Fix: version issue

app.py

@@ -1,9 +1,26 @@
+import os
+import warnings
+
+# ==========================================
+# 1. ENVIRONMENT CONFIGURATION (Must be at the top)
+# ==========================================
+# Bypass internal container proxies that block health checks
+os.environ["NO_PROXY"] = "localhost,127.0.0.1,::1"
+# Force Gradio to bind to all IPs on the correct port
+os.environ["GRADIO_SERVER_NAME"] = "0.0.0.0"
+os.environ["GRADIO_SERVER_PORT"] = "7860"
+
+# Suppress the non-fatal timm legacy warnings to keep logs clean
+warnings.filterwarnings("ignore", category=UserWarning, module="timm.models._factory")
 
 import torch
 import gradio as gr
 from torchvision import transforms
 from model import HybridDeepfakeDetector
 
+# ==========================================
+# 2. MODEL INITIALIZATION
+# ==========================================
 model = HybridDeepfakeDetector()
 model.load_state_dict(
     torch.load("deepfake_detector_phase2.pth", 
@@ -21,15 +38,26 @@ transform = transforms.Compose([
     )
 ])
 
+# ==========================================
+# 3. PREDICTION LOGIC
+# ==========================================
 def predict(image):
+    # Safety check: Prevent crash if user clicks submit before image uploads
+    if image is None:
+        return "Please upload an image."
+        
     tensor = transform(image).unsqueeze(0)
     with torch.no_grad():
         prob = model(tensor).item()
+    
     print(f"Raw prob: {prob:.4f}")
     label = "REAL" if prob > 0.5 else "FAKE"
     confidence = prob if label == "REAL" else 1 - prob
     return f"{label} ({confidence*100:.1f}% confident)"
 
+# ==========================================
+# 4. UI & DEPLOYMENT
+# ==========================================
 demo = gr.Interface(
     fn=predict,
     inputs=gr.Image(type="pil"),
@@ -38,4 +66,10 @@ demo = gr.Interface(
     description="Upload a face image to detect if it is real or AI-generated."
 )
 
-demo.launch()
+if __name__ == "__main__":
+    # Optimal launch parameters for Hugging Face Spaces
+    demo.launch(
+        share=False,       # Let HF Spaces handle the public URL tunneling
+        ssr_mode=False,    # Disable Server-Side Rendering to prevent localhost loop crashes
+        show_error=True    # Surface actual code errors to the UI if they happen
+    )