Recently, remarkable progress has been made in automated task-solving through the use of multi-agents driven by large language models (LLMs). However, existing works primarily focuses on simple tasks lacking exploration and investigation in complicated tasks mainly due to the hallucination problem. This kind of hallucination gets amplified infinitely as multiple intelligent agents interact with each other, resulting in failures when tackling complicated problems.Therefore, we introduce MetaGPT, an innovative framework that infuses effective human workflows as a meta programming approach into LLM-driven multi-agent collaboration. In particular, MetaGPT first encodes Standardized Operating Procedures (SOPs) into prompts, fostering structured coordination. And then, it further mandates modular outputs, bestowing agents with domain expertise paralleling human professionals to validate outputs and reduce compounded errors. In this way, MetaGPT leverages the assembly line work model to assign diverse roles to various agents, thus establishing a framework that can effectively and cohesively deconstruct complex multi-agent collaborative problems. Our experiments conducted on collaborative software engineering tasks illustrate MetaGPT's capability in producing comprehensive solutions with higher coherence relative to existing conversational and chat-based multi-agent systems. This underscores the potential of incorporating human domain knowledge into multi-agents, thus opening up novel avenues for grappling with intricate real-world challenges. The GitHub repository of this project is made publicly available on: https://github.com/geekan/MetaGPT

翻译：近期，通过大型语言模型（LLM）驱动的多智能体实现自动化任务求解取得了显著进展。然而，现有工作主要聚焦于简单任务，因幻觉问题缺乏对复杂任务的探索与研究。当多个智能体相互交互时，这种幻觉问题会被无限放大，导致处理复杂问题时的失败。为此，我们提出MetaGPT这一创新框架，将有效的人类工作流程作为元编程方法注入LLM驱动的多智能体协作中。具体而言，MetaGPT首先将标准化操作流程（SOP）编码为提示词，促进结构化协调；其次，强制要求模块化输出，赋予智能体与人类专家相当的领域专业知识，以验证输出并减少复合错误。通过这种方式，MetaGPT利用流水线工作模型为不同智能体分配多样化角色，从而构建一个能够高效、连贯地解构复杂多智能体协作问题的框架。我们在协作软件工程任务上的实验表明，相较于现有基于对话和聊天的多智能体系统，MetaGPT能生成连贯性更强的综合解决方案。这凸显了将人类领域知识融入多智能体的潜力，为应对现实世界复杂挑战开辟了新途径。本项目的GitHub代码库已公开：https://github.com/geekan/MetaGPT