code: def t_create_predictor(self, client_con, mock_executor):
      res = client_con.myproj.predictors.insert_one(
          {
              "name": "house_sales_model5",
              "predict": "ma",
              "connection": "mongo",
              "select_data_query": "db.house_sales.find({})",
              "training_options": {
                  "timeseries_settings": {
                      "order_by": "saledate",
                      "group_by": ["bedrooms", "type"],
                      "horizon": 4,
                      "window": 4,
                  },
                  "encoders.location.module": "CategoricalAutoEncoder",
              },
          }
      )
      ast = mock_executor.call_args[0][0]
  
      expected_sql = """
             CREATE PREDICTOR myproj.house_sales_model5 
             FROM mongo (
                  db.house_sales.find({})
             ) 
             PREDICT ma 
             ORDER BY saledate 
             GROUP BY bedrooms, type 
             WINDOW 4 
             HORIZON 4 
             USING encoders.location.module="CategoricalAutoEncoder"
          """
      assert (
          parse_sql(expected_sql, "mindsdb").to_string()
          == ast.to_string()
      )
  
imports: import datetime
  import json
  import threading
  import inspect
  from unittest.mock import patch
  import tempfile
  import os
  from pymongo import MongoClient
  from mindsdb_sql import parse_sql
  from mindsdb.api.executor.data_types.answer import ExecuteAnswer, ANSWER_TYPE
  from mindsdb.api.executor import Column
  from .executor_test_base import BaseUnitTest
label_desc: Use image node_id 6 for calling the TestMongoDBServer obj's underlying member method code with example usage: obj.t_create_predictor(client_con, mock_executor) without return types