app.py

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import gradio as gr

tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")

def predict(input, history=[]):
  new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')
  bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
  history = model.generate(bot_input_ids, max_length=500, pad_token_id=tokenizer.eos_token_id).tolist()
  response = tokenizer.decode(history[0]).replace("<|endoftext|>", "\n")
  return response, history

gr.Interface(fn=predict, theme="grass", css=".footer {display:none !important}", title="Chatbot Two", inputs=["text", "state"], outputs=["text", "state"]).launch()