class_docstr: Reference: https://ai.google.dev/api/python/google/generativeai/GenerationConfig
  
  The class `GeminiConfig` provides configuration for the Gemini's API interface. Here are the parameters:
  
  - `candidate_count` (int): Number of generated responses to return.
  
  - `stop_sequences` (List[str]): The set of character sequences (up to 5) that will stop output generation. If specified, the API will stop at the first appearance of a stop sequence. The stop sequence will not be included as part of the response.
  
  - `max_output_tokens` (int): The maximum number of tokens to include in a candidate. If unset, this will default to output_token_limit specified in the model's specification.
  
  - `temperature` (float): Controls the randomness of the output. Note: The default value varies by model, see the Model.temperature attribute of the Model returned the genai.get_model function. Values can range from [0.0,1.0], inclusive. A value closer to 1.0 will produce responses that are more varied and creative, while a value closer to 0.0 will typically result in more straightforward responses from the model.
  
  - `top_p` (float): Optional. The maximum cumulative probability of tokens to consider when sampling.
  
  - `top_k` (int): Optional. The maximum number of tokens to consider when sampling.
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code: def __init__(
      self,
      candidate_count: Optional[int] = None,
      stop_sequences: Optional[list] = None,
      max_output_tokens: Optional[int] = None,
      temperature: Optional[float] = None,
      top_p: Optional[float] = None,
      top_k: Optional[int] = 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/gemini.py
imports: import os, types, traceback, copy
  import json
  from enum import Enum
  import time
  from typing import Callable, Optional
  from litellm.utils import ModelResponse, get_secret, Choices, Message, Usage
  import litellm
  import sys, httpx
  from .prompt_templates.factory import prompt_factory, custom_prompt
label_desc: Use image node_id 1 to create a new GeminiConfig object  with example: obj = GeminiConfig(candidate_count, stop_sequences, max_output_tokens, temperature, top_p, top_k)