来自微软的AutoGen

https://microsoft.github.io/autogen/

AutoGen is a framework that enables development of LLM applications using multiple agents that can converse with each other to solve task. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools.
来自官方的简介:大概描述起来就是基于LLM模型,使用多角色互动来分解、解决问题的框架。目前已经出现了多个类似的,比如之前文章里面写过的MetaGPT

Main Features

  • 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 overcome their weaknesses.
  • It 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.
  • It provides a collection of working systems with different complexities. These systems span a wide range of applications from various domains and complexities. They demonstrate how AutoGen can easily support different conversation patterns.
  • AutoGen provides a drop-in replacement of openai.Completion or openai.ChatCompletion as an enhanced inference API. It allows easy performance tuning, utilities like API unification & caching, and advanced usage patterns, such as error handling, multi-config inference, context programming etc.

The figure below shows the built-in agents in AutoGen. 


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