def question_answer_hub(cls, question_str):
"""
问答主总控，基于aiml构建问题匹配器
:param question_str:问句输入
:return:
"""
if cls.user == None:
cls.user = User()
cls.user.set_age(20)
cls.user.set_sex('女')
question_str = cls.nlp_util.clear_question(question_str)
question_str = cls.clear_util.filter(question_str)
if '*' in question_str:
return ['很抱歉，请您注意文明用语']
aiml_response = ''
aiml_response_normal = ''
aiml_response_specify = ''
question_first,question_replaced_normal,question_replaced_spcify,entity_dict = cls.nlp_util.repalce_question(question_str)
#print(question_first,question_replaced_normal,question_replaced_spcify)
#print(question_first)
aiml_response = cls.aiml_util.response(question_first,cls.intent.get_intent())
#print(question_first,question_replaced_normal,question_replaced_spcify,entity_dict,aiml_response)
if 'task_' in aiml_response:
cls.intent.set_intent(aiml_response)
graph_response = Bot.task_response(aiml_response, entity_dict,question_str,cls.user.age,cls.user.sex)
elif aiml_response != '':
cls.intent.set_intent(aiml_response)
graph_response = [aiml_response]
else:
aiml_response_normal = cls.aiml_util.response(question_replaced_normal,cls.intent.get_intent())
if 'task_' in aiml_response_normal:
cls.intent.set_intent(aiml_response_normal)
graph_response = Bot.task_response(aiml_response_normal, entity_dict,question_str,cls.user.age,cls.user.sex)
elif aiml_response_normal != '':
cls.intent.set_intent(aiml_response_normal)
graph_response = [aiml_response_normal]
else:
aiml_response_specify = cls.aiml_util.response(question_replaced_spcify,cls.intent.get_intent())
if 'task_' in aiml_response_specify:
cls.intent.set_intent(aiml_response_specify)
graph_response = Bot.task_response(aiml_response_specify, entity_dict,question_str,cls.user.age,cls.user.sex)
elif aiml_response_specify != '':
cls.intent.set_intent(aiml_response_specify)
graph_response = [aiml_response_specify]
else:
#print(question_str)
response = dict(cls.search_bot.answer_question(question_str)[0])
#print(response)
if float(response['score']) > 0.7:
cls.intent.set_intent(response['answer'])
graph_response = [response['answer']]
else:
words, pattern, arcs_dict, postags, hed_index = NLPUtil.get_sentence_pattern(question_str)
#print(words, pattern, arcs_dict, postags, hed_index)
aiml_reponse = AIMLUtil.pedia_response(pattern)
answer = TaskManager.task_response(aiml_reponse, words, arcs_dict, postags, hed_index)
if answer != None:
cls.intent.reset_intent('pedia')
return [answer]
else:
cls.intent.reset_intent('chat')
#print("cls.chat.get_response(question_str)",cls.chat.get_response(question_str))
graph_response = [cls.chat.get_response(question_str)]
dialog_dict = {'intent':cls.intent.get_intent(),'question':question_str,'answer':graph_response[0]}
#print(aiml_response,aiml_response_normal,aiml_response_specify)
return graph_response
def question_answer_hub_master(self, question_str):
"""
问答主总控，基于aiml构建问题匹配器
:param question_str:问句输入
:return:
"""
question_str = self.nlp_util.clear_question(question_str)
aiml_response = ''
aiml_response_normal = ''
aiml_response_specify = ''
question_first, question_replaced_normal, question_replaced_spcify, entity_dict = self.nlp_util.repalce_question(
question_str)
aiml_response = self.aiml_util.response(question_first, self.type)
print(question_first, question_replaced_normal,
question_replaced_spcify, entity_dict, aiml_response)
if 'task_' in aiml_response:
graph_response = Bot.task_response(aiml_response, entity_dict,
question_str, self.age,
self.sex)
#print("graph_response",graph_response)
elif aiml_response != '':
graph_response = [aiml_response]
else:
aiml_response_normal = self.aiml_util.response(
question_replaced_normal, self.type)
#print("aiml_response_normal",aiml_response_normal, question_replaced_normal)
if 'task_' in aiml_response_normal:
graph_response = Bot.task_response(aiml_response_normal,
entity_dict, question_str,
self.age, self.sex)
elif aiml_response_normal != '':
graph_response = [aiml_response_normal]
else:
aiml_response_specify = self.aiml_util.response(
question_replaced_spcify, self.type)
if 'task_' in aiml_response_specify:
graph_response = Bot.task_response(aiml_response_specify,
entity_dict,
question_str, self.age,
self.sex)
elif aiml_response_specify != '':
graph_response = [aiml_response_specify]
else:
response = dict(
self.search_bot.answer_question(question_str)[0])
#print(response['answer'], response['score'], question_str, "===")
#print(response['score'], response['question'])
if float(response['score']) > 0.7:
graph_response = [response['answer']]
else:
words, pattern, arcs_dict, postags, hed_index = NLPUtil.get_sentence_pattern(
question_str)
print(words, pattern, arcs_dict, postags, hed_index)
aiml_reponse = AIMLUtil.response(pattern, self.type)
print(aiml_reponse)
answer = TaskManager.task_response(
aiml_reponse, words, arcs_dict, postags, hed_index)
if answer != None:
return [answer]
else:
graph_response = [
self.chat.get_response(question_str)
]
"""
import requests, json
github_url = "http://openapi.tuling123.com/openapi/api/v2"
data = json.dumps({
"reqType": 0,
"perception": {
"inputText": {
"text": question_str
},
},
"userInfo": {
"apiKey": "62f1c8991a6d499c8b22e497de6cdd11",
"userId": "219315"
}
})
r = requests.post(github_url, data)
print(r.json())
res_msg = r.json()['results'][0]['values']['text']
return [res_msg]
"""
'''
由于服务类同时具有共性与特性，所以生产两个模版，即一份模版将服务实体替换为service进行模版匹配，一类模版
不讲服务实体替换为service直接用原词汇匹配模版
'''
"""
question_first, question_replaced, question_replaced2, entity_dict = self.nlp_util.repalce_question(
question_str)
aiml_response = self.aiml_util.response(question_replaced)
print(aiml_response, question_replaced)
if 'task_' in aiml_response:
graph_response = Bot.task_response(aiml_response, entity_dict)
elif aiml_response!='':
graph_response=[aiml_response]
else:
aiml_response2 = self.aiml_util.response(question_replaced2)
print(aiml_response2,question_replaced2)
if 'task_' in aiml_response2:
graph_response = Bot.task_response(aiml_response2, entity_dict)
elif aiml_response2 != '':
graph_response = [aiml_response2]
else:
response = dict(self.search_bot.answer_question(question_str)[0])
print(response['answer'],response['score'],question_str,"===")
if float(response['score'])>0.7:
print(response['score'])
graph_response = [response['answer']]
else:
graph_response = ['很抱歉，我好像不明白，请您换一种说法']
"""
#print("===============haiyouma")
#self.set_type_by_response([aiml_response,aiml_response_normal,aiml_response_specify])
#print("===lll",self.type,self)
return graph_response