I need your help creating an example with Llama_index and MiniAutoGen: Lightweight and Flexible Agents for Multi-Agent Chats

[brunocapelao]

🌐 Hello, amazing community!

I'm exploring the integration of two powerful libraries: MiniAutoGen and LLama_index, and I would greatly appreciate your help and insights!

MiniAutoGen is an innovative open-source library designed to take applications with Large Language Models (LLMs) to the next level. Its differentiators are its lightweight and flexible approach, which allows for a high degree of customization.

Here are some notable features of MiniAutoGen:

• Multi-Agent Dialogues: The ability to create complex and nuanced interactions with multiple intelligent agents operating together.
• Agent Coordination: A mechanism that ensures harmony and efficient management among the agents.
• Customizable Agents: Total freedom to shape agent behaviors according to project needs.
• Action Pipeline: Simplifies and automates agent operations, facilitating scalability and maintenance.
• Integration with +100 LLMs: Expanding conversational capabilities with over 100 LLMs for intelligent and contextualized responses.

My Challenge: I'm seeking help from the community to develop new integrations and modules.

I Seek Your Help: Do you have examples, tips, or guidance on how I can accomplish this integration? Any insight or shared experience would be extremely valuable!

Check out MiniAutoGen on Google Colab: MiniAutoGen on Google Colab
And here is the GitHub repository for more information: GitHub - brunocapelao/miniAutoGen

I'm looking forward to your ideas and suggestions. Let's shape the future of AI conversations together! 🌟