Blindfold / app.py
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Update app.py
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#!/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;
}
""",
)