🎥 TubeTalk - YouTube Video Chat

Interact with YouTube videos by watching them instantly and asking questions based on their transcripts in multiple languages!

TubeTalk - YouTube Video Chat is an innovative web application that allows users to engage with YouTube videos by viewing them as soon as a URL is pasted and querying their transcripts in languages like Hindi, Gujarati, Marathi, English, and more. Powered by advanced AI technologies, including Hugging Face's language models and LangChain for retrieval-augmented generation, this app provides concise and accurate answers to user questions. Built with Streamlit, it offers a user-friendly interface for seamless interaction.

✨ Features

• Instant Video Playback: Paste a YouTube URL to instantly view the video in an embedded player.
• Multi-Language Transcript Processing: Fetch and analyze transcripts from YouTube videos in supported languages, including Hindi, Gujarati, Marathi, English, Spanish, French, German, Italian, Portuguese, Russian, Chinese, Japanese, and Korean.
• Smart Q&A: Ask questions about video content and receive tailored responses (e.g., summaries, lists, or detailed explanations) based on the transcript.
• Interactive Chat Interface: View chat history, clear conversations, and download them as Markdown files.
• Transcript Viewer: Access the full video transcript within the app after processing.
• Debug Mode: Enable debug logs for troubleshooting (optional).
• Responsive Design: Wide layout with a clean, modern UI optimized for desktop and mobile.
• Secure API Integration: Uses Hugging Face's Inference API with token-based authentication.

🛠️ Technologies Used

• Frontend: Streamlit for the web interface.
• Backend:
  • YouTube Transcript API: Fetches video transcripts in multiple languages.
  • LangChain: Handles text splitting, vector storage (FAISS), and retrieval-augmented generation.
  • Hugging Face:
    • sentence-transformers/all-MiniLM-L6-v2 for embeddings.
    • mistralai/Mixtral-8x7B-Instruct-v0.1 for response generation.
• Other Libraries:
  • sentence-transformers for text embeddings.
  • huggingface_hub for API interactions.
  • FAISS for efficient vector search.
  • re, datetime, io for utility functions.
  • streamlit.components for embedding the YouTube video player.

🚀 Getting Started

Follow these steps to set up and run TubeTalk - YouTube Video Chat locally.

Prerequisites

• Python 3.8 or higher
• A Hugging Face account with an API token
• A YouTube video with captions in a supported language (e.g., Hindi, Gujarati, Marathi, English, etc.)

Installation

1. Clone the Repository

   git clone https://github.com/rohanmistry231/Tubetalk-Youtube-Video-Chat
   cd Tubetalk-Youtube-Video-Chat
   

2. Create a Virtual Environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install Dependencies

   pip install -r requirements.txt
   

   Ensure your requirements.txt includes:

   streamlit
   streamlit-option-menu
   youtube-transcript-api
   langchain
   langchain-community
   sentence-transformers
   huggingface_hub
   faiss-cpu
   

4. Set Up Hugging Face API Token

   Create a secrets.toml file in the .streamlit directory (or directly in the project root for local runs):

   HF_API_TOKEN = "your-hugging-face-api-token"
   

   To get your token:

   • Visit Hugging Face.
   • Generate a new token with read access.

5. Run the Application

   streamlit run app.py
   

   The app will open in your default browser at http://localhost:8501.

📖 Usage

1. Navigate to the Chat Page:
   • Use the sidebar to select "Chat."
2. Enter a YouTube URL:
   • Paste a valid YouTube video URL (e.g., https://www.youtube.com/watch?v=VIDEO_ID) to instantly view the video in the embedded player.
   • Ensure the video has captions in a supported language for transcript processing.
3. Select a Language:
   • Choose your preferred transcript language (e.g., Hindi, Gujarati, Marathi, English) from the dropdown.
4. Process the Transcript:
   • Click "Process Video" to fetch and analyze the transcript. If the selected language is unavailable, the app will attempt other supported languages.
5. Ask Questions:
   • Type a question (e.g., "What is the main topic of the video?").
   • Click "Send" to get a response.
6. View Transcript:
   • Expand the "View Transcript" section to see the full transcript after processing.
7. Manage Chat:
   • Clear Chat: Reset the chat history.
   • Download Chat: Save the chat history as a Markdown file.

⚙️ How It Works

1. Video Playback:
   • The app extracts the video ID from the YouTube URL using regex patterns as soon as the URL is pasted.
   • The video is displayed instantly in an embedded player using Streamlit’s iframe component.
2. Transcript Fetching:
   • When "Process Video" is clicked, the YouTubeTranscriptApi fetches the transcript in the user’s preferred language (e.g., Hindi, Gujarati, Marathi) or falls back to other supported languages.
3. Text Processing:
   • The transcript is split into chunks using RecursiveCharacterTextSplitter.
   • Chunks are embedded using sentence-transformers/all-MiniLM-L6-v2.
   • Embeddings are stored in a FAISS vector store for efficient retrieval.
4. Question Answering:
   • User questions are processed using a LangChain retrieval chain.
   • Relevant transcript chunks are retrieved and passed to the Hugging Face Inference API (mistralai/Mixtral-8x7B-Instruct-v0.1).
   • Responses are formatted in Markdown with sections like Key Points.
5. UI Rendering:
   • Streamlit renders the video player, transcript, chat history, and responses.
   • Custom CSS styles buttons for a polished look.

🐛 Troubleshooting

• Invalid YouTube URL:
  • Ensure the URL is correct and includes the video ID (e.g., https://www.youtube.com/watch?v=VIDEO_ID).
  • If the video doesn’t display, verify the URL format and try again.
• No Transcript Available:
  • Verify the video has captions in a supported language (e.g., Hindi, Gujarati, Marathi, English).
• API Errors:
  • Rate Limit Exceeded: Wait and try again, or check your Hugging Face plan.
  • Invalid Token: Ensure HF_API_TOKEN is correct in secrets.toml.
  • Service Unavailable: Hugging Face servers may be down; try later.
• Processing Errors:
  • Enable "Debug Mode" in the sidebar to view detailed logs.
  • Check console output for specific error messages.
• Language Issues:
  • If the selected language is unavailable, the app will attempt other languages. Ensure captions exist for the video.

🌟 Future Enhancements

• Integration with additional LLMs for improved response generation in Indian languages.
• Enhanced UI with themes and accessibility features.
• Real-time video summary generation.
• Support for live YouTube streams with captions.
• Improved embedding models for better handling of Hindi, Gujarati, and Marathi.
• Video playback controls synced with transcript timestamps.

🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/YourFeature).
3. Commit changes (git commit -m "Add YourFeature").
4. Push to the branch (git push origin feature/YourFeature).
5. Open a Pull Request.

📬 Contact

For questions or feedback, reach out via:

• Email: [email protected]