ReAct: Synergizing Reasoning and Acting in Language Models

Authors: Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, Yuan Cao (2022)

arXiv: 2210.03629

TLDR (English)

ReAct interleaves reasoning and acting: LLM thinks (Thought), executes a tool call (Action), observes the result (Observation), and cycles. This is the prototype for modern AI agent frameworks, directly influencing LangChain, AutoGPT, and similar agent frameworks.

TLDR（中文）

ReAct 框架将推理（Reasoning）和行动（Acting）交织在一起：LLM 先思考（Thought）， 再执行工具调用（Action），观察结果（Observation），如此循环。这是现代 AI Agent 框架的原型，直接影响了 LangChain、AutoGPT 等 agent 框架的设计。