class_docstr: The output data of a request to the LLM.
  
  Args:
      request_id: The unique ID of the request.
      prompt: The prompt string of the request.
      prompt_token_ids: The token IDs of the prompt.
      outputs: The output sequences of the request.
class_docstr_tok: ["The","output","data","of","a","request","to","the","LLM",".","Args",":","request_id",":","The","unique","ID","of","the","request",".","prompt",":","The","prompt","string","of","the","request",".","prompt_token_ids",":","The","token","IDs","of","the","prompt",".","outputs",":","The","output","sequences","of","the","request","."]
code: def __init__(
      self,
      request_id: str,
      prompt: str,
      prompt_token_ids: List[int],
      outputs,
  ) -> None:
      self.request_id = request_id
      self.prompt = prompt
      self.prompt_token_ids = prompt_token_ids
      self.outputs = outputs
  
imports: from typing import Dict, List, Tuple
  from .sampling_params import SamplingParams
label_desc: Use image node_id 1 to create a new RequestOutput object  with example: obj = RequestOutput(request_id, prompt, prompt_token_ids, outputs)