ReAct: Reasoning and Acting in Language Models

This research introduces ReAct, a novel prompting method that enhances language models by synergizing reasoning and acting. ReAct prompts language models to generate interleaved reasoning traces and actions, allowing dynamic reasoning and interaction with external environments. Experiments across diverse tasks like question answering, fact verification, text-based games, and web navigation demonstrate ReAct's superiority over isolated reasoning or action approaches. The approach not only improves task performance but also enhances model interpretability and trustworthiness. Further analysis…