input: Write a function to generate a Markov chain given a text input. The function should split the text into words, create a Markov chain dictionary where each word maps to a dictionary of subsequent words and their occurrence counts, and then generate a 100-word text based on this chain. If there are fewer than 100 words available in the Markov chain, the function should generate as many words as possible. If the input text is empty, the function should return an empty string.
  
  def generateMarkov(text):
    words = text.split(' ')
    markovChain = {}
  
    for i in range(len(words) - 2):
      current = words[i]
      next = words[i + 1]
      if current in markovChain:
        if next in markovChain[current]:
          markovChain[current][next] += 1
        else:
          markovChain[current][next] = 1
      else:
        markovChain[current] = {next: 1}
  
    generatedText = ""
    current = random.choice(list(markovChain))
    generatedText += current
  
    for i in range(100):
      choices = markovChain[current]
      choices = [
        key for key, value in choices.items()
        for i in range(value)
      ]
      try:
        current = random.choice(choices)
        generatedText += " " + current
      except:
        break
  
    return generatedText
  
  assert generateMarkov('Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, `and what is the use of a book,' thought Alice `without pictures or conversation?') != ''
  assert generateMarkov('') == ''
  assert len(generateMarkov('A B A C A')) < 100
output: import random
  
  def generateMarkov(text):
      words = text.split(' ')
      markovChain = {}
  
      for i in range(len(words) - 1):
          current = words[i]
          next = words[i + 1]
          if current in markovChain:
              if next in markovChain[current]:
                  markovChain[current][next] += 1
              else:
                  markovChain[current][next] = 1
          else:
              markovChain[current] = {next: 1}
  
      if not markovChain:
          return ""
  
      generatedText = ""
      current = random.choice(list(markovChain))
      generatedText += current
  
      for i in range(99):
          if current not in markovChain:
              break
          choices = markovChain[current]
          choices = [
              key for key, value in choices.items()
              for i in range(value)
          ]
          current = random.choice(choices)
          generatedText += " " + current
  
      return generatedText