app.py

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

# Load model
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-small")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-small")

chat_history_ids = None

def chat(user_input):
    global chat_history_ids
    new_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
    bot_input_ids = torch.cat([chat_history_ids, new_input_ids], dim=-1) if chat_history_ids is not None else new_input_ids
    chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
    bot_response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
    return bot_response

iface = gr.Interface(fn=chat, inputs="text", outputs="text", title="Simple AI Chatbot")
iface.launch()