scriptoriumadmin/ReMe
1
0
Fork 0
mirror of https://github.com/agentscope-ai/ReMe.git synced 2026-08-28 05:25:04 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 11

update readme (#149)

Browse source
This commit is contained in:
jinliyl 2026-03-09 21:05:30 +08:00 • committed by GitHub
parent 8b45493634
commit 083ed6a137
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
2 changed files with 22 additions and 22 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

22
README.md
View file

@ -83,17 +83,17 @@ working_dir/
[ReMeLight](reme/reme_light.py) is the core class of the file-based memory system. It provides full memory management
capabilities for AI agents:
| Method | Function | Key components |
|-----------------------|--------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `check_context` | 📊 Check context size | [ContextChecker](reme/memory/file_based/components/context_checker.py) — checks whether context exceeds thresholds and splits messages |
| `compact_memory` | 📦 Compact history into summary | [Compactor](reme/memory/file_based/components/compactor.py) — ReActAgent that generates structured context summaries |
| `summary_memory` | 📝 Persist important memory to files | [Summarizer](reme/memory/file_based/components/summarizer.py) — ReActAgent + file tools (`read` / `write` / `edit`) |
| `compact_tool_result` | ✂️ Compact long tool outputs | [ToolResultCompactor](reme/memory/file_based/components/tool_result_compactor.py) — truncates long tool outputs and stores them in `tool_result/` while keeping file references in messages |
| `memory_search` | 🔍 Semantic memory search | [MemorySearch](reme/memory/file_based/tools/memory_search.py) — hybrid retrieval with vectors + BM25 |
| `ReMeInMemoryMemory` | 🗂️ In-session memory class | [ReMeInMemoryMemory](reme/memory/file_based/reme_in_memory_memory.py) — token-aware memory management with summary compression and state serialization |
| `pre_reasoning_hook` | 🔄 Pre-reasoning hook | `compact_tool_result` + `check_context` + `compact_memory` + `summary_memory` (async) |
| `start` | 🚀 Start memory system | Initialize file storage, file watcher, and embedding cache; clean up expired tool result files |
| `close` | 📕 Shutdown and cleanup | Clean up tool result files, stop file watcher, and persist embedding cache |
<table>
<tr><th>Category</th><th>Method</th><th>Function</th><th>Key components</th></tr>
<tr><td rowspan="4">Context Management</td><td><code>check_context</code></td><td>📊 Check context size</td><td><a href="reme/memory/file_based/components/context_checker.py">ContextChecker</a> — checks whether context exceeds thresholds and splits messages</td></tr>
<tr><td><code>compact_memory</code></td><td>📦 Compact history into summary</td><td><a href="reme/memory/file_based/components/compactor.py">Compactor</a> — ReActAgent that generates structured context summaries</td></tr>
<tr><td><code>compact_tool_result</code></td><td>✂️ Compact long tool outputs</td><td><a href="reme/memory/file_based/components/tool_result_compactor.py">ToolResultCompactor</a> — truncates long tool outputs and stores them in <code>tool_result/</code> while keeping file references in messages</td></tr>
<tr><td><code>pre_reasoning_hook</code></td><td>🔄 Pre-reasoning hook</td><td><code>compact_tool_result</code> + <code>check_context</code> + <code>compact_memory</code> + <code>summary_memory</code> (async)</td></tr>
<tr><td rowspan="2">Long-term Memory</td><td><code>summary_memory</code></td><td>📝 Persist important memory to files</td><td><a href="reme/memory/file_based/components/summarizer.py">Summarizer</a> — ReActAgent + file tools (<code>read</code> / <code>write</code> / <code>edit</code>)</td></tr>
<tr><td><code>memory_search</code></td><td>🔍 Semantic memory search</td><td><a href="reme/memory/file_based/tools/memory_search.py">MemorySearch</a> — hybrid retrieval with vectors + BM25</td></tr>
<tr><td>-</td><td><code>start</code></td><td>🚀 Start memory system</td><td>Initialize file storage, file watcher, and embedding cache; clean up expired tool result files</td></tr>
<tr><td>-</td><td><code>close</code></td><td>📕 Shutdown and cleanup</td><td>Clean up tool result files, stop file watcher, and persist embedding cache</td></tr>
</table>
---

22
README_ZH.md
View file

@ -74,17 +74,17 @@ working_dir/
[ReMeLight](reme/reme_light.py) 是该记忆系统的核心类，为 AI Agent 提供完整的记忆管理能力：
| 方法 | 功能 | 关键组件 |
|-----------------------|--------------|------------------------------------------------------------------------------------------------------------------------------|
| `check_context` | 📊 检查上下文大小 | [ContextChecker](reme/memory/file_based/components/context_checker.py) — 检查上下文是否超出阈值并拆分Message |
| `compact_memory` | 📦 压缩历史对话为摘要 | [Compactor](reme/memory/file_based/components/compactor.py) — ReActAgent 生成结构化上下文摘要 |
| `summary_memory` | 📝 将重要记忆写入文件 | [Summarizer](reme/memory/file_based/components/summarizer.py) — ReActAgent + 文件工具（read / write / edit） |
| `compact_tool_result` | ✂️ 压缩超长工具输出 | [ToolResultCompactor](reme/memory/file_based/components/tool_result_compactor.py) — 截断超长的工具调用结果并转存到 `tool_result/`，消息中保留文件引用 |
| `memory_search` | 🔍 语义搜索记忆 | [MemorySearch](reme/memory/file_based/tools/memory_search.py) — 向量 + BM25 混合检索 |
| `ReMeInMemoryMemory` | 🗂️ 会话内存类 | [ReMeInMemoryMemory](reme/memory/file_based/reme_in_memory_memory.py) — Token 感知的内存管理，支持压缩摘要和状态序列化 |
| `pre_reasoning_hook` | 🔄 推理前预处理钩子 | compact_tool_result + check_context + compact_memory + summary_memory(async) |
| `start` | 🚀 启动记忆系统 | 初始化文件存储、文件监控、Embedding 缓存；清理过期工具结果文件 |
| `close` | 📕 关闭并清理 | 清理工具结果文件、停止文件监控、保存 Embedding 缓存 |·
<table>
<tr><th>类别</th><th>方法</th><th>功能</th><th>关键组件</th></tr>
<tr><td rowspan="4">上下文管理</td><td><code>check_context</code></td><td>📊 检查上下文大小</td><td><a href="reme/memory/file_based/components/context_checker.py">ContextChecker</a> — 检查上下文是否超出阈值并拆分 Message</td></tr>
<tr><td><code>compact_memory</code></td><td>📦 压缩历史对话为摘要</td><td><a href="reme/memory/file_based/components/compactor.py">Compactor</a> — ReActAgent 生成结构化上下文摘要</td></tr>
<tr><td><code>compact_tool_result</code></td><td>✂️ 压缩超长工具输出</td><td><a href="reme/memory/file_based/components/tool_result_compactor.py">ToolResultCompactor</a> — 截断超长的工具调用结果并转存到 <code>tool_result/</code>，消息中保留文件引用</td></tr>
<tr><td><code>pre_reasoning_hook</code></td><td>🔄 推理前预处理钩子</td><td>compact_tool_result + check_context + compact_memory + summary_memory(async)</td></tr>
<tr><td rowspan="2">长期记忆</td><td><code>summary_memory</code></td><td>📝 将重要记忆写入文件</td><td><a href="reme/memory/file_based/components/summarizer.py">Summarizer</a> — ReActAgent + 文件工具（read / write / edit）</td></tr>
<tr><td><code>memory_search</code></td><td>🔍 语义搜索记忆</td><td><a href="reme/memory/file_based/tools/memory_search.py">MemorySearch</a> — 向量 + BM25 混合检索</td></tr>
<tr><td>-</td><td><code>start</code></td><td>🚀 启动记忆系统</td><td>初始化文件存储、文件监控、Embedding 缓存；清理过期工具结果文件</td></tr>
<tr><td>-</td><td><code>close</code></td><td>📕 关闭并清理</td><td>清理工具结果文件、停止文件监控、保存 Embedding 缓存</td></tr>
</table>
---