input: 
  def classify_sentiment(review: str) -> str:
      """ Classifies the sentiment of a movie review using the VADER sentiment analysis tool.
      >>> classify_sentiment('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      >>> classify_sentiment('It was a fantastic movie with an amazing plot!')
      'The sentiment of the sentence is positive!'
      """
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
  
      sid = SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      return 'The sentiment of the sentence is negative!' if scores['neg'] > scores['pos'] else 'The sentiment of the sentence is positive!'
  
output:     from nltk.sentiment.vader import SentimentIntensityAnalyzer
  
      sid = SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      return 'The sentiment of the sentence is negative!' if scores['neg'] > scores['pos'] else 'The sentiment of the sentence is positive!'