AI2026-05-17
ReAct (Reasoning and Acting)
Also known as: ReAct / Reasoning and Acting / 推論と行動
An agent framework that interleaves LLM reasoning traces with external actions (tool calls, searches, code execution), enabling the model to gather information and verify intermediate steps before concluding.
Overview
ReAct, proposed by Google in 2022, has the LLM cycle through 'Thought → Action → Observation' steps, using external tools (search engines, calculators, APIs) to gather information and verify intermediate results. Most modern AI-agent frameworks are built on this pattern.
Relationship to AI agents
Frameworks like LangChain, LlamaIndex, OpenClaw, and Claude Code implement the ReAct pattern at their core. The think-act loop enables LLMs to handle tasks requiring information retrieval or computation that the model cannot perform in a single inference step.
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