YouTube Video Summarizer 🎥📝

A FastAPI-powered tool that extracts YouTube video transcripts and summarizes them using OpenAI's GPT models. Perfect for quickly digesting long videos!

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Features ✨

• YouTube Transcript Extraction: Fetches transcripts automatically.
• AI-Powered Summaries: Summarizes content using OpenAI's GPT models.
• Customizable Output: Choose the length and format of your summary.

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How It Works 🔧

1. Extract Transcript: The tool fetches the transcript of a YouTube video using its URL.
2. Summarize with OpenAI: The transcript is sent to OpenAI's GPT model to generate a concise summary.
3. Customize Output: Users can specify the length (e.g., number of paragraphs) and format of the summary.

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Contributing 🤝

We welcome contributions to improve this tool! Here’s how you can get started:

Prerequisites

• Python 3.11+
• OpenAI API Key (Get it here)
• Basic knowledge of FastAPI and Docker

Steps to Contribute

1. Fork the Repository:
   Click the "Fork" button at the top right of this repository to create your own copy.

2. Clone Your Fork:

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

3. Set Up Environment Variables:

   • Create a .env file in the root directory.

4. Install Dependencies:
   Create a virtual environment and install the required packages:

   python -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt

5. Run the Application Locally:
   Start the FastAPI server:

   uvicorn api.main:app --reload

6. Make Your Changes:

   • Add new features, fix bugs, or improve documentation.
   • Write tests for your changes in the api/tests/ directory.

7. Submit a Pull Request:

   • Push your changes to your forked repository.
   • Open a pull request to the main branch of this repository.
   • Provide a clear description of your changes and why they’re valuable.

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Code Structure 🗂️

youtube-summarizer/
├── api/                       # FastAPI app and related code
│   ├── __init__.py
│   ├── main.py                # FastAPI app entry point
│   ├── models/                # Pydantic models
│   ├── routes/                # API endpoints
│   ├── services/              # Business logic (e.g., summarization)
│   ├── utils/                 # Helper functions (e.g., YouTube API calls)
│   └── tests/                 # Unit and integration tests
├── docker-compose.yml         # Docker Compose configuration
├── Dockerfile                 # Dockerfile for the API
├── requirements.txt           # Python dependencies
├── .env.example               # Example environment variables
├── .gitignore                 # Git ignore rules
├── .dockerignore              # Docker ignore rules
└── README.md                  # Project documentation

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License 📄

This project is licensed under the MIT License. See LICENSE for details.

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Support the Project 💖

If you find this tool useful, consider supporting its development by subscribing to the hosted service. For more details, visit our website (coming soon).

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Happy coding! 🚀