input: Write a python function to analyze sentiment of a given text using NLTK's VADER sentiment analyzer.
  assert analyze_sentiment("I love this product! It's absolutely amazing.") == "Positive sentiment!"
  assert analyze_sentiment("This is the worst experience I've ever had.") == "Negative sentiment!"
  assert analyze_sentiment("It's okay, not great, but not terrible either.") == "Negative sentiment!"
output: def analyze_sentiment(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      from nltk import download
      
      download('vader_lexicon')
      
      sia = SentimentIntensityAnalyzer()
      score = sia.polarity_scores(text)
      
      if score['compound'] >= 0.05:
          return "Positive sentiment!"
      elif score['compound'] <= -0.05:
          return "Negative sentiment!"
      else:
          return "Neutral sentiment!"