Unverified50% confidenceFactExact time
传统ReAct框架要求模型在每次工具调用后将结果写回上下文再重新读取整个对话历史决定下一步，导致Token消耗和延迟累积
1
Sources
50%
Confidence
Long-term
Relevance
7/12/2026
First Seen
Sources
Related Claims
VerifiedThe ReAct framework enables the model to interact with the external environment while reasoning—first reasoning about what to do, then calling external tools to act, then observing the results returned by the tools, iterating in a loop until the task is complete.81% similarUnverified在ReAct框架下，每次工具调用需将完整历史上下文重新传入模型，导致上下文窗口随执行步骤线性累积，而计费成本呈近似二次方增长81% similarUnverifiedThe ReAct pattern interweaves the language model's reasoning (Chain-of-Thought) with action calls to external tools within the same loop78% similarUnverifiedIn multi-turn conversations, before each new response is generated, the system must re-input all prior conversation history into the model, causing token consumption to accumulate and grow with each turn76% similarUnverifiedReAct establishes an alternating execution protocol between reasoning traces and actions, writing observations returned by tools into the context before the next round of reasoning, laying the theoretical foundation for mainstream agent frameworks such as LangChain, AutoGPT, and Claude tool calling.76% similar
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