YouTube Summarizer is a Streamlit-based web application that allows users to generate summaries of YouTube videos using AI-powered language models and optionally Whisper for transcription.

• YouTube Summarizer by TCSenpai
  • Features
  • Installation
  • Usage
  • Global Installation
  • Run with the included binary
  • Dependencies
  • Project Structure
  • Contributing
  • License
  • Credits

• Supports multiple YouTube frontends (e.g. YouTube, Invidious, etc.)
• Fetch and cache YouTube video transcripts
• Summarize video content using Ollama AI models
• Display video information (title and channel)
• Customizable Ollama URL and model selection
• Fallback to Whisper for transcription if no transcript is found
• Customizable Whisper URL and model selection
• Optional force Whisper transcription

1. Clone the repository:

   git clone https://github.com/yourusername/youtube-summarizer.git
   cd youtube-summarizer
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Set up environment variables: Create a .env file in the root directory and add the following:

   YOUTUBE_API_KEY=your_youtube_api_key
   OLLAMA_MODEL=default_model_name
   WHISPER_URL=http://localhost:8000/
   WHISPER_MODEL=Systran/faster-whisper-large-v3
   

   • Note: you can copy the env.example file to .env and modify the values.
   • Important: the WHISPER_URL should point to the whisper server you want to use. You can leave it as it is if you are not planning on using Whisper.

1. Run the Streamlit app:

   streamlit run src/main.py
   

2. Open your web browser and navigate to the provided local URL (usually http://localhost:8501).

3. Enter a YouTube video URL in the input field.

4. (Optional) Customize the Ollama URL and select a different AI model.

5. (Optional) Customize the Whisper URL and select a different Whisper model.

6. Click the "Summarize" button to generate a summary of the video.

You can install the application globally on your system by running the following command:

sudo ./install.sh

This will create a new command youlama that you can use to run the application.

You can also run the application with the included binary:

./youlama

• Streamlit
• Pytube
• Ollama
• YouTube Data API
• Python-dotenv
• pytubefix
• Gradio

• src/main.py: Main Streamlit application
• src/ollama_client.py: Ollama API client for model interaction
• src/video_info.py: YouTube API integration for video information
• src/whisper_module.py: Whisper API client for transcription
• src/yt_audiophile.py: Audio downloader for YouTube videos
• transcript_cache/: Directory for caching video transcripts
• downloads/: Directory for downloaded audio files, might be empty

Contributions are welcome! Please feel free to submit a Pull Request.

WTFPL License

Icon: "https://www.flaticon.com/free-icons/subtitles" by Freepik - Flaticon