What is ReAct Loop?
A reasoning-and-acting cycle where an AI agent alternates between thinking about a problem and taking actions to solve it.
The ReAct (Reasoning + Acting) loop is an agent execution pattern in which the model iterates through a cycle of observation, reasoning, and action. At each step, the agent observes the current state of the environment, reasons about what to do next using chain-of-thought style deliberation, selects and executes an action (such as calling a tool or reading a file), and then incorporates the result into its next reasoning step. This loop continues until the agent determines the task is complete or it hits a termination condition. ReAct enables agents to handle multi-step problems that cannot be solved in a single inference pass.