Multi-Agent AI System
A production-ready multi-agent AI system built for the Agentic AI In Production Certification Program.
🎯 Overview
This project demonstrates enterprise-grade AI system development with:
- Multi-Agent Architecture: Specialized agents for research, content generation, and validation
- Production Readiness: Comprehensive testing, security, and monitoring
- Quality Assurance: 70%+ test coverage with unit, integration, and E2E tests
- Security & Safety: Input validation, output filtering, and audit logging
- User Experience: Interactive web interface with real-time monitoring
- Operational Excellence: Health monitoring, metrics collection, and documentation
🚀 Quick Start
# Clone the repository
git clone https://github.com/ArnabSen08/multi-agent-ai-system.git
cd multi-agent-ai-system
# Install dependencies
pip install -r requirements.txt
# Configure environment
cp .env.sample .env
# Edit .env with your OpenAI API key
# Run system verification
python verify_deployment.py
# Start the application
streamlit run app.py
🏗️ Architecture
The system consists of four main components:
- CoordinatorAgent - Orchestrates workflows and manages agent communication
- ResearchAgent - Handles information gathering with multiple research types
- ContentAgent - Generates content with various styles and formats
- ValidationAgent - Ensures quality and safety with comprehensive validation
📊 Features
Production Readiness
- Robust error handling and graceful degradation
- Comprehensive logging and monitoring
- Scalable architecture with clear separation of concerns
Quality Assurance
- Unit tests for individual agent functions
- Integration tests for agent-to-agent communication
- End-to-end system tests for complete workflows
- 70%+ test coverage for core functionality
Security & Safety
- Input validation and sanitization
- Output filtering and content safety measures
- Comprehensive error handling
- Audit logging for compliance
User Experience
- Interactive web interface built with Streamlit
- Intuitive design abstracting technical complexity
- Clear error messages and user guidance
- Real-time progress indicators
📚 Documentation
🧪 Testing
Run the comprehensive test suite:
# Run all tests
pytest
# Run with coverage report
pytest --cov=src --cov-report=html
# Run system verification
python verify_deployment.py
🔧 Configuration
Key configuration options:
| Variable |
Description |
Default |
OPENAI_API_KEY |
OpenAI API key |
Required |
MAX_RETRIES |
Maximum retry attempts |
3 |
TIMEOUT_SECONDS |
Request timeout |
30 |
LOG_LEVEL |
Logging level |
INFO |
🎯 Certification Project
This project fulfills the requirements for the Agentic AI In Production Certification Program capstone project, demonstrating:
- Production-ready system architecture
- Comprehensive testing strategies
- Security and safety implementations
- Professional documentation standards
- Operational excellence practices
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🤝 Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests for new functionality
- Ensure all tests pass
- Submit a pull request
Built with ❤️ for the Ready Tensor Agentic AI Certification Program