From c730078b2729b07b45e953ead9afe356fd92ef35 Mon Sep 17 00:00:00 2001 From: Francisco Javier Arceo Date: Fri, 10 Oct 2025 16:49:11 -0400 Subject: [PATCH] updated vector io tests Signed-off-by: Francisco Javier Arceo --- tests/integration/vector_io/test_vector_io.py | 85 ++++++++++--------- 1 file changed, 46 insertions(+), 39 deletions(-) diff --git a/tests/integration/vector_io/test_vector_io.py b/tests/integration/vector_io/test_vector_io.py index 7bfe31dd6..284a3bffb 100644 --- a/tests/integration/vector_io/test_vector_io.py +++ b/tests/integration/vector_io/test_vector_io.py @@ -34,9 +34,9 @@ def sample_chunks(): @pytest.fixture(scope="function") def client_with_empty_registry(client_with_models): def clear_registry(): - vector_dbs = [vector_db.identifier for vector_db in client_with_models.vector_dbs.list()] - for vector_db_id in vector_dbs: - client_with_models.vector_dbs.unregister(vector_db_id=vector_db_id) + vector_stores = client_with_models.vector_stores.list() + for vector_store in vector_stores.data: + client_with_models.vector_stores.delete(vector_store_id=vector_store.id) clear_registry() yield client_with_models @@ -48,47 +48,48 @@ def client_with_empty_registry(client_with_models): def test_vector_db_retrieve(client_with_empty_registry, embedding_model_id, embedding_dimension): vector_db_name = "test_vector_db" - register_response = client_with_empty_registry.vector_dbs.register( - vector_db_id=vector_db_name, - embedding_model=embedding_model_id, - embedding_dimension=embedding_dimension, + create_response = client_with_empty_registry.vector_stores.create( + name=vector_db_name, + extra_body={ + "embedding_model": embedding_model_id, + "embedding_dimension": embedding_dimension, + }, ) - actual_vector_db_id = register_response.identifier + actual_vector_db_id = create_response.id - # Retrieve the memory bank and validate its properties - response = client_with_empty_registry.vector_dbs.retrieve(vector_db_id=actual_vector_db_id) + # Retrieve the vector store and validate its properties + response = client_with_empty_registry.vector_stores.retrieve(vector_store_id=actual_vector_db_id) assert response is not None - assert response.identifier == actual_vector_db_id - assert response.embedding_model == embedding_model_id - assert response.identifier.startswith("vs_") + assert response.id == actual_vector_db_id + assert response.name == vector_db_name + assert response.id.startswith("vs_") def test_vector_db_register(client_with_empty_registry, embedding_model_id, embedding_dimension): vector_db_name = "test_vector_db" - response = client_with_empty_registry.vector_dbs.register( - vector_db_id=vector_db_name, - embedding_model=embedding_model_id, - embedding_dimension=embedding_dimension, + response = client_with_empty_registry.vector_stores.create( + name=vector_db_name, + extra_body={ + "embedding_model": embedding_model_id, + "embedding_dimension": embedding_dimension, + }, ) - actual_vector_db_id = response.identifier + actual_vector_db_id = response.id assert actual_vector_db_id.startswith("vs_") assert actual_vector_db_id != vector_db_name - vector_dbs_after_register = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()] - assert vector_dbs_after_register == [actual_vector_db_id] - vector_stores = client_with_empty_registry.vector_stores.list() assert len(vector_stores.data) == 1 vector_store = vector_stores.data[0] assert vector_store.id == actual_vector_db_id assert vector_store.name == vector_db_name - client_with_empty_registry.vector_dbs.unregister(vector_db_id=actual_vector_db_id) + client_with_empty_registry.vector_stores.delete(vector_store_id=actual_vector_db_id) - vector_dbs = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()] - assert len(vector_dbs) == 0 + vector_stores = client_with_empty_registry.vector_stores.list() + assert len(vector_stores.data) == 0 @pytest.mark.parametrize( @@ -103,13 +104,15 @@ def test_vector_db_register(client_with_empty_registry, embedding_model_id, embe ) def test_insert_chunks(client_with_empty_registry, embedding_model_id, embedding_dimension, sample_chunks, test_case): vector_db_name = "test_vector_db" - register_response = client_with_empty_registry.vector_dbs.register( - vector_db_id=vector_db_name, - embedding_model=embedding_model_id, - embedding_dimension=embedding_dimension, + create_response = client_with_empty_registry.vector_stores.create( + name=vector_db_name, + extra_body={ + "embedding_model": embedding_model_id, + "embedding_dimension": embedding_dimension, + }, ) - actual_vector_db_id = register_response.identifier + actual_vector_db_id = create_response.id client_with_empty_registry.vector_io.insert( vector_db_id=actual_vector_db_id, @@ -142,13 +145,15 @@ def test_insert_chunks_with_precomputed_embeddings(client_with_empty_registry, e "remote::qdrant": {"score_threshold": -1.0}, } vector_db_name = "test_precomputed_embeddings_db" - register_response = client_with_empty_registry.vector_dbs.register( - vector_db_id=vector_db_name, - embedding_model=embedding_model_id, - embedding_dimension=embedding_dimension, + register_response = client_with_empty_registry.vector_stores.create( + name=vector_db_name, + extra_body={ + "embedding_model": embedding_model_id, + "embedding_dimension": embedding_dimension, + }, ) - actual_vector_db_id = register_response.identifier + actual_vector_db_id = register_response.id chunks_with_embeddings = [ Chunk( @@ -189,13 +194,15 @@ def test_query_returns_valid_object_when_identical_to_embedding_in_vdb( "inline::qdrant": {"score_threshold": 0.0}, } vector_db_name = "test_precomputed_embeddings_db" - register_response = client_with_empty_registry.vector_dbs.register( - vector_db_id=vector_db_name, - embedding_model=embedding_model_id, - embedding_dimension=embedding_dimension, + register_response = client_with_empty_registry.vector_stores.create( + name=vector_db_name, + extra_body={ + "embedding_model": embedding_model_id, + "embedding_dimension": embedding_dimension, + }, ) - actual_vector_db_id = register_response.identifier + actual_vector_db_id = register_response.id chunks_with_embeddings = [ Chunk(