🎥 YouTube Summarizer using LLM (Gemini)

This is a simple LLM-based YouTube Summarizer project using Google's Gemini-1.5-Flash model. The app fetches YouTube transcripts and summarizes them using the LLM, presented via a Streamlit interface.

⚠️ Note: You must run this project locally because YouTube may block requests originating from cloud servers.

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🚀 Features

• Summarizes YouTube videos using state-of-the-art LLM
• Uses Google Gemini model via API
• Streamlit-based interactive web interface
• Easily configurable with .env variables

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🛠️ Setup Instructions

Follow these steps to get the project up and running on your local system:

1. Clone the repo or create a new project folder in your local system using your preferred IDE or code editor.

2. Open the terminal in the project directory and create a virtual environment:

   python -m venv venv

   it will create virtual environmental files in your project folder.

3. Create a .env file in the root directory to store environment variables like your Google API Key.

   • Get your API key from Google AI Studio.

   • Add this line to your .env file:

     GOOGLE_API_KEY="your_google_api_key_here"
     

4. Create a requirements.txt file and include all required packages. Example:

    youtube_transcript_api
    streamlit
    google-generativeai
    python-dotenv
    pathlib

5. Activate the virtual environment:

   • On Windows:

     .\venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

6. Install all dependencies:

   pip install -r requirements.txt

7. Create your main Python file (e.g., app.py) and copy the main code into it.

   • Before running, make sure to:
     • Load environment variables correctly using dotenv.
     • Set your preferred Google model.
     • Customize the HTML/CSS/Streamlit UI as needed.

8. Run the Streamlit app:

   streamlit run app.py

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🧠 Model Info

This project uses gemini-1.5-flash (or other Gemini variants) to generate the summary. You can choose an appropriate model from Google's Gemini Models Documentation.

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📂 Directory Structure (Example)

youtube-summarizer/
│
├── .env
├── app.py
├── requirements.txt
└── venv/

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🔐 Important Notes

• Do NOT upload your .env file to GitHub. Add it to your .gitignore.
• Always test locally, as some YouTube endpoints block cloud-based IP addresses.
• Use your own API quota wisely, as summarizing long transcripts can consume tokens quickly.
• The prompt already given in the code and it limited to 250 words.

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📜 License

Feel free to use and modify for educational or personal projects.

🙌 Acknowledgements

• Google AI for the Gemini model
• Streamlit for the UI framework
• YouTube Transcript API for fetching transcripts
• Edureka for project overview

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📬 Suggestions or Contributions?

Feel free to open an issue or pull request if you have ideas or improvements! Happy coding 🚀