class_docstr: Reference: https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/providers?model=meta.llama2-13b-chat-v1
  
  Supported Params for the Amazon / Meta Llama models:
  
  - `max_gen_len` (integer) max tokens,
  - `temperature` (float) temperature for model,
  - `top_p` (float) top p for model
class_docstr_tok: ["Reference",":","https",":","\/\/us-west-2.console.aws.amazon.com\/bedrock\/home","?","region=us-west-2","#","\/providers","?","model=meta.llama2-13b-chat-v1","Supported","Params","for","the","Amazon","\/","Meta","Llama","models",":","-","`","max_gen_len","`","(","integer",")","max","tokens",",","-","`","temperature","`","(","float",")","temperature","for","model",",","-","`","top_p","`","(","float",")","top","p","for","model"]
code: def __init__(
      self,
      maxTokenCount: Optional[int] = None,
      temperature: Optional[float] = None,
      topP: 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)
  
imports: import json, copy, types
  import os
  from enum import Enum
  import time
  from typing import Callable, Optional, Any, Union
  import litellm
  from litellm.utils import ModelResponse, get_secret, Usage
  from .prompt_templates.factory import prompt_factory, custom_prompt
  import httpx
label_desc: Use image node_id 1 to create a new AmazonLlamaConfig object  with example: obj = AmazonLlamaConfig(maxTokenCount, temperature, topP)