YouTube Summarizer by TCSenpai

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

Features

• 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

Installation

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
   

Usage

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

Dependencies

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

Project Structure

• 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
• transcript_cache/: Directory for caching video transcripts

Contributing

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

License

WTFPL License

Credits

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