Create app.py

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+import gradio as gr
+
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
+model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
+
+
+
+def dialogpt(text):
+    history = gr.get_state() or []
+    # encode the new user input, add the eos_token and return a tensor in Pytorch
+    for step in range(50000):
+
+        new_user_input_ids = tokenizer.encode(text + tokenizer.eos_token, return_tensors='pt')
+
+        # append the new user input tokens to the chat history
+        bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
+
+        # generated a response while limiting the total chat history to 1000 tokens, 
+        chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+        response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
+        history.append((text, response))
+        gr.set_state(history)
+        # pretty print last ouput tokens from bot
+        html = "<div class='chatbot'>"
+        for user_msg, resp_msg in history:
+            html += f"<div class='user_msg'>{user_msg}</div>"
+            html += f"<div class='resp_msg'>{resp_msg}</div>"
+        html += "</div>"
+        return html
+
+
+inputs = gr.inputs.Textbox(lines=1, label="Input Text")
+outputs =  gr.outputs.Textbox(label="DialoGPT")
+
+title = "DialoGPT"
+description = "demo for Microsoft DialoGPT with Hugging Face transformers. To use it, simply input text or click one of the examples text to load them. Read more at the links below. *This is not a Microsoft product and is developed for Gradio*"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1911.00536'>DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation</a> | <a href='https://github.com/microsoft/DialoGPT'>Github Repo</a> | <a href='https://huggingface.co/microsoft/DialoGPT-large'>Hugging Face DialoGPT-large</a></p>"
+examples = [
+            ["Hi, how are you?"],
+            ["How far away is the moon?"],
+]
+
+gr.Interface(dialogpt, inputs, "html", title=title, description=description, article=article, examples=examples,css="""
+    .chatbox {display:flex;flex-direction:column}
+    .user_msg, .resp_msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%}
+    .user_msg {background-color:cornflowerblue;color:white;align-self:start}
+    .resp_msg {background-color:lightgray;align-self:self-end}
+""").launch(debug=True)