CRITICAL FIX: Pass features dict instead of ProcessingContext to runtime.process()

app.py

@@ -628,9 +628,9 @@ for idx, row in df.iterrows():
         metadata={},
     )
 
-    # Process with runtime
+    # Process with runtime (pass features dict, not ProcessingContext)
     t_start = time.perf_counter()
-    result = runtime.process(context)
+    result = runtime.process(context.features)
     t_elapsed = (time.perf_counter() - t_start) * 1000  # ms
 
     # Heavy model prediction if activated