CodeCopilot 🚀

AI-Powered Code Analysis & Optimization Platform

🌟 Live Demo

Frontend Application: CodeCopilot

Note: The backend service needs to be running locally or deployed separately for full functionality.

📖 Overview

CodeCopilot is an intelligent code analysis platform that helps developers identify issues, security vulnerabilities, and optimization opportunities in their web projects. With AI-powered insights and comprehensive security scanning, it's your co-pilot for better code quality.

✨ Features

🔍 Smart Code Analysis

• Dependency Analysis: Detect version mismatches and missing dependencies
• Security Scanning: Comprehensive security vulnerability detection
• Project Structure: Analyze project organization and best practices
• Configuration Validation: Validate project configuration files

🤖 AI-Powered Insights

• LLM Integration: Get intelligent solutions and explanations
• Root Cause Analysis: Understand why issues occur
• Step-by-Step Solutions: Detailed fix instructions
• Prevention Tips: Learn how to avoid similar issues

🛡️ Enterprise-Grade Security

• Zip Bomb Protection: Advanced compression ratio detection
• File Type Filtering: Automatic blocking of dangerous file types
• Path Traversal Prevention: Secure file extraction
• Size Limits: Configurable file and extraction size limits

📊 Comprehensive Reporting

• Health Score: Overall project health assessment
• Priority Issues: Critical, major, and minor issue categorization
• Security Warnings: Detailed security notifications
• Project Statistics: File counts, configuration analysis

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Frontend      │    │    Backend       │    │   AI Service    │
│   (React)       │◄──►│    (Flask)       │◄──►│                 │
│                 │    │                  │    │                 │
│ • Project Upload│    │ • Security Scan  │    │ • Code Analysis │
│ • Results Display│   │ • File Analysis  │    │ • Solutions     │
│ • Status Monitor │   │ • LLM Integration│    │ • Explanations  │
└─────────────────┘    └──────────────────┘    └─────────────────┘

🚀 Quick Start

Frontend Setup

# Clone the repository
git clone https://github.com/your-username/codecopilot.git
cd codecopilot/frontend

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env.local

# Start development server
npm run dev

Frontend Environment Variables:

VITE_BACKEND_URL=http://localhost:5000

Backend Setup

# Navigate to backend directory
cd ../backend

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

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env

# Start Flask server
python app.py

Backend Environment Variables:

SECRET_KEY=your-secret-key-here
GEMINI_API_KEY=your-gemini-api-key-here
FLASK_DEBUG=false
PORT=5000

📁 Project Structure

Frontend (/frontend)

src/
├── components/          # React components
│   ├── ProjectUpload.jsx
│   ├── ResultsDashboard.jsx
│   ├── BackendStatus.jsx
│   └── Logo.jsx
├── hooks/              # Custom React hooks
├── styles/             # Tailwind CSS styles
└── main.jsx           # Application entry point

Backend (/backend)

backend/
├── app.py              # Flask application
├── security_scanner.py # Security & zip bomb protection
├── project_analyzer.py # Code analysis logic
├── llm_analyzer.py     # Gemini AI integration
├── requirements.txt    # Python dependencies
└── .env.example       # Environment template

🔧 Configuration

File Size Limits

• Max Upload Size: 400MB
• Max Extracted Size: 800MB
• Max File Count: 50,000 files
• Max Compression Ratio: 50:1

Security Settings

• Blocked Extensions: .bat, .cmd, .ps1, .sh, .jar, etc.
• Max Directory Depth: 20 levels
• Path Traversal Protection: Enabled

🎯 Usage

1. Upload Your Project

• Zip your entire project folder (including node_modules if desired)
• Drag and drop or click to upload
• Supports projects up to 400MB

2. Automatic Analysis

• Security scanning and validation
• Dependency and configuration analysis
• AI-powered issue detection

3. Review Results

• Health score and project statistics
• Categorized issues with severity levels
• Detailed solutions and prevention tips

4. Implement Fixes

• Copy-paste commands for quick fixes
• Step-by-step solution guides
• AI-enhanced explanations

🔌 API Documentation

Health Check

GET /api/health

Response:

{
  "status": "healthy",
  "llm_available": true,
  "security": {
    "max_file_size_mb": 400,
    "max_extracted_size_mb": 800
  }
}

Project Analysis

POST /api/analyze
Content-Type: multipart/form-data

Body: file (ZIP archive)

🛠️ Development

Frontend Development

# Run in development mode
npm run dev

# Build for production
npm run build

# Preview production build
npm run preview

Backend Development

# Run with auto-reload
flask run --debug

# Run with custom port
python app.py --port 5000

🚀 Deployment

Frontend (Vercel)

1. Push code to GitHub
2. Connect repository to Vercel
3. Set environment variables in Vercel dashboard
4. Deploy automatically on git push

Backend (Render)

1. Connect GitHub repository to Render
2. Set build command: pip install -r requirements.txt
3. Set start command: python app.py
4. Configure environment variables

Environment Variables for Production

# Frontend
VITE_BACKEND_URL=https://your-backend-url.render.com

# Backend
SECRET_KEY=your-production-secret-key
GEMINI_API_KEY=your-gemini-api-key
FLASK_DEBUG=false

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

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

📊 Performance

• Frontend: Optimized React with Vite build system
• Backend: Flask with async processing for large files
• Security: Multi-layered protection against malicious uploads
• AI: Efficient Gemini API integration with fallback handling

🐛 Troubleshooting

Common Issues

Backend Connection Failed

• Check if backend server is running on port 5000
• Verify VITE_BACKEND_URL environment variable
• Check CORS configuration

File Upload Fails

• Ensure file is a valid ZIP archive
• Check file size (max 400MB)
• Verify network connectivity

AI Features Not Working

• Check Gemini API key configuration
• Verify API quota and limits
• Check backend logs for errors

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Google Gemini for AI-powered code analysis
• React & Vite for frontend framework
• Flask for backend API
• Tailwind CSS for styling
• Vercel & Render for deployment platforms

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