input: 
  from nltk.sentiment import SentimentIntensityAnalyzer
  
  def classify_sentiment(review: str) -> str:
      """ Classify the sentiment of a movie review using Natural Language Processing.
      The function uses the VADER sentiment analyzer from NLTK to determine if the sentiment
      is positive or negative.
      >>> classify_sentiment('The movie was terrible. It felt like it would never end!')
      'negative'
      >>> classify_sentiment('This was an amazing film with incredible visuals.')
      'positive'
      """
      sid = SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
      
      return 'positive' if scores['pos'] > scores['neg'] else 'negative'
  
output:     sid = SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
      
      return 'positive' if scores['pos'] > scores['neg'] else 'negative'