def test_tensor_search_with_version_below_2_11_query_input_embedding(self):
        """
        If the unstructured index is version 2.10 or below, the query will have query input:
        embedding_query instead of marqo__query_embedding
        """

        mock_vespa_client_query = mock.MagicMock()
        mock_vespa_client_query.return_value = QueryResult(
            **{'root': {
                'id': 'toplevel',
                'relevance': 1.0,
                'fields': {'totalCount': 2},
                'coverage': {'coverage': 100, 'documents': 2, 'full': True, 'nodes': 1, 'results': 1, 'resultsFull': 1},
                'children': [{'id': 'index:content_default/0/c81e728d5f3b597225351eac',
                              'relevance': 0.39966427718009545,
                              'source': 'content_default',
                              'fields': {
                                  'matchfeatures': {'closest(marqo__embeddings)': {'type': 'tensor<float>(p{})',
                                                                                   'cells': {'1': 1.0}}},
                                  'sddocname': 'aa4f36de0c4f4433a8c31e4143b28029b',
                                  'marqo__id': '2',
                                  'marqo__strings': ['defgh', 'on the mat'],
                                  'marqo__chunks': ['abc::defgh', 'this_cat_sat::on the mat'],
                                  'marqo__short_string_fields': {'abc': 'defgh', 'this_cat_sat': 'on the mat'}}}]
            }}
        )

        @mock.patch("marqo.vespa.vespa_client.VespaClient.query", mock_vespa_client_query)
        def run():
            res = tensor_search.search(
                config=self.config,
                index_name=self.index_with_version_2_10,
                text="dogs",
                search_method="TENSOR",
            )
            return res

        res = run()

        call_args = mock_vespa_client_query.call_args_list
        self.assertEqual(len(call_args), 1)

        vespa_query_kwargs = call_args[0][1]
        self.assertIn("nearestNeighbor(marqo__embeddings, embedding_query)",
                      vespa_query_kwargs["yql"])
        self.assertIn("embedding_query", vespa_query_kwargs["query_features"])
        self.assertNotIn("marqo__query_embedding", vespa_query_kwargs["query_features"])

        If the unstructured index is version 2.10 or below, the query will have query input:
        embedding_query instead of marqo__query_embedding
        
tests/integ_tests/tensor_search/integ_tests/test_search_unstructured.py