def test_hybrid_search_with_custom_vector_query(self):
        """
        Custom Vectory q should work similar to None q with a context vector
        """
        for index_name in [self.text_index_name, self.unstructured_text_index_name]:
            with self.subTest(index=index_name):
                self.client.index(index_name).add_documents(
                    self.docs_list,
                    tensor_fields=["text_field_1", "text_field_2", "text_field_3"] \
                    if "unstructured" in index_name else None
                )
                sample_vector = [0.5 for _ in range(384)]

                res_custom_vector = self.client.index(index_name).search(
                    q={"customVector": {"content": None, "vector": sample_vector}},
                    search_method="HYBRID",
                    hybrid_parameters={
                        "retrievalMethod": "tensor",
                        "rankingMethod": "tensor"
                    }
                )

                res_context = self.client.index(index_name).search(
                    q=None,
                    search_method="TENSOR",
                    context={"tensor": [{"vector": sample_vector, "weight": 1}]}
                )
                self.assertEqual(len(res_custom_vector["hits"]), len(res_context["hits"]))
                for i in range(len(res_custom_vector["hits"])):
                    self.assertEqual(res_custom_vector["hits"][i]["_id"], res_context["hits"][i]["_id"])

        Custom Vectory q should work similar to None q with a context vector
        
tests/api_tests/v1/tests/api_tests/structured_index/test_hybrid_search.py