from pathlib import Path
import zipfile

base = Path("/mnt/data/nova_ai_chatbot_pro")
base.mkdir(exist_ok=True)

app = r'''import os
import threading
import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer

MODEL_ID = os.getenv("MODEL_ID", "Qwen/Qwen2.5-0.5B-Instruct")
SYSTEM_PROMPT = (
    "You are Nova, a helpful, thoughtful AI assistant. "
    "Be clear, friendly, accurate, and concise. If you are unsure, say so."
)

_tokenizer = None
_model = None
_load_error = None


def get_model():
    global _tokenizer, _model, _load_error
    if _model is not None:
        return _tokenizer, _model
    if _load_error:
        raise RuntimeError(_load_error)
    try:
        _tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
        kwargs = {"low_cpu_mem_usage": True}
        if torch.cuda.is_available():
            kwargs["torch_dtype"] = torch.float16
            kwargs["device_map"] = "auto"
        else