code: def __init__(self, *args, **kwargs):
      require_dependencies("openai>=0.27.10")
      super().__init__(*args, **kwargs)
  
      if self._record_class is TokenClassificationRecord:
          raise NotImplementedError(
              "OpenAI does not support `TokenClassification` tasks."
          )
      elif (
          self._record_class is TextClassificationRecord
          and self._multi_label
      ):
          raise NotImplementedError(
              "OpenAI does not support `multi-label=True` TextClassification tasks."
          )
      else:
          pass
  
      self.sleep_timer = 10
      self.device = None
      self.finetune_id = None
  
      if self._seed is not None:
          self._logger.warning(
              "Seed is not supported for OpenAI. Ignoring seed for training."
          )
  
      if self._model is None:
          self._model = "gpt-3.5-turbo"
          self._logger.warning(
              f"No model defined. Using the default model {self._model}."
          )
  
      if any([self._model in model for model in OPENAI_LEGACY_MODELS]):
          self._logger.warning(
              "Using the OpenAI legacy mnodels within the Trainer, please use a newer model and take a look here https://platform.openai.com/docs/guides/legacy-fine-tuning.append()"
          )
          self.__legacy = True
      else:
          self.__legacy = False
  
      if isinstance(self._dataset, tuple):
          self._train_dataset = self._dataset[0]
          self._eval_dataset = self._dataset[1]
      else:
          self._train_dataset = self._dataset
          self._eval_dataset = None
  
      if not self.__legacy:
          self._train_dataset = self._convert_data_to_new_format(
              self._train_dataset
          )
          if self._eval_dataset is not None:
              self._eval_dataset = self._convert_data_to_new_format(
                  self._eval_dataset
              )
  
      self.init_training_args(model=self._model)
  
imports: import logging
  import os
  import time
  from typing import List, Optional, Union
  import numpy
  from argilla._constants import OPENAI_END_TOKEN, OPENAI_LEGACY_MODELS, OPENAI_SEPARATOR, OPENAI_WHITESPACE
  from argilla.client.models import TextClassificationRecord, TokenClassificationRecord
  from argilla.datasets import TextClassificationSettings, TokenClassificationSettings
  from argilla.training.base import ArgillaTrainerSkeleton
  from argilla.training.utils import filter_allowed_args
  from argilla.utils.dependency import require_dependencies
label_desc: Use image node_id 1 to create a new ArgillaOpenAITrainer object from inherited base classes: ArgillaTrainerSkeleton with example: obj = ArgillaOpenAITrainer()