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Meridian-powered cross-platform deployment orchestration for CrewAI agents

Project description

Meridian CrewAI Agent Deployment Orchestrator

Python 3.9+ License: MIT

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 steps
  • docker-compose.yml: Adjust resource limits, add services
  • prometheus.yml: Configure monitoring targets
  • health_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

  1. Fork the repository
  2. Create a feature branch
  3. Add tests for new functionality
  4. 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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