Update app.py

app.py

@@ -13,41 +13,58 @@ examples = [["How are you?"]]
 tokenizer = AutoTokenizer.from_pretrained("rinna/vicuna-13b-delta-finetuned-langchain-MRKL")
 model = AutoModelForCausalLM.from_pretrained("rinna/vicuna-13b-delta-finetuned-langchain-MRKL")
 
-def generate_response(input_text, chat_history=[]):
-    # Tokenize the new input sentence
-    new_user_input_ids = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors="pt")
+# tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+# model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
 
-    # Append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([torch.tensor(chat_history), new_user_input_ids], dim=-1)
 
-    # Generate a response
-    chat_output = model.generate(bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id)
+def user(message, history):
+    return "", history + [[message, None]]
 
-    # Decode the response tokens into text
-    response = tokenizer.decode(chat_output[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
 
-    return response
+def bot(history):
+    user_message = history[-1][0]
+    new_user_input_ids = tokenizer.encode(
+        user_message + tokenizer.eos_token, return_tensors="pt"
+    )
 
-def chatbot_interface(input_text):
-    # Generate response based on input text and chat history
-    response = generate_response(input_text, chat_history)
+    # append the new user input tokens to the chat history
+    bot_input_ids = torch.cat([torch.LongTensor([]), new_user_input_ids], dim=-1)
 
-    # Append the input and response to the chat history
-    chat_history.append(tokenizer.encode(input_text + response))
+    # generate a response
+    response = model.generate(
+        bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id
+    ).tolist()
 
-    return response
+    # convert the tokens to text, and then split the responses into lines
+    response = tokenizer.decode(response[0]).split("<|endoftext|>")
+    response = [
+        (response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)
+    ]  # convert to tuples of list
+    history[-1] = response[0]
+    return history
 
-chat_history = []  # Initialize chat history
 
-iface = gr.Interface(
-    fn=chatbot_interface,
-    inputs=gr.inputs.Textbox(lines=2, label="Chat"),
-    outputs=gr.outputs.Textbox(label="Response"),
-    layout="vertical",
-    title=title,
-    description=description,
-    examples=examples,
-    theme="london"
-)
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.Button("Clear")
+    
+    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, chatbot, chatbot
+    )
+    clear.click(lambda: None, None, chatbot, queue=False)
 
-iface.launch()
+demo.launch()
+
+# iface = gr.Interface(
+#     fn=chatbot_interface,
+#     inputs=gr.inputs.Textbox(lines=2, label="Chat"),
+#     outputs=gr.outputs.Textbox(label="Response"),
+#     layout="vertical",
+#     title=title,
+#     description=description,
+#     examples=examples,
+#     theme="london"
+# )
+
+# iface.launch()