def pickCase(self, des):
#用于搜索相似的新闻案例，基于Elastic
result = searchInEs(des, self._indexCase, self.doc_type_case,
self.caseKey, 1)
return result
def es_presearch(self,des):
'''
根据描述进行预搜索
'''
result=searchInEs(des,self.index,self.type,self.key,self.num)
#取出title
return [a['_source']['title'] for a in result]
def es_preSearch(self):
'''ES预搜索'''
result = searchInEs(self.des, self.index, self.docType, self.key,
self.res_limit)
title_list = []
for res in result:
title_list.append(res['_source']['title'])
return title_list
def getLawData(self):
'''
由ES引擎给出相关的具体法条
'''
#下列参数与具体的数据库相关,
#根据标题返回五个法条
resOfLaw1 = searchInEs(self.bestTitle, 'law_data', 'line', 'line', 5)
#下列参数与具体数据库相关
set = 0
if self.cause:
resOfLaw2 = searchInEs(self.cause, 'law_data', 'line', 'line', 5)
set = 1
#包装相关法条
lawLine = list()
for line in resOfLaw1:
lawLine.append(line['_source'])
if set == 1:
for line in resOfLaw2:
lawLine.append(line['_source'])
return lawLine
def es_presearch(self, des):
'''
根据描述进行预搜索
'''
result = searchInEs(des, self.index, "_doc", self.key, self.num)
print("{+} es搜索中...")
print(result)
#取出title
#special adjustment:
resultTitle = [a['_source']['title'] for a in result]
resultTitle.remove("骗子")
return resultTitle
def findAnswer(self, des):
'''答案查找主函数'''
result = searchInEs(des, self._index, self.doc_type, self.targetKey,
self.num_res)
answer = []
#process the result
for each in result:
#use dict to store every answer
answer_dict = {}
#build answer dict
answer_dict["score"] = each["_score"]
answer_dict["sim_question"] = each["_source"]["question"]
answer_dict['answer'] = each["_source"]["answer"]
answer.append(answer_dict)
#return 这一句里的作用是字典去重
return [dict(t) for t in set([tuple(d.items()) for d in answer])]