def main(self):
start = time.time()
self.parse_and_count()
save_counts_wordcloud.save_counts_wordcloud(self.unigram_count, self.bigram_count, self.trigram_count)
print("parse, count, wordcloud time:", time.time() - start)
del self.unigram_count
del self.bigram_count
del self.trigram_count
start = time.time()
generate_sentence.generate_sentence(self.data)
print("Generate sentence time:", time.time() - start)
def findMain(text, chat):
word_pos = nltk.pos_tag(nltk.word_tokenize(text))
mainWord = ''
mainPOS = ''
POS_Order = []
for i in range(0, len(word_pos)):
if 'NN' in word_pos[i][1]:
mainWord = word_pos[i][0]
mainPOS = word_pos[i][1]
#send_message('Main word is ' + mainWord, chat)
#send_message('Main POS is ' + mainPOS, chat)
break
for i in range(0, len(word_pos) - 1):
POS_Order.append((word_pos[i][1], word_pos[i + 1][1]))
valu = find_pos.best_pos(POS_Order)
PoS_seq = transitions.transition(valu)
print(PoS_seq)
sentence = generate_sentence(PoS_seq)
print("sentence = generate_sentence(PoS_seq)")
print("F**K YEA")
#send_message(str(POS_Order), chat)
#send_message(valu, chat)
send_message(sentence, chat)
return mainWord, mainPOS, POS_Order
def just_get_it_working():
if request.method == 'OPTIONS':
resp = app.make_default_options_response()
resp.headers['Access-Control-Allow-Origin'] = '*'
resp.headers['Access-Control-Allow-Headers'] = 'Content-Type'
return resp
results = []
for object in request.json:
results.append({"text": generate_sentence(object)})
#resp = jsonify(results)
resp = make_response(dumps(results))
resp.headers['Access-Control-Allow-Origin'] = '*'
resp.headers['Access-Control-Allow-Headers'] = 'Content-Type'
return resp
def main(argv=sys.argv[1:]):
parser = argparse.ArgumentParser()
parser.add_argument('--target',
type=argparse.FileType('r'),
default=sys.stdin)
parser.add_argument('--ngwords', default='NG_WORDS.txt')
parser.add_argument('--endwords', default='END_WORDS.txt')
parser.add_argument('--conf',
default='~/.config/mastodon/mstdn.jp.sub/user.txt')
parser.add_argument('--interval', type=int, default=60)
opts = parser.parse_args(argv)
with open(os.path.expanduser(opts.conf)) as fp:
token = fp.read().strip()
load_ng_words(opts.ngwords)
load_end_words(opts.endwords)
model = load_model(opts.target)
while not time.sleep(opts.interval):
try:
sentence = generate_sentence(model)
if sentence:
res = requests.post('https://mstdn.jp/api/v1/statuses/',
headers={
'Content-Type': 'application/json',
'Authorization': f'Bearer {token}',
},
json={
'status': sentence,
'in_reply_to_id': None,
'media_ids': None,
'sensitive': None,
'spoiler_text': None,
'visibility': 'unlisted',
})
print(res, sentence)
except SentenceGenerationError:
pass
# Основная программа from loadpairs import loadpairs from get_q_templs import get_q_templs from gram_filter import gram_filter from ngram import train from json import dumps from pymystem3 import Mystem from generate_sentence import generate_sentence ma = Mystem() pairs = loadpairs(filename = 'data.json') q_templs = get_q_templs( znanie = pairs, kolvo = 5, form = "Правда ли что %s %s %s?") model = train(corpus = 'voprosi') questions = gram_filter(q_templs,model) #print(questions) kutokens = [] for question in questions: kutokens = [] for a in ma.analyze(question): try: _ = a['analysis'][0]['lex'] kutokens += [_] except (KeyError, IndexError): pass #print(kutokens) print(generate_sentence(model,kutokens))
def index():
return generate_sentence.generate_sentence(model, retries=100)
def render_page():
sentence = generate_sentence()
return render_template('index.html', sentence=sentence)