Unverified50% confidenceFactExact time
The context window in LLMs determines how many conversation turns the model can remember when making modifications to previously generated content
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
Valid until: 9/30/2026
Sources
Building a WeChat Mini Program with Zero Code: A 3-Day Hands-On Journey with Codex + Antigravity
bilibiliEter-bibi6/1/2026
Related Claims
Unverified长上下文窗口机制使模型在切换说话角色后仍能保持人物设定与事件背景的一致性，区别于早期依赖外部知识库检索或手动状态管理的对话系统77% similarUnverifiedTransformer模型的注意力机制使模型能够在长达数千Token的上下文窗口内追踪对话语义，而早期LSTM模型受限于固定窗口的短期记忆74% similarUnverified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74% similarVerifiedLLM的'记忆'在技术实现上是将历史对话文本拼接到当前请求的Prompt中，让模型在同一次推理里看到历史内容72% similarUnverifiedLLM的记忆依赖于上下文窗口，即模型在单次推理时能够处理的最大Token数量70% similar
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