input: Write a python function to analyze the sentiment of a given text using NLTK's VADER sentiment analyzer.
  assert sentiment_analysis("I love this movie!") == 'positive'
  assert sentiment_analysis("I hate this movie!") == 'negative'
  assert sentiment_analysis("This movie is okay.") == 'neutral'
output: def sentiment_analysis(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon')
      
      sia = SentimentIntensityAnalyzer()
      score = sia.polarity_scores(text)
      
      if score['compound'] >= 0.05:
          return 'positive'
      elif score['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'