Meridian-powered cross-platform deployment orchestration for CrewAI agents
Project description
Meridian CrewAI Agent Deployment Orchestrator
Meridian-powered cross-platform deployment orchestration for CrewAI agents. Analyze agent codebases and generate optimized Docker configurations with one command.
Quick Start
# Install
pip install meridian-crewai-deploy-orchestrator
# Analyze an agent and generate deployment configs
meridian-crewai-deploy-orchestrator /path/to/agent --output ./deployment
# Or use directly with Python
python -m orchestrator /path/to/agent --output ./deployment
Installation
From PyPI
pip install meridian-crewai-deploy-orchestrator
From Source
git clone https://github.com/meridian-mind/crewai-deploy-orchestrator.git
cd crewai-deploy-orchestrator
pip install -r requirements.txt
Development Installation
pip install -e ".[dev]"
Features
- Agent Analysis: Parse CrewAI agent definitions to extract dependencies
- Dependency Detection: Identify Python packages and system requirements
- Docker Generation: Create optimized Dockerfile and docker-compose.yml
- Health Monitoring: Built-in health checks and monitoring setup
- Multi-Platform: Ready for cloud deployment (AWS, GCP, Azure, etc.)
Usage Examples
Basic Usage
# Analyze an agent and generate deployment configs
crewai-deploy /path/to/agent --output ./deployment
# With custom agent name
crewai-deploy /path/to/agent --output ./deployment --agent-name my-agent
Example with Included Examples
# Test with included examples
crewai-deploy examples/simple_agent --output simple_deployment
# Deploy
cd simple_deployment
docker-compose up -d
Output Structure
The tool generates the following files:
deployment/
├── Dockerfile # Optimized container definition
├── docker-compose.yml # Multi-service orchestration
├── requirements.txt # Python dependencies
├── health_check.py # Health monitoring endpoint
├── prometheus.yml # Monitoring configuration
└── logs/ # Log directory (mounted volume)
How It Works
1. Agent Analysis
The tool scans your CrewAI agent codebase for:
- Python imports and dependencies
- Agent class definitions (Agent, CrewAI patterns)
- Requirements files (requirements.txt, setup.py, pyproject.toml)
- System package requirements (apt-get install patterns)
2. Dependency Resolution
- Extracts all Python package dependencies
- Identifies system-level requirements
- Creates optimized installation order
3. Docker Configuration
- Generates optimized Dockerfile with caching
- Creates docker-compose.yml with health checks
- Includes monitoring setup (Prometheus)
- Sets up volume mounts for persistence
4. Health Monitoring
- Built-in FastAPI health endpoint
- Resource usage monitoring (CPU, memory)
- Agent status reporting
- Ready for integration with monitoring stacks
Testing
Run the test suite:
python test_orchestrator.py
The test suite includes:
- Simple agent analysis
- Web research agent analysis
- CLI interface testing
- Docker config generation
Example Agents
The repository includes two example agents:
1. Simple Agent (examples/simple_agent/)
- Basic data analysis agent
- Report generation workflow
- Minimal dependencies
2. Web Research Agent (examples/web_research_agent/)
- Multi-agent research system
- Web scraping capabilities
- Async processing
- Comprehensive reporting
Deployment Options
Local Development
docker-compose up -d
Production Considerations
- Set environment variables for API keys
- Configure resource limits in docker-compose.yml
- Add SSL/TLS termination
- Set up proper logging and monitoring
- Implement backup strategies
Cloud Deployment
- AWS: Deploy to ECS/EKS with Load Balancer
- GCP: Deploy to Cloud Run or GKE
- Azure: Deploy to Container Apps or AKS
- Kubernetes: Use generated manifests with
kompose convert
Configuration
Environment Variables
# Agent configuration
OPENAI_API_KEY=your_key_here
LOG_LEVEL=INFO
PYTHONPATH=/app
# Docker configuration
MEMORY_LIMIT=2g
CPU_LIMIT=1.0
Customizing Deployment
Edit generated files:
Dockerfile: Add custom build stepsdocker-compose.yml: Adjust resource limits, add servicesprometheus.yml: Configure monitoring targetshealth_check.py: Add custom health checks
Limitations (MVP)
- Currently supports Python/CrewAI agents only
- Basic dependency resolution (no conflict handling)
- Assumes FastAPI for health endpoints
- Limited system package detection
- No automatic cloud deployment integration
Roadmap
- Advanced dependency conflict resolution
- Cloud provider templates (AWS, GCP, Azure)
- Kubernetes manifests generation
- Database and cache integration
- Secret management
- CI/CD pipeline templates
- Multi-language agent support
- Performance optimization recommendations
Contributing
- Fork the repository
- Create a feature branch
- Add tests for new functionality
- Submit a pull request
License
MIT License - See LICENSE file for details.
Community
- GitHub Issues: Report bugs and feature requests
- Discussions: Share ideas and ask questions
- CrewAI Discord: Join the CrewAI community
Built for the CrewAI ecosystem • Deploy agents anywhere with confidence
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