Update app.py

app.py

@@ -64,9 +64,8 @@ sql_tokenizer = TapexTokenizer.from_pretrained(sql_model_name)
 sql_model = BartForConditionalGeneration.from_pretrained(sql_model_name)
 
 #sql_response = None
-conversation_history = []
 
-def predict(input): #history=[]):
+def predict(input, history=[]):
 
     #global sql_response
     # Check if the user input is a question
@@ -80,13 +79,7 @@ def predict(input): #history=[]):
 
     else:
     '''
-
-    bot_input = tokenizer.encode(input + tokenizer.eos_token, return_tensors="pt")
-    chat_history_ids = model.generate(bot_input, max_length=1000, pad_token_id=tokenizer.eos_token_id)
-    response = tokenizer.decode(chat_history_ids[:, bot_input.shape[-1]:][0], skip_special_tokens=True)
-    #return response
-
-    '''
+    
     # tokenize the new input sentence
     new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
     
@@ -99,20 +92,10 @@ def predict(input): #history=[]):
     # convert the tokens to text, and then split the responses into the right format
     response = tokenizer.decode(history[0]).split("<|endoftext|>")
     response = [(response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)]  # convert to tuples of list
-    '''
     
-    return response #, history
+    return response, history
 
-def chatbot_interface(user_input):
-    global conversation_history
-    
-    conversation_history.append(user_input)
 
-    dialog_prompt = "User: " + " ".join(conversation_history) + "\nBot:"
-    response = predict(dialog_prompt)
-    conversation_history.append(response)
-    return response
-    
 def sqlquery(input):
 
     sql_encoding = sql_tokenizer(table=table, query=input + sql_tokenizer.eos_token, return_tensors="pt")
@@ -123,11 +106,13 @@ def sqlquery(input):
 
 
 chat_interface = gr.Interface(
-    fn=chatbot_interface, 
-    inputs=gr.Textbox(prompt="You:"),
-    outputs=gr.Textbox(),
-    live=True,
-    
+    fn=predict,
+    theme="default",
+    css=".footer {display:none !important}",
+    inputs=["text", "state"],
+    outputs=["chatbot", "state"],
+    title="ST Chatbot",
+    description="Type your message in the box above, and the chatbot will respond.",
 )
 
 sql_interface = gr.Interface(