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wiki/concepts/Context-Reset.md
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wiki/concepts/Context-Reset.md
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title: "Context Reset"
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type: concept
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tags:
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- "agentic-ai"
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- "context-window"
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- "recovery"
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sources:
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- "Your-AI-Isn-t-Stupid---It-Just-Needs-a-Better-Harness--Lychee-Technology-Engineering-Blog"
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last_updated: 2026-04-20
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---
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## Overview
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Context Reset——当 [[Context-Anxiety]] 触发时,Harness 将当前 Agent 状态保存至磁盘、终止实例、启动全新 Agent 的程序化操作,用于解决长周期任务超出单次 context window 的问题。
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## Trigger Condition
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```python
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if (tokens_used / max_context) > 0.7: # 阈值需按模型调优
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trigger_context_reset()
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```
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## Procedure
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1. **Save state**: 完整项目状态写入持久存储(磁盘文件)
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2. **Terminate**: 终止当前 LLM 实例
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3. **Launch fresh**: 启动全新 Agent,加载保存状态
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4. **Orient**: 新 Agent 读取状态、定位自身、继续工作
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## Why Not In-Place Summarization?
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原地摘要(summarize → keep in same context)仍让模型在嘈杂、退化的上下文中操作。Context Reset 提供完全干净的上下文窗口——代价更高,但可靠性显著提升,适用于超长周期任务。
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## Trade-off
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- **In-place summarization**: 便宜,但 context 仍嘈杂
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- **Context Reset**: 昂贵(需重新加载状态),但可靠性高
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## Source
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- [[Your-AI-Isn-t-Stupid---It-Just-Needs-a-Better-Harness--Lychee-Technology-Engineering-Blog]]
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## See Also
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- [[Context-Anxiety]] — 触发条件
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- [[State-Externalization]] — 持久化状态文件格式
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- [[7-Layer-Harness-Stack]] — 第 7 层 Constraints & Recovery 的核心机制
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