feat(ingestion): index embedded chunks into Qdrant on upload

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.

src/bootstrap/lifespan.py

@@ -20,6 +20,7 @@ from src.infrastructure.minio.storage import MinioObjectStorage
 from src.infrastructure.observability.logging import configure_logging
 from src.infrastructure.postgres.database import create_engine, create_sessionmaker
 from src.infrastructure.qdrant.client import create_client as create_qdrant_client
+from src.infrastructure.qdrant.points import QdrantPointStorage
 
 logger = structlog.get_logger(__name__)
 
@@ -77,6 +78,13 @@ def create_lifespan(
         logger.info("lifespan.minio.client.created")
 
         qdrant_client = create_qdrant_client(resolved_settings.qdrant)
+        # No collection DDL here: `ensure_chunks_collection` is a deployment
+        # step (`python -m src.cli.qdrant_bootstrap`), for the same reason
+        # ADR-0009 keeps Alembic out of startup and ADR-0012 makes LangGraph's
+        # `.setup()` a deployment step.
+        point_storage = QdrantPointStorage(
+            qdrant_client, collection=resolved_settings.qdrant.collection
+        )
         logger.info("lifespan.qdrant.client.created")
 
         nomic_settings = resolved_settings.embedding.nomic
@@ -136,6 +144,7 @@ def create_lifespan(
             minio_client=minio_client,
             qdrant_client=qdrant_client,
             object_storage=object_storage,
+            point_storage=point_storage,
             ingestion_limiter=ingestion_limiter,
             dense_embedders=dense_embedders,
             sparse_embedder=sparse_embedder,