API service to fetch YouTube video transcripts with metadata and local file caching.

• 📥 Fetch YouTube video transcripts with metadata
• 🎧 transcript_from_audio generation using yt-dlp + ffmpeg with selectable backend: faster-whisper, assembly, openai, or gemini
• 🧵 Background transcription jobs with progress polling
• 🪵 Timestamped development logs with visible active log level and transcription backend at startup
• 💾 Local file caching with unlimited retention by default
• 🌍 Always returns first available transcript (native/original language)
• 🐳 Docker support
• 🔌 MCP (Model Context Protocol) server integration
• 📚 Interactive Swagger documentation
• ⚡ Rate limiting
• 🔒 Optional API key authentication
• 🖼️ Basic metadata includes: title, author, duration, views, publish date, thumbnail, description
• 📊 Full metadata endpoint with all yt-dlp fields (50+ fields)

# Install dependencies
sudo apt install python3-venv ffmpeg
python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt

# Copy environment variables and configure
cp .env.example .env
# Edit .env if needed

# Run server in dev mode (with hot-reload, no __pycache__)
./run-api-dev.sh

The development startup script:

• loads .env from the project root if present
• shows the active log level
• shows the active transcription backend
• enables timestamped Uvicorn logs through app/uvicorn_log_config.json

Or manually:

PYTHONDONTWRITEBYTECODE=1 uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload --log-config app/uvicorn_log_config.json

Docker uses a glibc-based Python image for compatibility with faster-whisper and ctranslate2, which are not reliably installable on python:3.14-alpine.

# Copy environment variables
cp .env.example .env
# Edit .env if needed

# Build and run with Docker Compose
sudo docker-compose up --build

# Or build and run manually
sudo docker build -t youtube-transcript-api .
sudo docker run -p 8000:8000 -v $(pwd)/cache:/app/cache -v $(pwd)/data:/app/data youtube-transcript-api

GET /api/v1/health

Returns application health and runtime information.

Response:

{
  "status": "healthy",
  "version": "1.1.0",
  "uptime_seconds": 12.34,
  "transcription_backend": "faster-whisper",
  "transcript_from_audio_enabled": true,
  "cache_path": "/app/cache",
  "cache_accessible": true,
  "whisper_model_loaded": false
}

GET /api/v1/youtube/transcript/{video_id}?use_cache=true&force_refresh=false&language=en

When _APP_TRANSCRIPT_FROM_AUDIO=true, this endpoint can automatically queue transcript_from_audio processing if direct YouTube transcript fetch fails for reasons such as disabled transcripts or YouTube-side access issues. Video unavailable remains a hard error.

Parameters:

• video_id (path): YouTube video ID (11 chars) or full URL
  • Examples: mQ-y2ZOTpr4 or https://www.youtube.com/watch?v=mQ-y2ZOTpr4
• use_cache (query): Enable or disable cache lookup for direct YouTube transcripts
• force_refresh (query): Skip direct transcript cache lookup and overwrite the direct cache section
• language (query): Preferred transcript language code (optional)

Returns:

• metadata - Basic video metadata
• transcript_youtube - Direct transcript fetched from YouTube
• transcript_audio - Transcript generated from the audio track if available
• source_preference - Response source ordering metadata

Response:

{
  "video_id": "mQ-y2ZOTpr4",
  "metadata": {
    "title": "Video Title",
    "author": "Channel Name",
    "duration": 218,
    "publish_date": "20251203",
    "view_count": 9084,
    "thumbnail": "https://i.ytimg.com/vi/...",
    "description": "Full description..."
  },
  "transcript_youtube": {
    "transcript": "Full transcript text here...",
    "language": "en",
    "source": "youtube",
    "cache_used": false,
    "cached_at": null
  },
  "transcript_audio": null,
  "source_preference": ["youtube", "audio"]
}

Fallback response when direct transcript fetching queues audio transcription:

{
  "video_id": "3LbZP0sYmPw",
  "status": "queued",
  "message": "Direct YouTube transcript fetch failed: Transcripts are disabled for video 3LbZP0sYmPw. Transcript_from_audio status for video_id 3LbZP0sYmPw is 'queued'. Background transcription message: Transcript queued for background processing by video_id using backend 'assembly'. The transcript should be available in a few minutes. Check status by the same video_id.",
  "progress_percent": 0,
  "transcript_from_audio_reason": "Transcripts are disabled for video 3LbZP0sYmPw",
  "result": null
}

GET /api/v1/youtube/transcript/raw/{video_id}?use_cache=true&force_refresh=false&language=en

Returns complete yt-dlp metadata together with separated transcript payloads.

Response:

{
  "video_id": "mQ-y2ZOTpr4",
  "metadata": {
    "title": "Video Title",
    "channel_id": "UC123..."
  },
  "transcript_youtube": {
    "transcript": "Full transcript text here...",
    "language": "en",
    "source": "youtube",
    "cache_used": true,
    "cached_at": "2026-03-13T12:34:56"
  },
  "transcript_audio": null,
  "source_preference": ["youtube", "audio"]
}

POST /api/v1/youtube/audio-transcript/{video_id}

Queues background transcription for the provided video_id, downloads the audio track, normalizes it with ffmpeg, transcribes it with the configured backend, and stores the result under transcript_from_audio in cache.

Supported backends:

• faster-whisper
• assembly
• openai
• gemini

Response:

{
  "status": "queued",
  "video_id": "mQ-y2ZOTpr4",
  "message": "Transcript queued for background processing by video_id using backend 'assembly'",
  "progress_percent": 0,
  "result": null
}

GET /api/v1/youtube/audio-transcript/{video_id}

Returns the current background transcription state with step-level progress.

Possible states:

• queued
• downloading_audio
• extracting_audio
• loading_model
• uploading_audio
• awaiting_provider
• transcribing
• completed
• failed

Response:

{
  "video_id": "mQ-y2ZOTpr4",
  "status": "transcribing",
  "current_step": "transcribing",
  "message": "Transcribing audio with backend 'assembly' from data/work/mQ-y2ZOTpr4/audio.wav",
  "progress_percent": 70,
  "created_at": "2026-03-12T05:40:00",
  "updated_at": "2026-03-12T05:41:10",
  "error": null,
  "result": null
}

GET /api/v1/cache

Response:

{
  "status": "healthy",
  "cache_size": 12,
  "cache_path": "./cache",
  "cache_size_bytes": 482102,
  "cache_size_mb": 0.46,
  "max_cache_size_mb": 0
}

GET /api/v1/cache/entries

Requires API key authentication when enabled.

Response:

{
  "status": "healthy",
  "entries": [
    {
      "video_id": "mQ-y2ZOTpr4",
      "file_name": "mQ-y2ZOTpr4.json",
      "size_bytes": 20480,
      "updated_at": "2026-03-13T20:00:00"
    }
  ],
  "cache_size": 1,
  "cache_size_bytes": 20480,
  "cache_size_mb": 0.02,
  "max_cache_size_mb": 0
}

DELETE /api/v1/cache

Requires API key authentication when enabled.

DELETE /api/v1/cache/{video_id}

Requires API key authentication when enabled.

GET /

Returns API information and available endpoints.

The API returns the best available transcript based on YouTube availability and your optional preferred language.

• Prefers manual transcripts over auto-generated ones
• Optional language query parameter can be used as a preferred transcript language hint
• Response separates direct and audio transcript payloads instead of concatenating them
• Cache is stored as video_id.json with separate sections for direct and audio transcripts

1. The API first checks cache by video_id.
2. If not found, it fetches a transcript from YouTube.
3. Direct transcripts are stored under direct_from_youtube.
4. Audio transcription results are stored under transcript_from_audio.
5. Cached transcript files live under cache/{video_id}.json.
6. By default, _APP_MAX_CACHE_SIZE_MB=0 keeps cache size unlimited.
7. By default, _APP_CACHE_TTL_DAYS=0 disables cache expiration.
8. Automatic eviction only happens if _APP_MAX_CACHE_SIZE_MB is set to a value greater than 0.
9. Automatic expiration only happens if _APP_CACHE_TTL_DAYS is set to a value greater than 0.

If _APP_TRANSCRIPT_FROM_AUDIO=true and direct transcript fetching fails for an eligible reason, the standard transcript endpoint and MCP get_youtube_transcript tool automatically queue or reuse background audio transcription for the same video_id.

1. The request endpoint normalizes the input to video_id.
2. It checks cache/<video_id>.json for transcript_from_audio.
3. If not cached, it creates or reuses a file-backed background status entry in data/jobs/.
4. The worker uses data/work/<video_id>/ as temporary workspace.
5. The worker downloads audio with yt-dlp.
6. ffmpeg converts audio to mono 16k WAV.
7. The configured backend generates the final transcript.
8. The result is stored in cache and exposed through HTTP and MCP polling.
9. Temporary work files are removed after processing when _APP_JOB_CLEANUP_TEMP_FILES=true.

Interactive API documentation is available at:

• Swagger UI
• ReDoc

MCP (Model Context Protocol) server is integrated with FastAPI and supports StreamableHttpTransport.

Set _APP_MCP_HIDE_CLEAR_CACHE=true to hide the clear_cache tool from the MCP tools list.

• MCP Endpoint: http://localhost:8000/api/v1/mcp
• Transport: streamable_http
• Tools:
  • get_youtube_transcript
  • request_youtube_audio_transcript
  • get_youtube_audio_transcript
  • clear_cache

from mcp.client.session import ClientSession
from mcp.client.streamable_http import streamable_http_transport

async with streamable_http_transport("http://localhost:8000/api/v1/mcp") as transport:
    async with ClientSession(transport) as session:
        await session.initialize()
        await session.call_tool(
            "get_youtube_transcript",
            arguments={"video_id": "9Wg6tiaar9M"},
        )

{
  "mcpServers": {
    "youtube-transcript": {
      "url": "http://localhost:8000/api/v1/mcp",
      "transport": "streamable_http"
    }
  }
}

All environment variables use the _APP_ prefix. Copy .env.example to .env and adjust values for your environment.

Key groups:

• API paths and CORS
• Cache, jobs, and work directories
• Transcript and audio fallback behavior
• Provider/backend configuration
• Optional API key authentication
• Logging and port binding

_APP_API_KEY is used only for external provider authentication. _APP_X_API_KEY independently enables API access control for incoming HTTP and MCP requests. Leaving _APP_X_API_KEY empty keeps incoming API and MCP authentication disabled.

_APP_TRANSCRIPTION_BACKEND=faster-whisper
_APP_WHISPER_MODEL=large-v3
_APP_WHISPER_DEVICE=cpu
_APP_WHISPER_COMPUTE_TYPE=int8

_APP_TRANSCRIPTION_BACKEND=assembly
_APP_API_KEY=your-assembly-api-key
_APP_BASE_URL=https://api.assemblyai.com
_APP_MODEL=universal-3-pro,universal-2
_APP_LANGUAGE_DETECTION=true

_APP_TRANSCRIPTION_BACKEND=openai
_APP_API_KEY=your-openai-api-key
_APP_BASE_URL=https://api.openai.com/v1
_APP_MODEL=gpt-4o-mini-transcribe

_APP_TRANSCRIPTION_BACKEND=gemini
_APP_API_KEY=your-gemini-api-key
_APP_BASE_URL=https://generativelanguage.googleapis.com
_APP_MODEL=gemini-2.5-flash

app/
├── main.py
├── config.py
├── models.py
├── middleware/
│   ├── auth.py
│   └── process_time.py
├── routers/
│   ├── transcript.py
│   └── transcript_from_audio.py
├── services/
│   ├── background_transcription_service.py
│   ├── cache_service.py
│   ├── job_service.py
│   ├── service_container.py
│   ├── transcription_backend_service.py
│   ├── transcript_from_audio_cache_service.py
│   └── youtube_service.py
├── utils/
│   └── transcript_utils.py
└── mcp/
    └── server.py

Current version: 1.1.0

Implemented features:

• Cache service with atomic writes, optional TTL, and optional max-size eviction
• Direct transcript and audio transcript fallback flows
• Cache retention defaults to unlimited size and no expiration
• Background job status files stored under data/jobs
• Background worker temporary files stored under data/work
• Shared service container across REST and MCP
• REST cache management endpoints
• Optional CORS middleware
• Optional API key authentication
• Docker and Compose support
• Swagger and ReDoc documentation

Runtime data is split between persistent cache entries and background-processing state.

cache/
├── {video_id}.json

data/
├── jobs/
│   └── {video_id}.json
└── work/
    └── {video_id}/
        ├── source_audio.*
        └── audio.wav

cache/{video_id}.json contains:

• video_id
• direct_from_youtube
• transcript_from_audio

data/jobs/{video_id}.json contains the current background job state, including:

• status
• current_step
• progress_percent
• message
• error
• result

data/work/{video_id}/ contains temporary downloaded and normalized audio files while a background job is running.

MIT