- purge route: include a "failed" key in the 200 body listing requested doc
types that were not purged, so Astrolabe knows consent isn't yet enforced
for them (scanner backstop still catches up)
- tests: add @pytest.mark.unit / module-level pytestmark to the new test
modules so they run under `pytest -m unit`; add a partial-failure route test
- capabilities: comment why the cache is keyed per-user despite a global value
- semantic/scanner: doc/comment clarifications (sorted-order, eviction timing)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- scanner: gate the consent backstop with a per-(user,doc_type) one-shot
marker so a standing admin-disable doesn't re-enqueue idempotent deletes
every scan tick; the marker clears when the type is re-enabled. Derive
_TEXT_BACKSTOP_DOC_TYPES from INDEXED_DOC_TYPES so new indexed types are
covered automatically
- semantic: extract _consent_narrowed_doc_types so the search-side narrowing
is unit-testable; add tests for restrict/intersect/disjoint/empty
- purge route: cap doc_types length (abuse guard) -> 400
- tests: one-shot + re-enable backstop, too-many-doc_types 400
Deferred (noted on PR): per-document allowed_doc_types call is cache-hot;
purge "last error wins" — both logged. SonarCloud broad-except hotspots are
deliberate (noqa BLE001), reviewable in the UI.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Billing product model finalized (Deck #281): bill pages externally, record
tokens internally. Rename the data-plane metric literals to match the now-
canonical contract (Deck #284) — the control plane's METRIC_EVENT_NAMES is
already renamed, so the old names would be unmapped and never sync to Stripe.
Rename (values unchanged):
- embeddings_queries → tokens_embedded (value = real token count, already
emitted by this PR; the unit upstream providers bill on).
- pages_chunks → pages_embedded (value kept as len(chunk_texts) interim;
TODO(#282): real normalized "pages indexed" count — real pages for paginated
types, chars/tokens-per-page constant otherwise — is deferred to the
instrumentation card, this only lands the name/contract).
- All literals, log strings, docstrings, comments, the migration comment, and
tests renamed; grep confirms zero old strings remain.
Observability (new): export embedding token cost to Prometheus as
astrolabe_embedding_tokens_total{provider,operation} (operation = index|query)
so the billed cost unit is visible in Grafana, not just the per-tenant billing
DB. Dedicated counter (doesn't inflate the existing chunk/request metrics) and
always-on (independent of USAGE_METERING_ENABLED, so OSS/self-host gets it).
Wired on both the indexing batch embed and the search query embed (query inside
the per-request cache-miss branch, so reused embeddings aren't double-counted).
Note: the rename orphans any pre-existing embeddings_queries/pages_chunks rows
in tenant app DBs (CP no longer maps them) — acceptable; pipeline is inert with
throwaway dev/sandbox data.
Deck #284 (folded into PR #875).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Round-5 claude-review (merge-ready; all nits):
- 🟡 Added test_empty_doc_types_normalizes_to_null pinning doc_types=[] → None
in record_search_usage metadata (matches the None case).
- 🟡 record_search_usage docstring now notes nc_semantic_search_answer always
meters with doc_types=None (it exposes no doc_types parameter).
- 🟢 BM25HybridSearchAlgorithm.__init__ now sets query_embedding /
query_token_count alongside _embedded_query, so all three cache fields are
instance attributes from construction (was relying on the class-level
SearchAlgorithm defaults).
- 🟢 Ollama embed_batch_with_usage caches _dimension inline (mirrors
OpenAI/Mistral), so the dimension is set via any embed path.
- 🟢 record_indexing_usage documents the independent-record / partial-failure
semantics under SUM aggregation.
Deck #67.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Round-4 claude-review findings (no blockers):
- 🟡 Untested server-layer metering hook (raised across rounds): extracted the
nc_semantic_search embeddings_queries recording into a module-level
record_search_usage() helper (mirroring record_indexing_usage) and added
tests/unit/server/test_semantic_metering.py — value = query token count,
flag-off no-op, None token → 0, doc_types metadata bounding, best-effort
failure swallowed.
- 🟡 Dedup-hit skipped metering invisibly: the existing dedup info log now
states "no embedding/usage recorded" so a "fewer embeddings_queries rows than
expected" audit lands on the dedup path directly.
Deferred 🟢 nits (stated on the PR): search 0-token rows are recorded
deliberately (the query embedding ran; zero is a sum no-op) — documented in the
helper; embed_tokens closure locality and the OpenAI embed() dual path are
unchanged (correct as-is / separate refactor).
Deck #67.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
