route patterns.
#
# Each entry is a table with:
# - `name`: unique resource name, surfaced via `x-ratelimit-resource`.
# - `limit` / `window_secs`: quota within the window.
# - `key_by`: `"ip"` (per peer address) or `"principal"` (per user).
# - `paths`: regex patterns against the request path; the FIRST resource
#   with a matching pattern owns the request, so list order is priority
#   (specific resources must precede broad ones such as `^/api/`).
# - `count`: optional, default `true`; `false` never records requests.
#
# Invalid names, duplicate patterns and unparseable regexes abort startup.
#
#security_rate_limit_resources = [{ name = "auth", limit = 20, window_secs = 900, key_by = "ip", paths = ["^/api/auth/"] }, { name = "ota", limit = 30, window_secs = 60, key_by = "ip", paths = ["^/api/ota"] }, { name = "mcp", limit = 5000, window_secs = 3600, key_by = "principal", paths = ["^/mcp"] }, { name = "core", limit = 5000, window_secs = 3600, key_by = "principal", paths = ["^/api/"] }]

# Per-account login failures allowed within the lockout window.
#
#security_login_fail_limit = 5

# Login failure lockout window in seconds.
#
#security_login_fail_window_secs = 900

# Security event retention in days before the cleanup loop deletes them.
#
#security_event_retention_days = 30

# Security retention cleanup interval in seconds.
#
#security_cleanup_interval_secs = 21600

# Whether every request matching `security_api_access_log_path_prefixes`
# is persisted to the access log table.
#
#security_api_access_log_enabled = true

# API access log retention in days before the cleanup loop deletes them.
#
#security_api_access_log_retention_days = 30

# Path prefixes whose requests are persisted to the access log table.
#
#security_api_access_log_path_prefixes = ["/api/", "/mcp"]

# WebSocket URL scheme (ws or wss).
#
#ws_schema = "ws"

# Available values: void, earshot.
#
# Voice Activity Detection model to use.
#
#vad_model = "earshot"

# Path to the VAD model file or directory.
#
#vad_path = "auto-derived from model+variant"

# Variant of the VAD model to load.
#
#vad_variant = "auto-detected"

# Number of threads for VAD inference.
#
#vad_num_threads = 4

# VAD detection threshold (0.0–1.0). Higher = fewer false positives, more false negatives.
#
#vad_threshold = 0.5

# VAD deactivation threshold for hysteresis. Must be < vad_threshold.
# Speech stops when score drops below this value during active speech.
#
#vad_deactivation_threshold = 0.35

# Minimum silence duration in ms before VAD considers speech ended.
#
#vad_min_silence_duration = 550

# Minimum continuous speech duration in ms before VAD triggers is_speech.
# Prevents short noise bursts from being classified as speech.
#
#vad_min_speech_duration = 300

# Available values: mute, matcha_tts.
#
# Text-to-Speech model to use.
#
#tts_model = "matcha_tts"

# Path to the TTS model file or directory.
#
#tts_path = "auto-derived from model manifest"

# Variant override for the active TTS model.
#
# When not set, the default variant is read from the embedded model manifest.
# This is useful for switching between different model variants without
# changing the model type.
#
#tts_variant = "auto-detected from model manifest"

# Variant override for the TTS reference audio.
#
#tts_reference_variant = "auto-detected from model manifest"

# Override the auto-derived prompt text from manifest.
#
#tts_reference_prompt_text = "auto-derived"

# Override the auto-derived prompt wav path from manifest.
#
#tts_reference_prompt_wav_path = "auto-derived"

# TTS model-specific options as a JSON object.
#
# For MatchaTTS:
#   - num_threads:     inference threads (default 2)
#   - noise_scale:     generation noise parameter (default 0.667)
#   - length_scale:    speed scaling (default auto-detected)
#   - speed:           playback speed (default 1.0)
#   - debug:           debug output (default false)
#   - dict_dir:        pronunciation dictionary directory
#   - data_dir:        espeak-ng data directory
#   - acoustic_model:  onnx path (auto-discovered)
#   - vocoder:         onnx path (auto-discovered)
#
#tts_options = {}

# Available values: xasr, void.
#
# Automatic Speech Recognition model to use.
#
#asr_model = "x_asr"

# Path to the ASR model file or directory.
#
#asr_path = "auto-derived from model+variant"

# Variant of the ASR model to load.
#
#asr_variant = "auto-detected from model manifest"

# Available values: local_qwen3, local_echo, remote_open_ai_compatible.
#
# LLM provider to use.
#
#llm_provider = "local_qwen3"

# Path to the local LLM model file or directory.
# Only used with local providers (local_qwen3, local_echo).
#
#llm_path = "auto-derived from model+variant"

# Model variant for the local LLM.
# Only used with local providers (local_qwen3, local_echo).
#
#llm_variant =

# Base URL for the remote OpenAI-compatible API.
# Only used with remote_open_ai_compatible provider.
#
#llm_api_url = "http://localhost:11434/v1/"

# API key for remote OpenAI-compatible providers.
# Leave empty for local-only setups.
#
#llm_api_key =

# Remote model identifier sent to the API.
# Only used with remote_open_ai_compatible provider.
#
#llm_model = "qwen3.5:4b"

# Output audio sample rate in Hz.
#
#audio_output_sample_rate = 16000

# Number of output audio channels.
#
#audio_output_channel = 1

# Output audio frame duration in milliseconds.
#
#audio_output_frame_duration = 20

# Time in ms before closing connection when no activity detected.
#
#session_close_connection_no_activity_time = 30000

# Silence timeout in ms during active voice session.
#
#session_silence_voice_timeout = 1200

# Default system prompt (persona) injected into each Ling instance.
#
#ling_system_prompt = "你是一个知识丰富的语音对话助手，用亲切自然的语气与用户交流。回答必须有实质内容，直接提供有价值的信息。避免只问不答——先给出信息，再视情况补充。必须使用中文口述。禁止使用 Markdown、emoji、特殊符号、HTML 标签、英文标点符号。必须使用中文标点符号（。！？，；：）分隔句子，每句话末尾必须带句号、问号或感叹号。禁止使用换行符代替标点来分隔内容。所有数字必须用中文书写（二十三而不是23），日期用中文（七月二十四日）。如果用户输入为空，请求用户描述清楚。",

# Maximum number of prompt tokens.
#
#session_max_prompt_len = 3000

# Barge-in lockout duration in ms. After TTS starts or stops,
# barge-in is suppressed for this duration to prevent echo-triggered interruptions.
#
#session_barge_in_lockout_ms = 250

# List of MCP server configurations. Each entry uses one of three auth modes:
# - `self_signed = true`: server signs its own token for the local `/mcp`.
# - `token`: static token for external servers. It is a bare token; the
#   Streamable HTTP transport adds the `Bearer ` prefix itself.
# - neither: no Authorization header is sent (open server).
#
#mcp_server_list = [{ uri = "http://127.0.0.1:3000/mcp", self_signed = true }]

# Enable Matrix messaging integration.
#
#matrix_enable = false

# Matrix client application name.
#
#matrix_client_name = "vanling"

# Matrix homeserver URL.
#
#matrix_homeserver = "http://127.0.0.1:8008"

# Matrix client user ID.
#
#matrix_client_username = "@vanling:localhost.localdomain"

# Matrix client password.
#
#matrix_client_password =

# Enable console logging
#
#log_console_enabled = true

# Console log level (trace, debug, info, warn, error)
#
#log_console_level = "info"

# Console log format (text, json, compact, pretty)
#
#log_console_format = "text"

# Enable file logging
#
#log_file_enabled = false

# File log level (trace, debug, info, warn, error)
#
#log_file_level = "info"

# File log format (text, json, compact, pretty)
#
#log_file_format = "json"

# File log directory
#
#log_file_directory = "./logs"

# File log name prefix
#
#log_file_name = "server"

# Max log files to retain
#
#log_file_max_files = 10

# Log rotation (daily, hourly, never)
#
#log_file_rotation = "daily"

# Enable tracing-flame profiling output
#
#log_flame_enabled = false

# Flame graph output directory
#
#log_flame_directory = "./flame"

# Enable tokio-console
#
#log_tokio_console_enabled = false