def test_custom_vector_doc(self):
        """
        Tests the custom_vector field type.
        Ensures the following features work on this field:
        1. lexical search
        2. filter string search
        3. tensor search
        4. get document
        """

        DEFAULT_DIMENSIONS = 384

        add_docs_res = self.client.index(index_name=self.text_index_name).add_documents(
            documents=[
                {
                    "custom_vector_field_1": {
                        "content": "custom vector text",
                        "vector": [1.0 for _ in range(DEFAULT_DIMENSIONS)],
                    },
                    "content": "normal text",
                    "_id": "doc1",
                },
                {
                    "content": "second doc",
                    "_id": "doc2"
                }
            ])

        # lexical search test
        lexical_res = self.client.index(self.text_index_name).search(
            "custom vector text", search_method="lexical")
        assert lexical_res["hits"][0]["_id"] == "doc1"

        # filter string test
        filtering_res = self.client.index(self.text_index_name).search(
            "", filter_string="custom_vector_field_1:(custom vector text)")
        assert filtering_res["hits"][0]["_id"] == "doc1"

        # tensor search test
        tensor_res = self.client.index(self.text_index_name).search(q={"dummy text": 0}, context={
            "tensor": [{"vector": [1.0 for _ in range(DEFAULT_DIMENSIONS)], "weight": 1}]})
        assert tensor_res["hits"][0]["_id"] == "doc1"

        # get document test
        doc_res = self.client.index(self.text_index_name).get_document(
            document_id="doc1",
            expose_facets=True
        )
        assert doc_res["custom_vector_field_1"] == "custom vector text"
        assert doc_res['_tensor_facets'][0]["custom_vector_field_1"] == "custom vector text"
        assert doc_res['_tensor_facets'][0]['_embedding'] == [1.0 for _ in range(DEFAULT_DIMENSIONS)]

        Tests the custom_vector field type.
        Ensures the following features work on this field:
        1. lexical search
        2. filter string search
        3. tensor search
        4. get document
        
tests/api_tests/v1/tests/api_tests/structured_index/test_add_documents.py