fix: 海马体合并在 LLM 返回 null tag 时静默失败 - #22
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deduplicate_and_store() unions LLM-extracted tags into the matched memory
before calling update_memory(). When the extraction LLM returns a JSON array
containing null, that None lands in Memory.tags and takes down both writers:
* _sync_write_toml() called tomli_w.dumps() without _clean_for_toml(),
unlike its sibling _sync_write_toml_to_path() -> 'Object of type
NoneType is not TOML serializable'
* MemoryIndex.upsert() did ' '.join(tags) -> 'sequence item 0: expected
str instance, NoneType found'
Either way update_memory() caught the exception and returned False, so the
extractor logged 'Failed to merge memory <id>' and the merged text was
dropped -- the new information never reached disk. Intermittent by nature:
only fires on the turns where the LLM happens to emit a null.
Not a timeout: the merge_facts() timeout path has a semicolon-join fallback
and never reaches the writer with a broken value.
Fixes:
* _sync_write_toml() now runs _clean_for_toml() like its sibling
* MemoryIndex.upsert() and rebuild filter tags to non-empty strings
* deduplicate_and_store() drops non-string tags at the source
Adds a regression test that fails with either writer fix reverted.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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📝 WalkthroughWalkthrough本次变更统一清理记忆标签，并在 TOML 序列化前移除 Changes记忆标签规整
Estimated code review effort: 2 (Simple) | ~10 minutes Merge Risk: 🟡 Moderate · up to The patch fixes LLM-generated null tags in the main write path, but malformed or non-list tags can still cause merges or index rebuilds to fail, losing updates, while TOML and SQLite may retain different tag sets; the normalization gaps should be addressed before merging. Poem
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| Filename | Overview |
|---|---|
| memory/memory_extractor.py | Normalizes both existing and extracted tags before merging, preventing malformed values from aborting the batch. |
| memory/memory_index.py | Centralizes list-tag validation and applies it consistently during upsert and filesystem rebuild. |
| memory/toml_tree_store.py | Normalizes tags and recursively removes TOML-incompatible values before atomic serialization. |
| tests/test_storage_layer.py | Adds regression tests covering null and invalid tags and agreement between TOML and SQLite representations. |
Reviews (2): Last reviewed commit: "fix: tag 规整收敛为单一规则，修复合并批次被整批丢弃" | Re-trigger Greptile
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Inline comments:
In `@memory/memory_extractor.py`:
- Around line 536-537: 在合并标签的流程中，先将 matched.tags 和 fact["tags"] 规整为仅包含字符串的
list[str]，并将 None 视为空列表，再执行 set(matched.tags) 与 existing_tags.update(tags)
的集合合并；保留现有合并及持久化行为，并定位修改现有标签合并逻辑。
In `@memory/memory_index.py`:
- Line 332: Validate that tags is a list before filtering its elements,
replacing non-list values with an empty list to avoid iterating strings or
dictionary keys. Apply this change at memory/memory_index.py lines 332 and 931,
in the corresponding bulk_upsert and rebuild_from_filesystem paths, while
preserving the existing string-and-nonempty-item filtering.
In `@memory/toml_tree_store.py`:
- Line 997: Update the TOML write path around _clean_for_toml() to apply the
same non-empty-string tag normalization used by MemoryIndex.upsert(), removing
empty and whitespace-only labels before serialization. Reuse the existing
normalization logic rather than introducing divergent rules, and add or update
the regression assertion to verify empty-string tags are absent from the TOML
output.
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memory/memory_extractor.pymemory/memory_index.pymemory/toml_tree_store.pytests/test_storage_layer.py
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CodeRabbit review 的三条意见： 1. extractor 合并处过滤顺序错误。`set(matched.tags)` 先于过滤执行， TOML 里手工写进去的 dict/list 会在集合运算那一步抛 unhashable TypeError。fact 循环外面只有 hippocampus_process 一个大 try， 所以异常不是丢一个 tag，而是本批剩余 facts 连同升维反思、画像 更新一起被吞掉。 2. TOML 与 SQLite 存出不同的 tag 集合。`_clean_for_toml` 只剥 None， 索引侧 upsert 还过滤非字符串和空白项，同一次 update_memory 两边 落不同数据，重建索引后集合再漂一次。 3. 规则散落在四处。收敛为 memory_index.normalize_tags()，放在三者 最深的公共依赖上，零新文件、零循环导入。upsert、 rebuild_from_filesystem、_sync_write_toml、extractor merge 全部 改为调用它。非 list 容器整体视为空，避免字符串被逐字符拆成垃圾 tag。 _clean_for_toml 保留，它还负责 source 等其它字段里的 None。 测试：补上原先缺失的空字符串断言，并新增 TOML/索引一致性回归。 两条测试在源码改动单独 stash 后均失败，修复后通过。73 passed。 Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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1 participant
问题
海马体合并记忆时静默失败，日志报
Failed to merge memory <id>，新信息丢失。跟 LLM 速度无关 ——
merge_facts()的超时路径有分号拼接兜底，不会走到写入层。真正原因是提取 LLM 在 JSON 的tags数组里吐出null。根因
deduplicate_and_store()在合并时把 LLM 提取的 tags union 进旧记忆：这个
None会同时打掉两条写入路径：TOML 侧 ——
_sync_write_toml()直接调tomli_w.dumps()，没走_clean_for_toml()（旁边的_sync_write_toml_to_path()走了，注释还写着「TOML 不支持 None」）：索引侧 ——
MemoryIndex.upsert()的" ".join(tags or [])：两种情况下
update_memory()都会 catch 住异常返回False，于是 extractor 打出Failed to merge memory <id>并丢弃合并结果 —— 用户感知为「相近的信息没有被合并进已有记忆」。间歇性发作：只在 LLM 恰好吐
null的那几轮触发，所以看起来像是随机/性能问题。修复
_sync_write_toml()补上_clean_for_toml()，和它的姊妹函数对齐MemoryIndex.upsert()和 rebuild 路径把 tags 过滤为非空字符串deduplicate_and_store()在源头就丢掉非字符串 tag，避免脏标签进入记忆三处都改是因为它们是独立的失败点：源头过滤挡住新数据，两个写入层的防御则保护已经落盘的历史脏数据（rebuild 路径会重新读到）。
验证
新增回归测试
test_update_memory_survives_null_tags_from_llm。这个测试是有效闸门 —— 把任一 writer 的修复回退掉它就会失败，并复现出报告里那条一模一样的日志：全量测试 72/72 通过（新增 1 个）。整个复现和验证过程不需要真实 LLM / API key。
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Summary by CodeRabbit
Bug 修复
测试