docstr: Retrieves standard info about a model, e.g. data types. 
docstr_tok: ["Retrieves","standard","info","about","a","model",",","e.g",".","data","types","."]
code: def get_columns(self, table_name: str) -> Response:
      """Retrieves standard info about a model, e.g. data types."""  # noqa
      predictor_record = get_model_record(
          name=table_name, ml_handler_name=self.name
      )
      if predictor_record is None:
          return Response(
              RESPONSE_TYPE.ERROR,
              error_message=f"Error: model '{table_name}' does not exist!",
          )
  
      data = []
      if predictor_record.dtype_dict is not None:
          for key, value in predictor_record.dtype_dict.items():
              data.append((key, value))
      result = Response(
          RESPONSE_TYPE.TABLE,
          pd.DataFrame(data, columns=["COLUMN_NAME", "DATA_TYPE"]),
      )
      return result
  
imports: import socket
  import datetime
  from typing import Optional
  import pandas
  from sqlalchemy import func, null
  from sqlalchemy.sql.functions import coalesce
  from mindsdb_sql import parse_sql
  from mindsdb.utilities.config import Config
  import mindsdb.interfaces.storage.db
  from mindsdb.integrations.libs.response import HandlerResponse, RESPONSE_TYPE
  from mindsdb.__about__ import __version__
  from mindsdb.utilities.hooks import after_predict
  from mindsdb.interfaces.model.model_controller import ModelController
  from mindsdb.interfaces.model.functions import get_model_record
  from mindsdb.integrations.libs.const import PREDICTOR_STATUS
  from mindsdb.interfaces.database.database import DatabaseController
  from mindsdb.interfaces.storage.model_fs import ModelStorage, HandlerStorage
  from mindsdb.utilities.context import context
  from mindsdb.interfaces.model.functions import get_model_records
  from mindsdb.utilities.functions import mark_process
  import mindsdb.utilities.profiler
  from mindsdb.utilities.ml_task_queue.producer import MLTaskProducer
  from mindsdb.utilities.ml_task_queue.const import ML_TASK_TYPE
  from mindsdb.integrations.libs.process_cache import process_cache, empty_callback
label_desc: Use image node_id 4 for calling the BaseMLEngineExec obj's underlying member method code with example usage: obj.get_columns(table_name) and returns: result, Response