Update app.py

app.py

@@ -7,4 +7,27 @@ model = AutoModelForCausalLM.from_pretrained("jslin09/bloom-560m-finetuned-fraud
 
 def predict(input, history=[]):
     # tokenize the new input sentence
-    new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
+    new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
+
+    # append the new user input tokens to the chat history
+    bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
+
+    # generate a response 
+    history = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id).tolist()
+
+    # convert the tokens to text, and then split the responses into lines
+    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
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    state = gr.State([])
+
+    with gr.Row():
+        txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)
+
+    txt.submit(predict, [txt, state], [chatbot, state])
+            
+if __name__ == "__main__":
+    demo.launch()