@@ -897,26 +897,26 @@ def test_retrieve_online_documents(environment, fake_document_data):
897897 ).to_dict ()
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899899
900- @pytest .mark .integration
901- @pytest .mark .universal_online_stores (only = ["milvus" ])
902- def test_retrieve_online_milvus_documents (environment , fake_document_data ):
903- fs = environment .feature_store
904- df , data_source = fake_document_data
905- item_embeddings_feature_view = create_item_embeddings_feature_view (data_source )
906- fs .apply ([item_embeddings_feature_view , item ()])
907- fs .write_to_online_store ("item_embeddings" , df )
908- documents = fs .retrieve_online_documents (
909- feature = None ,
910- features = [
911- "item_embeddings:embedding_float" ,
912- "item_embeddings:item_id" ,
913- "item_embeddings:string_feature" ,
914- ],
915- query = [1.0 , 2.0 ],
916- top_k = 2 ,
917- distance_metric = "L2" ,
918- ).to_dict ()
919- assert len (documents ["embedding_float" ]) == 2
920-
921- assert len (documents ["item_id" ]) == 2
922- assert documents ["item_id" ] == [2 , 3 ]
900+ # @pytest.mark.integration
901+ # @pytest.mark.universal_online_stores(only=["milvus"])
902+ # def test_retrieve_online_milvus_documents(environment, fake_document_data):
903+ # fs = environment.feature_store
904+ # df, data_source = fake_document_data
905+ # item_embeddings_feature_view = create_item_embeddings_feature_view(data_source)
906+ # fs.apply([item_embeddings_feature_view, item()])
907+ # fs.write_to_online_store("item_embeddings", df)
908+ # documents = fs.retrieve_online_documents(
909+ # feature=None,
910+ # features=[
911+ # "item_embeddings:embedding_float",
912+ # "item_embeddings:item_id",
913+ # "item_embeddings:string_feature",
914+ # ],
915+ # query=[1.0, 2.0],
916+ # top_k=2,
917+ # distance_metric="L2",
918+ # ).to_dict()
919+ # assert len(documents["embedding_float"]) == 2
920+ #
921+ # assert len(documents["item_id"]) == 2
922+ # assert documents["item_id"] == [2, 3]
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