GraphFusionAI: A toolkit for graph-based AI agents and multi-agent systems

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GraphFusionAI is an open-source framework for building adaptive multi-agent systems using the power of knowledge graphs and neural memory networks. It provides a foundation for creating collaborative, real-time learning agents capable of dynamic task orchestration and semantic understanding.

The project is designed for modularity and accessibility, enabling developers to build graph-based AI agents and multi-agent systems across industries like healthcare, finance, education, and more.

Key Features

• Graph-Based Memory: Combines structured knowledge graphs with neural memory for adaptable and queryable agent memory.
• Multi-Agent Collaboration: Supports dynamic task orchestration and collaboration between AI agents.
• Integrations with LLMs: Expandable with large language model tools for enhanced capabilities.

Getting Started

Prerequisites

• Python 3.9+
• Virtual environment (recommended)
• Required dependencies (see requirements.txt)

Installation

1. Clone the repository:

   git clone https://github.com/GraphFusion/GraphFusionAI.git
   cd GraphFusionAI

2. Install the package via pip:

   pip install .

3. Install additional dependencies for development:

   pip install -r requirements.txt

Quick Start

1. Run the Simple Agent Workflow example:

   python examples/simple_agent_workflow.py

2. Review outputs to observe agent interactions, memory updates, and graph modifications.

Contributing

We welcome contributions to make GraphFusionAI even better! You can contribute by:

• Identifying bugs by running examples/simple_agent_workflow.py.
• Suggesting or implementing new features.
• Improving documentation.

Steps to Contribute

1. Fork the repository.
2. Create a branch for your feature/bugfix:

   git checkout -b feature-name

3. Commit your changes:

   git commit -m "Description of changes"

4. Push your branch and open a Pull Request.

Issues

Run examples/simple_agent_workflow.py to identify the following types of issues:

1. Bugs in knowledge graph updates or neural memory workflows.
2. Optimization opportunities for multi-agent collaboration.
3. Missing integrations with external LLM tools or APIs.
4. Gaps in documentation and user experience.

Check the issues page for a complete list.

Documentation

For detailed usage instructions, visit our official documentation.

Community

Join the conversation, share feedback, and collaborate on new ideas:

• Discord: Join our community
• GitHub Discussions: Start a thread

License

GraphFusionAI is open-source and licensed under the MIT License.