def build_tweet(mention, grade):
print grade
seeds = []
mentions = []
mentions1 = []
for m in api.morphs(api.sentences(r['text'])['sentences'][0])['morphs']:
mentions1.append(to_chainform(m).split(':')[0])
r_now = ' '.join(mentions1)[4:-4]
SV = w2v_dialog.sentence_vectorizer('matrix25.w7.model')
w2v_list = SV.use_database('NTCIR.wakati.u20', r_now.encode('utf-8'))
seeds.append(''.join(w2v_list[0].split()))
seeds.append(''.join(w2v_list[1].split()))
seeds.append(''.join(w2v_list[2].split()))
#print r['text']
print "w2v_list", '\n'.join(w2v_list)
#api.send_reply(name, r['mention_id'], r['user_name'], ''.join(w2v_list[0].split()))
for sent in api.sentences(mention)['sentences']:
for m in api.morphs(sent)['morphs']:
mentions.append(to_chainform(m))
if m['pos'][-2] == u'名' and m['pos'] != u'代名詞' :
#print m
seeds.append(m)
#print seeds
texts = []
for _ in range(0, 5):
if not seeds: seeds = [{ u'norm_surface': u'BOS', u'pos': u'BOS' }]
for s in seeds:
pass
#print s[u'norm_surface']
#c = api.markov_chain(s)
#texts.append(to_string(api.rewrite(c, grade)))
print " ".join(mentions)
trigger_result = api.trigger(mentions, grade)
texts += trigger_result
texts += trigger_result
texts += trigger_result
print '\n'.join(trigger_result)
for s in seeds:
pass
#print api.search_tweet(s[u'norm_surface'])
#for t in api.search_tweet(s[u'norm_surface'])[u'texts']:
# for sent in api.sentences(t)['sentences']:
# texts.append(to_string(api.rewrite([to_chainform(m) for m in api.morphs(sent)['morphs']], grade)))
# #print to_string(api.rewrite([to_chainform(m) for m in api.morphs(sent)['morphs']]))
#for t in api.search_reply(s[u'norm_surface'])[u'texts']:
# for sent in api.sentences(t)['sentences']:
# texts.append(to_string(api.rewrite([to_chainform(m) for m in api.morphs(sent)['morphs']], grade)))
#print to_string(api.rewrite([to_chainform(m) for m in api.morphs(sent)['morphs']]))
texts = seeds
random.shuffle(texts)
print texts[0]
return texts[0]
#!/usr/bin/python
# coding:utf-8
from api import API
import w2v_dialog
import MeCab
from crontab import CronTab
with API() as api:
# ツイートする
# api.tweet('tweet test2')
SV = w2v_dialog.sentence_vectorizer('/work/asakura/bot/matrix50.model')
# リプを取得
for mention in api.get_mentions():
text = mention['text']
tweet_id = mention['id_str']
screen_name = mention['user']['screen_name']
# ユーザ情報(プロフィール)
name = mention['user']['name']
zone = mention['user']['time_zone']
location = mention['user']['location']
description = mention['user']['description']
print mention
#print text, tweet_id, screen_name, name, zone, location, description
tagger = MeCab.Tagger('-Owakati')
#result = tagger.parse(' '.join(text.split()[1:]).decode('utf-8'))
result = tagger.parse(' '.join(text.split()[1:]).encode('utf-8'))