YouTube Video Analyzer with Gemini AI

A powerful web application that analyzes YouTube videos using Google's Gemini AI with URL context support. Simply paste a YouTube URL and get detailed insights about the video content.

✨ Features

• YouTube Video Analysis: Analyze any public YouTube video using Google's Gemini AI
• URL Context Support: Leverages Gemini's urlContext tool for direct video processing
• Beautiful Web Interface: Clean, responsive design with loading states and error handling
• RESTful API: Well-documented API endpoints for programmatic access
• Comprehensive Testing: Full test suite with 9 automated tests
• Production Ready: Deployed on Vercel with proper error handling and CORS support

🚀 Live Demo

• Web Interface: https://gemini-youtube-new.vercel.app
• API Endpoint: POST /api/analyze

🛠️ Quick Start

Prerequisites

• Node.js 18+
• Google Gemini API key (Get one here)

Installation

1. Clone the repository

   git clone https://github.com/aviz85/gemini-youtube-analyzer.git
   cd gemini-youtube-analyzer

2. Install dependencies

   npm install

3. Set up environment variables

   echo "GEMINI_API_KEY=your_api_key_here" > .env

4. Run locally

   # Option 1: Using Vercel dev
   npm run vercel-dev
   
   # Option 2: Simple Express server
   node -e "
   const express=require('express');
   const app=express();
   app.use(express.json(),express.static('.'));
   app.all('/api/*',(req,res)=>require('./api/'+req.path.split('/')[2])(req,res));
   app.listen(8080,()=>console.log('✅ Running: http://localhost:8080'));
   "

5. Run tests

   npm test

📋 API Usage

Analyze Video

Endpoint: POST /api/analyze

Request Body:

{
  "youtubeUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
  "prompt": "What is this video about? Provide a detailed summary."
}

Response:

{
  "success": true,
  "analysis": "This video is the official music video for Rick Astley's iconic song 'Never Gonna Give You Up.' It features Rick Astley singing and dancing in various locations..."
}

Error Response:

{
  "error": "Please provide a valid YouTube URL"
}

Test Connection

Endpoint: GET /api/analyze

Response:

{
  "message": "YouTube Analyzer API is working",
  "timestamp": "2025-08-19T08:52:36.715Z",
  "endpoints": {
    "POST /api/analyze": "Analyze YouTube video content"
  }
}

🔧 Configuration

Environment Variables

• GEMINI_API_KEY (required): Your Google Gemini API key

Deployment

Vercel (recommended):

npm run deploy

Other platforms:

• The app works on any Node.js hosting platform
• API functions are in the /api directory
• Static files are served from the root

🧪 Testing

The project includes comprehensive tests covering:

• CORS handling
• Input validation
• YouTube URL format validation
• API error handling
• Streaming response aggregation
• Edge cases and error scenarios

# Run all tests
npm test

# Run tests in watch mode
npm run test:watch

# Run tests with coverage
npm run test:coverage

📁 Project Structure

├── api/
│   ├── analyze.js          # Main YouTube analyzer endpoint
│   └── hello.js            # Test endpoint
├── __tests__/
│   └── analyze.test.js     # Comprehensive test suite
├── index.html              # Beautiful web interface
├── vercel.json            # Vercel deployment config
├── package.json           # Dependencies and scripts
└── README.md              # This file

🔐 Security Features

• Input validation and sanitization
• CORS headers properly configured
• Environment variable protection
• Error message sanitization
• Rate limiting ready (can be easily added)

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Run tests (npm test)
4. Commit changes (git commit -m 'Add amazing feature')
5. Push to branch (git push origin feature/amazing-feature)
6. Open a Pull Request

📝 License

MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Google Gemini AI for the powerful video analysis capabilities
• Vercel for seamless deployment platform
• The open-source community for inspiration and tools

⚡ Performance

• Streaming responses for faster perceived performance
• Efficient error handling
• Minimal dependencies
• Optimized for both development and production

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Made with ❤️ by aviz85