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.
      finished: Whether the whole request is finished.
code: def from_seq_group(cls, seq_group: SequenceGroup) -> "RequestOutput":
      # Get the top-n sequences.
      n = seq_group.sampling_params.n
      seqs = seq_group.get_seqs()
      if seq_group.sampling_params.use_beam_search:
          sorting_key = lambda seq: seq.get_beam_search_score(
              seq_group.sampling_params.length_penalty
          )
      else:
          sorting_key = lambda seq: seq.get_cumulative_logprob()
      sorted_seqs = sorted(seqs, key=sorting_key, reverse=True)
      top_n_seqs = sorted_seqs[:n]
  
      # Create the outputs.
      outputs: List[CompletionOutput] = []
      for seq in top_n_seqs:
          logprobs = seq.output_logprobs
          if seq_group.sampling_params.logprobs is None:
              # NOTE: We need to take care of this case because the sequence
              # always has the logprobs of the sampled tokens even if the
              # logprobs are not requested.
              logprobs = {}
          finshed_reason = SequenceStatus.get_finished_reason(
              seq.status
          )
          output = CompletionOutput(
              seqs.index(seq),
              seq.output_text,
              seq.get_output_token_ids(),
              seq.get_cumulative_logprob(),
              logprobs,
              finshed_reason,
              seq.get_output_token_latency(),
          )
          outputs.append(output)
  
      # Every sequence in the sequence group should have the same prompt.
      prompt = top_n_seqs[0].prompt
      prompt_token_ids = top_n_seqs[0].data.prompt_token_ids
      finished = seq_group.is_finished()
      return cls(
          seq_group.request_id,
          prompt,
          prompt_token_ids,
          outputs,
          finished,
      )
  
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 2 for calling the RequestOutput obj's underlying member method code with example usage: obj.from_seq_group(cls, seq_group) and returns: cls