class_docstr: Base class for QA
class_docstr_tok: ["Base","class","for","QA"]
code: def _clean_answer(self, answer):
      import string
  
      if not answer:
          return answer
      remove_list = [
          "is ",
          "are ",
          "was ",
          "were ",
          "of ",
          "include ",
          "including ",
          "in ",
          "of ",
          "the ",
          "for ",
          "on ",
          "to ",
          "-",
          ":",
          "/",
          "and ",
      ]
      for w in remove_list:
          if answer.startswith(w):
              answer = answer.replace(w, "", 1)
      answer = answer.replace(" . ", ".")
      answer = answer.replace(" / ", "/")
      answer = answer.replace(" :// ", "://")
      answer = answer.strip()
      if answer and answer[0] in string.punctuation:
          answer = answer[1:]
      if answer and answer[-1] in string.punctuation:
          answer = answer[:-1]
      return answer
  
imports: from transformers import AutoModelForQuestionAnswering, AutoTokenizer, TFAutoModelForQuestionAnswering
  from whoosh import index, qparser
  from whoosh.fields import *
  from whoosh.qparser import QueryParser
  from ...None import utils
  from ...imports import *
  from ...torch_base import TorchBase
  from ..None import preprocessor
  from ..None import textutils
  from itertools import chain, zip_longest
label_desc: Use image node_id 4 for calling the ExtractiveQABase obj's underlying member method code with example usage: obj._clean_answer(answer) and returns: answer, answer