input: from typing import List, Dict
  
  def analyze_sentiment(text: str) -> str:
      """The function should analyze the sentiment of a given text and categorize it into
      one of three possible sentiments: 'positive', 'negative', or 'neutral'. It tokenizes
      the text into sentences, then analyzes the sentiment of each sentence. The overall
      sentiment is determined based on which sentiment is predominant among the sentences.
      
      >>> analyze_sentiment("I love this product! It's amazing!")
      'positive'
      
      >>> analyze_sentiment("I hate Mondays. They are always so gloomy.")
      'negative'
      
      >>> analyze_sentiment("Today is neither good nor bad.")
      'neutral'
      """
output:     sentiment_scores = {
          'positive': 0,
          'negative': 0,
          'neutral': 0
      }
      
      sentences = text.split('. ')
      
      for sentence in sentences:
          if 'love' in sentence or 'amazing' in sentence or 'good' in sentence:
              sentiment_scores['positive'] += 1
          elif 'hate' in sentence or 'gloomy' in sentence or 'bad' in sentence:
              sentiment_scores['negative'] += 1
          else:
              sentiment_scores['neutral'] += 1
      
      if sentiment_scores['positive'] > sentiment_scores['negative'] and sentiment_scores['positive'] > sentiment_scores['neutral']:
          return 'positive'
      elif sentiment_scores['negative'] > sentiment_scores['positive'] and sentiment_scores['negative'] > sentiment_scores['neutral']:
          return 'negative'
      else:
          return 'neutral'