input: Write a python function to analyze the sentiment in a given text using NLP techniques and a pre-trained sentiment classifier.
  assert analyze_sentiment("I love sunny days!") == "positive"
  assert analyze_sentiment("This is the worst movie I have ever seen.") == "negative"
  assert analyze_sentiment("The book was quite average, not too bad but not great either.") == "neutral"
output: def analyze_sentiment(text):
      from transformers import pipeline
  
      # Load a pre-trained sentiment-analysis pipeline
      sentiment_pipeline = pipeline('sentiment-analysis')
  
      # Analyze the sentiment of the text
      result = sentiment_pipeline(text)
  
      # Extract the sentiment label
      sentiment = result[0]['label'].lower()
  
      if sentiment == 'negative':
          return 'negative'
      elif sentiment == 'positive':
          return 'positive'
      else:
          return 'neutral'