class_docstr: Custom Handler for integrating vLLM
class_docstr_tok: ["Custom","Handler","for","integrating","vLLM"]
docstr: Post Process Function returns the text response from the vLLM output.
  Args:
      inference_output (list): It contains the response of vLLM
  Returns:
      (list): Returns a list of the Predictions and Explanations.
docstr_tok: ["Post","Process","Function","returns","the","text","response","from","the","vLLM","output",".","Args",":","inference_output","(","list",")",":","It","contains","the","response","of","vLLM","Returns",":","(","list",")",":","Returns","a","list","of","the","Predictions","and","Explanations","."]
code: def postprocess(self, inference_output):
      """Post Process Function returns the text response from the vLLM output.
      Args:
          inference_output (list): It contains the response of vLLM
      Returns:
          (list): Returns a list of the Predictions and Explanations.
      """
  
      return [
          inf_output.outputs[0].text for inf_output in inference_output
      ]
  
file_path: serve/examples/large_models/vllm/mistral/custom_handler.py
imports: import logging
  import torch
  import vllm
  from vllm import LLM, SamplingParams
  from ts.context import Context
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 5 for calling the CustomHandler obj's underlying member method code with example usage: obj.postprocess(inference_output) and returns: unknown