input: Write a python function to analyze the sentiment of a given text using NLTK's VADER sentiment analyzer.
  assert analyze_sentiment("I love programming") == "Positive sentiment"
  assert analyze_sentiment("It's an average day") == "Neutral sentiment"
  assert analyze_sentiment("I hate bugs in my code") == "Negative sentiment"
output: def analyze_sentiment(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon', quiet=True)
      
      sia = SentimentIntensityAnalyzer()
      sentiment_score = sia.polarity_scores(text)['compound']
      
      if sentiment_score >= 0.05:
          return "Positive sentiment"
      elif sentiment_score <= -0.05:
          return "Negative sentiment"
      else:
          return "Neutral sentiment"