DevOps Copilot

A Next.js application for code review and analysis using AI. This tool helps developers analyze pull requests, identify code smells, and generate comprehensive summaries using Google's Gemini AI.

Features

• 🤖 AI-powered code review using Gemini AI
• 🔍 Code smells analysis and detection
• 📝 Pull request summary generation
• 🔐 Firebase integration for data persistence
• 🎨 Modern UI with Tailwind CSS and shadcn/ui
• 🔒 Secure HTML sanitization with DOMPurify

Docker Setup

Prerequisites

• Docker (version 20.10.0 or higher)
• Docker Compose (version 2.0.0 or higher)
• Node.js 20.x (for local development)

Environment Variables

Create a .env file in the root directory with your Firebase and Gemini configuration:

# Firebase Configuration
NEXT_PUBLIC_FIREBASE_API_KEY=your_api_key
NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your_auth_domain
NEXT_PUBLIC_FIREBASE_PROJECT_ID=your_project_id
NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your_storage_bucket
NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your_messaging_sender_id
NEXT_PUBLIC_FIREBASE_APP_ID=your_app_id

# Gemini AI Configuration
NEXT_PUBLIC_GOOGLE_AI_API_KEY=your_gemini_api_key

Getting Your Gemini API Key

1. Go to Google AI Studio
2. Sign in with your Google account
3. Click on "Get API key" or "Create API key"
4. Copy your API key and add it to the .env file as NEXT_PUBLIC_GOOGLE_AI_API_KEY

Running with Docker

1. Build and start the containers:

docker compose up --build

2. The application will be available at http://localhost:9002

3. To stop the application:

docker compose down

Development

To run the application in development mode:

1. Install dependencies:

npm install

2. Start the development server:

npm run dev

3. Start the Genkit development server:

npm run genkit:dev

The development server will be available at http://localhost:3000

Building for Production

1. Build the application:

npm run build

2. Start the production server:

npm start

Project Structure

devopsCopilot/
├── src/
│   ├── ai/              # AI flows and prompts
│   ├── components/      # React components
│   ├── hooks/          # Custom React hooks
│   ├── lib/            # Utility functions
│   └── app/            # Next.js app directory
├── public/             # Static assets
├── docker-compose.yml  # Docker Compose configuration
├── Dockerfile         # Docker build configuration
└── package.json       # Project dependencies

AI Capabilities

The application uses Google's Gemini AI model for:

• Code review analysis
  • Syntax and style checking
  • Best practices validation
  • Security vulnerability detection
• Identifying code smells
  • Code duplication
  • Complex methods
  • Long parameter lists
  • Inconsistent naming
• Generating pull request summaries
  • Change overview
  • Impact analysis
  • Risk assessment
  • Recommendations

Troubleshooting

Common Issues

1. Docker Build Fails

   • Ensure Docker and Docker Compose are up to date
   • Check if all environment variables are set correctly
   • Clear Docker cache: docker system prune -a

2. AI Analysis Not Working

   • Verify your Gemini API key is valid
   • Check browser console for any errors
   • Ensure the input PR diff is properly formatted

3. HTML Rendering Issues

   • Clear browser cache
   • Check if DOMPurify is properly initialized
   • Verify the HTML content is properly sanitized

Getting Help

If you encounter any issues:

1. Check the browser console for error messages
2. Review the Docker logs: docker compose logs -f
3. Open an issue on the project repository

Security

• All HTML content is sanitized using DOMPurify
• Environment variables are properly handled
• Firebase security rules are enforced
• API keys are never exposed to the client

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

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

Make sure to keep your Gemini API key secure and never commit it to version control.