🎓 yt-study

Automated, AI-powered study notes from YouTube videos.

yt-study is a command-line tool that transforms video content into structured, academic-quality Markdown notes. It handles transcripts, detects chapters, and preserves technical details like code snippets and SQL queries using state-of-the-art LLMs.

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Key Features

• Model Flexibility: Use Gemini, GPT-4, Claude, or Groq via a unified interface.
• Chapter Intelligence: Automatically splits long videos (>1hr) into separate, detailed chapter notes.
• Deep Context: Processes massive transcripts (100k+ tokens) without summarization loss using recursive chunking.
• Universal Language: Translates foreign content (e.g., Hindi, Spanish) directly into English notes.
• Robust Batch Processing: Handle playlists or URL lists with a rich TUI dashboard that dynamically adjusts to your workload.
• IP Block Handling: Gracefully detects YouTube rate limits and pauses/alerts without crashing.
• Developer Ready: Fully type-checked (Mypy), linted (Ruff), and tested (100% pass rate, >90% coverage).

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Installation

Requires Python 3.10 or higher.

pip install yt-study

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Quick Start

1. Configure

Run the interactive wizard to set up your LLM provider and API keys.

yt-study setup

2. Run

Generate notes for a single video:

yt-study process "https://youtube.com/watch?v=VIDEO_ID"

Or an entire playlist:

yt-study process "https://youtube.com/playlist?list=PLAYLIST_ID"

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Documentation

Full documentation is available in the docs/ directory.

• Installation Guide
• Configuration & Models
• Usage & CLI Options
• Architecture

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Output Example

Notes are organized automatically:

output/
└── Complete Python Course/
    ├── 01_Introduction.md
    ├── 02_Data_Types.md
    └── 03_Control_Flow.md

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Contributing

We welcome contributions! Please see CONTRIBUTING.md for details on setting up the development environment.

License

MIT © Jaydeep Solanki