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youtube-to-docs

PyPI version

Click on the image below to see a demo of YouTube to docs:

Convert YouTube videos into structured docs, summaries, audio, and visual assets for easier discovery.

View all available CLI options:

uvx youtube-to-docs --help

Optional Features

To keep the installation light, some features are optional. You can enable them by specifying "extras":

  • audio: Required for downloading audio and video from YouTube (uses yt-dlp, with yt-dlp-ejs and Deno to solve YouTube's challenges).
  • video: Required for video generation (uses static-ffmpeg).
  • workspace: Required for Google Drive integration.
  • m365: Required for Microsoft SharePoint/OneDrive integration.
  • huggingface: Required for storing artifacts to a Hugging Face dataset (uses huggingface_hub).
  • aws: AWS Bedrock support.
  • azure: Required for Azure OpenAI models.
  • gcp: Required for Google Gemini, Vertex AI models, and GCP Cloud TTS (uses google-genai and google-cloud libs).
  • app: Web app with browser-based UI (uses fastapi, uvicorn).
  • all: Installs everything.

Example: Run with audio and video support

uvx --with "youtube-to-docs[audio,video]" youtube-to-docs ...

Example: Run with everything

uvx --with "youtube-to-docs[all]" youtube-to-docs ...

Note: The commands above require uv. You can install it via:

  • macOS/Linux: curl -LsSf https://astral.sh/uv/install.sh | sh
  • Windows: powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Install as a plugin (the process_video MCP server and the youtube-to-docs skill) in Claude Code:

claude plugin marketplace add DoIT-Artificial-Intelligence/youtube-to-docs
claude plugin install youtube-to-docs@youtube-to-docs

or in Antigravity:

agy plugin install https://github.com/DoIT-Artificial-Intelligence/youtube-to-docs

Then ask for what you want, e.g. "Make the best accessible captions for https://www.youtube.com/watch?v=B0x2I_doX9o", or run /youtube-to-docs <url>.

Run as a web app:

uvx --from "youtube-to-docs[all]" youtube-to-docs-app

Then open http://localhost:8000 in your browser. See the Web App docs for details.

Created with the help of AI. All artifacts have been checked and work as expected.

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