Xue-Jun/StructureBasedSimilarityNetwork

1import os2 3import gradio as gr4 5from utils import calculate_md5, run_community_analysis, run_usalign, save_pdb_files6 7os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"8 9# Create Gradio interface10with gr.Blocks() as demo:11    gr.Markdown("# This is a Temp Title")12 13    with gr.Row():14        file_input = gr.File(15            label="Upload PDB Files",16            file_count="multiple",17            file_types=[".pdb"],18        )19 20    output = gr.Textbox(21        label="Upload Results", lines=5, max_lines=5, container=True  # 默认显示行数  # 最大可见行数（超过后自动滚动）22    )23 24    threshold = gr.Slider(minimum=0, maximum=1, value=0.75, label="Threshold")25 26    with gr.Row():27 28        submit_btn = gr.Button("Upload Files")29        run_usalign_btn = gr.Button("Run USalign")30        community_btn = gr.Button("Run Community")31 32    md5_hash = gr.State("")33    with gr.Tab("USalign Results"):34        results_df = gr.DataFrame(35            label="USalign Results",36            wrap=True,37        )38    with gr.Tab("TM Matrix"):39        # Add new output components for community analysis with height limits40        tm_matrix_output = gr.DataFrame(label="TM Matrix", wrap=True, show_label=True)41    with gr.Tab("Newick Tree"):42        newick_output = gr.Textbox(43            label="Newick Tree", lines=5, max_lines=10, container=True  # 默认显示行数  # 最大可见行数（超过后自动滚动）44        )45    # with gr.Tab("Structure Similarity Network"):46    #     network_plot = gr.Plot(label="Structure Similarity Network")47 48    # Combine download buttons into a single row49    with gr.Row():50        with gr.Column():51            gr.Markdown("### Download Results")52            download_tm = gr.File(label="Download Files")53 54    submit_btn.click(fn=save_pdb_files, inputs=[file_input], outputs=output)55 56    def update_md5_hash(files):57        if files:58            return calculate_md5(files)59        return ""60 61    file_input.change(fn=update_md5_hash, inputs=[file_input], outputs=[md5_hash])62 63    run_usalign_btn.click(fn=run_usalign, inputs=[md5_hash], outputs=[results_df])64 65    def process_community_analysis(results_df, md5_hash, threshold):66        if results_df.empty:67            return None, None, None68 69        results = run_community_analysis(results_df, "./data", md5_hash, threshold)70 71        if "Error" in results:72            return None, None, None73 74        # Prepare download files75 76        return (77            results["tm_matrix"],78            results["newick_str"],79            # results["network_fig"],80            results["files"],81        )82 83    community_btn.click(84        fn=process_community_analysis,85        inputs=[results_df, md5_hash, threshold],86        outputs=[87            tm_matrix_output,88            newick_output,89            # network_plot,90            download_tm,91        ],92    )93 94if __name__ == "__main__":95    demo.launch(server_name="0.0.0.0")96