input: import nltk
  from nltk.sentiment import vader
  
  def sentiment_classifier(review: str) -> str:
      """ Given a movie review, this function uses NLTK, specifically the VADER
      sentiment analysis tool, to classify the sentiment of the review. The
      function returns a string indicating whether the sentiment is positive or
      negative.
      >>> sentiment_classifier('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      >>> sentiment_classifier('I loved the movie! The acting was excellent.')
      'The sentiment of the sentence is positive!'
      """
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'
output:     sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'