code: def test_get_endpoint():
      client = get_deploy_client("http://localhost:5000")
      mock_resp = mock.Mock()
      mock_resp.json.return_value = {
          "model": {"name": "gpt-4", "provider": "openai"},
          "name": "completions",
          "endpoint_type": "llm/v1/completions",
          "endpoint_url": "http://localhost:5000/endpoints/chat/invocations",
      }
      mock_resp.status_code = 200
      with mock.patch(
          "requests.Session.request", return_value=mock_resp
      ) as mock_request:
          resp = client.get_endpoint(endpoint="test")
          mock_request.assert_called_once()
          assert resp.dict() == {
              "name": "completions",
              "endpoint_type": "llm/v1/completions",
              "model": {"name": "gpt-4", "provider": "openai"},
              "endpoint_url": "http://localhost:5000/endpoints/chat/invocations",
          }
          ((_, url), _) = mock_request.call_args
          assert url == "http://localhost:5000/api/2.0/endpoints/test"
  
file_path: mlflow/tests/deployments/mlflow/test_mlflow.py
imports: from unittest import mock
  import pytest
  from mlflow.deployments import get_deploy_client
  from mlflow.deployments.mlflow import MlflowDeploymentClient
label_desc: Use image node_id 5 for calling a global function with example usage: test_get_endpoint() without return types