Update app.py

app.py

@@ -44,14 +44,16 @@ def predict(input, history=[]):
 
     if is_question: 
         sql_encoding = sql_tokenizer(table=table, query=input + sql_tokenizer.eos_token, return_tensors="pt")
-        #sql_outputs = sql_model.generate(**sql_encoding)
-        #response = sql_tokenizer.batch_decode(sql_outputs, skip_special_tokens=True)
-       
+        sql_outputs = sql_model.generate(**sql_encoding)
+        response = sql_tokenizer.batch_decode(sql_outputs, skip_special_tokens=True)
+
+        history.append(response)
+        '''
         bot_input_ids = torch.cat([torch.LongTensor(history), sql_encoding], dim=-1)
         history = sql_model.generate(bot_input_ids, max_length=1000, pad_token_id=sql_tokenizer.eos_token_id).tolist()
         response = sql_tokenizer.decode(history[0]).split("<|endoftext|>")
         response = [(response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)]
-        
+        '''
     else:
         # tokenize the new input sentence
         new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')