input: Write a python function to perform sentiment analysis on a given text using NLTK's VADER SentimentIntensityAnalyzer.
  assert sentiment_analysis("I love this product!") == 'positive'
  assert sentiment_analysis("This is the worst experience ever.") == 'negative'
  assert sentiment_analysis("It's okay, nothing special.") == 'neutral'
output: def sentiment_analysis(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      sid = SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(text)
      if scores['compound'] >= 0.05:
          return 'positive'
      elif scores['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'