chore: Test sparse recommend

tests/congruence_tests/conftest.py

@@ -9,17 +9,27 @@
 )
 
 
-@pytest.fixture
-def local_client() -> QdrantClient:
-    client: QdrantClient = init_local()
-    initialize_fixture_collection(client)
+@pytest.fixture(scope="session")
+def storage() -> str:
+    return ":memory:"
+
+
+@pytest.fixture(scope="session")
+def prefer_grpc() -> bool:
+    return False
+
+
+@pytest.fixture(scope="session")
+def local_client(storage: str) -> QdrantClient:
+    client: QdrantClient = init_local(storage=storage)
+    # initialize_fixture_collection(client)
     yield client
     delete_fixture_collection(client)
 
 
-@pytest.fixture
-def remote_client() -> QdrantClient:
-    client: QdrantClient = init_remote()
-    initialize_fixture_collection(client)
+@pytest.fixture(scope="session")
+def remote_client(prefer_grpc: bool) -> QdrantClient:
+    client: QdrantClient = init_remote(prefer_grpc=prefer_grpc)
+    # initialize_fixture_collection(client)
     yield client
     delete_fixture_collection(client)

tests/congruence_tests/test_sparse_recommend.py

@@ -203,14 +203,13 @@ def recommend_batch(client: QdrantBase) -> list[list[models.ScoredPoint]]:
         )
 
 
-def test_simple_recommend() -> None:
+def test_simple_recommend(local_client: QdrantBase, remote_client: QdrantBase) -> None:
     fixture_points = generate_sparse_fixtures()
 
     secondary_collection_points = generate_sparse_fixtures(100)
 
     searcher = TestSimpleRecommendation()
 
-    local_client = init_local()
     init_client(
         local_client,
         fixture_points,
@@ -225,7 +224,6 @@ def test_simple_recommend() -> None:
         sparse_vectors_config=sparse_vectors_config,
     )
 
-    remote_client = init_remote()
     init_client(
         remote_client,
         fixture_points,
@@ -270,16 +268,13 @@ def test_simple_recommend() -> None:
             raise e
 
 
-def test_query_with_nan():
+def test_query_with_nan(local_client: QdrantBase, remote_client: QdrantBase) -> None:
     fixture_points = generate_sparse_fixtures()
     sparse_vector_dict = random_sparse_vectors({"sparse-image": sparse_image_vector_size})
     sparse_vector = sparse_vector_dict["sparse-image"]
     sparse_vector.values[0] = np.nan
     using = "sparse-image"
 
-    local_client = init_local()
-    remote_client = init_remote()
-
     init_client(
         local_client,
         fixture_points,