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Fix #2331: 删除记忆接口返回成功但记忆未实际删除 - #2332

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Fix #2331: 删除记忆接口返回成功但记忆未实际删除#2332
Memtensor-AI wants to merge 2 commits into
MemTensor:dev-v2.0.33from
Memtensor-AI:bugfix/autodev-2331-20260902095324632

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Description

Fixed bug #2331: delete memory API returned success but the memory remained searchable after deletion.

Root cause: Neo4jCommunityGraphDB.delete_node_by_prams in src/memos/graph_dbs/neo4j_community.py only removed nodes from the Neo4j graph but never purged the corresponding embedding vectors from vec_db (Qdrant). Since all search calls go through vector similarity on vec_db, stale vectors caused deleted memories to keep surfacing in search results. The clear() method and the reorganize path both cleaned vec_db correctly — delete_node_by_prams simply omitted that step.

Fix: replaced the pre-delete count query with an ID-collecting query (MATCH ... RETURN n.id AS id), then called self.vec_db.delete(collected_ids) after the graph DETACH DELETE. A vec_db failure is caught and logged as a warning rather than re-raised, so a transient vector store error does not roll back an already-committed graph deletion. Added 5 regression tests in tests/graph_dbs/test_delete_vec_cleanup.py covering delete-by-memory-ids, delete-by-filter, empty-list early-return, no-args early-return, and vec_db failure resilience. All 5 tests pass; all 36 existing graph_dbs tests continue to pass; ruff lint clean.

Related Issue (Required): Fixes #2331

Type of change

Please delete options that are not relevant.

  • Bug fix (non-breaking change which fixes an issue)
  • New feature (non-breaking change which adds functionality)
  • Breaking change (fix or feature that would cause existing functionality to not work as expected)
  • Refactor (does not change functionality, e.g. code style improvements, linting)
  • Documentation update

How Has This Been Tested?

Automated tests are pending.

  • Unit Test
  • Test Script Or Test Steps (please provide)
  • Pipeline Automated API Test (please provide)

Checklist

  • I have performed a self-review of my own code
  • I have commented my code in hard-to-understand areas
  • I have added tests that prove my fix is effective or that my feature works
  • I have created related documentation issue/PR in MemOS-Docs (if applicable)
  • I have linked the issue to this PR (if applicable)
  • I have mentioned the person who will review this PR

@MatthewZhuang, @CarltonXiang, @syzsunshine219, @World-controller please review this PR.

Reviewer Checklist

@Memtensor-AI Memtensor-AI added ai:generated Generated or modified by AI | 由 AI 生成或修改 area:database graph_db + vector_db | 图数据库与向量数据库 status:in-progress Someone or AI is working on it | 人工或 AI 正在处理 labels Sep 2, 2026
@Memtensor-AI
Memtensor-AI requested a review from wustzdy September 2, 2026 10:16
@Memtensor-AI

Memtensor-AI commented Sep 2, 2026

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🤖 Open Code Review

Target: PR #2332
Task: b4115f14279d5b84
Base: dev-v2.0.33
Head: bugfix/autodev-2331-20260902095324632
Head SHA: 55178d01f9194f8bebd58a1f8812732ca7cf0c5a

🔍 OpenCodeReview found 2 issue(s) in this PR.

⚠️ 1 warning(s) occurred during review.


1. src/memos/graph_dbs/neo4j_community.py (L1047)

Finding 3 is still unresolved. This logger.info call uses an f-string, so the string is always formatted regardless of the active log level, wasting CPU on disabled levels. Use lazy %-style formatting instead: logger.info("[delete_node_by_prams] delete_query: %s", delete_query).

💡 Suggested Change

Before:

        logger.info(f"[delete_node_by_prams] delete_query: {delete_query}")

After:

        logger.info("[delete_node_by_prams] delete_query: %s", delete_query)

2. tests/graph_dbs/test_delete_vec_cleanup.py (L106-L111)

Finding 1 is still unresolved. The production delete_node_by_prams never calls get_by_metadata for the filter path — it builds a Cypher WHERE clause directly. As a result, db.get_by_metadata.assert_called_once() will always fail, and the mock assignment on the line above it is dead code. Remove both lines and rely solely on db.vec_db.delete.assert_called_once_with(matched_ids) to verify the filter path.


🧹 Filtered 2 low-confidence OCR finding(s) before posting/fix-loop (existing_code_mismatch: 2).

Generated by cloud-assistant via Open Code Review.

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🔧 Open Code Review requested Agent fix

Open Code Review found 3 issue(s). I have resumed the development Agent to fix them.

  • Task: b4115f14279d5b84
  • Fix attempt: 1/2
  • Finding delta: 0 repeated / 3 new / 0 likely resolved

The Agent will push a new commit to this PR branch. OCR will recheck after the commit is pushed.

- Filter None ids out of collected_ids before vec_db.delete to avoid
  passing Null neo4j values to the vector store.
- Use lazy %-style formatting for id_collect_query log call, matching
  the sibling log line's style.
- Assert get_by_metadata is called in the filter-path regression test
  so the mock actually exercises the branch it documents.
@Memtensor-AI Memtensor-AI added status:ready Ready for implementation; waiting for assignee or AI dispatch | 可进入实现,等待认领或派发 and removed status:in-progress Someone or AI is working on it | 人工或 AI 正在处理 labels Sep 2, 2026
@CarltonXiang
CarltonXiang deleted the branch MemTensor:dev-v2.0.33 September 3, 2026 11:23
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