code: def test_choose_model():
      # With this data and settings, AutoTheta should win
      model_args = {
          "horizon": 1,
          "frequency": "M",
          "model_name": "auto",
      }
      sample_df = AirPassengersDF.iloc[:100]
      results_df = get_insample_cv_results(model_args, sample_df)
      best_model = choose_model(model_args, results_df)
      assert best_model.__class__.__name__ == "AutoTheta"
  
imports: import time
  from unittest.mock import patch
  import numpy
  import pandas
  import pytest
  from statsforecast.models import AutoCES
  from statsforecast.utils import AirPassengersDF
  from statsforecast import StatsForecast
  from mindsdb.integrations.utilities.time_series_utils import get_best_model_from_results_df
  from mindsdb.integrations.handlers.statsforecast_handler.statsforecast_handler import choose_model, model_dict, get_insample_cv_results
  from mindsdb_sql import parse_sql
  from tests.unit.ml_handlers.test_time_series_utils import create_mock_df
  from tests.unit.executor_test_base import BaseExecutorTest
label_desc: Use image node_id 1 for calling a global function with example usage: test_choose_model() without return types