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AI Coding Tools Collaborative - Production Ready

CI Coverage Python Version License Code style: black

Enterprise-grade orchestration system for collaborative AI coding assistants

Features • Quick Start • Documentation • Production Deployment

🚀 Features

Core Capabilities

  • 🤝 Multi-Agent Collaboration - Coordinate Claude, Codex, Gemini, and Copilot
  • 💬 Interactive Shell - REPL-style interface with context preservation
  • 📝 Session Management - Save and restore conversation history
  • ⚙️ Configurable Workflows - Define custom collaboration patterns
  • 🔧 Extensible Architecture - Easy to add new AI agents

Production-Ready Features

🛡️ Security

  • ✅ Input validation and sanitization
  • ✅ Rate limiting with token bucket algorithm
  • ✅ Secret management utilities
  • ✅ Audit logging for security events
  • ✅ Security scanning with Bandit
  • ✅ Vulnerability checking with Safety

📊 Monitoring & Observability

  • ✅ Prometheus metrics integration
  • ✅ Structured logging with structlog
  • ✅ Performance tracking and profiling
  • ✅ Health checks and readiness probes
  • ✅ Distributed tracing support (optional)

🎯 Reliability

  • ✅ Retry logic with exponential backoff
  • ✅ Circuit breaker pattern
  • ✅ Graceful degradation
  • ✅ Error handling with custom exceptions
  • ✅ Timeout management

⚡ Performance

  • ✅ Async execution support
  • ✅ In-memory and file-based caching
  • ✅ Connection pooling
  • ✅ Concurrent agent execution
  • ✅ Resource optimization

🔍 Code Quality

  • ✅ Comprehensive type hints (MyPy)
  • ✅ Code formatting (Black, isort)
  • ✅ Linting (Flake8, Pylint)
  • ✅ Pre-commit hooks
  • ✅ >80% test coverage

🚢 Deployment

  • ✅ Docker support with multi-stage builds
  • ✅ Docker Compose for local development
  • ✅ Kubernetes manifests
  • ✅ Helm charts (coming soon)
  • ✅ Systemd service file

🔄 CI/CD

  • ✅ GitHub Actions workflows
  • ✅ Automated testing (unit, integration, security)
  • ✅ Multi-platform support (Linux, macOS, Windows)
  • ✅ Automated releases
  • ✅ Container image publishing

📋 Requirements

  • Python 3.8 or higher
  • AI CLI tools (Claude, Codex, Gemini, Copilot)
  • Docker (optional, for containerized deployment)
  • Kubernetes (optional, for cluster deployment)

⚡ Quick Start

Installation

# Clone the repository
git clone https://github.com/your-org/ai-orchestrator.git
cd ai-orchestrator

# Run installation script
./scripts/install.sh

# Or install manually
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e ".[dev]"

Configuration

# Copy environment template
cp .env.example .env

# Edit configuration
vim .env

# Validate configuration
./ai-orchestrator validate

Basic Usage

# Start interactive shell
./ai-orchestrator shell

# Run a one-shot task
./ai-orchestrator run "Create a REST API with user authentication"

# Check available agents
./ai-orchestrator agents

# List workflows
./ai-orchestrator workflows

🏗️ Architecture

┌─────────────────────────────────────────────┐
│         AI Orchestrator CLI                 │
│  (User Interface & Workflow Management)     │
└─────────────────┬───────────────────────────┘
                  │
        ┌─────────┴─────────┐
        │   Core Components  │
        │  ┌──────────────┐ │
        │  │ Orchestrator │ │
        │  ├──────────────┤ │
        │  │ Config Mgr   │ │
        │  ├──────────────┤ │
        │  │ Metrics      │ │
        │  ├──────────────┤ │
        │  │ Security     │ │
        │  ├──────────────┤ │
        │  │ Cache        │ │
        │  └──────────────┘ │
        └─────────┬─────────┘
                  │
    ┌─────────────┼─────────────┬─────────────┐
    │             │             │             │
┌───▼───┐   ┌────▼────┐   ┌────▼────┐   ┌────▼────┐
│ Codex │   │ Gemini  │   │ Claude  │   │ Copilot │
│Adapter│   │ Adapter │   │ Adapter │   │ Adapter │
└───┬───┘   └────┬────┘   └────┬────┘   └────┬────┘
    │            │             │             │
┌───▼───┐   ┌────▼────┐   ┌────▼────┐   ┌────▼────┐
│Codex  │   │Gemini   │   │Claude   │   │Copilot  │
│CLI    │   │CLI      │   │Code     │   │CLI      │
└───────┘   └─────────┘   └─────────┘   └─────────┘

🐳 Production Deployment

Docker

# Build image
docker build -t ai-orchestrator:latest .

# Run container
docker run -it --rm \
  -v $(pwd)/config:/app/config \
  -v $(pwd)/output:/app/output \
  ai-orchestrator:latest

# Using Docker Compose
docker-compose up -d

# With monitoring stack
docker-compose --profile monitoring up -d

Kubernetes

# Apply manifests
kubectl apply -f deployment/kubernetes/

# Check deployment
kubectl get pods -l app=ai-orchestrator

# View logs
kubectl logs -f deployment/ai-orchestrator

# Access metrics
kubectl port-forward svc/ai-orchestrator 9090:9090

Systemd

# Copy service file
sudo cp deployment/systemd/ai-orchestrator.service /etc/systemd/system/

# Create configuration
sudo mkdir -p /etc/ai-orchestrator
sudo cp .env.example /etc/ai-orchestrator/environment

# Enable and start service
sudo systemctl enable ai-orchestrator
sudo systemctl start ai-orchestrator

# Check status
sudo systemctl status ai-orchestrator

📊 Monitoring

Metrics

Prometheus metrics are exposed on port 9090 at /metrics:

  • orchestrator_tasks_total - Total tasks executed
  • orchestrator_task_duration_seconds - Task duration
  • orchestrator_agent_calls_total - Agent invocations
  • orchestrator_agent_errors_total - Agent errors
  • orchestrator_cache_hits_total - Cache hits
  • And more...

Health Checks

# Check health
curl http://localhost:9090/health

# Check readiness
curl http://localhost:9090/ready

🧪 Testing

# Run all tests
make test

# Run with coverage
make test-coverage

# Run specific test suite
pytest tests/test_orchestrator.py -v

# Run integration tests
pytest tests/ -v -m integration

# Run security tests
pytest tests/ -v -m security

🔧 Development

# Install development dependencies
make install-dev

# Format code
make format

# Run linters
make lint

# Type checking
make type-check

# Security scan
make security

# Run all checks
make all

Pre-commit Hooks

# Install hooks
pre-commit install

# Run on all files
pre-commit run --all-files

📚 Documentation

🔒 Security

For security issues, please see SECURITY.md.

Key security features:

  • Input validation and sanitization
  • Rate limiting
  • Secret management
  • Audit logging
  • Regular security scanning

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

📄 License

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

🙏 Acknowledgments

📞 Support

Made with ❤️ for the AI development community

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