[vector store scale-out 4/5] Keep user properties out of the vector store by edwinyyyu · Pull Request #1702 · MemMachine/MemMachine

edwinyyyu · 2026-09-21T18:22:34Z

Purpose of the change

The event backend wrote every property of an event into its vector record and mapped the caller's whole filter onto the vector store, so a user key a deployment never declared was both stored and filtered there: on Qdrant and Milvus as unindexed payload a filtered query scans for. With #1670 a tenant can no longer declare indexes; this closes the other half, so a tenant's properties cannot shape what the vector store stores or scans either. The segment store already holds every property and already receives the whole filter for the context windows, so the vector side only duplicated work the segment store does anyway.

The vector record now carries the keys the collection declares: EventMemory's reserved segment uuid and timestamp, and the _-prefixed system properties an adapter stamps on the event, which after #1670 are exactly the collection's schema (collection.config.indexed_properties_schema). The vector store is queried with the conjuncts of the filter that name only such fields; a conjunct is dropped whole when any field under it is a user property, so dropping only ever widens the vector search, and the segment store narrows it back on the windows. User keys never reach the vector store.

filter_fields joins the filter parser: every field name a tree addresses. Tests: a user property stays on the segment and off the record; a user-property conjunct reaches only the segment store; a user property under an OR leaves the vector search unfiltered; filter_fields names every field under every node.

This is the routing half of what was #1628 on speedkick (its store-side half, the stores rejecting undeclared keys, is deferred to after #1627); it is re-derived onto main's collection shape from the same commit.

Stack

23 PRs on main: 5 independent ones, and three consecutive stages numbered on their own: the vector store scale-out, the SQLite store fixes and the vector store contract changes. A stacked PR's diff on GitHub is cumulative until the PRs under it merge.

Independent PRs, each directly on main; review and merge in any order:

#	PR	change
—	#1541	fix(event-backend): make expand_context return timeline-neighbor episodes
—	#1661	Overhaul segment store: shared tables with incarnation-scoped tenant keys (port of #1548)
—	#1630	Bound every request to a remote vector store by a configured timeout
—	#1682	Hand the Qdrant vector store a metrics factory, so its tracker emits (port of #1532)
—	#1624	Make no memory request create a project

The vector store stages, consecutive: each stacked on the one below. [vector store scale-out 1/5] is directly on main and 2/5 on it alone; they do not depend on the independent PRs. From 3/5 up, the chain's history also carries the independent PRs' commits beneath it, since the later stages were written on top of them ([vector store contract 2/6] on #1624's session policy, for one); so a merge of an independent PR rebases the chain without conflict, and until they merge those PRs' changes show in a stacked PR's diff.

#	PR	change
		Stage 1, the vector store scale-out: what horizontal scalability without sharding requires.
[vector store scale-out 1/5]	#1671	Remove custom sharding from the Qdrant store (port of #1654)
[vector store scale-out 2/5]	#1631	Mint an incarnation per collection life in a SQL-arbitrated registry, so any process may serve any Qdrant or Milvus collection
[vector store scale-out 3/5]	#1670	Remove per-project filterable properties (port of #1606)
[vector store scale-out 4/5]	#1702 (this PR)	Keep user properties out of the vector store
[vector store scale-out 5/5]	#1627	Make a vector store one collection, with string-keyed partitions
		Stage 2, the SQLite store fixes, on [vector store scale-out 5/5]: re-derived on the one-collection store.
[sqlite store fixes 1/7]	#1460	Publish vector index files atomically (but not durably) (as merged into `speedkick`, #1588)
[sqlite store fixes 2/7]	#1469	Never reuse a row id in SQLiteVectorStore (as merged into `speedkick`, #1589)
[sqlite store fixes 3/7]	#1672	Own the search engine's concurrency in the store, not in each engine (port of #1612)
[sqlite store fixes 4/7]	#1673	Serialize a partition's writes so the engine sees them in order (port of #1607)
[sqlite store fixes 5/7]	#1674	Refuse a pending row replay cannot honor, instead of dropping it (port of #1608)
[sqlite store fixes 6/7]	#1675	Take SQLite's write lock at BEGIN, not at the first write (port of #1609)
[sqlite store fixes 7/7]	#1676	Give every write a fresh row id, so a key names one version (port of #1610)
		Stage 3, the vector store contract changes, on [sqlite store fixes 7/7].
[vector store contract 1/6]	#1663	Answer with cosine scores and uuids, not vectors and stale properties, and require a vector on the record (port of #1598 and #1603)
[vector store contract 2/6]	#1622	Create a session's storage with the session, never on a request
[vector store contract 3/6]	#1625	Remove open-or-create and close from both stores
[vector store contract 4/6]	#1618	Let a deployment tune a Qdrant collection's HNSW, optimizers and quantization
[vector store contract 5/6]	#1628	Make a vector store filter only on the properties it declares
[vector store contract 6/6]	#1616	Close the filter union, and make negation the complement on every backend

This PR's own change is its one commit, c164c56e2; the rest of its diff is the PRs under it. Stacked on #1670; #1627 is stacked on it.

Verification

This PR's commits are being re-verified as this is written: the re-order that moved #1460 into the SQLite stage changed the trees under it only by the absence of #1460's files, and before the re-order every commit had passed ruff check, ruff format --check, ty check clean as CI runs it (uv run --frozen --all-extras ty check --project packages/server) and the full server suite without integration tests passes (pytest packages/server/server_tests -m "not integration"). This paragraph is replaced with the result.

🤖 Generated with Claude Code

https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

…odes (speedkick) (MemMachine#1547) * fix(event-backend): make expand_context return timeline-neighbor episodes Fixes MemMachine#1540. On the event backend, expand_context was silently inert: EventMemory fetched and materialized the expanded segment windows, but LongTermMemory._search_scored_event read only the seed segment's _episode_uid and score from each window, and the response schema has no context field - so responses were byte-identical for expand_context 0 and 5 while every request paid the LATERAL fetch. The declarative backend, by contrast, folds neighbor episodes into the returned list (_unify_scored_anchored_episode_contexts). This brings the event backend to parity: - Each scored window now contributes the episodes its segments belong to (chronological within the window, the seed's episode as nucleus). - Windows are unified best-score-first with the same fill algorithm as the declarative backend: taken whole while they fit within num_episodes_limit, then filled by weighted index-proximity to the nucleus (forward recall preferred) until the limit is met; an episode keeps the score of the first window that contributed it. - The unified context is returned chronologically, matching the declarative backend's ordering contract for expanded results. - expand_context is clamped to num_episodes_limit - 1 (declarative parity). expand_context == 0 behavior is unchanged (score-ordered seeds, exactly as before). Reranked configurations gain the same folding on top of reranker-scored windows. Tests: end-to-end via the in-memory event-backend wiring (neighbors returned, chronological order, limit respected) and unit tests for the window-to-episode-uid extraction and the unification algorithm (whole-context fit, overflow proximity with forward preference, first-window score retention). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * style: ruff format Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(event-backend): clamp expand_context above zero, and make the expansion tests actually discriminate Self-review of the two commits above turned up one defect and one hole. Defect: the quota clamp `min(max(0, expand_context), num_episodes_limit - 1)` goes negative when `num_episodes_limit == 0` -- reachable, since `SearchMemoriesSpec.top_k` carries no lower bound. `EventMemory._query` then derives `max_backward_segments = -1 // 3 = -1` and hands the segment store a negative window, which the SegmentStorePartition contract does not define: the SQLAlchemy store happens to short-circuit on `<= 0`, the in-memory store computes an empty slice and drops the seed. Apply the floor last so the clamp can only ever produce a non-negative window. Hole: neither end-to-end test could tell the fix from its absence -- both pass unmodified against the pre-fix `long_term_memory.py`. `FakeEmbedder` maps text to `[len(text), -len(text)]`, so under cosine every document scores exactly 1.0 against every query; all seven timeline episodes become seeds of equal rank, ties keep insertion order (which is chronological), and `num_episodes_limit=7` returns all seven with or without expansion. The "expansion adds episodes" assertion compared a limit-2 search against a limit-7 one, so the limit alone explained the difference. Embed on a keyword instead: only `tl-3` matches the query, so `tl-4` and `tl-5` -- which score zero -- can reach the result only through the expansion. The tests now pin the exact window (`[tl-3, tl-4, tl-5]`, chronological, each keeping the window's score), the clamp against an oversized `expand_context`, and the non-negative window above. All three fail against the code they cover. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PVtg6Zea292Pb9L7GXnTJp * test(event-backend): assert the expansion contract, not a ranking The tests added in the previous commit discriminate, but they pin an outcome: an exact episode list (`[tl-3, tl-4, tl-5]`) and exact score values. Both are properties of the fixture's ranking and of the backward/forward split `expand_context // 3`, neither of which the fix claims -- change the split or the scoring and the tests fail while the behaviour under test is still correct. Restate them as the contract. Each episode now gets its own similarity from an explicit search rank, with the match's four timeline neighbours ranked last, so: - no correct top-k can return those neighbours, and any nonzero window around the match reaches at least one of them whatever the split. The assertion is "expansion returned a neighbour the search itself would not", plus chronological order and the episode limit. - the clamp is asserted on the call made to the segment store (0 <= backward + forward <= limit - 1, over several limit/expand_context pairs) rather than on which episodes come back. - `expand_context == 0` is asserted as "matches only, best score first", without naming them. Exact lists and score values stay in the unit tests, which own the fill algorithm and the score-retention rule and are meant to track them. All three expansion tests still fail against the code they cover. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PVtg6Zea292Pb9L7GXnTJp --------- Co-authored-by: Claude Fable 5 <noreply@anthropic.com>

…keys (fixes MemMachine#1544, MemMachine#1546, MemMachine#1549) (speedkick) (MemMachine#1548) * Fix: Detach segment store partitions before dropping them, and lock partition metadata on delete Deleting a partition on PostgreSQL dropped its child tables with CASCADE. The foreign key from segment_store_dv_ln to segment_store_sg is declared on the partitioned parents, so the CASCADE dropped the parent-level constraint rather than only the part belonging to the deleted partition. After the first partition deletion the store stopped enforcing the link for every remaining partition, and ON DELETE CASCADE stopped removing derivative links with it, so delete_segments left orphaned rows that get_derivative_uuids_by_segment_uuids still returned. Detaching each child before dropping it keeps the constraint and the cascade intact. delete_partition also took only a row lock on the partition row. ROW SHARE does not conflict with the SHARE ROW EXCLUSIVE table lock the create paths take, so a concurrent create and delete could reach segment_store_sg and segment_store_dv_ln in opposite order and deadlock; that reproduced in 4 of 7 sampled interleavings against PostgreSQL 16, and in 0 of 7 once delete takes the same table lock first. The row lock stays, because it is what makes delete wait for in-flight writers holding FOR SHARE on that row. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MpFwBnZ6SxdMe3pSuMTCHD * fix: address partition child tables directly for segment DML Fixes #1546. Parent-table queries carry the partition key as a bind parameter; once asyncpg's prepared statement flips to a cached generic plan (after five executions) PostgreSQL locks every child partition on every execution before runtime pruning. With hundreds of partitions and concurrent sessions this exhausts the lock table (searches fail 500 'out of shared memory') and saturates the database CPU with lock churn and generic-plan startup. The partition handle now maps the ORM entities onto its own child tables (orm.aliased with adapt_on_names) and targets them for insert/delete, so every plan references exactly one partition. SQLite keeps the parent tables (it has no children). Measured on a store with 316 partitions: max relation locks held by a backend during a read loop drops 1276 -> 4; the 239 HTTP 500s in a 4-worker load test disappear; throughput at 128 concurrent requests rises ~20-30% with PostgreSQL no longer pinned at its CPU cap. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Test: Pin the partition-delete lock ordering The foreign-key half of this branch has a regression test; the lock ordering did not. A deadlock test would be timing-dependent, so assert the invariant the deadlock analysis rests on instead: delete_partition issues LOCK TABLE segment_store_pt IN SHARE ROW EXCLUSIVE MODE, and issues it before any DETACH or DROP of a child table. Without the lock the test fails and reports the statement sequence it saw. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MpFwBnZ6SxdMe3pSuMTCHD * Style: Apply ruff format to the lock-ordering test Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MpFwBnZ6SxdMe3pSuMTCHD * test: segment DML must address only the partition's child tables Regression test for #1546. Captures the SQL the partition handle emits across add / seed read / windowed read / filtered read / uuid maps / delete and asserts no statement references the partitioned parents -- the deterministic observable of the generic-plan lock explosion (lock counts would need timing-dependent pg_locks sampling). Fails against the parent-table implementation, passes with per-partition DML. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * style: drop annotation-only AliasedClass and Table imports This SQLAlchemy version exports no public AliasedClass name (only the aliased() factory), so the attribute annotations forced an import from sqlalchemy.orm.util. The annotations were documentation only; the branch comment already records that the attributes hold either the ORM class or its child-table alias. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: derive partition table names from one helper and the models The parent names come from the models' __tablename__ and the child naming pattern lives in _pg_child_table_name, used by child-table creation, teardown, and the per-partition DML targets, so the three sites cannot drift apart. Physical names are unchanged; the regression tests keep literal names to pin the on-disk naming contract. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Fix: Drop detached children, and stop holding the store-wide lock while waiting for writers Three follow-ups from review of this branch. The child-table probe asked whether the table exists, but the statement it guards is DETACH PARTITION, which requires that the table be attached. A child left detached by manual maintenance or an interrupted DETACH PARTITION CONCURRENTLY (that form is not transactional) passed the probe and made DETACH raise "is not a partition of", rolling back the transaction, so the partition became neither deletable nor recreatable -- a state the CASCADE drop this branch replaced used to clean up. Probe pg_inherits for attachment instead, in one round trip for both children, and drop an unattached child directly. delete_partition took the partitions-table lock before the row lock that waits for in-flight writers, so a slow writer on one partition stalled open_or_create_partition for every partition, which runs on the request path. Take the row lock first; the table lock only has to be held across the child DDL for the deadlock argument to hold. Re-measured: 4/7 sampled interleavings deadlock with no table lock, 0/7 with either ordering. Tests: the foreign key is now asserted to be enforced after a partition delete, not only that the cascade fires -- the PR's measurements list those as separate things the CASCADE drop broke. A second test leaves a child detached and requires deletion to succeed and the key to be reusable. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MpFwBnZ6SxdMe3pSuMTCHD * fix: memoize partition entities per key; validate keys in the naming helper Review follow-ups on the child-table change: - The child Table objects and aliases are now built once per partition key (functools.cache) instead of per handle. SQLAlchemy's compiled- statement cache keys on the Table objects a statement references, so per-handle tables made every handle's statements recompile and polluted the cache for everything else (verified: cache keys differed across handles for the same partition; now identical). - The tables carry columns only. The to_metadata copies dragged along foreign keys with unresolvable targets and duplicate index names -- latent hazards for anything walking that MetaData. - _pg_child_table_name validates the partition key itself, so every SQL string built from a child table name (including the DDL literals) is safe by construction rather than by call-site convention; the store's validator moved to module level beside it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: make partition key validation part of the segment store contract Partition keys are embedded in native storage identifiers by any implementation, so the alphabet/length rule is interface-level, not a SQLAlchemy detail: validate_partition_key now lives in the package's data_types (exported from the package), the SegmentStore.create_partition docstring states the contract, and the SQLAlchemy store imports it. Deliberately NOT unified with the vector store's identical identifier rule: the repo-wide naming contract is not wired through yet, so the convergence is treated as incidental for now. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: move partition key validation to segment_store/utils.py Mirrors the vector store's layout (validate_identifier in vector_store/utils.py); the interface docstring states the key rule plainly instead of referencing a code path. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * style: state partition key naming constraints in the VectorStore format Same ABC-level 'Naming constraints:' block the vector store uses, no method-level restatement, and the length limit is enforced and documented in bytes, matching validate_identifier. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * style: state the key rule as the regex, not a prose fragment Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * style: restore the ABC's original naming-constraints docstring Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: make validate_partition_key boolean, call sites raise Mirrors the vector store's validate_identifier: the predicate returns bool so callers can compose it, and each entry point raises its own error in the vector store's message style. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * Revert "refactor: make validate_partition_key boolean, call sites raise" This reverts commit 88be86603c36e4b759da0f876968e6dd6db8d913. * fix: bound the partition-entity cache with lru_cache(4096) functools.cache grew ~29 KiB per distinct partition key (measured) for the life of the process, including deleted partitions. The LRU cap bounds it at ~115 MiB per worker; eviction is harmless since a rebuilt entry is identical and only costs recompiling that partition's statements once. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * style: drop point-in-time memory figures from the cache comment Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: address second review round - Type the partition entities: _pg_partition_entities returns a NamedTuple with real field types instead of a positional tuple of object, which was adding 55 ty diagnostics (the CI static check would have failed) and forcing blind unpacking; callers and the memoization test use named fields, and the private _generate_cache_key assertion (redundant given object identity) is dropped. - DROP TABLE gains IF EXISTS back, so an out-of-band drop landing between the state probe and the drop cannot leave a partition half-deleted. - open_or_create_partition opens existing partitions without the store-wide management lock (double-checked: unlocked read, then lock and re-check only when creating), so request-path opens no longer serialize behind a concurrent deletion's DDL window; pinned by test_open_existing_partition_takes_no_management_lock. - The engine's compiled-statement cache is raised from the default 500 (per-partition statements would thrash it once enough partitions are live concurrently). - Comments and the DML test docstring scope the lock claim honestly: PostgreSQL's FK integrity triggers still address the parents internally, costing a one-shot per-backend lock spike on writes/deletes when a trigger plan first goes generic (verified: ~10 locks steady, one spike at execution six, then back) -- tracked on #1546. - The detach test cleans up its detached child unconditionally so a failure cannot poison the session-scoped container for later tests; the statement recorder is a shared fixture instead of copy-paste; the byte-length check encodes once. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: drop the typing casts from the partition entities inspect(Model).columns yields real Column objects (the stubs type __table__ as FromClause, which forced the cast), and SQLAlchemy's typing convention represents an aliased entity as the mapped class type, so the NamedTuple fields are type[SegmentRow] / type[DerivativeLinkRow] and aliased() assigns without coercion. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * design: shared segment store tables with incarnation-scoped keys Design record for replacing the per-tenant partitioned layout with shared tables on every dialect: the tenant registry carries an incarnation, data rows are keyed by <logical_key>@<incarnation>, deletion is an O(1) registry write plus a purge queue, and fencing fails stale handles loudly. Records the measured comparison against PARTITION OF and standalone-table layouts and the scaling requirements (cheap tenant creation at 1e5-1e6 tenants, 1e4-1e7 rows per tenant) that decided it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor!: shared segment store tables, incarnation fencing, O(1) delete Implements design/segment_store_shared_tables.md. Fixes #1544, #1546, and #1549 by construction: - The ORM models are the physical schema on every dialect; PostgreSQL partitioning, per-tenant DDL, the detach machinery, the store-wide management lock, and the per-partition entity cache are all removed. No partitions means no generic-plan lock fan-out (client or RI-trigger) and no DDL for lifecycle deadlocks to live in -- the churn smoke that measured 41-83 deadlocks per 20s on every partitioned build measures zero, with 60x more write throughput. - segment_store_pt becomes the tenant registry: partition_key + incarnation. Data rows are keyed by <logical_key>@<incarnation>, so a deleted-and-recreated tenant never sees its predecessor's rows. - create_partition is a row insert (no DDL); delete_partition is O(1): FOR UPDATE on the registry row (drains writer pins), enqueue the physical key on segment_store_gc, delete the row. purge_deleted_partitions reclaims rows in chunked background batches. - Writes pin the registry row FOR SHARE with an incarnation predicate; reads check it too: a stale handle raises SegmentStorePartitionStaleError on every dialect, SQLite included. Measured cost: one extra registry round trip per read operation. - The segment table's FK to the registry is removed (registry and data rows are deliberately decoupled for O(1) deletion); the link-table FK and cascade remain. Same-moment ABAB vs the partitioned build: ingest and windowed reads at parity, lifecycle cycles 4-6x faster, tenant creation ~1000x cheaper (row insert vs DDL). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: identify tenant data rows by incarnation UUID alone Data rows drop the composite <logical_key>@<incarnation> string for a bare incarnation UUID column: a data query cannot be constructed without resolving the registry, so referencing the wrong tenant is structurally impossible; index entries narrow from a 41-byte varchar to a native 16-byte uuid; random UUIDs are globally unique across nodes without coordination, so tenant moves between databases carry rows verbatim; and collisions among incarnations with live traces are rejected by constraints (unique on the registry, primary key on the purge queue) instead of left to probability. The purge queue keeps the logical key for forensics. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: finish the physical-key -> incarnation wording in the design doc Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: fence by incarnation alone The incarnation is unique-constrained, so it resolves the registry row by itself; the logical-key predicate was a leftover from the composite string design and contradicted the rule that the incarnation is the handle's sole authority. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: rename the stale error to name the handle, not the partition The handle is what is stale -- the partition is deleted -- and SegmentStorePartitionHandleStaleError follows the existing noun+state convention (ConfigMismatch, AlreadyExists). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: inline uuid4 for incarnation generation new_incarnation() was a one-line wrapper adding indirection for no behavior; the multi-node rationale lives in the design doc. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: normalize segment timestamps to UTC before persisting Segment-store slice of #1462: SQLite's DateTime(timezone=True) discards tzinfo and stores wall-clock fields verbatim, so a non-UTC timezone-aware timestamp written without UTC normalization read back shifted by its offset (13:30:45-08:00 came back as 05:30:45-08:00). The read path already assumed UTC and reapplies the separately stored offset; only the write was missing the conversion. PostgreSQL timestamptz stores a true instant, so this is a no-op there. Regression test parametrized over UTC/-08:00/+05:30 runs on both backends; verified the non-UTC params fail without the fix and pass with it (sqlite 54, pg 58). The companion filter-bound normalization lives in shared sql_filter_util.py (used by episode and cluster stores too) and stays in #1462. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: normalize datetime filter bounds to UTC in SQL filter compilation Second half of the #1462 segment-store slice: timestamp columns now hold the UTC instant, so comparison bounds must be named in the same frame. On SQLite an aware datetime bind is rendered as wall-clock digits with tzinfo dropped and compared lexically, so `timestamp <= 2024-01-01T08:00+08:00` excluded a row stored at 00:00Z -- the same instant. _normalize_column_value converts datetime values (Comparison and In leaves) to UTC before binding; PostgreSQL compares timestamptz by instant either way, so the two backends now agree. The helper lives in the shared sql_filter_util because that is where column leaves are compiled; other stores' write paths (episode, cluster) are intentionally not touched here. Regression test parametrized over the same instant named in +00:00, +08:00, and -08:00, on both backends; verified the non-UTC bounds fail without the fix and pass with it (sqlite 57, pg 61; full server suite 1880 passed, 3 skipped). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * feat: promote purge_deleted_partitions to the SegmentStore ABC Physical reclamation of deleted partitions is now an ABC capability: callers schedule it however they want; the store never schedules it itself. delete_partition's contract notes that reclamation may be deferred. Implementations whose deletes reclaim physically implement it as a no-op returning False. Signature review against the prior purge iterations (#1199/#1205): - The old three-step orphan-derivative API (get_orphaned / mark / purge) existed only because derivative purging interleaved with vector-collection deletes between steps; incarnation purge is fully internal to the store, so a single method suffices. - The old scheduling knob (purge_interval loop in ExtraMemory) lived in the consumer -- preserved: no scheduling in the store. - The bound is max_segments (domain unit; derivative links ride along uncounted) rather than max_batches, which presumed chunked-transaction implementations. batch_size stays as a keyword on the SQLAlchemy implementation only, as a transaction-size tuning knob. - Returns bool ("reclaimable work may remain") instead of rows deleted: a row count cannot distinguish "drained" from "stopped at the bound" when a dead incarnation has zero data rows, and the scheduling caller needs exactly the more-work signal. New test pins the bound and the completion signal on both dialects. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: drop batch_size from purge_deleted_partitions With max_segments as the caller's bound, a per-call batch_size is redundant: bounded calls already cap every delete transaction at the remaining budget, so the knob only governed the unbounded case -- where transaction sizing is engine policy, not caller policy. The chunk is now an internal constant (_PURGE_CHUNK_SIZE); if a deployment ever needs to tune it, it belongs in SQLAlchemySegmentStoreParams, not per call. Tests exercise multi-chunk draining by patching the constant. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: purge is one atomic slice per call; fix open_or_create race Purge contract resolved to atomic-slice-per-call: each purge_deleted_partitions call is a single transaction that reclaims up to max_segments rows and either commits that progress or nothing. Draining a backlog is the caller's loop (call until False), so reclamation never holds a long transaction, committed slices survive interruption, and there is no internal chunking competing with the caller's bound. max_segments=None means the store-chosen slice size (_PURGE_SLICE_SEGMENTS), keeping engine-appropriate transaction sizing out of callers' hands. Rationale over the alternatives: cross-call atomicity is anti-useful for gc (a huge atomic purge is exactly the long-transaction hazard, and an error would forfeit all progress), while batch_size+max_batches exposes the store's transaction quantum and bounds a call only as a product of two knobs. Also fixes a TOCTOU in _open_or_create_partition caught by the new lifecycle churn test: losing the insert race and then finding no row (a concurrent delete removed the winner) raised RuntimeError; the read-then-insert sequence now retries, since every retry implies another actor changed the state. New deterministic fencing tests: test_write_landing_during_delete_is_never_orphaned (the write pin means rows can never land under an incarnation the purge queue no longer tracks) and test_concurrent_remote_delete_yields_single_queue_entry (the delete pin means racing deletions enqueue exactly once). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: lock-necessity suite verified by per-lock ablation in both generations New test_segment_store_locking.py (PostgreSQL integration lane) pins each locking property through the public API, using only surface shared with the pre-overhaul partitioned store so the module runs against both generations. All interleavings are staged event-driven: blocked-ness is decided by observing pg_stat_activity lock waits, not elapsed time; there are no grace sleeps, and paused writers are released in finally blocks so a failing assertion cannot wedge fixture teardown. The lane adds under a second of CI time. Ablation matrix (each lock removed one at a time via source-patched variant trees, PYTHONPATH-shadowed; old = pre-overhaul partitioned store at 14b8f0a2~1): - write pin ablated (either generation): write-pin test fails, plus the no-orphaned-writes fencing test on the new store. - delete pin ablated (new store): churn, concurrent-delete, and single-queue-entry tests fail (double-enqueue IntegrityError). - delete row pin ablated (old store): write-pin test fails (the delete no longer waits out the in-flight writer). - ordered delete_segments row locks ablated (either generation): no test fails -- identical DELETE shapes lock rows in identical orders on PostgreSQL (sorted scalar-array probes, TID-ordered bitmap scans), so the AB/BA cycle needs plan divergence the store never produces. The overlap test is kept as a regression canary and documented as such; whether to keep the pre-lock itself is a separate decision. - old store with ALL locks intact: churn and concurrent-delete tests fail with DeadlockDetectedError in the two cycle shapes documented on #1546 (delete-vs-delete lock upgrade over the table mutex; create-vs-delete DDL cycles through the shared parents). Those deadlocks are inherent to the partitioned layout -- the property the shared-table overhaul removes, and these tests now pin. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: purge claims queue entries with SKIP LOCKED; correct lock-order rationale Concurrent purgers were a real deadlock surface: two processes draining the same dead incarnation delete overlapping row sets through unordered scans. Claiming queue entries with FOR UPDATE SKIP LOCKED removes the contention instead of ordering it -- racing purgers partition the queue, and only the claiming call touches a dead incarnation's rows (writers cannot; the fence pins live incarnations only), so reclamation is deadlock-free by construction. This is the claiming half of the purger scale-out design in the design doc; the ABC now states the contract (concurrent calls, including cross-process, must neither error nor deadlock). Tests: test_purge_skips_entries_claimed_by_concurrent_purger stages a purger from another process holding its claim uncommitted -- a concurrent purge must skip the entry and complete without blocking; verified to fail (blocks on the held queue row) with the claim ablated and pass with it. test_concurrent_purges_reclaim_everything pins the correctness property on both dialects: racing drain loops terminate cleanly with full reclamation. Also rewords the ordered-row-lock rationale in the locking suite: the consistent acquisition order that makes the ablation unobservable is current PostgreSQL executor behavior, not a guarantee any engine documents -- the pre-lock imposes the order deliberately, and the canary catches divergence if an engine or plan change ever produces it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: accept any task result type in _wait_until_blocked_or_done The helper only observes done-ness; Task[None] rejected the purge task (Task[bool]). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: reject minting an incarnation whose garbage is still awaiting purge Data rows are keyed by incarnation alone, so a fresh mint colliding with a dead-but-unpurged incarnation would adopt its garbage and then be erased by the purger. The registry's unique constraint only guarded collisions with live incarnations; the purge-queue case was guarded by uuid randomness alone. The mint (shared by create_partition and open_or_create_partition) now re-checks the purge queue inside the insert transaction and re-mints on collision. The check is race-free with the existing tables -- no ledger table needed: it runs after the registry insert, so a concurrent deletion moving a colliding row to the queue (the insert waited on its uncommitted registry delete) is already visible, and no new queue entry for the minted value can appear before commit because the only registry row carrying it is uncommitted. The locking read sees latest-committed state on dialects whose plain reads serve transaction-start snapshots; SQLite serializes whole transactions. An incarnation value can therefore never be reused while any trace of it remains within a database; across databases, uniqueness still rests on random-uuid collision resistance. test_incarnation_with_garbage_left_is_never_reused forces the collision by stubbing the mint (both creation paths, both dialects); verified to fail with the re-check ablated and pass with it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: one collision error for live and garbage incarnation mints Both collision causes look the same to the mint's callers and share the same remedy -- mint a fresh incarnation and retry -- so they now share one error, with the cause classification (key taken vs incarnation collision) resolved inside _insert_partition_row: an IntegrityError with a committed row under the key means the key is taken (SegmentStorePartitionAlreadyExistsError: open or delete it instead); without one, the incarnation collided with a live row. Errors are typed by the decision the caller makes, not by the failing constraint, and both call sites shrink to one remedy branch per error. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: fold locking tests into the segment store test file; drop "slice" All SQLAlchemy segment store tests live in one file. The separate locking module existed so the same tests could import against the pre-overhaul partitioned store for the lock-ablation matrix; that verification is done and recorded, so the split's constraint is spent. The per-lock coverage map moves to a section comment. Also replaces the "one slice per call" purge wording, which was circular (a slice being defined as whatever one call does), with the actual contract: each call reclaims at most max_segments segments -- in this store, one transaction that commits that progress or nothing -- and None means the store's default bound (_DEFAULT_PURGE_MAX_SEGMENTS, renamed from _PURGE_SLICE_SEGMENTS). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: correct design-doc drift; drop dead _is_postgresql flag Accuracy review of the design doc against the code: - The create bullet said "one row insert"; the mint transaction also re-checks the purge queue. - The locking model omitted the purger's SKIP LOCKED queue claims and the mint's collision-case queue pin; it now lists every row lock and why reclamation cannot contend with anything. - The consequences section claimed the only remaining dialect split is the LATERAL-vs-loop read strategy; the PostgreSQL-only ordered row locks in delete_segments and SQLite's foreign-key pragma are splits too. _is_postgresql was assigned and never read -- dead since the overhaul removed the DDL branches. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * feat: make the default purge bound a store construction parameter SQLAlchemySegmentStoreParams.default_purge_max_segments (default 10000) replaces the module constant: each purge call is one transaction, so the right default bound is dialect- and deployment-dependent, and the construction parameter lets an application set it once instead of every purge caller reading configuration to pass max_segments. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: cover live-incarnation collision and purge-bound params wiring Coverage audit of the recent additions found two unpinned paths: - The live half of the mint's collision handling (registry unique violation classified by the key re-read, then re-mint) had no test -- only the garbage half did. test_incarnation_colliding_with_live_ partition_is_never_reused forces the collision on both creation paths and both dialects; verified to fail with the classification ablated (create_partition misreports AlreadyExists) and pass with it. - The purge tests patched the store's default-bound attribute directly, leaving the SQLAlchemySegmentStoreParams.default_purge_max_segments wiring itself untested. test_default_purge_bound_comes_from_params constructs a store with a small configured bound and observes it govern an unbounded purge call. Also converts the two override-method docstrings (delete_partition, purge_deleted_partitions) to body comments: the contract lives on the ABC; overrides keep only implementation mechanics. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: rename _logical_partition_key to _partition_key The "logical" qualifier contrasted with the physical partition key of the composite-key era; data rows now carry no key at all, so there is nothing physical to distinguish from. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: rename PurgeRow to PurgeQueueRow The model classes are named for what a row represents (PartitionRow, SegmentRow, DerivativeLinkRow); a segment_store_gc row is not a purge but an entry of the purge queue. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: restore @staticmethod on _resolve_segment_field It became an instance method when field resolution went through the handle's per-partition aliased entities; the shared-table overhaul resolves against the module-level SegmentRow again, leaving self unused. Call sites return to the original class-qualified form. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: pin the mint's insert-then-check statement ordering The collision guard relies on checking the purge queue AFTER the registry insert: under READ COMMITTED, the insert's unique-index wait on a concurrent deletion's uncommitted registry delete is what forces that deletion's queue entry to be committed -- and therefore visible to the later check. Checked before the insert, the queue is read too early and the mint commits a live partition whose incarnation is on the purge queue, handing its rows to the purger. Only a concurrent interleave distinguishes the orderings, so the sequential collision tests cannot pin it: verified by swapping the two statements -- the sequential tests all still pass (the opposite order is correct for non-concurrent use), while the new test_mint_detects_collision_with_concurrent_deletion fails (it is incorrect for concurrent use). The test stages the interleave deterministically: a raw-session deletion held uncommitted, the colliding mint observed blocking on it via pg_stat_activity, then the deletion committed. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: plain "maximum number of segment rows purged per call" wording Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: match params docstring to the pydantic field description Convention in the class: the Attributes entry carries the field description plus the default; the field expresses the default via its default attribute only. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: purge claims queue entries one at a time The claim SELECT had no limit: it materialized and row-locked every unclaimed queue entry even when max_segments exhausted on the first incarnation -- a mass-deletion backlog was fetched wholesale per call, and the first purger claimed the entire queue, so concurrent purgers skipped everything and exited instead of sharing the backlog. Claims are now LIMIT 1 FOR UPDATE SKIP LOCKED, issued as the call processes entries: a bounded call locks exactly what it works on. Within the transaction each claimed entry is retired before the next claim, so the call's own claims (which SKIP LOCKED does not skip) cannot recur and the loop terminates. test_purge_claims_queue_entries_incrementally pins the property via recorded SQL: every queue claim carries LIMIT, and a call whose bound exhausts on its first incarnation issues exactly one claim; verified to fail against the previous claim-all form. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: batch, not chunk, for the purge deletion unit Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: purge runs on an engine connection for typed rowcount AsyncSession.execute has no DML overload -- it is typed Result[Any] for every non-typed statement, so reading rowcount needed an isinstance narrowing to CursorResult (whose unreachable else-branch would have fabricated a zero count). AsyncConnection.execute is typed CursorResult in every overload, and the purge transaction is pure Core DML with no session features, so it now runs on self._engine.begin(): the library's own annotations carry the type and the narrowing disappears. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: manual formatting Signed-off-by: Edwin Yu <edwinyyyu@gmail.com> * fix: address code-review findings (round 3) Six confirmed-or-verified defects from a second review session, each fixed with a test verified to fail on the pre-fix code: - SQLite write fence was a no-op: the driver defers BEGIN to the first data-modifying statement, so the fence SELECT ran outside the write transaction and a write racing a delete-plus-purge committed rows no queue entry tracked. The write fence (and deletion's row check) now issue a no-op registry UPDATE first, opening the write transaction so the check is transactional and racing deletions serialize. - The shared column-leaf UTC normalization silently changed OTHER stores' datetime filters: their write paths still store wall clock, so on SQLite their filters stopped matching rows they had just written. Normalization is now an explicit compile_sql_filter opt-in (column_datetimes_are_utc) that only the segment store sets; other stores regain their previous behavior, and #1462 flips the opt-in for the stores whose write paths it fixes. - Mint collision retries were unbounded: any persistent IntegrityError with the key absent became an infinite hot loop. Both creation paths cap consecutive collision retries (_MAX_MINT_ATTEMPTS) and re-raise the underlying error -- consecutive failures at that depth mean a permanent cause, not a race. - purge_deleted_partitions accepted non-positive bounds and returned True unconditionally, spinning the documented drain loop; it now raises ValueError. Empty incarnations charge one segment of budget, so a backlog of empty tenants is bounded per call instead of drained in one unbounded transaction. - open_or_create committed the registry row before materializing the payload codec, leaving an unopenable partition behind on codec failure; the codec is loaded before the insert again. - validate_partition_key used re.match with $, accepting keys with a trailing newline; now re.fullmatch. Also from the review: the ABC documents the stale-handle contract on SegmentStorePartition and corrects purge's False semantics (work owned by a concurrent purger is not counted); the blocked-or-done test helper scopes pg_stat_activity to the current database. Rejected findings, with grounds recorded in the PR discussion: the read-fence round trip is the deliberate loud-fencing contract (#1549); fence/live-check unification, the forensic enqueued_at column, and FIFO claiming are declined as taste; the partition-key rule's overlap with service_locator stays per the incidental-convergence ruling. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: LongTermMemory erasure drains the purge queue inline delete_partition's physical reclamation is deferred by design, but the review found its one production caller now leaked: session deletion previously removed data physically (DROP on PostgreSQL, cascade on SQLite) and nothing anywhere called purge_deleted_partitions. The erasure path drains the queue inline before returning, restoring physical removal semantics; background scheduling remains available to other callers. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: UTC-normalize every SQL store; self-checking SQLite fence; FIFO purge Four follow-ups to the review round, per direction: - The datetime-normalization opt-in is gone: instead of scoping the shared compiler's UTC bound normalization to the segment store, every SQL store's write path is fixed honestly in this PR. #1462's episode and cluster fixes (created_at + start/end bounds; last_ts + pending created_at) are ported with their regression tests, and the compiler normalizes column datetime bounds unconditionally -- correct for all consumers, since the semantic-storage columns it also serves are server-generated UTC (func.now()). Fixes #1558 and #1559 here. - The SQLite fence is one self-checking statement instead of a no-op UPDATE plus a SELECT: the proper primitive, BEGIN IMMEDIATE, is only expressible engine-wide in SQLAlchemy (it would put every read transaction behind the write lock), so the registry-row UPDATE acquires the same write lock scoped to the transaction, and its match count is the staleness check. Deletion opens its transaction the same way, with zero matches as the idempotent no-op case. - The purge queue is FIFO: claims order by enqueued_at (indexed), so the oldest garbage is reclaimed first and the name is honest. Queue entries carry their own per-call bound (SQLAlchemySegmentStoreParams.purge_max_partitions, default 1000) instead of charging a fake segment of budget: their cost is round trips rather than row deletions, and empty partitions are cheap to mass-create-and-delete, normally or adversarially. Empty entries no longer consume max_segments. - PostgreSQL-only concurrency coverage gains SQLite counterparts wherever the property exists on both dialects: lifecycle churn, racing deletions (plus a single-enqueue assertion), overlapping segment deletes now run on both; new SQLite tests pin the mint-vs-deletion collision race and O(1) deletion via recorded SQL. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: precise rationale for the SQLite fence primitive BEGIN IMMEDIATE is expressible per-transaction in principle, but only atop engine-wide rewiring (isolation_level=None plus a begin-event hook) that the store cannot apply to a caller-owned, possibly shared engine; say that instead of "only expressible engine-wide". Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: two-character index name tokens, matching the prior convention pk_ev / pk_ts_ev_bk_ix / pk_su used two characters per indexed column; in (incarnation) and ea (enqueued_at) follow, replacing inc and enq. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor!: purge takes no arguments; cap derivatives at ingestion purge_deleted_partitions() -> bool. Callers cannot know engine-appropriate transaction sizing -- the same argument that made the default a construction parameter removes the per-call override: the caller's whole protocol is "call until False", and every bound (purge_max_segments, renamed from default_purge_max_segments; purge_max_partitions) is implementation policy set once at construction. Non-positive bounds are now impossible by pydantic validation, superseding the runtime ValueError. The derivative side is bounded where it is created, not where it is reclaimed: purge keeps relying on the link-table ON DELETE CASCADE -- benchmarked against manual link deletion on the real schema and 50-68% faster (1 link/segment: ~312k vs ~209k segs/s; 4 links: ~266k vs ~158k; the manual pattern's extra round trips and array shipping cost more than the per-row indexed trigger probes) -- and ingestion rejects more than max_derivatives_per_segment links per segment (default 100), so one purge call's work is at most purge_max_segments segment rows plus that many times the cap in link rows. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * revert: drop the store-level derivatives-per-segment cap The cap rejected at add_segments time, when the caller has already segmented and derived and can do nothing to obey it -- the bound on link fan-out is ingestion-pipeline policy (deriver/segmenter design), not a store contract. Performance also gives the cap no case: measured across densities, cascade deletion saturates around 3M link rows/s (380k segments/s at one link per segment, 302k at 4, 175k at 16, 46k at 64 -- per-row cost FALLS with density, 1.3us/row at 1 link to 0.34us at 64), so a purge_max_segments=10000 call finishes in ~0.45s even at 64 links per segment. The design doc records where the bound lives and the measured sensitivity. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: state the purge contract's promise to callers The bounds are implementation policy; what the caller is promised is that a purge call does not noticeably degrade concurrent request serving. The design doc also records why a store-level link cap would be unactionable (only the deployment's segmenter/deriver choice can change the ingested shape, so a dedicated error type would have no useful handler). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: rebalance the purge entry bound to measured cost Retiring an empty queue entry measures ~0.95 ms through the store (four round trips), roughly 200x a segment row at the measured purge rate -- not the ~10x the old default implied. purge_max_partitions drops from 1000 (a ~0.95 s transaction when saturated, 20x the row bound's ~46 ms) to 50, putting a full-entry call and a full-row call at comparable transaction duration. Backlog drain throughput is unchanged (~1k entries/s regardless of slicing); only per-call transaction length shrinks. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: public SegmentStorePermanentError; power-of-ten entry bound Mint-retry exhaustion raised "last_collision.__cause__ or last_collision" -- expedient plumbing that leaked either the wrapped SQLAlchemy IntegrityError or the private collision type to callers. Per the error-design principle (type by the caller's decision), the decision here is "retrying will not fix this; diagnose", so both creation paths now raise the ABC-declared SegmentStorePermanentError with the underlying error chained as the cause. The ABC documents it on create_partition and open_or_create_partition. purge_max_partitions defaults to 100 instead of 50: sibling fields of one config keep to the same numeric family (powers of ten, alongside purge_max_segments=10000); a saturated entry call (~95 ms measured) and a saturated row call (~46 ms) stay within the same order of transaction duration. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: rename SegmentStorePermanentError to SegmentStoreRetriesExhaustedError "Permanent" asserted a diagnosis the store cannot make -- sustained adversarial churn could in principle clear on a later attempt. The name now states only what happened (internal retries exhausted), with the guidance phrased as likelihood: an immediate retry is unlikely to succeed; diagnose the chained cause. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: drop illustrative examples from contract docstrings Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: bound open_or_create's lost-race arm with the same retry cap The collision arm was capped but the AlreadyExists arm looped unboundedly -- the reviewer's livelock finding. Both non-terminating outcomes now count toward one retry budget, and exhausting it raises SegmentStoreRetriesExhaustedError with the last error chained. With this, every retry construct in the store is bounded: purge makes guaranteed progress per call, deletion is a single idempotent transaction, fences raise stale, and reads are single-pass -- the creation paths were the only sites with retries to exhaust. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * refactor: attempts, not retries SegmentStoreAttemptsExhaustedError, with the counter and docstrings using the same word: "retry" is ambiguous between a re-attempt and the whole attempt sequence, and _MAX_MINT_ATTEMPTS already counted attempts. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: attempts vocabulary in the mint-exhaustion message Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * nit: increase max mint attempts from 8 to 10 Signed-off-by: Edwin Yu <edwinyyyu@gmail.com> * nit: manual formatting Signed-off-by: Edwin Yu <edwinyyyu@gmail.com> * review: fold the read fence into the data statement; harden creation, drain, purge Third review round (15 findings; 12 acted on, 3 declined with grounds in the PR body). - Reads no longer issue a separate registry round trip: the liveness predicate rides in each data statement as an EXISTS conjunct (one statement, one snapshot -- a stale handle reads nothing), and the registry check is issued on its own only when a read returns no rows, to tell an empty partition from a stale handle. The write fence and the read check share one query builder (`_registry_row_query`) and one checker (`_ensure_partition_live(pin=...)`). - `create_partition` materializes the payload codec before inserting, like `open_or_create_partition`; its mint loop uses the same attempt-counter idiom and message as the other path, which also removes the possibly-unbound `last_collision`. - `drop_session_partition` nulls its handles before the inline drain, so a drain failure cannot leave them pointing at deleted resources; the drain's comment states exactly what it guarantees (the queue is global, the drain uncapped, and an entry a concurrent drain claimed is finished by that drain). - The purge queue's enqueue stamp is the database clock (`now()`), so every server's entries order on one clock; the unreachable `remaining <= 0` guard is gone; the purge comment and design doc state SQLite's actual claiming behavior (plain read, serialized on the database write lock at the DELETE; duplicated round trips only). - `startup()` refuses the old partitioned layout (registry without the incarnation column) with a directive to recreate the schema, instead of letting create_all leave the old tables in place for an opaque missing-column error later. - Cluster store reads use the shared `ensure_tz_aware`; the private clone is deleted. Contract wording: "every data operation" raises the stale-handle error (the config property never did). Tests: unloadable codec guard parametrized over both creation paths, FIFO pinned with explicit stamps set against insertion order, the database-clock stamp and the folded liveness check pinned via recorded SQL, the startup probe on both dialects, and the LTM nulling order under a failing drain. The codec and nulling tests were each verified to fail with their fix ablated. Read-path ABAB against the previous HEAD (interleaved rounds, medians): seed context reads 1.17 vs 1.42 ms, event lookups 1.04 vs 1.61 ms, derivative lookups 1.05 vs 1.33 ms (5 rounds), windowed context expansion 8.74 vs 9.67 ms (8 rounds x 600 reps, paired median -0.91 ms); reads that find nothing unchanged (two statements either way). Server-side EXPLAIN ANALYZE: the EXISTS conjunct plans as a one-time InitPlan (~3 us per statement); a windowed read's 3 statements execute in 0.069 ms vs the previous 4 statements' 0.067 ms. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: purge bound scales with link fan-out; queue stamp is transaction time Follow-up notes from the review session: the purge_max_segments description says its derivative links cascade uncounted, so a call's transaction also scales with the deployment's links per segment (the promise in the ABC is kept by sizing this bound with that fan-out in mind, which is the deployment's knob, not the caller's); the enqueue stamp comment records that PostgreSQL's now() is transaction-start time and that one deletion per transaction makes it one stamp per entry. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: a deleted partition's handle is permanently invalid "Obtain a fresh handle to continue" read as if deletion-and-recreation were a routine flow; the contract is simply that deletion permanently invalidates the handle, including against a later same-key creation. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * revert: drop the old-layout startup probe Handling pre-existing partitioned-layout deployments is out of scope for the opt-in, pre-GA event backend; existing databases recreate their schema, and startup stays a plain create_all. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * nit: slim the purge claiming comment The code comment keeps only the invariants the loop relies on; the full rationale stays in design/segment_store_shared_tables.md, which the comment now points at. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * nit: params docstring matches field descriptions, defaults at the end The purge bounds' field descriptions carry the full text and the docstring repeats them verbatim, with (default: N) moved to the end of each description per the params convention. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * review: second-round fixes across locator, stores, and race tests Second review round from the local review session (9 findings; 7 acted on here, the background-purger suggestion lands separately, and the unbounded link-retire guard is kept with its tradeoff stated in a comment -- bounding it would add a budget for a case that indicates a broken schema). - partition_key_for_session validated with a drifted private copy of the store's key contract: its re.match passed a trailing-newline session id through unhashed, and the store's re.fullmatch then hard-rejected it, failing session creation where hashing would have succeeded. The copy is deleted; the locator (and its tests) now call the store's own validate_partition_key, and the hash slice length comes from the now-public PARTITION_KEY_MAX_BYTES, so the two can never disagree again. Regression test verified to fail pre-fix. - The SegmentStorePartition contract states that a call with empty input does no work and returns without checking the handle -- the empty-set guards return before any fence, which the docstring's "from then on" overstated. - delete_partition on SQLite resolves the incarnation in the pin UPDATE itself via RETURNING; the locking select is PostgreSQL's path only, removing SQLite's extra round trip and its unreachable row-is-None branch. - _open_or_create_partition loads the payload codec only on the create path (still before any registry write); opening an existing partition no longer materializes a codec it discards. - Episode-store reads use ensure_tz_aware instead of an inline clone in the same file that imports it for writes. - The purge's link-retire guard comment states it is normally a zero-row delete and unbounded only if referential integrity was actually broken. - The two SQLite race tests gained started-events proving the racing task ran before the sample, so a loaded box cannot pass them vacuously by never scheduling it; the remaining grace periods are annotated (SQLite exposes no lock-wait state to observe). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * feat: background purge tick in the resource manager Nothing but the inline drain in drop_session_partition ever called purge_deleted_partitions, so a drain interrupted by a crash or a dropped connection left its queue entry (and the partition's rows) waiting for the next session deletion anywhere in the deployment. The resource manager -- the component that owns each segment store -- now runs one background task per store: one bounded purge call per fixed tick, exceptions logged and retried next tick, cancelled in close() before the stores shut down. One call per tick keeps the background work bounded by construction (a backlog drains over successive ticks), and no purger coordination is needed at any instance count because the store's claiming already makes racing purgers safe. The store itself still never schedules reclamation; this loop is the caller-side scheduler the ABC contract calls for. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: purge loop reads the backlog signal purge_deleted_partitions() returning True is the API's statement that more work remains; discarding it drained a backlog at one bounded call per tick (~167 rows/s at the defaults). The loop now runs bounded calls back-to-back while the store reports more and sleeps one tick only when it reports done or a call fails -- full-rate recovery, still bounded per call, still one idle call per tick. Pinned by a test that drains a three-call backlog under a deliberately huge tick interval. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: empty-input calls MAY skip the handle check The contract permits the shortcut rather than mandating it; an implementation that checks anyway still conforms. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test: pin the config-mismatch guard directly The guard, its error type, and the ABC declaration predate this branch, but no test staged a mismatch -- only the lifecycle-churn test tolerated it as a domain outcome. Plaintext is the only concrete codec config, so the test stands in a subclass for a future variant (pydantic instances survive validation unrevalidated and compare unequal by class). Verified to fail with the guard ablated. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * purge: bound the integrity-escape link delete; warn on it and on collisions The retire-path guard delete was the one unbounded statement in the purge, unbounded precisely when it was not a no-op. It is now batched under the same per-call budget as the segment rows: a full batch leaves the queue entry for the next call (the existing call-until- False contract absorbs it, callers unchanged), the normal case still costs one zero-row statement, and reclaiming rows there logs a warning naming the incarnation, since it means referential integrity failed somewhere. Pinned by a test that stages orphan link rows through a second SQLite engine without the foreign-key pragma and drains them in warned batches; verified to fail against the unbounded form. The module's logger also gains the only other events worth an operator's attention: a minted incarnation colliding (with garbage or in the registry) is warning-logged at the detection site -- a genuine collision is astronomically unlikely, so the log marks either broken randomness or a misclassified persistent database error, visible even when retries eventually succeed. Everything else either raises to the caller or is normal operation, and stays unlogged. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: shared purge budget is measured, not a guessed ratio Measured with the purge's batched-delete shape on 100k rows each (3 interleaved rounds): a segment row deletes at ~3.3 us and a derivative-link row at ~1.0 us, so link rows are about 3x cheaper -- they are narrower, carry fewer indexes, and fire no cascade. That is why integrity-escaped links draw count-for-count on the segment budget instead of getting their own limit: one budget calibrated on the most expensive row type upper-bounds the call, whereas a separate link limit would be safe only under an assumed cost ratio. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: the row-cost direction is the shared budget's precondition The shared purge budget stays conservative only while a link row deletes cheaper than a segment row; widening the link table or adding indexes to it revisits the choice. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * review: pace the purger, state the drain's real guarantee, close cleanly Round-3 findings 1, 2, 5 and 6 -- the first three introduced by the background purger itself. - The purge loop now pauses briefly after every productive call instead of running delete transactions back-to-back: the pause yields the database (and SQLite's single write lock) to request serving, while a backlog still drains at one bounded call per pause and an idle store costs one call per tick. This also removes the in-process busy-timeout window between the background task and the inline drain on SQLite. - The inline drain's comment claimed "the server schedules no other purger", which the purger commit falsified, and "reclaimed before returning", which SKIP LOCKED claiming never strictly guaranteed under any concurrent purger. Comment, design doc, and PR body now state the actual promise: rows are reclaimed promptly -- normally before the drain returns, and otherwise within the bounded call of whichever purger claimed the entry, moments later. - close() clears the purge-task list and the store registry, so a second close is a no-op and a post-close get_segment_store can no longer hand back a shut-down store that silently never purges. - The design doc no longer implies deployments can already tune the purge bounds through server configuration: the server constructs its stores with the defaults, and config plumbing is future work. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * review: one datetime-normalization rule per filter path Round-3 findings 3 and 11. - The properties_json In branch bound raw values while its Comparison sibling normalized through _cast_properties_json_value; a datetime In list would bind datetime objects against the stored ISO-string form (an InterfaceError on Python 3.14's sqlite3, a never-matching comparison on PostgreSQL). Both leaf shapes now cast and normalize through the one function, which also aligns the float and bool casts the old branch fell through to as_string/as_integer. Same defensive-reachability status as the column-leaf In normalization kept deliberately: unreachable by In's declared value types, reachable at runtime. - The episode store's start_time/end_time bounds re-implemented the UTC normalization inline; sql_filter_util's normalize_column_value is now public and both bounds use it, so the storage convention has one definition across compiled filters and dedicated bounds. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * review: StaticPool guard raises; empty add_segments short-circuits Round-3 findings 9 and 10. - The params validator's StaticPool guard was a bare assert, stripped under python -O -- and the design depends on multiple connections (the registry fence, deletion waiting out writers, SKIP LOCKED claiming all degrade on one shared connection). It now raises ValueError like the ephemeral-SQLite check beside it; pinned by a test, and the check stays a ValueError because pydantic converts only ValueError/AssertionError into a ValidationError. - add_segments returns early on empty input, matching delete_segments and the ABC's empty-input permission; previously it opened a transaction and, on SQLite, took the write lock to insert nothing. The stale-handle test pins the shortcut. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * filter: datetime values normalize to UTC at node construction The filter language now owns datetime semantics: a value denotes an instant, and a naive value means UTC. Comparison.__post_init__ normalizes datetime values to UTC-aware instants (In gets the same defensively -- its declared types exclude datetimes, but runtime lists are unchecked), so every consumer -- parsed trees and programmatically built ones, SQL compilers and vector stores alike -- receives normalized instants by construction, and compilers only choose a representation. This is where the rule the recent fixes kept restating per leaf actually belongs: the same aware-to-UTC-or-naive-means-UTC conversion appeared in the SQL column leaf, the properties_json leaf, the episode bounds, and twice in the Milvus store, and two of the drifted copies were bugs fixed this round. With the invariant at the node, the SQL column leaf's re-normalization became redundant and is reverted (it binds tree values as-is); the properties_json leaf keeps its routing because datetime-to-ISO-string is representation, not normalization; the episode start/end bounds keep the shared helper because they are raw API values outside any tree; other backends' now-idempotent defenses are left for separate cleanup. Pinned by tests that a programmatically built Comparison and a parsed date() literal with a non-UTC offset both carry the UTC instant. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * filter: drop normalize_column_value; contract stated on the protocol With datetime normalization at node construction, the compiler-side helper had no filter role left, and its one remaining consumer -- the episode store's start/end bounds, which arrive outside any filter tree -- now spells the convention inline as the two explicit steps, ensure_tz_aware(...).astimezone(UTC). A composed to_utc() helper was considered and rejected: the name does not pin the naive-means-UTC tagging decision (an alternative design under the same name could reject naive datetimes entirely), so the explicit steps are clearer at each site. The FilterExpr protocol docstring now states the construction-time contract where the next value-carrying node's author will read it: such a node normalizes datetime values to UTC-aware instants, and compilers bind instants without re-normalizing. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: the two-step datetime spelling is deliberate Record the datetime convention in the design doc so a future cleanup does not consolidate the repeated ensure_tz_aware(...).astimezone(UTC) sequences back into the composed helper b636d62a deliberately removed: a name that pins only the conversion, not the naive-means-UTC tagging, hides a real design decision, so the repetition is load-bearing. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs: second ground for rejecting the composed datetime helper A shared helper earns its place only when the name honestly pins the unit AND the composition structurally prevents half-applied normalization. The second condition fails here regardless of naming: read paths legitimately need the tagging step alone (segment reads reapply the stored original offset; cluster and episode reads only tag naive database values), so ensure_tz_aware stays independently available and the helper could not have removed the partial-use error class. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix: SQLite foreign keys enforced from engine creation Round-4 findings 1, 4 and 5. The store registered its foreign_keys pragma as a per-store connect listener, which has two structural faults: connections the caller's shared engine pooled before the store existed never receive the pragma, so cascade deletes silently leave orphaned link rows for LIV…

The decorator was stacked twice in the speedkick merge (MemMachine#1548); one application is the whole effect. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

…edkick) (MemMachine#1654) Remove custom sharding from the Qdrant store The Qdrant store could shard its native collection by logical collection (`QdrantConf.is_distributed`, CUSTOM sharding, one shard key per logical collection, a shard-key selector on every operation) so that a logical collection could be deleted by dropping its shard. The payload partition key was written and filtered in both modes, with the shard key on top, so no query changes here; what changes is the cost of a tenant. A shard key is a physical structure, and its cost is per tenant. Measured in MemMachine#1564 (Qdrant 1.19.0, one hundred tenants): admitting a tenant is an explicit `create_shard_key` call of about 450 ms, 45 s for the hundred against 0.3 s with payload partitioning alone, including 10,000 points; 505 segments against 5, and still 5 after deleting and reusing tenants; and cluster mode is required, with a bootstrap `--uri`. At ten thousand tenants that is over an hour of shard-key creation and some 50,000 segments before a point is written. Qdrant's own guidance says the same: a physical structure per tenant is for the few oversized ones, the long tail is a payload value. What the shard bought was the O(1) delete, and with it a kind of fencing (a write to a dropped shard fails). Deletion is about to become a registry write that is O(1) and atomic as seen by every reader, a stale handle is fenced by that registry, and the points are reclaimed afterward by a filter-delete off the request path, so a shard per logical collection would only add its cost; it goes now, on the current shape, so the later changes do not carry it. Promoting a single oversized tenant to its own custom-sharded collection later, Qdrant's tiered arrangement, stays open: it is a separate collection, not a flag on this one. `is_distributed` was never documented; a configuration naming it is rejected. Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> (cherry picked from commit 779362c)

The Qdrant and Milvus clients were built without a timeout, so a remote write could hang a request indefinitely. `request_timeout` on QdrantConf and MilvusConf, in seconds, is passed to the client; it is required, with no default, so a deployment states how long it is willing to wait, and the configuration wizard supplies 30 seconds as the starting point. The sample configurations and the configuration docs show the option. A breaking configuration change on `speedkick`. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 5c669ee)

A required field bounds only the deployments that added it and fails the rest at load; a default bounds every deployment, including one whose cfg.yml predates the option, and matches every other field on QdrantConf and MilvusConf. The wizard no longer carries the value: it constructs the confs and the field supplies it. Zero and negative values are rejected at load rather than handed to httpx as the request timeout and to pymilvus as the gRPC deadline, where zero expires every request on arrival. Without the option, qdrant-client already bounded a request at 5 seconds (httpx's default for REST, DEFAULT_GRPC_TIMEOUT for gRPC); pymilvus passed no deadline, so a Milvus request could wait forever. The default applies 30 seconds to both. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 98f09b2)

Neither client's keyword carries the unit, and the field mirrors neither (both take `timeout`), so it follows max_retry_interval_seconds on the embedder and language model configurations instead. The sample configurations lose their "seconds" comments, which the name now carries. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 0fe31cd)

MilvusClient's constructor timeout is the time it waits for the channel to become ready, at construction and on reconnect; a request is bounded only by the timeout passed to that request, and pymilvus keeps no default for it, so every request the store made had no deadline. The store now takes request_timeout_seconds and passes it on every request; the client keeps it as its connection bound. A test wraps every request method and checks the timeout reaches each call. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 92f536e)

qdrant-client takes its timeout as an int and rounds a fraction up, so a fractional value was honored by pymilvus and silently changed for Qdrant. An int is honored exactly by both, and matches max_retry_interval_seconds on the embedder and language model configurations. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 5e9f363)

…e the stores are configured MilvusVectorStoreCollection.get() was the one client request without `timeout=`; the spy test now exercises it, so a request without the timeout fails the test. The configuration parameter table gains `request_timeout_seconds`, the databases page's Milvus example carries it, and the configuration page gains a Qdrant example beside the Milvus one. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

QdrantVectorStore was the fourth component built without a metrics factory. OperationTracker accepts metrics_factory=None and then discards every timing without an error, so the store looked instrumented and emitted nothing - the same defect as the Neo4j store, the episode store and the session store, which is why no Qdrant latency was observable. QdrantConf gains MetricsFactoryIdMixin so it can resolve one, and database_manager passes it through. test_qdrant_creates_vector_store pinned the exact params and had to change. It now asserts metrics_factory is not None rather than pinning it: passing the keyword is not the property worth guarding, since None is accepted and silently discards everything. Removing the wiring fails it. Ported to main without MemMachine#1532's Dockerfile change (the EXTRAS build arg), which is unrelated to the wiring; the `metrics_factory_id` key is added to the database configuration table in the docs. (cherry picked from commit b6c90ab) Claude-Session: https://claude.ai/code/session_01Nr9kacmpFVTTfkZRw6esxP Co-authored-by: Claude Opus 5 <noreply@anthropic.com>

The simple chatbot example, the TypeScript REST demo and the Dify plugin's add-memory tool wrote to a project without creating it, relying on the write to create it. Each now creates its project before its first memory request and accepts 409 as the project already existing. No behavior changes for them; they stop depending on a write creating a project. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 4cae58a)

Adding memories to, or searching, a project that did not exist created it, with the server's default configuration, without the caller's knowledge. Now only the create-project request creates a project: a write or a search opens the session and answers 404 for an unknown project, as the search endpoint already promised; the manager's open-or-create goes. Two callers depended on the implicit creation. `org_id` and `project_id` default to `universal`, so the API promises the project `universal/universal`; the server creates it, once, at startup, and leaves one that already exists as it is. The MCP add tool names its own project and has no create-project counterpart, so it creates the project it writes to, once, and says so. The API doc strings and the OpenAPI document say which requests create a project. A breaking API change on `speedkick`. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit d21a5d0)

…anything, on every entry point A write persisted its episodes before opening episodic memory, and a write or search that targeted only semantic memory never opened it, so a request naming a project nobody created could still insert episode rows under that key and answer 200. Every write now checks the registry first, and a search that does not open episodic memory checks it too; the check is one registry read, and the episodic open, which refuses an unknown project itself, is unchanged. `memmachine-server --stdio` built its resources without setting or starting the module-level MemMachine the tools read, and so never created the default project either; it now starts and stops through the same calls as the HTTP servers. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

… points Qdrant and Milvus have no transactions, unique constraints or conditional writes, so the catalog each store keeps inside its backend (the per-namespace `__registry` collections) cannot arbitrate two server processes creating, deleting or reclaiming the same logical collection: create is a read then a write under a per-process lock, and two processes both succeed. That is what the VectorStore contract's "at most one process per collection" sentence has been standing in for. SqlCollectionRegistry keeps the catalog in the deployment's relational database instead: one table pair per backend kind, shared by every store on that kind of backend and scoped by the configured backend's id, with a row per live collection keyed by (backend, namespace, name) that carries the incarnation minted for that life of the name and the configuration the collection was created with, and a purge queue of dead incarnations. Creation is an insert the primary key arbitrates (a minted incarnation colliding with a live or queued one is re-minted, up to _MAX_MINT_ATTEMPTS, then VectorStoreAttemptsExhaustedError); deletion is one transaction that moves the row to the queue; a purge claim is a row lock under FOR UPDATE SKIP LOCKED on PostgreSQL, so concurrent purgers split a backlog. A queue entry is the incarnation's tombstone: the backend holds the points, and a write the registry read as live can land there after the purge that followed the deletion, so one purge cannot be the last. A round that finds points keeps the entry due; a round that finds none stamps it clean; the entry is removed only by a round that finds nothing again once the tombstone retention (on the database clock) has passed since the stamp, and until then the incarnation is never re-minted. The claim carries the namespace, name and configuration so a purger can find the native collection the points are in. VectorStoreCollectionHandleStaleError is the error a handle bound to a dead incarnation raises; the stores adopt it in the commits that put them on the registry. Tests run the registry on SQLite and PostgreSQL: creation, concurrent creators, backend scoping, deletion, the purge rounds, the retention, a raising round, and the re-mint paths. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

…y; delete logically, reclaim by purge QdrantVectorStore keeps its catalog in SqlCollectionRegistry instead of the per-namespace `__registry` collections, and the per-process creation locks go with them. A logical collection is identified to callers by its (namespace, name) and inside the store by the incarnation the registry mints when it is created: every point carries the incarnation in the payload field that carried the name (the `is_tenant` index stays), and a handle is bound to one incarnation. A collection deleted and re-created under the same name starts empty, its predecessor's points are never seen by it and never reclaimed out from under it, and the old handle raises VectorStoreCollectionHandleStaleError on every operation, `get` included. Creation creates the native collection first (idempotent, as MemMachine#1681 left it) and registers last, so a crash between the two leaves an empty native collection the next creation of the same configuration adopts, never a row whose points have nowhere to go; the registry's primary key arbitrates, so a racing creator on any process gets AlreadyExists and open-or-create adopts the winner's row. Deletion is one registry transaction: the collection is unreachable when it commits and its points wait on the queue. The new `purge_deleted_collections` does one round on the oldest tombstone due: it looks for one point under the incarnation in the native collection the tombstone names and, if there is one, deletes by filter in a single server-side operation, `wait=True`; the registry keeps or removes the tombstone by what the round found. A handle checks liveness before an operation, to refuse a handle known to be dead, and after it, so an operation completed under an incarnation that died meanwhile raises instead of reporting success. No lock spans the remote call: a write that lands under a dead incarnation is the purge's to reclaim, which is what the tombstone's retention is for. The VectorStore contract states this: the ABC's "at most one process per collection" sentence becomes each store's own statement (QdrantVectorStore serves any process sharing the backend and the registry database; the SQLite stores keep their bound in their class docstrings), a handle's staleness is part of the collection contract, and `purge_deleted_collections` is part of the store contract, returning False on the stores whose deletion reclaims physically (both SQLite stores, and Milvus until its own commit). QdrantConf gains `registry_database`, the name of a relational database under `resources.databases`, required, and `tombstone_retention_seconds` (default 86400); `registry_replication_factor` goes with the registry collections it sized. DatabaseManager hands the store the engine and the backend's id, which scopes its rows in the tables every Qdrant store on one relational database shares. The wizard and the sample configurations' Qdrant blocks point the registry at their SQLite database, and the docs' parameter table and databases page describe the two keys and which stores serve any process. Tests: the collection lifecycle contract (stale handles, empty re-creation, open-or-create adopting the live incarnation, idempotent deletion, purge reclaiming what deletion deferred and sparing live collections, a write landing under a dead incarnation) runs against the local-mode client and, as integration tests, the REST and gRPC clients; the cross-worker tests use two clients over one registry and pin that a strict create is created once. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

…y; delete logically, reclaim by purge The same change as the Qdrant commit, for MilvusVectorStore: the catalog moves from the per-namespace `memmachine_<ns>__registry` collections to SqlCollectionRegistry, the per-process creation locks go, and every entity carries the incarnation of its collection's life in the native partition-key field that carried the name (a uuid hex fits the field's 32 characters) and in its primary id, so a handle bound to a dead incarnation cannot reach the entities of the next life and raises VectorStoreCollectionHandleStaleError on every operation, before and after the remote call. Creation is native collection first, registry row last; deletion is one registry transaction; `purge_deleted_collections` looks for one entity under the claimed incarnation and deletes by filter when it finds one, reporting False when the native collection itself is gone. This also closes the second half of the create race the registry-in-Milvus had: `insert` into a Milvus collection does not enforce primary-key uniqueness, so two creators left two live entries under one name; the SQL registry's primary key leaves one. MilvusConf gains `registry_database` (required) and `tombstone_retention_seconds` (default 86400), DatabaseManager hands the store the engine and the backend's id, and the wizard, the sample configurations' Milvus blocks and the Milvus examples in the docs point the registry at the relational database beside them. The lifecycle contract runs against Milvus Lite; the test that pinned the registry lookup's output fields goes with the lookup. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 09329d2)

…n the collection a racing creator won The registry-backed stores never schedule their own reclamation; the resource manager starts one sweeper per vector store the first time it hands the store out, driving `purge_deleted_collections` after a short pause while rounds find something and after the idle interval otherwise, logging and retrying a round that raises. close() cancels the sweepers before the database manager closes the clients, and a get after close is refused with ResourceManagerClosedError. Concurrent sweepers on other processes need no coordination: a purge claim is a row lock the registry hands to one of them. The event backend's service locator creates a session's collection when it finds none, strictly. With creation arbitrated across processes, that create can lose to another worker's; the locator then opens the collection the winner registered instead of failing the request. The semantic manager's open-or-create needs nothing: the store adopts the winner's row itself. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn (cherry picked from commit 23ccac0)

…ck) (MemMachine#1606) * Regenerate the OpenAPI document under the locked FastAPI `docs/openapi.json` predates the FastAPI release in `uv.lock` (0.141.1), whose `ValidationError` component carries `input` and `ctx`; regenerating the document with `docs/tools/generate_openapi.py` adds the two fields and changes nothing else. Separate from the API changes above it so their diffs of this file show only what they change. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn * Remove per-project filterable properties A project could declare `properties_schema`, a set of caller property keys with types, on its long-term memory configuration; the event backend merged it into the vector store collection's indexed schema and rejected filters on any other `m.<key>`. That let a tenant create database resources (indexes, columns) by naming them in a request, which is what forced per-collection native resources named by a hash of their schema on the backends that limit them. The option is removed from the server configuration, the project API and the memory-configuration API, the Python SDK, the sample configurations, the configuration docs and the OpenAPI document. A filter may name any `m.<key>`; the stores evaluate it on the properties they hold. What a store indexes is decided by the deployment, not per project. A breaking API change on `speedkick`. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn --------- Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> (cherry picked from commit a8322a7)

The event backend wrote every property of an event into its vector record and mapped the caller's whole filter onto the vector store, so a user key that a deployment never declared was both stored and filtered there: on Qdrant and Milvus as unindexed payload a filtered query scans for. The segment store already holds every property and already receives the whole filter for the context windows, so the vector side only duplicated work the segment store does anyway. The vector record now carries the keys the collection declares: EventMemory's reserved segment uuid and timestamp, and the `_`-prefixed system properties an adapter stamps on the event, which after MemMachine#1670 are exactly the collection's schema. The vector store is queried with the conjuncts of the filter that name only such fields; a conjunct is dropped whole when any field under it is a user property, so dropping only ever widens the vector search, and the segment store narrows it back on the windows. User keys never reach the vector store, so a tenant's properties cannot shape what it stores or scans. `filter_fields` joins the filter parser: every field name a tree addresses. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ESpWYTmCR7X3bJEpoA8SAn

edwinyyyu and others added 3 commits September 21, 2026 11:12

edwinyyyu changed the title ~~[vector store 3/9] Keep user properties out of the vector store~~ [vector store scale-out 3/4] Keep user properties out of the vector store Sep 21, 2026

edwinyyyu and others added 4 commits September 21, 2026 15:25

edwinyyyu and others added 13 commits September 21, 2026 15:25

edwinyyyu force-pushed the feat/vector-store-declared-routing-main branch from 48951bf to c164c56 Compare September 21, 2026 22:44

edwinyyyu changed the title ~~[vector store scale-out 3/4] Keep user properties out of the vector store~~ [vector store scale-out 4/5] Keep user properties out of the vector store Sep 21, 2026

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[vector store scale-out 4/5] Keep user properties out of the vector store - #1702

[vector store scale-out 4/5] Keep user properties out of the vector store#1702
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edwinyyyu commented Sep 21, 2026 •

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