
Synergizing Reasoning and Acting in Language Models
ReAct is an open-source prompting technique and framework that enables large language models to synergize reasoning and acting. It allows agents to interleave thoughts with actions, interacting with external tools to gather information, overcome hallucination, and improve task performance. Best for researchers and developers building advanced, interpretable AI agents. Free and open source.
ReAct is a prompting technique and framework that combines reasoning traces and task-specific actions in large language models. It allows LLMs to generate both thoughts and actions in an interleaved manner, enhancing problem-solving, reducing hallucination, and improving interpretability. This research project demonstrates state-of-the-art few-shot performance across various language and decision-making tasks.
ReAct uniquely synergizes reasoning and acting by interleaving thought processes with external actions, allowing models to dynamically induce, track, and update action plans while interacting with environments like a Wikipedia API to gather information and handle exceptions.
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