Research Agentic AI

Build and optimize AI agents with collaborative multi-agent frameworks.

AutoGen

AutoGen is an innovative open-source programming framework designed to build AI agents and facilitate collaboration among multiple agents to tackle complex tasks. It empowers developers to create next-generation AI applications by offering customizable and conversable agents that seamlessly integrate with large language models (LLMs), tools, and human input. AutoGen supports a variety of conversation patterns, autonomous and human-in-the-loop workflows, and enhances LLM inference and optimization, thereby maximizing performance and reducing costs.

Developed through a collaboration between Microsoft, Penn State University, and the University of Washington, AutoGen stands out by accelerating research and development in agentic AI, much like PyTorch does for deep learning. Its unique features include a multi-agent conversation framework, customizable agents, and support for diverse conversation patterns. AutoGen simplifies LLM workflow orchestration and offers enhanced LLM inference and optimization, making it a powerful tool for building AI agents, developing multi-agent systems, automating LLM workflows, and enhancing LLM performance across various domains.

Research Agentic AI Tools

1 Tools for Research Agentic AI

AutoGen