This project provides a clean, ad-free YouTube frontend focused on user control and offline playback. It targets users seeking a distraction-free viewing experience, offering features like channel management, video downloading, sponsor blocking, and AI-powered summaries.

How It Works

The application fetches channel subscriptions and video metadata using yt-dlp without requiring API keys. It presents a chronological feed, allowing users to download videos for offline playback. A key differentiator is its optional integration with local or hosted AI models (via Ollama, LMStudio, OpenAI, Anthropic) to summarize video content. The frontend is built with plain HTML, CSS, and JavaScript, leveraging Server-Sent Events for real-time updates and the HTML5 <track> element for subtitles.

Quick Start & Requirements

• Install: Clone the repository, run npm install, and then npm start. Alternatively, use docker compose up --build -d or docker run -p 3000:3000 -v $HOME/my-yt-data:/app/data christianfei/my-yt:latest.
• Prerequisites: Node.js, yt-dlp, and ffmpeg.
• AI Integration: Requires setting environment variables for API keys, model names, hosts, and endpoints if AI features are used.
• Docs: https://github.com/christian-fei/my-yt

Highlighted Details

• Minimalist UI with optional dark mode.
• SponsorBlock integration for automatic sponsor removal.
• Native Chromecast support and background playback.
• Option to disable clickbait thumbnails.
• Automatic transcoding to h264 for broad device compatibility.

Maintenance & Community

The project is actively maintained by its creator, Christian Fei. Further community engagement details are not explicitly provided in the README.

Licensing & Compatibility

The project is licensed under the MIT License, permitting commercial use and integration with closed-source applications.

Limitations & Caveats

The project relies on yt-dlp and ffmpeg, which must be installed separately if not using Docker. While it aims for broad compatibility via transcoding, users with resource-constrained systems might experience performance issues during video processing.