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 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=1000,pad_token_id=tokenizer.eos_token_id).tolist()
  response = tokenizer.decode(history[0]).split("<|endoftext|>")
  response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)]
  return response, history

demo = gr.Interface(fn=predict,
             inputs=["text", "state"],
             outputs=["chatbot", "state"])

demo.launch()