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app.py

@@ -25,33 +25,33 @@ app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], all
 DEVICE = torch.device("cpu")
 
 # ── Ensemble configs (from optimizer) ──
-# Using image_ensemble_v2 + ai_gen (the two models with confirmed working architectures)
-# These achieve 99.3-99.4% F1 across all platforms
+# Using image_ensemble_v2 only — ai_gen model has class-mapping issues (always predicts fake)
+# Will re-enable ai_gen after retraining/fixing
 ENSEMBLE_CONFIGS = {
     "clean": {
-        "models": ["image_ensemble_v2", "ai_gen"],
-        "weights": [0.556, 0.444],
-        "threshold": 0.55
+        "models": ["image_ensemble_v2"],
+        "weights": [1.0],
+        "threshold": 0.50
     },
     "whatsapp": {
         "models": ["image_ensemble_v2"],
         "weights": [1.0],
-        "threshold": 0.65
+        "threshold": 0.55
     },
     "instagram": {
-        "models": ["image_ensemble_v2", "ai_gen"],
-        "weights": [0.6, 0.4],
-        "threshold": 0.60
+        "models": ["image_ensemble_v2"],
+        "weights": [1.0],
+        "threshold": 0.50
     },
     "telegram": {
-        "models": ["image_ensemble_v2", "ai_gen"],
-        "weights": [0.75, 0.25],
-        "threshold": 0.60
+        "models": ["image_ensemble_v2"],
+        "weights": [1.0],
+        "threshold": 0.50
     },
     "screenshot": {
-        "models": ["image_ensemble_v2", "ai_gen"],
-        "weights": [0.667, 0.333],
-        "threshold": 0.55
+        "models": ["image_ensemble_v2"],
+        "weights": [1.0],
+        "threshold": 0.50
     }
 }