stella-workflow 0.1.0

A workflow engine for AI agents

Stella Workflow

A powerful, flexible workflow engine for AI agents and asynchronous task processing.

Features

• Agent-Based Architecture: Define independent agents that communicate through messages
• Asynchronous Processing: Built on Python's asyncio for efficient concurrent execution
• State Management: Track and persist agent state across executions
• Memory Storage: Store and retrieve data between agent invocations
• Conditional Execution: Control agent execution based on dynamic conditions
• Loop Processing: Process collections of items with built-in loop functionality
• Redis Integration: Use Redis as a reliable message broker and storage backend
• Extensible Design: Easily add new brokers, agents, and functionality

Installation

pip install stella-workflow

Quick Start

import asyncio
from stella_workflow.workflow import stella_agent
from stella_workflow.brokers import RedisBroker

# Create a broker
broker = RedisBroker({
    "host": "localhost",
    "port": 6379
})

# Define agents
@stella_agent(name="data_producer", broker=broker, topic="example_workflow")
async def data_producer():
    return {"message": "Hello from producer!"}

@stella_agent(name="data_consumer", broker=broker, topic="example_workflow", depends_on=["data_producer"])
async def data_consumer(message):
    producer_data = message["dependency_messages"]["data_producer"]["data"]
    print(f"Received: {producer_data['message']}")
    return {"status": "processed"}

async def main():
    # Connect to broker
    await broker.connect()
    
    try:
        # Start the workflow
        await stella_agent.start_workflow()
        
        # Wait for processing to complete
        await asyncio.sleep(2)
    finally:
        # Clean up
        await stella_agent.stop_workflow()
        await broker.close()

if __name__ == "__main__":
    asyncio.run(main())

Examples

The package includes several examples demonstrating different use cases:

• Document Processor: Process different document types through a workflow
• Bulk Email Processor: Send personalized emails to a list of users
• State Memory Pipeline: Collect, process, and analyze data with state tracking
• Message Flow: Create complex message flows between multiple agents
• Multiple Producers: Handle messages from multiple producer agents

Check the examples/ directory for complete implementations.

Documentation

For detailed documentation, see:

• Agent System

Additional documentation is coming soon!

Development

Setup

# Clone the repository
git clone https://github.com/yourusername/stella-workflow.git
cd stella-workflow

# Install dependencies
pip install poetry
poetry install

Testing

# Run all tests
poetry run pytest

# Run specific tests
poetry run pytest tests/test_workflow.py

Linting

# Run linting
poetry run ruff check .

# Run formatting
poetry run ruff format .

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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