# ReAct (Reasoning + Acting)

> ReAct is an agent loop that interleaves reasoning with tool actions — Thought, Action, Observation, repeat — so the model plans, calls a tool, and revises.

**ReAct (Reasoning + Acting) is an agent pattern that interleaves reasoning traces with tool actions and their observations — Thought, Action, Observation, then repeat — so the model plans a step, calls a tool, reads the result, and revises before acting again.**

Each cycle, the model writes a short reasoning trace (the "Thought"), chooses an action — typically a tool call via [function calling](/glossary/function-calling) — and then receives an Observation: the tool's actual output. That observation feeds the next Thought, so the loop grounds reasoning in real results instead of guessing the whole plan in advance. It is essentially [chain-of-thought](/glossary/chain-of-thought) extended with the ability to act in the world and learn from what happens.

This is the canonical loop behind most tool-using [AI agents](/glossary/ai-agent). Its strength is robustness under uncertainty — the model recovers from surprising tool output, failed calls, or missing data because it observes before committing. The caveat is that each cycle costs a full model call, loops can wander or repeat themselves without step limits and clear stopping conditions, and a wrong observation early can mislead the entire trajectory.

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_Source: https://agentscamp.com/glossary/react-agent — Term on AgentsCamp._