GitHub - sliday/ytsum: TLDW: Awesome Video Summarizer

Awesome YouTube Video Summary/Podcast/Video

A Python script to generate summaries (Claude), podcasts (Whisper), and videos (RunwayML or Luma AI) from annoyingly long YouTube content.

Example

• Original video: https://www.youtube.com/watch?v=_K-L9uhsBLM
• Summary: https://dl.dropbox.com/scl/fi/mdkbglfbs4m9ydeo9a2k7/video-_K-L9uhsBLM.mp4?rlkey=3wrowryg9gio1walaxhdbp2is&dl=0

Features

• Generate concise summaries of YouTube videos
• Create engaging podcast scripts with multiple voices
• Generate AI-powered videos with synchronized podcast audio
• Support for multiple languages
• Multiple transcription options
• Multiple video generation providers

Installation

1. Clone the repository:

git clone https://github.com/sliday/ytsum.git
cd ytsum

2. Install dependencies:

pip install -r requirements.txt

3. Install FFmpeg (required for audio/video processing):
   • macOS: brew install ffmpeg
   • Ubuntu/Debian: sudo apt-get install ffmpeg
   • Windows: Download from FFmpeg website

Environment Setup

Create a .env file with your API keys:

ANTHROPIC_API_KEY=your_claude_api_key
OPENAI_API_KEY=your_openai_api_key
LUMAAI_API_KEY=your_lumaai_api_key
RUNWAYML_API_SECRET=your_runwayml_api_key
REPLICATE_API_TOKEN=your_replicate_api_key

Usage

Basic Summary

python ytsum.py "https://www.youtube.com/watch?v=VIDEO_ID"

Generate Podcast

python ytsum.py --podcast "https://www.youtube.com/watch?v=VIDEO_ID"

Generate Video with Podcast

# Using Luma AI (faster, recommended)
python ytsum.py --podcast --lumaai "https://www.youtube.com/watch?v=VIDEO_ID"

# Using RunwayML
python ytsum.py --podcast --runwayml "https://www.youtube.com/watch?v=VIDEO_ID"

Additional Options

• --language: Specify output language (default: english)
• --ignore-subs: Force transcription even when subtitles exist
• --fast-whisper: Use Fast Whisper for transcription (faster)
• --whisper: Use OpenAI Whisper for transcription (more accurate)
• --replicate: Use Replicate's Incredibly Fast Whisper

Output Files

All output files are saved in the out directory:

• summary-{video_id}.txt: Text summary
• podcast-{video_id}.txt: Podcast script
• podcast-{video_id}.mp3: Podcast audio
• video-{video_id}.mp4: Final video with podcast audio

Video Generation

The tool supports two AI video generation providers:

Luma AI (Recommended)

• Faster generation times
• High-quality cinematic videos
• Supports camera movements and scene transitions
• Maintains visual consistency
• Optional image input for style reference

RunwayML

• High-quality video generation
• Requires input image
• Longer processing times
• Professional-grade output

Both providers:

1. Generate base images using Flux AI
2. Create video segments based on podcast content
3. Combine segments with audio
4. Support custom duration and aspect ratio

Transcription Options

1. Fast Whisper (Default)

   • Quick transcription
   • Good accuracy
   • No API key required

2. OpenAI Whisper

   • High accuracy
   • Slower processing
   • Requires OpenAI API key

3. Replicate Whisper

   • Fastest option
   • Good accuracy
   • Requires Replicate API key

Testing

Run the test suite:

Run specific test groups:

# Run Luma AI tests only
pytest -v -m luma

# Run RunwayML tests only
pytest -v -m runway

Dependencies

• anthropic: Claude API for text generation
• openai: Whisper API for transcription and TTS
• lumaai: Luma AI for video generation (recommended)
• runwayml: RunwayML for video generation
• replicate: Flux AI for image generation
• ffmpeg-python: Audio/video processing
• colorama: Terminal output formatting
• pytest: Testing framework

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.