code: def test_promptflow_log_and_load_model():
      model = get_promptflow_example_model()
      with mlflow.start_run():
          logged_model = mlflow.promptflow.log_model(
              model,
              "promptflow_model",
              input_example={"text": "Python Hello World!"},
          )
  
      loaded_model = mlflow.promptflow.load_model(
          logged_model.model_uri
      )
  
      assert "promptflow" in logged_model.flavors
      assert logged_model.signature is not None
      assert str(logged_model.signature.inputs) == "['text': string]"
      assert str(logged_model.signature.outputs) == "['output': string]"
      assert isinstance(loaded_model, Flow)
  
file_path: mlflow/tests/promptflow/test_promptflow_model_export.py
imports: import json
  from pathlib import Path
  import pytest
  from promptflow import load_flow
  from promptflow._sdk.entities._flow import Flow
  from pyspark.sql import SparkSession
  import mlflow
  from mlflow import MlflowException
  from mlflow.deployments import PredictionsResponse
  from mlflow.pyfunc.scoring_server import CONTENT_TYPE_JSON
  from tests.helper_functions import pyfunc_serve_and_score_model
label_desc: Use image node_id 3 for calling a global function with example usage: test_promptflow_log_and_load_model() without return types