Adding property to private_service_connect_ip_address to endpoint VectorSearchVectorStore

libs/vertexai/langchain_google_vertexai/vectorstores/vectorstores.py

@@ -268,6 +268,7 @@ def from_components(  # Implemented in order to keep the current API
         gcs_bucket_name: str,
         index_id: str,
         endpoint_id: str,
+        private_service_connect_ip_address: Optional[str] = None,
         credentials_path: Optional[str] = None,
         embedding: Optional[Embeddings] = None,
         stream_update: bool = False,
@@ -282,6 +283,8 @@ def from_components(  # Implemented in order to keep the current API
             order for the index to be created.
             index_id: The id of the created index.
             endpoint_id: The id of the created endpoint.
+            private_service_connect_ip_address: The IP address of the private
+            service connect instance.
             credentials_path: (Optional) The path of the Google credentials on
             the local file system.
             embedding: The :class:`Embeddings` that will be used for
@@ -301,6 +304,11 @@ def from_components(  # Implemented in order to keep the current API
         index = sdk_manager.get_index(index_id=index_id)
         endpoint = sdk_manager.get_endpoint(endpoint_id=endpoint_id)
 
+        if private_service_connect_ip_address:
+            endpoint.private_service_connect_ip_address = (
+                private_service_connect_ip_address
+            )
+
         return cls(
             document_storage=GCSDocumentStorage(bucket=bucket),
             searcher=VectorSearchSearcher(

libs/vertexai/tests/integration_tests/test_vectorstores.py

@@ -80,6 +80,25 @@ def vector_store() -> VectorSearchVectorStore:
     return vector_store
 
 
+@pytest.fixture
+def vector_store_private() -> VectorSearchVectorStore:
+    embeddings = VertexAIEmbeddings(model_name="textembedding-gecko-default")
+
+    vector_store_private = VectorSearchVectorStore.from_components(
+        project_id=os.environ["PROJECT_ID"],
+        region=os.environ["REGION"],
+        gcs_bucket_name=os.environ["GCS_BUCKET_NAME"],
+        index_id=os.environ["INDEX_ID"],
+        endpoint_id=os.environ["ENDPOINT_ID"],
+        private_service_connect_ip_address=os.environ[
+            "PRIVATE_SERVICE_CONNECT_IP_ADDRESS"
+        ],
+        embedding=embeddings,
+    )
+
+    return vector_store_private
+
+
 @pytest.fixture
 def datastore_vector_store() -> VectorSearchVectorStoreDatastore:
     embeddings = VertexAIEmbeddings(model_name="textembedding-gecko-default")