#!/usr/bin/env python3
"""
Gradio-based tool to remove vision components from Qwen models and upload to Hugging Face.
This can be deployed as a Hugging Face Space with OAuth authentication.
Uses git clone/commit/push for efficient storage usage in Spaces.

Entry point for the Blindfold Model application.
"""

import os
import logging
import gradio as gr
from ui import create_interface

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Check if running in Hugging Face Space
IS_HF_SPACE = os.environ.get("SPACE_ID") is not None


if __name__ == "__main__":
    interface = create_interface()

    # Disable share on Hugging Face Spaces (not supported)
    # Use queue to handle long-running operations and prevent timeouts
    # The queue allows the server to process long tasks without blocking the connection
    interface.queue(
        default_concurrency_limit=1,  # Process one request at a time
        max_size=10,  # Maximum number of requests in queue
    )
    interface.launch(
        share=not IS_HF_SPACE,  # Only enable share when not running on HF Space
        theme=gr.themes.Soft(),
        css="""
        .gradio-container {
            max-width: 1200px !important;
        }
        """,
    )