input: Write a python function to determine the sentiment of a given text using NLTK's VADER sentiment analysis.
  assert determine_sentiment("I am so excited about this project") == 'pos'
  assert determine_sentiment("I am very sad and disappointed") == 'neg'
  assert determine_sentiment("It is an average day") == 'neu'
  assert determine_sentiment("I don't have any strong feelings about this") == 'neu'
output: def determine_sentiment(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      from nltk import download
      download('vader_lexicon')
      
      sia = SentimentIntensityAnalyzer()
      sentiment_scores = sia.polarity_scores(text)
      
      if sentiment_scores['compound'] >= 0.05:
          return 'pos'
      elif sentiment_scores['compound'] <= -0.05:
          return 'neg'
      else:
          return 'neu'