code: def test_log_model_with_config():
      model = get_promptflow_example_model()
      model_config = {"connection.provider": "local"}
      with mlflow.start_run():
          logged_model = mlflow.promptflow.log_model(
              model, "promptflow_model", model_config=model_config
          )
  
      assert mlflow.pyfunc.FLAVOR_NAME in logged_model.flavors
      assert (
          mlflow.pyfunc.MODEL_CONFIG
          in logged_model.flavors[mlflow.pyfunc.FLAVOR_NAME]
      )
      logged_model_config = logged_model.flavors[
          mlflow.pyfunc.FLAVOR_NAME
      ][mlflow.pyfunc.MODEL_CONFIG]
      assert logged_model_config == model_config
  
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 4 for calling a global function with example usage: test_log_model_with_config() without return types