Chatbot interface using `DialoGPT-medium`

app.py

@@ -1,3 +1,41 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
+import torch
 
-gr.Interface.load("models/ingen51/DialoGPT-medium-GPT4").launch()
+
+# tokenizer = AutoTokenizer.from_pretrained("chavinlo/gpt4-x-alpaca")
+# model = AutoModelForCausalLM.from_pretrained("chavinlo/gpt4-x-alpaca")
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+
+def user(message, history):
+    return "", history + [[message, None]]
+
+def bot(history):
+    user_message = history[-1][0]
+    new_user_input_ids = tokenizer.encode(user_message + 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 history
+
+## Use the above methods to create the Chatbot interface
+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)
+
+demo.launch()