AutoGen

Developed by Microsoft, AutoGen is a open-source famework that enables the development of next-gen LLM applications using multiple agents that can converse with each other to solve tasks.

Key Features

• AutoGen agents are customizable, conversable, and seamlessly allow human participation.
• AutoGen enables building next-gen LLM applications based on multi-agent conversations with minimal effort.
• It simplifies the orchestration, automation, and optimization of a complex LLM workflow.
• It maximizes the performance of LLM models and overcomes their weaknesses.

Use Cases

AutoGen supports diverse conversation patterns for complex workflows. With customizable and conversable agents, developers can use AutoGen to build a wide range of conversation patterns concerning conversation autonomy, the number of agents, and agent conversation topology.

AutoGen also provides a drop-in replacement of openai.Completion or openai.ChatCompletion as an enhanced inference API. This demonstrates how AutoGen can easily support diverse conversation patterns.

The framework also allows easy performance tuning, utilities like API unification and caching, and advanced usage patterns, such as error handling, multi-config inference, context programming, etc.

AutoGen is powered by collaborative research studies from Microsoft, Penn State University, and the University of Washington.

AutoGen

Enable Next-Gen Large Language Model Applications.

Go to AutoGen

AutoGen Tutorials

Building AI Agents with AutoGen

In this guide, we’ll discuss how to get started building AI agents using Microsoft’s open source framework: AutoGen.

MLQ.aiPeter Foy

AI Agents for Data Visualization with AutoGen

In this guide, we’ll look at how to build AI agents for data visualization using AutoGen.

MLQ.aiPeter Foy

Getting Started with AutoGen: MLQ Academy

In this video tutorial, we’ll walk through how to get started building AI agents with the open source framework: AutoGen.

MLQ.aiPeter Foy