code: def get_value(
      self, dataset, value, type_annotation, mode
  ) -> Tuple[String, Any]:
      if dataset is None:
          return String(tuple()), value
  
      try:
          columns = list(dataset["dataframe"].columns)
      except KeyError:
          columns = []
  
      if (isinstance(self.add_none, bool) and self.add_none) or (
          callable(self.add_none) and self.add_none(mode)
      ):
          columns.insert(0, "None")
  
      if isinstance(value, str):
          value = [value]
      if value is None:
          value = [columns[0]]
  
      value = DatasetValue._compute_current_values(
          value, columns, self.prefer_with
      )
  
      return (
          String(tuple(columns)),
          value if type_annotation == Tuple[str, ...] else value[0],
      )
  
imports: import os
  from abc import abstractmethod
  from dataclasses import dataclass
  from typing import Any, Callable, List, Optional, Sequence, Set, Tuple, Union
  from llm_studio.src.nesting import Dependency
label_desc: Use image node_id 1 for calling the Columns obj's underlying member method code with example usage: obj.get_value(dataset, value, type_annotation, mode) and returns: String,  unknown, String,  value