class_docstr: The output data of one completion output of a request.
  
  Args:
      index: The index of the output in the request.
      text: The generated output text.
      token_ids: The token IDs of the generated output text.
      cumulative_logprob: The cumulative log probability of the generated
          output text.
      logprobs: The log probabilities of the top probability words at each
          position if the logprobs are requested.
      finish_reason: The reason why the sequence is finished.
code: def __init__(
      self,
      index: int,
      text: str,
      token_ids: List[int],
      cumulative_logprob: float,
      logprobs: Optional[List[Dict[int, float]]],
      finish_reason: Optional[str] = None,
      output_token_latency: Optional[List[float]] = None,
  ) -> None:
      # bigdl-llm change start
      # summary: add token-recording arguments
      self.index = index
      self.text = text
      self.token_ids = token_ids
      self.cumulative_logprob = cumulative_logprob
      self.logprobs = logprobs
      self.finish_reason = finish_reason
      self.output_token_latency = output_token_latency
  
file_path: BigDL/python/llm/src/bigdl/llm/vllm/outputs.py
imports: from typing import Dict, List, Optional
  from bigdl.llm.vllm.sequence import SequenceGroup, SequenceStatus
label_desc: Use image node_id 1 to create a new CompletionOutput object  with example: obj = CompletionOutput(index, text, token_ids, cumulative_logprob, logprobs, finish_reason, output_token_latency)