ReAct is a prompting framework that interleaves reasoning traces with actionable steps, enabling large language models to think, act, and observe in a loop. This approach improves problem-solving and factuality by allowing the model to query external tools or knowledge bases. Developers and AI researchers benefit from enhanced performance on complex tasks like question answering and decision-making.
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