code: def test_promptflow_model_serve_predict():
      # Assert predict with promptflow model
      logged_model = log_promptflow_example_model()
      # Assert predict with serve model
      input_value = "Python Hello World!"
      response = pyfunc_serve_and_score_model(
          logged_model.model_uri,
          data=json.dumps({"inputs": {"text": input_value}}),
          content_type=CONTENT_TYPE_JSON,
          extra_args=["--env-manager", "local"],
      )
      expected_result = f"Write a simple {input_value} program that displays the greeting message when executed.\n"
      assert PredictionsResponse.from_json(
          response.content.decode("utf-8")
      ) == {"predictions": {"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 7 for calling a global function with example usage: test_promptflow_model_serve_predict() without return types