Metadata-Version: 2.1
Name: multi-agent-alpha
Version: 0.1.3
Summary: Multi-Agent Alpha is a robust, open-source framework for building, managing, and deploying intelligent multi-agent systems. It provides a flexible architecture for creating custom agents, with a focus on code quality, testing, and continuous integration.
License: CC-BY-NC-4.0
Author: Nishchal Gaba
Author-email: nishgaba.ai@gmail.com
Requires-Python: >=3.12,<4.0
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: fastapi (>=0.112.1,<0.113.0)
Requires-Dist: langchain (>=0.2.14,<0.3.0)
Requires-Dist: numpy (>=1.26.0,<2.0.0)
Requires-Dist: pandas (>=2.2.2,<3.0.0)
Requires-Dist: pydantic (>=2.2.1,<3.0.0)
Requires-Dist: requests (>=2.31.0,<3.0.0)
Description-Content-Type: text/markdown

# Multi-Agent Alpha

![CI](https://github.com/nishgaba-ai/multi-agent-alpha/workflows/CI/badge.svg)

Multi-Agent Alpha is a robust, open-source framework designed to simplify the process of building, managing, and deploying intelligent multi-agent systems. This project serves as a stepping stone for individuals and organizations to automate complex multi-agent workflows with ease, including support for custom hooks and capabilities.

## Key Features

- **Modular Architecture**: Easily build and manage multi-agent systems with a flexible and scalable architecture.
- **Custom Hooks**: Extend the functionality of your agents with custom hooks, allowing for seamless integration with other tools and systems.
- **Non-Commercial Use**: Built with open-source principles, supporting non-commercial use while encouraging community contributions.
- **PEP 8 Compliance**: Ensures code quality and consistency through adherence to Python’s PEP 8 standards, with built-in linters and formatters.
- **Integration with LangChain**: Leverage advanced agent workflows with integration support for LangChain.
- **Continuous Integration**: Automatically test and validate your code with GitHub Actions, ensuring that every change is stable and reliable.

## Getting Started

To get started with Multi-Agent Alpha, follow these steps:

### Clone the Repository

```
git clone https://github.com/nishgaba-ai/multi-agent-alpha.git
cd multi-agent-alpha
```

## Install Dependencies
Use Poetry to install the project dependencies:
```
poetry install
```

## Run Tests
Ensure everything is working by running the tests:
```
poetry run pytest
```

## Installation
To install Multi-Agent Alpha in your project, use Poetry:
```
poetry add multi-agent-alpha
```

## Usage
Here's a simple example of how to create and run a custom agent:
```
from multi_agent_alpha.agents import CustomAgent

# Initialize a custom agent
agent = CustomAgent(name="MyAgent")

# Use the agent to perform a task
result = agent.example_usage(query="Post this message to LinkedIn")
print(result)
```

## Contributing
We welcome contributions from the community! Please follow these steps to contribute:

1. Fork the repository and clone it locally.
2. Create a new branch for your feature or bug fix.
3. Commit your changes with clear commit messages.
4. Push to your branch and submit a pull request.

Please ensure that your code adheres to the existing code style and passes all tests before submitting.

## License
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. See the LICENSE file for more details.

## Acknowledgements
Special thanks to all the contributors and the open-source community for their support and collaboration.

## Contact
For any questions, feel free to reach out to the project maintainer, Nishchal Gaba, at nishgaba.ai@gmail.com.

