sys.path.append('/Users/wxg12/Documents/python_workspace/chatbot/')
from config.DatabaseConfig import *
from utils.Database import Database
from utils.Preprocess import Preprocess
# 전처리 객체 생성
p = Preprocess(word2index_dic='train_tools/dict/chatbot_dict.bin',
userdic='utils/user_dic.tsv')
# 질문/답변 학습 디비 연결 객체 생성
db = Database(host=DB_HOST,
user=DB_USER,
password=DB_PASSWORD,
db_name=DB_NAME)
db.connect() # 디비 연결
# 원문
# query = "오전에 탕수육 10개 주문합니다"
# query = "화자의 질문 의도를 파악합니다."
# query = "안녕하세요"
query = "자장면 주문할게요"
# 의도 파악
from models.intent.IntentModel import IntentModel
intent = IntentModel(model_name='models/intent/intent_model.h5', proprocess=p)
predict = intent.predict_class(query)
intent_name = intent.labels[predict]
# 개체명 인식
from config.DatabaseConfig import *
from utils.Database import Database
from utils.Preprocess import Preprocess
# 전처리 객체 생성
p = Preprocess(word2index_dic='../train_tools/dict/chatbot_dict.bin',
userdic='../utils/user_dic.tsv')
# 질문/답변 학습 DB 연결 객체 생성
db = Database(host=DB_HOST,
user=DB_USER,
password=DB_PASSWORD,
db_name=DB_NAME)
db.connect() # DB 연결
# 원문
query = input()
# 의도 파악
from models.intent.IntentModel import IntentModel
intent = IntentModel(model_name='../models/intent/intent_model.h5',
preprocess=p)
predict = intent.predict_class(query)
intent_name = intent.labels[predict]
# 개체명 인식
from models.ner.NerModel import NerModel
ner = NerModel(model_name='../models/ner/ner_model.h5', preprocess=p)
predicts = ner.predict(query)
ner_tags = ner.predict_tags(query)