class_docstr: The class `MaritTalkConfig` provides configuration for the MaritTalk's API interface. Here are the parameters:
  
  - `max_tokens` (integer): Maximum number of tokens the model will generate as part of the response. Default is 1.
  
  - `model` (string): The model used for conversation. Default is 'maritalk'.
  
  - `do_sample` (boolean): If set to True, the API will generate a response using sampling. Default is True.
  
  - `temperature` (number): A non-negative float controlling the randomness in generation. Lower temperatures result in less random generations. Default is 0.7.
  
  - `top_p` (number): Selection threshold for token inclusion based on cumulative probability. Default is 0.95.
  
  - `repetition_penalty` (number): Penalty for repetition in the generated conversation. Default is 1.
  
  - `stopping_tokens` (list of string): List of tokens where the conversation can be stopped/stopped.
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code: def __init__(
      self,
      max_tokens: Optional[int] = None,
      model: Optional[str] = None,
      do_sample: Optional[bool] = None,
      temperature: Optional[float] = None,
      top_p: Optional[float] = None,
      repetition_penalty: Optional[float] = None,
      stopping_tokens: Optional[List[str]] = None,
  ) -> None:
      locals_ = locals()
      for key, value in locals_.items():
          if key != "self" and value is not None:
              setattr(self.__class__, key, value)
  
file_path: litellm/litellm/llms/maritalk.py
imports: import os, types
  import json
  from enum import Enum
  import requests
  import time, traceback
  from typing import Callable, Optional, List
  from litellm.utils import ModelResponse, Choices, Message, Usage
  import litellm
label_desc: Use image node_id 1 to create a new MaritTalkConfig object  with example: obj = MaritTalkConfig(max_tokens, model, do_sample, temperature, top_p, repetition_penalty, stopping_tokens)