mirror of
https://github.com/house-of-vanity/conf_bot.git
synced 2025-07-06 14:24:08 +00:00
88 lines
2.6 KiB
Python
88 lines
2.6 KiB
Python
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import random
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from collections import deque
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import re
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class Dictogram(dict):
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def __init__(self, iterable=None):
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super(Dictogram, self).__init__()
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self.types = 0
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self.tokens = 0
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if iterable:
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self.update(iterable)
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def update(self, iterable):
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for item in iterable:
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if item in self:
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self[item] += 1
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self.tokens += 1
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else:
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self[item] = 1
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self.types += 1
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self.tokens += 1
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def count(self, item):
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if item in self:
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return self[item]
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return 0
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def return_random_word(self):
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random_key = random.sample(self, 1)
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return random_key[0]
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def return_weighted_random_word(self):
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random_int = random.randint(0, self.tokens-1)
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index = 0
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list_of_keys = list(self.keys())
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for i in range(0, self.types):
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index += self[list_of_keys[i]]
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if(index > random_int):
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return list_of_keys[i]
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def get(text):
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def generate_random_start(model):
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if 'END' in model:
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seed_word = 'END'
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while seed_word == 'END':
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seed_word = model['END'].return_weighted_random_word()
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return seed_word
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return random.choice(list(model.keys()))
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def generate_random_sentence(length, markov_model):
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current_word = generate_random_start(markov_model)
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sentence = [current_word]
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for i in range(0, length):
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current_dictogram = markov_model[current_word]
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random_weighted_word = current_dictogram.return_weighted_random_word()
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current_word = random_weighted_word
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sentence.append(current_word)
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sentence[0] = sentence[0].capitalize()
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return ' '.join(sentence) + '.'
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return sentence
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def make_markov_model(data):
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markov_model = dict()
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for i in range(0, len(data)-1):
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if data[i] in markov_model:
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markov_model[data[i]].update([data[i+1]])
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else:
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markov_model[data[i]] = Dictogram([data[i+1]])
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return markov_model
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# simple cleanup
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text = text.replace('—','')
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text = text.replace('«','')
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text = text.replace('»','')
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text = text.replace('(','')
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text = text.replace(')','')
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text = "START " + text
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text = text.replace('.', ' END')
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text_list = text.split()
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model = make_markov_model(text_list)
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generated = generate_random_sentence(50, model)
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generated = generated.replace(' END', '.')
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print(generated)
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