old_contents: from prompt_toolkit import prompt
  from prompt_toolkit.history import FileHistory
  import logging
  import numpy as np
  
  
  def tagger_repl(tagger, **kwargs):
      mxlen = int(kwargs.get('mxlen', 100))
      zeropad = int(kwargs.get('zeropad', 0))
      prompt_name = kwargs.get('prompt', 'class> ')
      history_file = kwargs.get('history_file', '.history')
      history = FileHistory(history_file)
  
      while True:
          text = prompt(prompt_name, history=history)
          text = text.strip()
          if text == 'quit':
              break
          try:
              tokens = text.split(' ')
              best = tagger.predict_text(mxlen, tokens, zeropad)
              print(best)
          except Exception as e:
              logging.exception('Error')
  
  def classifier_repl(classifier, **kwargs):
  
      mxlen = int(kwargs.get('mxlen', 100))
      k = int(kwargs.get('k', 1))
      thresh = float(kwargs.get('thresh', 0.0))
      zeropad = int(kwargs.get('zeropad', 0))
      prompt_name = kwargs.get('prompt', 'class> ')
      history_file = kwargs.get('history_file', '.history')
      history = FileHistory(history_file)
  
      while True:
          text = prompt(prompt_name, history=history)
          text = text.strip()
          if text == 'quit':
              break
          try:
              tokens = text.split(' ')
              outcomes = classifier.classify_text(mxlen, tokens, zeropad)
              k = min(k, len(outcomes))
              probs = outcomes[:k]
              for prob_i in probs:
                  if prob_i[1] > thresh:
                      print('Guess [%s]: %.3f' % prob_i)
  
          except Exception as e:
              logging.exception('Error')
  
  
  
new_contents: from prompt_toolkit import prompt
  from prompt_toolkit.history import FileHistory
  import logging
  import numpy as np
  
  
  def tagger_repl(tagger, **kwargs):
      mxlen = int(kwargs.get('mxlen', 100))
      zeropad = int(kwargs.get('zeropad', 0))
      prompt_name = kwargs.get('prompt', 'class> ')
      history_file = kwargs.get('history_file', '.history')
      history = FileHistory(history_file)
  
      while True:
          text = prompt(prompt_name, history=history)
          text = text.strip()
          if text == 'quit':
              break
          try:
              tokens = text.split(' ')
              best = tagger.predict_text(mxlen, tokens, zeropad)
              print(best)
          except Exception as e:
              logging.exception('Error')
  
  def classifier_repl(classifier, **kwargs):
  
      mxlen = int(kwargs.get('mxlen', 100))
      k = int(kwargs.get('k', 1))
      thresh = float(kwargs.get('thresh', 0.0))
      zeropad = int(kwargs.get('zeropad', 0))
      prompt_name = kwargs.get('prompt', 'class> ')
      history_file = kwargs.get('history_file', '.history')
      history = FileHistory(history_file)
  
      while True:
          text = prompt(prompt_name, history=history)
          text = text.strip()
          if text == 'quit':
              break
          try:
              tokens = text.split(' ')
              outcomes = classifier.classify_text(tokens, mxlen=mxlen, zeropad=zeropad)
              k = min(k, len(outcomes))
              probs = outcomes[:k]
              for prob_i in probs:
                  if prob_i[1] > thresh:
                      print('Guess [%s]: %.3f' % prob_i)
  
          except Exception as e:
              logging.exception('Error')
  
  
  
subject: Update param order