refactor(test): share the Qdrant point-seeding helper

Why:
- The helper turning a SeedSpec into an upsertable ChunkPoint lived inside one
  integration test. A second suite now needs to seed real Qdrant the same way,
  and a copy would let the two drift.

Changes:
- Move `_chunk_point` into tests/support/point_contract.py as `chunk_point_for`,
  beside the `build_point` read model it derives its payload from.

Impact:
- Pure move. No behaviour change; enables the API suite that follows.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

tests/integration/qdrant/test_point_repository.py

@@ -18,18 +18,12 @@ from collections.abc import Awaitable, Callable
 import pytest
 from qdrant_client import AsyncQdrantClient, models
 
-from src.application.ingestion.models import SparseVector
-from src.application.points.models import ChunkPoint
 from src.config import QdrantSettings
-from src.infrastructure.qdrant.collection import (
-    DENSE_NOMIC_DIMENSIONS,
-    DENSE_OPENAI_DIMENSIONS,
-    ensure_chunks_collection,
-)
+from src.infrastructure.qdrant.collection import ensure_chunks_collection
 from src.infrastructure.qdrant.point_repository import QdrantPointRepository
 from src.infrastructure.qdrant.points import QdrantPointStorage
 from tests.support import point_contract
-from tests.support.point_contract import SeedSpec, build_point, seed_specs
+from tests.support.point_contract import chunk_point_for, seed_specs
 
 pytestmark = [
     pytest.mark.integration,
@@ -54,33 +48,13 @@ IDS = {
 }
 
 
-def _chunk_point(spec: SeedSpec) -> ChunkPoint:
-    """The contract's `Point` re-expressed as something upsertable.
-
-    `build_point` produces the read model; Qdrant needs vectors and a flat
-    payload dict, so the payload is taken straight off the model to guarantee
-    the two representations cannot drift apart.
-    """
-    point = build_point(spec)
-    payload = point.model_dump(mode="json", exclude={"point_id", "vectors"})
-    return ChunkPoint(
-        point_id=point.point_id,
-        dense={
-            "dense_nomic": [0.1] * DENSE_NOMIC_DIMENSIONS,
-            "dense_openai": [0.2] * DENSE_OPENAI_DIMENSIONS,
-        },
-        sparse=SparseVector(indices=[1, 2], values=[0.5, 0.25]),
-        payload=payload,
-    )
-
-
 async def _seeded(
     qdrant_client: AsyncQdrantClient, qdrant_settings: QdrantSettings
 ) -> QdrantPointRepository:
     await ensure_chunks_collection(qdrant_client, collection=qdrant_settings.collection)
     storage = QdrantPointStorage(qdrant_client, collection=qdrant_settings.collection)
     await storage.upsert_points(
-        [_chunk_point(spec) for spec in seed_specs(TENANT_A, TENANT_B, FILE_A, FILE_B, FILE_C)]
+        [chunk_point_for(spec) for spec in seed_specs(TENANT_A, TENANT_B, FILE_A, FILE_B, FILE_C)]
     )
     # Payload indexes are built asynchronously; without waiting, a full-text or
     # ordered query can run against a half-built index and return short.

tests/support/point_contract.py

@@ -21,8 +21,14 @@ from dataclasses import dataclass
 from datetime import UTC, datetime
 
 from src.application.ingestion.chunking import chunk_id_for
+from src.application.ingestion.models import SparseVector
+from src.application.points.models import ChunkPoint
 from src.application.points.point import Point
 from src.application.ports.point_repository import PayloadPatch, PointRepository
+from src.infrastructure.qdrant.collection import (
+    DENSE_NOMIC_DIMENSIONS,
+    DENSE_OPENAI_DIMENSIONS,
+)
 
 # Two tenants and two files, so every scenario can assert both that the right
 # rows come back and that the wrong ones do not.
@@ -76,6 +82,26 @@ def build_point(spec: SeedSpec) -> Point:
     )
 
 
+def chunk_point_for(spec: SeedSpec) -> ChunkPoint:
+    """A `SeedSpec` as something upsertable into real Qdrant.
+
+    The payload is taken straight off `build_point`'s read model rather than
+    hand-written, so the write shape and the read shape cannot drift apart. The
+    vectors are constant filler: nothing in plan 002's read paths scores by
+    similarity, so their values are irrelevant and their dimensions are not.
+    """
+    point = build_point(spec)
+    return ChunkPoint(
+        point_id=point.point_id,
+        dense={
+            "dense_nomic": [0.1] * DENSE_NOMIC_DIMENSIONS,
+            "dense_openai": [0.2] * DENSE_OPENAI_DIMENSIONS,
+        },
+        sparse=SparseVector(indices=[1, 2], values=[0.5, 0.25]),
+        payload=point.model_dump(mode="json", exclude={"point_id", "vectors"}),
+    )
+
+
 def seed_specs(
     tenant_a: uuid.UUID,
     tenant_b: uuid.UUID,