input: 
  def classify_movie_sentiment(review: str) -> str:
      """ Classify the sentiment of a given movie review using Natural Language Processing.
      Uses the VADER sentiment analysis tool from NLTK. The function returns a string indicating 
      whether the sentiment is positive or negative based on the highest sentiment score.
      
      >>> classify_movie_sentiment('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      >>> classify_movie_sentiment('This movie was absolutely fantastic! Highly recommended.')
      'The sentiment of the sentence is positive!'
      """
      import nltk
      from nltk.sentiment import SentimentIntensityAnalyzer
  
      sid = 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:     import nltk
      from nltk.sentiment import SentimentIntensityAnalyzer
  
      sid = 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!'