Update app.py

app.py

@@ -7,8 +7,6 @@ import nibabel as nib
 import traceback
 import tempfile
 import torch
-from nnunetv2.inference.predict_from_raw_data import nnUNetPredictor
-from batchgenerators.utilities.file_and_folder_operations import join
 
 # GLOBAL SETUP & MODEL INITIALIZATION
 # Set dummy environment variables to prevent nnU-Net path errors in HF Spaces
@@ -18,6 +16,9 @@ os.environ['nnUNet_preprocessed'] = './tmp/nnUNet_preprocessed'
 os.makedirs('./tmp/nnUNet_raw', exist_ok=True)
 os.makedirs('./tmp/nnUNet_preprocessed', exist_ok=True)
 
+from nnunetv2.inference.predict_from_raw_data import nnUNetPredictor
+from batchgenerators.utilities.file_and_folder_operations import join
+
 # Dynamically assign device (prevents crashes if deployed on a CPU space)
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 print(f"Initializing nnU-Net on device: {device}")
@@ -135,7 +136,7 @@ def process_scan(nifti_file, no_chemo, pd_surgery):
 # GRADIO UI LAYOUT
 
 
-with gr.Blocks(theme=gr.themes.Base()) as demo:
+with gr.Blocks() as demo:
     gr.Markdown("# Preoperative R1 Resection Risk Predictor")
     
     with gr.Row():
@@ -168,4 +169,9 @@ with gr.Blocks(theme=gr.themes.Base()) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo = create_interface()
+    demo.launch(
+        server_name="0.0.0.0", 
+        server_port=7860,
+        theme=gr.themes.Base() 
+    )