def test_search_with_custom_vector_field_score_modifiers(self):
        """
        Search for the doc, with score modifiers
        """
        # custom vector cannot be used as score modifier, as it cannot be numeric.
        # Using another field as score modifier on a custom vector:
        for index in self.indexes:
            with self.subTest(f"Index: {index.name}, type: {index.type}"):
                add_docs_res = self.add_documents(
                    config=self.config, add_docs_params=AddDocsParams(
                        index_name=index.name,
                        docs=[
                            {
                                "_id": "doc0",
                                "my_custom_vector": {
                                    "content": "vec 1",
                                    "vector": self.random_vector_1  # size is 512
                                },
                                "multiply": 0.001  # Should make score tiny
                            },
                            {
                                "_id": "doc1",
                                "my_custom_vector": {
                                    "content": "vec 2",
                                    "vector": self.random_vector_2  # size is 512
                                },
                                "multiply": 1000.  # Should make score huge
                            },
                        ],
                        device="cpu",
                        mappings=self.mappings if isinstance(index, UnstructuredMarqoIndex) else None,
                        tensor_fields=["my_custom_vector"] if isinstance(index, UnstructuredMarqoIndex) else None
                    )
                )

                # Normal search should favor doc0
                res = tensor_search.search(
                    config=self.config, index_name=index.name, text={"dummy text": 0},
                    search_method=enums.SearchMethod.TENSOR,
                    context=SearchContext(**{"tensor": [{"vector": self.random_vector_1, "weight": 1}], })
                )
                assert res["hits"][0]["_id"] == "doc0"

                # Search with score modifiers multiply should favor doc1
                res = tensor_search.search(
                    config=self.config, index_name=index.name, text={"dummy text": 0},
                    search_method=enums.SearchMethod.TENSOR,
                    context=SearchContext(**{"tensor": [{"vector": self.random_vector_1, "weight": 1}], }),
                    score_modifiers=ScoreModifierLists(**{"multiply_score_by":
                                                         [{"field_name": "multiply",
                                                           "weight": 1}
                                                          ]
                                                          })
                )
                assert res["hits"][0]["_id"] == "doc1"

        Search for the doc, with score modifiers
        
tests/integ_tests/tensor_search/integ_tests/test_custom_vector_field.py