def test_search_with_custom_vector_field(self):
        """
        Tensor search for the doc, with highlights
        """
        for index in self.indexes:
            with self.subTest(f"Index: {index.name}, type: {index.type}"):
                self.add_documents(
                    config=self.config, add_docs_params=AddDocsParams(
                        index_name=index.name,
                        docs=[
                            {
                                "_id": "custom_vector_doc",
                                "my_custom_vector": {
                                    "content": "custom content is here!!",
                                    "vector": self.random_vector_1  # size is 512
                                }
                            },
                            {
                                "_id": "empty_content_custom_vector_doc",
                                "my_custom_vector": {
                                    "vector": self.random_vector_2  # size is 512
                                }
                            },
                            {
                                "_id": "normal_doc",
                                "text_field": "blah"
                            }
                        ],
                        device="cpu",
                        mappings=self.mappings if isinstance(index, UnstructuredMarqoIndex) else None,
                        tensor_fields=["my_custom_vector", "text_field"] if isinstance(index, UnstructuredMarqoIndex) else None
                    )
                )

                # Searching with context matching custom vector returns custom vector
                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"] == "custom_vector_doc"
                assert res["hits"][0]["_score"] == 1.0
                assert res["hits"][0]["_highlights"][0]["my_custom_vector"] == "custom content is here!!"

                # Tensor search should work even if content is empty (highlight is empty string)
                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_2, "weight": 1}], })
                )
                assert res["hits"][0]["_id"] == "empty_content_custom_vector_doc"
                assert res["hits"][0]["_score"] == 1.0
                assert res["hits"][0]["_highlights"][0]["my_custom_vector"] == ""

                # Searching with normal text returns text
                res = tensor_search.search(
                    config=self.config, index_name=index.name, text="blah",
                    search_method=enums.SearchMethod.TENSOR
                )
                assert res["hits"][0]["_id"] == "normal_doc"

        Tensor search for the doc, with highlights
        
tests/integ_tests/tensor_search/integ_tests/test_custom_vector_field.py