Update app.py

app.py

@@ -191,14 +191,23 @@ def predict_scores(df):
     feats=["red_ratio","green_ratio","red_diff","green_diff","z_red","z_green"]
     X=df[feats].copy()
     ag=ag_predictor()
+    available_models = ag.get_model_names()
+    safe_models = [m for m in available_models if "fastai" not in m.lower()]
+    print(f"[INFO] Using models: {safe_models}")
     try:
-        proba=ag.predict_proba(X)
-        if isinstance(proba,pd.DataFrame) and (1 in proba.columns): return proba[1]
-    except: pass
-    s=pd.Series(ag.predict(X)).astype(float)
+        proba=ag.predict_proba(X, models=safe_models)
+        if isinstance(proba,pd.DataFrame) and (1 in proba.columns):
+            return proba[1]
+    except Exception as e:
+        print("[WARN] AutoGluon fastai model failed, falling back to safe models only:", e)
+        proba=ag.predict_proba(X, models=safe_models)
+        if isinstance(proba,pd.DataFrame) and (1 in proba.columns):
+            return proba[1]
+    s=pd.Series(ag.predict(X, models=safe_models)).astype(float)
     rng=(s.quantile(0.95)-s.quantile(0.05)) or 1.0
     return ((s-s.quantile(0.05))/rng).clip(0,1)
 
+
 def pick_events(df,score,fps):
     z=rolling_z(score,45); strong=(z>4.0); keep=strong.rolling(3,min_periods=1).sum()>=2
     min_dist=max(1,int(MIN_SEP_S*fps))