code: def test_client_query_embeddings(gateway):
      gateway_client = MlflowGatewayClient(gateway_uri=gateway.url)
      routes = gateway_client.search_routes()
      expected_output = {
          "object": "list",
          "data": [
              {
                  "object": "embedding",
                  "embedding": [
                      0.1,
                      0.2,
                      0.3,
                  ],
                  "index": 0,
              },
              {
                  "object": "embedding",
                  "embedding": [
                      0.4,
                      0.5,
                      0.6,
                  ],
                  "index": 1,
              },
          ],
          "model": "text-embedding-ada-002",
          "usage": {"prompt_tokens": 8, "total_tokens": 8},
      }
      data = {"text": ["Jenny", "What's her number?"]}
  
      mock_response = mock.Mock()
      mock_response.json.return_value = expected_output
  
      with mock.patch.object(
          gateway_client, "_call_endpoint", return_value=mock_response
      ):
          response = gateway_client.query(
              route=routes[2].name, data=data
          )
          assert response == expected_output
  
imports: from unittest import mock
  import pytest
  from requests.exceptions import HTTPError, Timeout
  import mlflow.gateway.utils
  from mlflow.environment_variables import MLFLOW_GATEWAY_URI
  from mlflow.exceptions import InvalidUrlException, MlflowException
  from mlflow.gateway import MlflowGatewayClient, set_gateway_uri
  from mlflow.gateway.config import Route
  from mlflow.gateway.constants import MLFLOW_GATEWAY_SEARCH_ROUTES_PAGE_SIZE
  from mlflow.gateway.utils import resolve_route_url
  from tests.gateway.tools import Gateway, save_yaml
label_desc: Use image node_id 22 for calling a global function with example usage: test_client_query_embeddings(gateway) without return types