input: Write a function to classify the sentiment of a movie review using Natural Language Processing. If the negative sentiment is greater than the positive sentiment, return 'The sentiment of the sentence is negative!'. Otherwise, return 'The sentiment of the sentence is positive!'. You need to use NLTK and the VADER sentiment analysis tool.
  
  import nltk
  from nltk.sentiment import vader
  nltk.download('vader_lexicon')
  
  def analyze_sentiment(review):
      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!'
  
  assert analyze_sentiment('The movie was terrible. It felt like it would never end!')=='The sentiment of the sentence is negative!'
  assert analyze_sentiment('The movie was amazing. I loved every second of it!')=='The sentiment of the sentence is positive!'
  assert analyze_sentiment('')=='The sentiment of the sentence is positive!'
output: def analyze_sentiment(review):
      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!'