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ReMe/reme2/config/reme_todo.md
huangsen 8465f6d06e ``` 
docs(protocol): add typed edge link protocol documentation

Add comprehensive documentation for the link protocol supporting
typed edges in body text. This includes specification for three
legal inline forms (bare wikilink, line-level Dataview,
inline-bracketed Dataview), predicate syntax rules, and the
machine-managed Relations section convention for organizing
discovered edges.

fix(memory): update path reference from vault_root to working_dir

Change the memory_create operation's path anchoring from
vault_root to working_dir to maintain consistency with the
current working directory configuration.

refactor(components): remove edge_extractor module and simplify parsing

Remove the edge_extractor component module entirely and
inline edge extraction logic directly into LinkedFileParser
using parse_wikilinks utility. This simplifies the architecture
by eliminating the separate edge extraction component and
delegating edge discovery to the maintainer's enrichment operations.

feat(parser): update parse method signature and simplify edge extraction

Modify LinkedFileParser to return (FileNode, list[FileChunk])
tuple instead of ParsedFile, remove dependency on BaseEdgeExtractor,
and implement direct wikilink parsing from body text only.
```
2026-05-11 19:45:53 +08:00

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ReMe重构

  1. 根目录 a. ✅ vault_root → working_dir @sen
  2. file_parser a. 抽象基类 parse: @jinli ⅰ. 输入是path：相对路径 ⅱ. 输出是FileMetadata & list[FileChunks] & list[FileEdge] b. default parser 兼容老方案 @jinli ⅰ. 带overlap的chunking策略 ，不输出FileEdge c. markdown parser @sen ⅰ. 根据markdown ast做chunk，不需要overlap ⅱ. 增加一个索引的chunk chunk_type @锦鲤 file_chunk_type content/index ⅲ. 增加link的正则解析：predicate:: path#anchor
  3. file_store @sen a. 抽象存储： ⅰ. filenode = file + path + st_mtime + metadata + list[FileEdge] ⅱ. graph=dict[str, filenode] 内存+json ⅲ. list[FileChunk] 存db b. 抽象基类 ⅰ. graph：fellow dict的操作 update/get/set ⅱ. chunks dict[str, list[chunk]]
    1. delete_chunks_by_path
    2. update_chunks_by_path
    3. list_chunks_by_path
    4. vector_search/keyword_search ⅲ. 手写一个bm25检索 ⅳ. 【核心】检索机制 vector bm25 graph 如何进行融合
  4. file_watcher @jinli a. 抽象基类 ⅰ. on_start:
    1. file_store 的start 在前，加载graph，file_watcher在后，递归扫描目录 a. 通过ms_time对比graph，on_change 进行改动 ⅱ. on_change:
    2. 更新/增加: a. delete_chunks_by_path 更新数据库 b. upate_chunks_by_path 更新数据库 c. 更新graph
    3. 删除 a. delete_chunks_by_path 更新数据库

MemorySchema

  1. markdown文件结构 @sen a. formatter： ⅰ. title ⅱ. desc ⅲ. tags ⅳ.
  2. memory文件结构目录 a. MEMORY.md b. msg/files -> daily/YYYYMMDD/YYYYMMDD.md + xxxx.md ⅰ. YYYYMMDD.md
    1. xxx -> xxxx.md
    2. xxx -> xxxd.md ⅱ. c. daily -> topic/topic_l1/topic_l1.md + xxx.md + topic_l2 d. proactive

steps:

  1. 治理（算法+LLM）： a. 节点关联P0：现有的链接做补充，挖掘新的LLM的link ⅰ. /Users/yuli/workspace/ReMe/reme2/component/edge_extractor/llm_edge_extractor.py ⅱ. 移动到steps b. 节点整合/节点拆分/节点归档 c. 健康度检查
  2. retrieve 调用store的检索
  3. 原子steps：reme edit
  4. 组合steps：总结： a. - freq (every_n_turn、compact) -> daily_summarizer b. topic (/dream ) -> topic_summarizer(daily_xx -> topic_xx) c. proactive -> proactive_summarizer(personal_xxx -> proactive_query - pre_query

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