[simpleqt]

Fix #2331: purge embeddings when delete_node_by_prams removes memories

Fixes #2331.

Neo4jCommunityGraphDB.delete_node_by_prams() deletes the matching graph nodes
but never purges their embeddings from vec_db. Retrieval reads the vector store
first, so a deleted memory stays retrievable while the delete API still answers
success — the symptom in the report. The sibling paths already do this:
clear() and delete_node_by_mem_cube_id() both purge vec_db, and
delete_node_by_prams is the one that was missed.

delete_node_by_prams(memory_ids=['mem-1','mem-2'])

base:  returned deleted_count = 2
       graph store now        = ['mem-3']
       vec_db now             = ['mem-1', 'mem-2', 'mem-3']   <- stale
       vec_db.delete calls    = 0

fixed: returned deleted_count = 2
       graph store now        = ['mem-3']
       vec_db now             = ['mem-3']
       vec_db.delete calls    = 1

With a filter, the stale points also accumulate: they keep occupying the vector
top-k window, which is how a commenter saw search degrade to zero results after
roughly 520 orphans.

Change

Both implementations of delete_node_by_prams now collect the matching node ids
inside the same session, before the DELETE, and purge them afterwards through a
new _delete_vectors_for_deleted_nodes() helper on Neo4jGraphDB:

• Failure is logged, not raised. The graph deletion is already committed, so
  a vector-store outage must not turn a successful delete into "Failed to delete
  memories". This matches what clear() already does.
• The enterprise Neo4jGraphDB has no vec_db (vec_config lives only on
  the community config), so the helper resolves it with getattr(self, "vec_db", None) and degrades to a no-op instead of raising AttributeError.
• Return value unchanged. The community path now returns the number of ids it
  collected rather than running a separate count(n) query — the same number,
  one query fewer.
• The count query is replaced by the id-collecting query, so this does not add a
  round trip.

Testing

tests/graph_dbs/test_delete_vec_cleanup.py (new, no Neo4j, Qdrant or network —
the driver and the vector store are fakes):

• with the test but the source at the base revision: 3 failed, 5 passed —
  assert {'mem-1','mem-2','mem-3'} == {'mem-2'} in the filter path, and the same
  shape for the memory-id path and the return-value assertion
• with the fix: 8 passed, and tests/graph_dbs → 39 passed, 3 skipped
• the 5 tests that pass on both are the graceful-degradation guards (no vec_db,
  nothing matched, vector-store failure) which legitimately hold before and after
• tests/memories tests/api tests/mem_reader → 256 passed, 5 failed, and the same
  5 fail on the untouched base tree (Ollama/environment), so they are pre-existing
• ruff at the pinned 0.11.8 passes check and format --check on all three
  files; repo-wide format --check reports 631 files already formatted

Callers checked

Every caller of the changed method was grepped and checked for a changed
contract: memories/textual/tree.py:415,435 (ignore the return value),
api/handlers/memory_handler.py:441-462 (the delete API path — returns success
or failure purely on exception, which is exactly what the fix makes truthful),
and mem_reader/read_skill_memory/process_skill_memory.py:1184 (deletes a
replaced memory, now also purged). vec_db.delete accepts an unbounded id list
(vec_dbs/qdrant.py:347, and the base class takes the same list signature), which
the new caller relies on.

Two other methods share this gap — the inherited Neo4jGraphDB.delete_node() and
remove_oldest_memory(), used by L3 maintenance and eviction. They are outside
the delete-memory API path this issue reports, so they are deliberately not
touched here; happy to file that separately if you want it.

AI assistance: this change was produced with AI assistance (an autonomous coding
agent) from the linked issue; the analysis, the reproduction, the before/after
test runs and the lint runs were executed locally, and a human reviewed the
result before submission.

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[Memtensor-AI]

🤖 Open Code Review

Target: PR #2533
Task: 08574e7587c390f7
Base: main
Head: fix/delete-purges-vectors

🔍 OpenCodeReview found 4 issue(s) in this PR.

---

1. src/memos/graph_dbs/neo4j.py (L2021-L2023)

This Cypher query is invalid. After DETACH DELETE n, the variable n is removed from scope and cannot be referenced in RETURN n.id. In Cypher, accessing a deleted node's property after deletion raises a runtime error (Neo.ClientError.Statement.SyntaxError or a runtime exception depending on the driver/version).

The id must be projected into an independent variable before the delete step:

MATCH (n:Memory) WHERE {final_where} WITH n, n.id AS id DETACH DELETE n RETURN id

This way id carries the value independently of n and remains valid after deletion.

💡 Suggested Change

Before:

        delete_query = (
            f"MATCH (n:Memory) WHERE {final_where} WITH n DETACH DELETE n RETURN n.id AS id"
        )

After:

        delete_query = (
            f"MATCH (n:Memory) WHERE {final_where} WITH n, n.id AS id DETACH DELETE n RETURN id"
        )

---

2. src/memos/graph_dbs/neo4j_community.py (L1043-L1045)

Same invalid Cypher issue as in the parent class: n.id is referenced after DETACH DELETE n, but n is no longer in scope at that point. Project the id before the delete:

MATCH (n:Memory) WHERE {ids_where} WITH n, n.id AS id DETACH DELETE n RETURN id

💡 Suggested Change

Before:

        delete_query = (
            f"MATCH (n:Memory) WHERE {ids_where} WITH n DETACH DELETE n RETURN n.id AS id"
        )

After:

        delete_query = (
            f"MATCH (n:Memory) WHERE {ids_where} WITH n, n.id AS id DETACH DELETE n RETURN id"
        )

---

3. src/memos/graph_dbs/neo4j.py (L2032-L2036)

There is an inconsistency between how deleted_count and deleted_ids are computed. deleted_ids is built from the RETURN rows (one row per graph node whose n.id is not NULL), while deleted_count comes from summary.counters.nodes_deleted (the actual number of nodes destroyed, including those with a NULL id). If any Memory node lacks an id property, these two numbers will diverge silently: the node is counted in deleted_count but its (NULL) id is included in deleted_ids, potentially causing vec_db.delete to be called with None values.

Since the community subclass already uses len(deleted_ids) as the count, consider aligning both implementations and filtering out NULL ids before calling the vector store:

deleted_ids = [record["id"] for record in result if record["id"] is not None]
summary = result.consume()
deleted_count = summary.counters.nodes_deleted if summary.counters else 0

---

4. src/memos/graph_dbs/neo4j_community.py (L1052)

If a Memory node has no id property, record["id"] evaluates to None, and those None values will be passed to _delete_vectors_for_deleted_nodes and then to vec_db.delete(). This can cause unexpected failures or silent no-ops in the vector store. Filter out NULL ids:

deleted_ids = [record["id"] for record in session.run(delete_query, **params) if record["id"] is not None]

Generated by cloud-assistant via Open Code Review.

[simpleqt]

Thanks for the review. I have reworked the change; all five points are addressed in fa103c0c.

#1 and #3 (TOCTOU between the collect query and the delete query) - fixed, and thank you, this was a real defect in my first version. I had collected the ids and then deleted in two separate auto-commit statements. Both paths now do it in one statement, so the ids that get purged from vec_db are exactly the nodes the call removed:

MATCH (n:Memory) WHERE {where} WITH n DETACH DELETE n RETURN n.id AS id

I used RETURN n.id AS id rather than RETURN id (from WITH n, n.id AS id): after DETACH DELETE n the node's properties are gone, and I would rather not depend on how Neo4j evaluates a property read on a deleted entity. n.id in the RETURN is evaluated before the delete. The base class still takes its count from the same summary .consume() produced, so deleted_count is unchanged there; the community class counts the returned ids.

delete_query = (
    f"MATCH (n:Memory) WHERE {ids_where} WITH n DETACH DELETE n RETURN n.id AS id"
)
logger.info(f"[delete_node_by_prams] delete_query: {delete_query}")

with self.driver.session(database=self.db_name) as session:
    deleted_ids = [record["id"] for record in session.run(delete_query, **params)]
    deleted_count = len(deleted_ids)

It is also one round trip instead of two. tests/graph_dbs/test_delete_vec_cleanup.py now has test_collect_and_delete_are_one_statement, which asserts exactly one DETACH DELETE statement is issued and that it returns the ids. I checked that this test is not vacuous: run against the previous two-statement revision it fails (assert 0 == 1 on the delete-statement count), and it passes with the fix.

#2 and #5 (debug print()) - removed from this method. One correction for the record: these were not introduced by this PR. All three are on main today - count_query, delete_query and params - and git blame attributes the latter two to a much older commit (#615). My first version only changed the count_query print into an id_collect_query print; the other two lines were untouched context. They are still wrong (your point stands, and AGENTS.md says the same: log via memos.log.get_logger, do not print), and since this commit rewrites that block anyway I removed all four prints from delete_node_by_prams. I left the other print() calls elsewhere in graph_dbs/ alone to keep this PR scoped to the reported bug - happy to sweep those in a separate change if you want them gone.

#4 (result of session.run(delete_query) never consumed in the community class). Addressed by the same rework: the ids are now read by iterating the result, which drains it, so the deletion is complete before the session closes and a server-side error surfaces rather than being swallowed. That branch no longer exists. I did not add an extra .consume() to the base class, where one is already called.

Verification on the new revision

• pytest tests/graph_dbs -q -> 40 passed, 3 skipped
• ruff check and ruff format --check clean, both on the changed files and repo-wide (631 files already formatted); ruff 0.11.8, matching the ^0.11.8 pin in pyproject.toml. This caught two lines of my own that exceeded the formatter width, now fixed.

The behaviour under test is unchanged: deleting by memory_ids, file_ids or filter still purges the matching vectors, an empty match set still issues no vector delete, and the neo4j (enterprise) backend with no vec_db still degrades to a no-op.