input: def classify_sentiment(review: str) -> str:
      """Classify the sentiment of a given movie review using VADER sentiment analysis.
      >>> classify_sentiment('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      >>> classify_sentiment('The movie was amazing. I loved every minute of it!')
      'The sentiment of the sentence is positive!'
      """
      import nltk
      from nltk.sentiment import vader
  
      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:     if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      elif scores['pos'] > scores['neg']:
          return 'The sentiment of the sentence is positive!'
      else:
          return 'The sentiment of the sentence is neutral!'