input: Write a python function to determine the sentiment of a given text using NLTK's VADER sentiment analysis tool.
  assert analyze_sentiment("This movie was truly amazing") == "Positive"
  assert analyze_sentiment("I hated every moment of it") == "Negative"
  assert analyze_sentiment("It was an okay experience") == "Neutral"
output: def analyze_sentiment(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon', quiet=True)
      
      sia = SentimentIntensityAnalyzer()
      scores = sia.polarity_scores(text)
      
      if scores['compound'] >= 0.05:
          return "Positive"
      elif scores['compound'] <= -0.05:
          return "Negative"
      else:
          return "Neutral"