🚀 AutoGen - AI-Powered Project Generator

The Ultimate AI Assistant for Full-Stack Project Generation

From idea to production-ready code in minutes, not weeks ⚡

🌟 What Makes AutoGen Special?

Imagine having 5 senior developers working together 24/7 to build your project:

• 🎯 Business Analyst - Analyzes requirements and creates user stories
• 🏗️ System Architect - Designs scalable architecture and databases
• 💻 Full-Stack Developer - Generates production-ready code
• 🧪 QA Engineer - Creates comprehensive test suites
• 🚀 DevOps Expert - Sets up CI/CD and deployment configs

All powered by Google Gemini AI with advanced RAG (Retrieval-Augmented Generation) system!

✨ Features That Will Blow Your Mind

🤖 Multi-Agent AI System

• 5 Specialized Gemini APIs working in perfect harmony
• Each agent has unique expertise and responsibilities
• Intelligent context sharing between agents
• Advanced error handling and retry mechanisms

🧠 Smart RAG System

• Scans existing project files to understand context
• Continues from where you left off - no starting over!
• Learns from your codebase patterns
• Provides intelligent suggestions based on existing code

🔄 Resume-Anywhere Workflow

# Resume from any stage - your progress is never lost!
await workflow.resume_workflow(user_input)

📁 Complete Project Structure

projects/your_project/
├── 01_requirements/     # Business analysis & user stories
├── 02_architecture/     # System design & tech stack
├── 03_code/            # Production-ready source code
├── 04_tests/           # Comprehensive test suites
├── 05_deployment/      # Docker, K8s, CI/CD configs
└── logs/               # Detailed generation logs

🎬 See It In Action

From Idea to Production in 5 Steps

Requirements Analysis	Architecture Design	Code Generation

Testing & Review	Deployment Setup

🚀 Quick Start

1. Clone & Setup

git clone https://github.com/doanngocthanh/AutoGen.git
cd AutoGen
pip install -r requirements.txt

2. Configure API Keys

# Create .env file
echo "GEMINI_API_KEYS=your_key1,your_key2,your_key3,your_key4,your_key5" > .env

3. Generate Your First Project

python version2.py

4. Describe Your Dream Project

I want to build an e-commerce platform with:
- Product & category management
- Shopping cart & checkout
- Order management system
- User authentication
- Admin dashboard
- Mobile API
- Payment integration (VNPay, Momo)
- Multi-language support

5. Watch the Magic Happen! ✨

💡 Real-World Example

Here's what AutoGen generated for an E-commerce Platform:

// Generated backend API (FastAPI)
@app.post("/api/products")
async def create_product(product: ProductCreate, db: Session = Depends(get_db)):
    return crud.create_product(db=db, product=product)

// Generated frontend component (React)
const ProductList: React.FC = () => {
    const [products, setProducts] = useState<Product[]>([]);
    // Complete component implementation...
}

// Generated tests
def test_create_product():
    response = client.post("/api/products", json={...})
    assert response.status_code == 201

🛠️ Advanced Features

Smart Context Management

The RAGManager class scans your project and provides intelligent context:

# Automatically understands your project structure
rag_context = self.rag_manager.get_context_for_stage("deployment")

Error Recovery & Resilience

Advanced JSON parsing with multiple fallback strategies:

def parse_partial_json(self, text: str) -> Dict:
    """Finds and parses the first JSON object with smart error recovery"""

Parallel Code Generation

Generate multiple modules simultaneously for faster development:

# Generate backend, frontend, and database modules in parallel
tasks = [self.generate_module_code(module, prompt, context) for module in modules]
results = await asyncio.gather(*tasks)

📊 What You Get

📋 Requirements Analysis

• Detailed user stories
• Acceptance criteria
• Timeline estimates
• Priority rankings

🏗️ System Architecture

• Technology stack recommendations
• Database schema design
• API structure planning
• Scalability considerations

💻 Production Code

• Complete, runnable source code
• Best practices implementation
• Proper error handling
• Security considerations

🧪 Comprehensive Testing

• Unit tests with full coverage
• Integration tests
• End-to-end scenarios
• Performance benchmarks

🚀 Deployment Ready

• Dockerfiles for all services
• Kubernetes manifests
• CI/CD pipelines (GitHub Actions)
• Monitoring & logging setup

🎯 Perfect For

• 🚀 Startup MVPs - From idea to prototype in hours
• 🏢 Enterprise Projects - Scalable architecture & best practices
• 📚 Learning & Education - See how experts structure projects
• 🔬 Prototyping - Rapid proof-of-concept development
• 🛠️ Boilerplate Generation - Skip the repetitive setup

🤝 Contributing

We love contributions! Here's how you can help:

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

📄 License

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

🙏 Acknowledgments

• Google Gemini AI for the powerful language models
• FastAPI for the awesome Python web framework
• React for the incredible frontend library
• Docker for containerization made simple

🌟 Star History

Star History

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