This project provides a framework for integrating MemGPT and AutoGEN to create multi-agent AI systems powered by local Large Language Models (LLMs). It targets developers and researchers looking to leverage the combined capabilities of memory-augmented LLMs and agent orchestration for complex AI tasks.

How It Works

The system connects MemGPT as an assistant agent alongside local LLMs orchestrated by AutoGEN. This allows for dynamic switching between agent functionalities based on a configurable flag, enabling seamless collaboration between memory-enhanced agents and general-purpose LLMs. The integration relies on setting up API endpoints for local LLMs, likely through a service like Runpods, to facilitate communication between the agents.

Quick Start & Requirements

• Install: Python, VS Code, Runpods account with credits.
• Prerequisites: Virtual environment, openai, pyautogen, memgpt libraries.
• Setup: Requires configuring API endpoints for local LLMs deployed on a platform like Runpods.
• Resources: Deployment on Runpods suggests potential GPU and cloud compute requirements.
• Documentation: A YouTube video tutorial is provided for setup and understanding: https://youtu.be/bMWXXPoDnDs

Highlighted Details

• Integrates MemGPT's memory capabilities with AutoGEN's agent orchestration.
• Enables dynamic switching between MemGPT and AutoGEN agents.
• Facilitates the use of local LLMs via API endpoints.

Maintenance & Community

Information regarding maintenance, community channels, or notable contributors is not detailed in the provided README.

Licensing & Compatibility

The README does not specify licensing information. Compatibility with commercial or closed-source projects is unknown.

Limitations & Caveats

The project appears to be demonstrated through a YouTube video tutorial, suggesting it may be a personal project rather than a formally maintained open-source library. Setup relies on external services like Runpods, which may incur costs and introduce dependencies.