Create app.py

app.py

@@ -0,0 +1,116 @@
+import sys
+import gradio as gr
+import os
+import hashlib
+from pathlib import Path
+import pandas as pd
+from io import StringIO
+from usalign_runner import USalignRunner
+from utils import (calculate_md5, get_TM_mat_from_df, get_cluster_z_from_df, get_newick_str_from_Z,
+                  build_graph_from_mat_df, fill_community_to_graph, get_graph_fig, run_community_analysis, run_usalign, save_pdb_files)
+import matplotlib.pyplot as plt
+os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# This is a Temp Title")
+    
+    with gr.Row():
+        file_input = gr.File(
+            label="Upload PDB Files",
+            file_count="multiple",
+            file_types=[".pdb"],
+            height=200,
+            # lines=5,           # 默认显示行数
+            # max_lines=10,      # 最大可见行数（超过后自动滚动）
+            # container=True  
+        )
+
+    output = gr.Textbox(label="Upload Results",
+                lines=5,           # 默认显示行数
+                max_lines=5,      # 最大可见行数（超过后自动滚动）
+                container=True  )
+    
+    threshold = gr.Slider(minimum=0, maximum=1, value=0.75, label="Threshold")
+    
+    with gr.Row():
+       
+        submit_btn = gr.Button("Upload Files")
+        run_usalign_btn = gr.Button("Run USalign")
+        community_btn = gr.Button("Run Community")
+    
+    md5_hash = gr.State("")
+    with gr.Tab("USalign Results"):
+        results_df = gr.DataFrame(label="USalign Results",height=400,wrap=True,)
+    with gr.Tab("TM Matrix"):    
+        # Add new output components for community analysis with height limits
+        tm_matrix_output = gr.DataFrame(label="TM Matrix",height=400,wrap=True,show_label=True)
+    with gr.Tab("Newick Tree"):
+        newick_output = gr.Textbox(label="Newick Tree",
+            lines=5,           # 默认显示行数
+            max_lines=10,      # 最大可见行数（超过后自动滚动）
+            container=True  )
+    with gr.Tab("Structure Similarity Network"):
+        network_plot = gr.Plot(label="Structure Similarity Network")
+    
+    # Combine download buttons into a single row
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### Download Results")
+            download_tm = gr.File(label="Download Files")
+
+    submit_btn.click(
+        fn=save_pdb_files,
+        inputs=[file_input],
+        outputs=output
+    )   
+
+    def update_md5_hash(files):
+        if files:
+            return calculate_md5(files)
+        return ""
+    
+    file_input.change(
+        fn=update_md5_hash,
+        inputs=[file_input],
+        outputs=[md5_hash]
+    )
+    
+    run_usalign_btn.click(
+        fn=run_usalign,
+        inputs=[md5_hash],
+        outputs=[results_df]
+    )
+    
+    def process_community_analysis(results_df, md5_hash,threshold):
+        if results_df.empty:
+            return None, None, None, None, None, None
+        
+        results = run_community_analysis(results_df, "./data", md5_hash,threshold)
+        
+        if "Error" in results:
+            return None, None, None, None, None, None
+            
+        # Prepare download files
+
+        
+        return (
+            results["tm_matrix"],
+            results["newick_str"],
+            results["network_fig"],
+            results["files"]
+        )
+    
+    community_btn.click(
+        fn=process_community_analysis,
+        inputs=[results_df, md5_hash,threshold],
+        outputs=[
+            tm_matrix_output,
+            newick_output,
+            network_plot,
+            download_tm,
+        ]
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0",server_port=7869)