app.py

import gradio as gr
import os
import sys

# Repository: https://github.com/liuff19/LangScene-X
# <div align="center">

# Note: This project requires CUDA-enabled GPU and complex build dependencies
# The original repository uses custom CUDA extensions that need compilation

def process_3d(input_file):
    """3D processing function - placeholder for actual implementation"""
    if input_file is None:
        return "Please upload a 3D file or image"
    
    info = """
    ## ⚠️ Build Requirements Notice
    
    This project requires:
    1. CUDA-enabled GPU
    2. Custom C++/CUDA extensions compilation
    3. Specific versions of PyTorch with CUDA support
    
    The git dependencies in requirements.txt need PyTorch to be installed first.
    
    For full functionality:
    1. Install PyTorch with CUDA: `pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118`
    2. Install build tools: `apt-get install build-essential python3-dev ninja-build`
    3. Then install other requirements
    
    Original repository: https://github.com/liuff19/LangScene-X
    """
    
    return info

# Gradio interface
with gr.Blocks(title="LangScene-X") as demo:
    gr.Markdown(f"""
    # Langscene X
    
    <div align="center">
    
    This space was created from: [https://github.com/liuff19/LangScene-X](https://github.com/liuff19/LangScene-X)
    
    **Note**: This project has complex build requirements. See below for details.
    """)
    
    with gr.Row():
        with gr.Column():
            input_file = gr.File(label="Upload 3D File or Image")
            process_btn = gr.Button("Process", variant="primary")
        
        with gr.Column():
            output_info = gr.Markdown()
    
    process_btn.click(
        fn=process_3d,
        inputs=input_file,
        outputs=output_info
    )

if __name__ == "__main__":
    demo.launch()