def doge_response(sentence, word_POS_freqs, transition_probs):
sen_list = makelist(sentence)
c = return_max(collapse, sentence, word_POS_freqs, transition_probs)
# for e in c: print(e)
important = set(["nn", "nn$", "nnS", "nns$", "np", "np$", "nps", "nps$", "nr"])
others = set(["jj", "jjr", "jjs", "jjt"])
stockphrases = [" Such ", " Very ", " Many ", " Wow ", " OMG ", " how to "]
say = []
for i in range(len(c)):
# print (i in important)
if c[i] in others:
say.append(sen_list[i])
# print("checking")
if c[i] in important:
for j in wikiscraping(sen_list[i]):
say.append(j)
# print("checking")
def pickrand(list):
return list[random.randint(0, len(list))]
return c
def generate(n, stock, say):
response = ""
for i in range(n):
response += stock[random.randint(0, len(stock) - 1)] + say[random.randint(0, len(say) - 1)] + "."
response += " Amaze!"
return response
if len(say) == 0:
return "Wow, Amaze! Many brilliant"
else:
return generate(min(3, len(say)), stockphrases, say)
def collapse (sentence, word_POS_freqs, transition_probs):
sen_list = makelist(sentence)
print (sen_list)
POS_combinations = list(iterate(sentence, word_POS_freqs, POS_basefreqs))
numbers = [(calc_transition_prob(POS_combo, transition_probs)
* calc_base_prob(sen_list, POS_combo, word_POS_freqs))
for POS_combo in POS_combinations]
for i in range(min(len(list(POS_combinations)) -1, 100)): print(numbers[i])
return dict(zip(POS_combinations, numbers))
def iterate(sentence, dictionary, partset):
return itertoolsproduct(*(dictionary.get(word, partset).keys() for word in makelist(sentence)))
def greedy (sentence, word_POS_freqs, transition_probs, all_POS):
POS_basefreqs = init_normalize(all_POS)
sen_list = makelist(sentence)
POS_combinations = iterate(sentence, word_POS_freqs, POS_basefreqs)
return dict(zip(POS_combinations, [calc_base_prob(sen_list, POS_combo, word_POS_freqs)
for POS_combo in POS_combinations]))
