ngram_textgen.py

# code courtesy of https://nlpforhackers.io/language-models/

import random

# starting words
text = ["today", "the"]
sentence_finished = False
 
while not sentence_finished:
  # select a random probability threshold  
  r = random.random()
  accumulator = .0

  for word in model[tuple(text[-2:])].keys():
      accumulator += model[tuple(text[-2:])][word]
      # select words that are above the probability threshold
      if accumulator >= r:
          text.append(word)
          break

  if text[-2:] == [None, None]:
      sentence_finished = True
 
print (' '.join([t for t in text if t]))