A file shared across many users — directly, or via a group folder shared
to a group — was parsed and embedded once per user. Chunk point IDs are
user-agnostic (uuid5(tenant_id, doc_id=fileid, chunk_index)), but the
per-user freshness gate filtered Qdrant by user_id, so two readers
ping-ponged: each overwrote the other's points and each kept seeing "not
indexed for me", reprocessing every scan. Production telemetry (note
386945, finding #5) measured identical docs re-processed every few hours
at 7-13s each, with PDF parse ~62% of per-doc cost.
Layer 1 — tenant-wide dedup:
- Thread the scanner's tag-REPORT etag into the file DocumentTask and the
chunk payload; index `etag` as a KEYWORD field.
- vector/sharing_state.find_indexed_content scrolls tenant-wide (no
user_id filter) for a non-placeholder point matching
(doc_id, doc_type, etag), gated on embedding_identity in Python so a
model switch correctly forces a re-embed.
- Scanner skips enqueue and the processor skips fetch/parse/embed when a
match exists (cross-worker race-guard before WebDAV read). Dedup is
fail-safe: a Qdrant error degrades to "process normally".
Layer 2 — observed-access ACL (no admin / GroupFolders API needed):
- Each point carries `acl_principals` = the set of user:<uid> whose
scanner has observed (hence can read) the file. The per-user tag REPORT
is the access oracle; group membership/GroupFolders enumeration is
admin-only and unavailable in multi-user modes.
- build_ownership_filter ORs MatchAny(acl_principals, ["user:<me>"]) so a
deduplicated shared/group-folder point surfaces to every reader;
verify-on-read (_verify_files) remains the precise ACL gate.
- Deletion/eviction become "release one user": drop the principal and
delete the points only when the set empties, so one user untagging a
shared file doesn't evict it for the others. Legacy points without the
field keep the original per-user delete.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Production was logging two cascading classes of Qdrant errors against the
welcomed-malamute deployment:
1. HTTP 400 — "Bad request: Index required but not found for \"doc_id\" of
one of the following types: [keyword]". The collection was created via
create_collection() with no payload indexes, so any FieldCondition
filter on doc_id failed at the Qdrant layer (placeholder writes/reads,
eviction, search context lookups).
2. Compounding the missing index, producers wrote a mix of int and str
doc_ids: webhook_parser stringified node_id, scanner stringified note
IDs, news IDs, and deck card IDs — but the file scanner passed the
numeric file_id through unchanged. A keyword index would not have
covered both kinds even if it had existed.
This change:
- Normalizes doc_id to str at every producer site (scanner.py:459,
DocumentTask.doc_id, indexed_*_ids reads from Qdrant).
- Tightens str|int annotations to str across placeholder.py,
eviction.py, search/verification.py, search/context.py,
SearchResult.id, and the auth/api visualization endpoints.
- Defensive str() coercion on doc_id reads in semantic.py /
bm25_hybrid.py / vector/visualization.py for the transition window
before the backfill runs.
- Adds an idempotent startup migration in get_qdrant_client():
- _ensure_keyword_payload_indexes creates KEYWORD indexes for
doc_id, user_id, and doc_type (tolerates "already exists" 400s).
- _backfill_doc_id_to_string scrolls the collection once and rewrites
int doc_ids to str. Skipped after a quick sample shows no legacy
int payloads.
- Public API preserved: SemanticSearchResult.id stays int via explicit
int(r.id) narrowing in server/semantic.py — surfaces a TypeError with
actionable context if a future doc_type ships non-numeric ids.
- Documents the startup migration in docs/configuration.md.
Tests: 11 new unit tests in tests/unit/vector/test_qdrant_client.py
covering happy path / already-exists / unrelated-400 for the index
helpers, and sample-skip / mixed-batch rewrite / payload=None edge cases
for the backfill. 889 unit tests pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The vector index lags Nextcloud (5-min webhook cron + scanner interval),
producing ghost records for deleted/unshared documents until the next
reconciliation. Verify each unique document against Nextcloud at query
time, drop inaccessible results, and lazily evict the corresponding
Qdrant points.
Per-doc_type batch verifiers: notes/files/deck cards run concurrently
per id; news items use a single fetch + intersect to avoid the per-item
fetch-all amplification. Transient errors fail open (keep result, log
warning) — only definitive 4xx drops. Multiple chunks of the same doc
collapse to one verification call.
Wired into nc_semantic_search before the limit trim and before context
expansion. nc_semantic_search_answer's per-note re-fetch retained as a
sub-second race guard since verification now happens upstream.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
