DockGen AI Backend

AI-Powered Dockerfile Generator Backend API

🚀 Features

• 🤖 AI-powered Dockerfile generation for JavaScript frameworks (React, Next.js, Vue, Angular)
• 🐳 Automatic Docker image building with real Docker commands
• 🔍 GitHub repository analysis and tech stack detection
• 📝 Syntax validation and error handling
• 📊 Real-time progress tracking with status updates
• 💾 Generation history and result management

🛠️ Tech Stack

• Backend: Node.js + Express.js + TypeScript
• Database: MongoDB + Mongoose
• AI Agent: Google Gemini 2.0 Flash + LangChain.js ReAct Agent
• Containerization: Docker + Docker API

⚡ Quick Start

Prerequisites

• Node.js (v18 or higher)
• MongoDB (running locally or cloud)
• Docker (for building images)
• Google Gemini API key
• GitHub Personal Access Token

Installation

# Install dependencies
npm install

# Create environment file
cp .env.example .env

Environment Configuration

Create a .env file in the backend directory:

# Google Gemini Configuration
GEMINI_API_KEY=your_gemini_api_key_here

# MongoDB Configuration
MONGODB_URI=mongodb://localhost:27017/dockgen

# GitHub Configuration
GITHUB_TOKEN=your_github_token_here

# Server Configuration
PORT=3001
NODE_ENV=development

# CORS Configuration
FRONTEND_URL=http://localhost:3000

Development

# Start development server
npm run dev

# Build for production
npm run build

# Start production server
npm start

🔧 API Endpoints

Generation

• POST /api/generation/generate - Start Dockerfile generation
• GET /api/generation/status/:id - Get generation status
• GET /api/generation/history - Get generation history
• POST /api/generation/push-dockerfile - Push Dockerfile to repository

Health

• GET /health - Backend health check

🏗️ Architecture

Backend (Express.js)

• RESTful API with TypeScript
• MongoDB integration with Mongoose
• GitHub API integration for repository fetching
• Google Gemini 2.0 Flash for AI-powered analysis
• Docker API integration for image building
• Error handling and logging

AI Agent Workflow

1. Repository Analysis - Fetch and analyze GitHub repository
2. Tech Stack Detection - Identify frameworks and dependencies
3. Dockerfile Generation - Create optimized Dockerfile
4. Image Building - Build actual Docker image
5. Result Storage - Save results to database

🚀 Deployment

Production Build

npm run build
npm start

Environment Variables (Production)

GEMINI_API_KEY=your_production_gemini_key
MONGODB_URI=your_production_mongodb_uri
GITHUB_TOKEN=your_github_token
PORT=3001
NODE_ENV=production
FRONTEND_URL=https://your-frontend-domain.com

📊 Monitoring

• Health checks at /health endpoint
• Generation status tracking
• Error logging and debugging
• Performance metrics for AI operations

🔒 Security

• GitHub token validation
• CORS configuration
• Input sanitization
• Error message sanitization
• Rate limiting (recommended for production)

🧪 Testing

# Test backend API
curl http://localhost:3001/health

# Test generation endpoint
curl -X POST http://localhost:3001/api/generation/generate \
  -H "Content-Type: application/json" \
  -d '{"githubUrl":"https://github.com/username/repo","githubToken":"your_token"}'

📝 Development

Adding New Features

1. Routes: Add routes in src/routes/
2. Services: Add business logic in src/services/
3. Models: Add database models in src/models/

Code Style

• TypeScript for type safety
• ESLint for code quality
• Prettier for code formatting
• Conventional commits for version control