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

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

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)

    response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)

    return response

gr.Interface(fn=chat, inputs="text", outputs="text", title="🤖 NetherMite Chatbot").launch()