def replace_with_context(self, sessionid_in):
self._deal_last_question(sessionid_in)
# todo 添加分类
user_cur = usermanager.get_user(sessionid_in)
# todo 添加当前槽位切换
domain_classification = self._domain_classification_class.classify(user_cur['str_synonym'])
mylog.info('domain_classification:\t\t{}'.format(domain_classification))
usermanager.update(sessionid_in, domain_classification=domain_classification)
# usermanager.get_user(sessionid_in).update_slots(index=-1,sentence_pattern_classification=sentence_pattern_classification_from_kg)
# self._usermanager_class.update(sessionid_in,{'str_raw':str_in,'str_synonym':str_synonym,
# 'domain_classification':domain_classification,'str_synonym_cut':str_synonym_cut})
words_list_out, dst_word_to_fufill, label2entities_cur_dict = self.replace_with_context_only_question(
sessionid_in)
# print('words_list_out, dst_word_to_fufill, label2entities_cur_dict==>',words_list_out, dst_word_to_fufill, label2entities_cur_dict)
flag_inter, abbrev_str, abbrev2std_list = self._fuzzy_interaction_class.deal_fuzzy_interaction(sessionid_in,
label2entities_cur_dict,
user_cur[
'str_raw'],
words_list_out)
usermanager.get_user(sessionid_in).insert_slots(
**{'question': user_cur['str_synonym'], 'slots_question': label2entities_cur_dict,
'domain_classification': user_cur['domain_classification'],
'sentence_pattern_classification': user_cur['sentence_pattern_classification']})
rds.set(user_cur['jdpin_id'] + _flag_recomm_sent_pattern, 0)
return words_list_out, dst_word_to_fufill, label2entities_cur_dict, flag_inter, abbrev_str, abbrev2std_list
def _response(self, input):
_data_return = copy.deepcopy(self._data_return)
bool_input, _msg = self._check(input)
if bool_input:
_data_return['status'] = 1
# str_synonym, words = self._preprocess_class.process(input.question)
user_cur = self._usermanager.create(input.jdpin, input.session)
# user_cur.update({'str_synonym':str_synonym,'str_synonym_cut':str_synonym})
usermanager.update(input.session, str_raw=input.question)
_data_return['data'] = self._rewrite(sessionid_in=input.session)
_data_return['data']['str_synonym'] = user_cur['str_synonym']
else:
_data_return['status'] = 0
_data_return['msg'] = _msg
return _data_return
def replace_with_context_only_question(self, sessionid_in):
"""
根据历史对话，从历史对话提取实体，根据当前str中是否存在指代词，决定 实体是补充还是替换
args:
str_in: 输入字符串
words_list_in：输入字符串分词结果
jdpin_in： id
return：
words_list_out: 补全后的分词列表
dst_word_out： 从历史对话记录提取的slots
label2entities_cur_dict： 当前用户话提取的slots，准备存入列表的slots
"""
user_cur = self._usermanager_class.get_user(sessionid_in)
sentence_classification = self._classification_sentence_pattern(sessionid_in,user_cur['str_raw'])
mylog.info('sentence_classification:\t\t{}\tstr_raw\t{}'.format(sentence_classification, user_cur['str_raw']))
self._usermanager_class.update(sessionid_in, sentence_pattern_classification=sentence_classification)
src_prounoun_word, dst_word_to_fufill = self._get_prounoun_and_dst_words(sessionid_in)
label2entities_cur_dict, words_timestap = self._prounoun_class.get_entity_from_strs([user_cur['str_synonym']],
user_cur[
'domain_classification'])
words_list_out = self.replace_words_list(user_cur['str_synonym_cut'], src_prounoun_word, dst_word_to_fufill)
usermanager.update(sessionid_in,**{'dst_word_to_fufill':dst_word_to_fufill,'label2entities_cur_dict':label2entities_cur_dict})
return words_list_out, dst_word_to_fufill, label2entities_cur_dict
s = '旅行险投保年龄意外险是什么两全险'
# s='境外旅行能选择这款保险计划吗'
# s='公司几点上班'
s = '安行万里租的车保吗'
s = '我要去境外旅行'
s = '我想买个两全险'
s = '安行万里境外险的保单信息'
s='86岁能投保安行万里吗'
words = jieba.lcut(s)
jdpin = str(12345678)
session = 'session' + jdpin
pd = PronounDeal()
ner = NerDeal()
usermanager.create(jdpin, session)
usermanager.update(session, str_raw=s)
out = ner.replace_with_context(session)
print(out)
"""
'domain_classification':None,
'str_raw':None,
'str_synonym':None,
'str_raw_cut':None,
'str_synonym_cut':None,
'slots_history':{},
'slots_cur':{},
'sentence_pattern_classification':None,
'session_id':None,
'jdpin_id':None,
'login_time':None,