Update chatgpt_app.py

chatgpt_app.py

@@ -58,24 +58,25 @@ with col1:
 
     if submitted and user_input:
 
-        ## Sentence-BERT 기반
-        question_vectors = model.encode(q_fin)
-        target_vector = model.encode(user_input)
-        similarities_sbert = util.cos_sim(question_vectors, target_vector) # compute similarity between sentence vectors
-
-        ## Sequence Matcher 기반
-        # similarities_seqmat = []
-        # user_sent_bytes = bytes(user_input, 'utf-8')
-        # user_sent_bytes_list = list(user_sent_bytes)
-
-        # for sent in q_fin:
-        #     sent_bytes = bytes(sent, 'utf-8')
-        #     sent_bytes_list = list(sent_bytes)
-        #     score = difflib.SequenceMatcher(None, user_sent_bytes_list, sent_bytes_list).ratio()    
-        #     similarities_seqmat.append(score)
-
-        # similarities_seqmat = np.array(similarities_seqmat)
-        
+        with st.spinner('Wait for it...'):
+            ## Sentence-BERT 기반
+            question_vectors = model.encode(q_fin)
+            target_vector = model.encode(user_input)
+            similarities_sbert = util.cos_sim(question_vectors, target_vector) # compute similarity between sentence vectors
+    
+            ## Sequence Matcher 기반
+            # similarities_seqmat = []
+            # user_sent_bytes = bytes(user_input, 'utf-8')
+            # user_sent_bytes_list = list(user_sent_bytes)
+    
+            # for sent in q_fin:
+            #     sent_bytes = bytes(sent, 'utf-8')
+            #     sent_bytes_list = list(sent_bytes)
+            #     score = difflib.SequenceMatcher(None, user_sent_bytes_list, sent_bytes_list).ratio()    
+            #     similarities_seqmat.append(score)
+    
+            # similarities_seqmat = np.array(similarities_seqmat)
+            
         if similarities_sbert.max() < 0.2:
             output = "잘 못 알아듣겠어요 선생님. 다시 말씀해주세요..."
         else: