AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation¶
组织：Microsoft Research、宾夕法尼亚州立大学、华盛顿大学、西安电子科技大学
AutoGen 是一个开源框架，允许开发人员通过多个代理构建 LLM 应用程序，这些代理可以相互交谈以完成任务。AutoGen 代理是可定制的、可对话的，并且可以在多种模式下运行，这些模式采用 LLMs、人工输入和工具的组合。使用 AutoGen，开发人员还可以灵活地定义代理交互行为。自然语言和计算机代码都可用于为不同的应用程序编写灵活的对话模式。AutoGen 用作通用基础设施，用于构建各种复杂性和 LLM能力的不同应用。实证研究表明，该框架在许多示例应用程序中的有效性，领域包括数学、编码、问答、运筹学、在线决策、娱乐等。
AutoGen is an open-source framework that allows developers to build LLM applications via multiple agents that can converse with each other to accomplish tasks. AutoGen agents are customizable, conversable, and can operate in various modes that employ combinations of LLMs, human inputs, and tools. Using AutoGen, developers can also flexibly define agent interaction behaviors. Both natural language and computer code can be used to program flexible conversation patterns for different applications. AutoGen serves as a generic infrastructure to build diverse applications of various complexities and LLM capacities. Empirical studies demonstrate the effectiveness of the framework in many example applications, with domains ranging from mathematics, coding, question answering, operations research, online decision-making, entertainment, etc.
Figure 1: AutoGen enables diverse LLM-based applications using multi-agent conversations. (Left) AutoGen agents are conversable, customizable, and can be based on LLMs, tools, humans, or even a combination of them. (Top-middle) Agents can converse to solve tasks. (Right) They can form a chat, potentially with humans in the loop. (Bottom-middle) The framework supports flexible conversation patterns.¶
备注
为了减少开发人员跨各个域创建复杂的 LLM，AutoGen 的一个核心设计原则是使用多代理对话来简化和整合多代理工作流。此方法还旨在最大限度地提高已实施代理的可重用性。 AutoGen 的两个关键概念：可交互代理和对话编程。 conversable agents and conversation programming
图 13：给定任务中的双代理聊天 （a） 和群聊 （b） 的比较。群聊通过更顺畅的对话成功解决任务，而两个代理聊天在同一任务上失败，并以重复对话结束。¶