code: def test_promptflow_model_predict_pyfunc():
      logged_model = log_promptflow_example_model()
      loaded_model = mlflow.pyfunc.load_model(logged_model.model_uri)
      # Assert pyfunc model
      assert "promptflow" in logged_model.flavors
      assert type(loaded_model) == mlflow.pyfunc.PyFuncModel
      # Assert predict with pyfunc model
      input_value = "Python Hello World!"
      result = loaded_model.predict({"text": input_value})
      expected_result = f"Write a simple {input_value} program that displays the greeting message when executed.\n"
      assert result == {"output": expected_result}
  
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 6 for calling a global function with example usage: test_promptflow_model_predict_pyfunc() without return types