code: def test_chat_single_variable(tmp_path):
      mlflow.openai.save_model(
          model="gpt-3.5-turbo",
          task=openai.ChatCompletion,
          path=tmp_path,
          messages=[{"role": "user", "content": "{x}"}],
      )
  
      model = mlflow.pyfunc.load_model(tmp_path)
      data = pd.DataFrame(
          {
              "x": [
                  "a",
                  "b",
              ]
          }
      )
      expected_output = [
          [{"content": "a", "role": "user"}],
          [{"content": "b", "role": "user"}],
      ]
      assert (
          list(map(json.loads, model.predict(data))) == expected_output
      )
  
      data = [
          {"x": "a"},
          {"x": "b"},
      ]
      assert (
          list(map(json.loads, model.predict(data))) == expected_output
      )
  
      data = [
          "a",
          "b",
      ]
      assert (
          list(map(json.loads, model.predict(data))) == expected_output
      )
  
imports: import importlib
  import json
  from copy import deepcopy
  from unittest import mock
  import numpy
  import openai
  import openai.error
  import pandas
  import pytest
  import yaml
  from pyspark.sql import SparkSession
  import mlflow
  import mlflow.pyfunc.scoring_server
  from mlflow.exceptions import MlflowException
  from mlflow.models.signature import ModelSignature
  from mlflow.types.schema import ColSpec, ParamSchema, ParamSpec, Schema, TensorSpec
  from mlflow.utils.openai_utils import _exclude_params_from_envs, _mock_chat_completion_response, _mock_models_retrieve_response, _mock_request
  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_chat_single_variable(tmp_path) without return types