Update app.py

app.py

@@ -1,20 +1,27 @@
 import gradio as gr
-# import pandas as pd
-# from sentence_transformers import SentenceTransformer
-# from sklearn.metrics.pairwise import cosine_similarity
+import pandas as pd
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
 
-# title = "🍀고민 해결 도서 추천 챗봇🍀"
-# description = "고민이 무엇인가요? 고민 해결을 도와줄 책을 추천해드립니다"
-# examples = [["요즘 잠이 안 온다"]]
+title = "🍀고민 해결 도서 추천 챗봇🍀"
+description = "고민이 무엇인가요? 고민 해결을 도와줄 책을 추천해드립니다"
+examples = [["요즘 잠이 안 온다"]]
 
 
-# model = SentenceTransformer('jhgan/ko-sroberta-multitask')
+model = SentenceTransformer('jhgan/ko-sroberta-multitask')
 
-def response(message, history):
-    return message
+def recommend(message):
+  embedding = model.encode(message)
+  df_emb['거리'] = df_emb['서평임베딩'].map(lambda x: cosine_similarity([embedding], [x]).squeeze())
+  answer = df.loc[df_emb['거리'].idxmax()]
+  Book_title = answer['제목']
+  Book_author = answer['작가']
+  Book_publisher = answer['출판사']
+  Book_comment = answer['서평']
+  return Book_title
 
 gr.ChatInterface(
-        fn=response,
+        fn=recommend,
         textbox=gr.Textbox(placeholder="말걸어주세요..", container=False, scale=7),
         title="어떤 챗봇을 원하심미까?",
         description="물어보면 답하는 챗봇임미다.",