Update app.py

app.py

@@ -66,22 +66,33 @@ def update_video_display(selection):
 def run_omnisign_vlm(video_path):
     """
     Submits the video to the private backend.
-    CRITICAL: Must use positional arguments for handle_file().
+    Fixed to ensure gr.Label always receives {str: float}
     """
-    if not video_path: return {"Error": "No input detected."}
-    if not client: return {"Neural Engine Offline": 0.0}
+    # FIX 1: Value must be 0.0 (float), not a string message
+    if not video_path: 
+        return {"⚠️ No Input Selected": 0.0} 
+    
+    # FIX 2: Value must be 0.0 (float)
+    if not client: 
+        return {"⚠️ Neural Engine Offline": 0.0} 
 
     try:
-        # --- THE FIX IS HERE ---
-        # We pass handle_file(video_path) as the FIRST argument (positional).
-        # We do NOT use 'video_file=' or 'video=' as a keyword.
+        # 1. Send to Private Space
         result = client.predict(
             handle_file(video_path),
             api_name="/predict_sign"
         )
+        
+        # 2. Safety Check on Result
+        # Sometimes connection errors return strings instead of dicts.
+        # We must intercept that before giving it to gr.Label
+        if isinstance(result, str):
+            return {f"⚠️ Backend Error: {result}": 0.0}
+            
         return result
+
     except Exception as e:
-        return {f"Neural Analysis Failed: {str(e)}": 0.0}
+        return {f"❌ Analysis Failed: {str(e)}": 0.0}
 
 # 6. UI DESIGN
 with gr.Blocks(theme=gr.themes.Soft()) as demo: