Engineering Team AI Agent

🤖 Generate complete software systems from natural language requirements

A powerful multi-agent system built with CrewAI that automatically creates production-ready applications including modular code, tests, documentation, and Gradio-based UIs.

✨ What It Does

Transform this:

Create a Task Management System for small teams with user authentication, 
project creation, and real-time notifications.

Into this:

• 📦 Modular Python Code with clean architecture
• 🧪 Comprehensive Tests with high coverage
• 🖥️ Professional Gradio UI ready to deploy
• 📚 Complete Documentation and setup guides
• ⚙️ Environment Configuration with security best practices

🚀 Quick Start

1. Clone and Configure

git clone https://github.com/your-org/engineering-team-ai-agent.git
cd engineering-team-ai-agent
cp .env.example .env
# Add your OPENAI_API_KEY to .env

2. Run the Agent (Choose One)

Docker (Recommended)

# Run with default req.txt file
docker-compose up

# Or run interactively to input requirements
docker compose run --rm engineering-agent python -m engineering_team.main_flow --interactive

• Interactive mode lets you enter requirements line by line (type 'END' to finish).
• To use a different requirements file, replace req.txt before running.

UV (Modern Python)

uv sync
uv run engineering_team

Traditional Python

pip install -e .
engineering_team

🎯 Key Features

• 🏗️ Architecture Planning: Designs modular systems automatically
• 🔧 Code Generation: Creates production-ready Python modules
• 🔄 Self-Correction: Built-in retry logic with error feedback
• 🖥️ Gradio Integration: Professional UIs for all generated apps
• 🧪 Testing: Comprehensive test suites with validation
• 📖 Documentation: Auto-generated README and API docs
• 🔐 Security: Environment variable management and validation

📋 Usage

1. Edit req.txt with your project requirements, or use interactive mode.
2. Run the agent (see Quick Start above).
3. Check your generated project in the output/ directory.

⚙️ Configuration

Environment Variables

Required variables for the .env file:

# Required
OPENAI_API_KEY=your_openai_api_key_here
# Optional integrations
SERPER_API_KEY=your_serper_api_key
SENDGRID_API_KEY=your_sendgrid_key

Custom Configuration

from engineering_team.config import Config
config = Config(
    output_dir="my_projects",
    req_file="my_requirements.txt"
)

📁 Generated Project Structure

Every generated project includes:

output/
├── README.md                 # Project documentation
├── requirements.txt          # Python dependencies
├── .env.example             # Environment template
├── app.py                   # Gradio web application
├── test_system.py           # Comprehensive tests
├── system_integration.py    # Module orchestration
├── module1.py               # Business logic modules
├── module2.py               # (Generated based on requirements)
└── ...

🛠️ Advanced Usage

• Multiple Deployment Methods: See Quick Start for pip, UV, and Docker options.
• Custom Requirements: Edit req.txt or use --interactive mode.
• Development Mode: Use docker compose --profile dev up for live code changes.

🧪 Testing Generated Applications

cd output/
python test_system.py         # Run the test suite
python app.py                 # Launch the web application (http://localhost:7860)
pip install -r requirements.txt
python -m pytest              # If pytest tests are generated

🔧 Troubleshooting

Common Issues

"OpenAI API key not found"

cp .env.example .env
echo "OPENAI_API_KEY=your_key_here" >> .env

"Module creation failed"

• Check your internet connection
• Verify API key is valid
• The system automatically retries with error feedback

"Permission denied (Docker)"

sudo usermod -aG docker $USER
# Then logout and login again
# If you see permission errors with appuser, the Dockerfile has been fixed
# Rebuild the image: docker compose build --no-cache

Performance Tips

• Large projects: Complex requirements may take 10-15 minutes
• Docker: Use development profile for faster iteration
• UV: Fastest dependency management for Python projects

📖 Documentation

• Developer Guide - Technical details for contributors
• API Reference - Core classes and methods
• Architecture Overview - System design

🤝 Contributing

We welcome contributions! See our Developer Guide for:

• Development setup with Docker/UV
• Code quality standards
• Testing requirements
• Pull request process

Quick development setup:

git clone https://github.com/your-org/engineering-team-ai-agent.git
cd engineering-team-ai-agent
uv sync --dev
pre-commit install

📄 License

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

🙏 Credits

• Built with CrewAI multi-agent framework
• UI powered by Gradio
• Dependency management with UV

---

⭐ Star this repo if it helped you build amazing applications!# Trigger workflow