Why:
- POST /v1/files was reporting chunks_indexed=0/points_created=0 unconditionally
— chunks were parsed and embedded but never written to Qdrant, so nothing
was actually searchable after upload.
Changes:
- upload_source_file() now calls index_chunks() after embedding, inside the
same INGESTION_TIMEOUT_SECONDS window, and marks the job failed
(error_code=index_failed, 502) if it raises.
- Job counters (points_created, points_soft_deleted) and the response's
chunks_indexed now reflect the real indexing result instead of a hardcoded
zero.
- Wired PointStorage through AppResources/lifespan/the files router.
Impact:
- A successful upload is now searchable in Qdrant by the time 201 returns.
Why:
- Ingested chunks need to become searchable Qdrant points before the upload
response returns, with tenant/domain isolation and a safe re-ingestion
story per ADR-0001/0017.
Changes:
- src/application/points/: index_chunks() is the sole entry point, owning
payload construction, batched/bounded-concurrency upserts
(upsert_concurrency semaphore), and a soft-delete sweep for points a
shorter re-ingestion leaves behind. The sweep runs only after every upsert
in the attempt succeeds, so a failed attempt can leave a stale prefix but
never removes content from a working index.
- PointStorage port (application/ports/) + QdrantPointStorage adapter
(infrastructure/qdrant/points.py), keeping the qdrant_client SDK out of
application code per ADR-0015.
- FakePointStorage test double for exercising the ordering/idempotency
guarantees without a real Qdrant.
Why:
- ADR-0001's Qdrant payload records embedding_model_version so a future model
swap can identify which chunks need re-embedding. The embedder is what
knows which model produced its vectors, so it reports this rather than the
call site reconstructing it from settings.
Changes:
- DenseEmbedder/SparseEmbedder protocols gain a model_version: str attribute.
- OpenAICompatibleEmbedder reports its configured model; Bm25SparseEmbedder
reports its analyzer (bm25-<analyzer>).
Why:
- The chunks collection needs four named vectors (dense_nomic, dense_openai,
sparse, late_interaction) and payload indexes defined at creation time per
ADR-0001; sparse/multivector fields cannot be added to an existing
collection without recreating it, so schema drift here is expensive.
- Creating it at FastAPI startup would mirror the DDL-at-boot anti-pattern
ADR-0009 already rejects for Postgres and ADR-0012 rejects for LangGraph's
setup(), so it is a deployment step instead.
Changes:
- src/infrastructure/qdrant/collection.py: ensure_chunks_collection(),
idempotent and schema-verifying (raises on dimension/modifier mismatch
rather than silently accepting a misconfigured collection).
- src/cli/qdrant_bootstrap.py: the operator entry point
(python -m src.cli.qdrant_bootstrap).
- QdrantSettings gains collection/upsert_batch_size/upsert_concurrency.
Impact:
- Deployments must run the new bootstrap command before the first upload;
see ADR-0001's new "Collection provisioning" section.
Why:
- Plan 001 Phase 4 needs batched, concurrency-bounded embedding wired into
the inline upload path, with process-wide capacity/timeout/chunk-limit
guards (ADR-0017).
- The BM25 analyzer and dense-model config are ported from the `emet`
evaluation lab, which benchmarked them against the real Farsi corpus
(bm25-fa-norm-stop; nomic-embed-text-v2-moe at 768-dim; text-embedding-3-large
at native 3072-dim), closing open items in ADR-0001/ADR-0005.
Changes:
- New: embedding ports, orchestration (embed_chunks), request-bounds
helpers, and dense/sparse adapters (analyzers.py, bm25.py,
openai_compatible.py).
- upload.py now parses/chunks/embeds inline behind INGESTION_MAX_CONCURRENCY
(503), INGESTION_TIMEOUT_SECONDS (504), and the chunk-count ceiling (413);
every failure path still writes a terminal job row.
- Lifespan builds and warms both dense embedders at startup (fail-soft) and
creates the sparse embedder and concurrency semaphore.
- httpx moves from dev to main dependencies (adapters use it directly).
Impact:
- Qdrant point upserts are still Phase 5 -- chunks_indexed stays 0.
- New EMBEDDING_* env vars documented in .env.example; safe defaults.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Why:
- Code under test (auth resolution, the two-phase upload) opens more than
one session per operation; the existing fixture only exposed one
rolled-back session.
Changes:
- Add a db_sessionmaker fixture sharing one outer transaction.
- Pin loop_scope="session" -- without it, a second async test against the
session-scoped Postgres container fails with "Event loop is closed."
Why:
- Implements plan 001 Phase 3's upload orchestration.
Changes:
- ObjectStorage port and MinIO adapter, thread-offloaded per ADR-0017.
- Tenant-scoped repositories for api_keys, source_files, ingestion_jobs.
- upload_source_file implementing the two-transaction shape with
(tenant_id, domain, content_sha256) idempotency.
Impact:
- This phase stores bytes only -- chunks_indexed is always 0 until
Phase 4/5 add parsing/embedding.
Why:
- The package exposed 8 modules directly, pushing source-type dispatch and
the ADR-0017 thread-offload obligation onto every caller.
Changes:
- Add parse_and_chunk_document as the sole public entry point.
- Demote the individual parsers to internal/test-only.
Testcontainers reports the container host as `localhost`, which resolves
to ::1 before 127.0.0.1 on this machine. Docker publishes the mapped port
on IPv4 only, and the IPv6 SYN is dropped rather than refused, so asyncpg
blocked on the first address until its connect timeout instead of falling
back to the second -- the migration fixture hung rather than failing.
127.0.0.1 connects in 0.07s where localhost timed out at 15s; the
integration suite now runs in 3.6s, inside the 10s pytest-timeout.
Adds src/application/ingestion/ -- Persian normalization, DOCX body
walk with structural data/layout table classification, CSV/XLSX row
rendering, and fixed-size token chunking (cl100k_base, 400/60/512) --
as pure functions per ADR-0015, tested against real production
documents (asia_data_sample, kept out of the repo). ADR-0018 records
where this diverges from ADR-0004 (fixed-size default, no invented
headings/tree, structural table classification, header-provable
labeling only). Plan 001's scope line is corrected from CSV-only to
DOCX/XLSX/CSV, and CLAUDE.md's stale project-status paragraph is
updated to match current implementation state.
alembic/env.py previously always overwrote sqlalchemy.url from
Settings().postgres.dsn, which made it impossible for a test fixture to
point Alembic at a Testcontainers-managed database. Now env.py only
sets it when unset, and a new integration suite runs `alembic upgrade
head` against a real Postgres container per ADR-0016 (no create_all()).
