Update app.py

app.py

@@ -174,10 +174,10 @@ def train_model(df: pd.DataFrame, feats_num, feats_cat, target):
     return pipe, {"r2": r2_score(y_test, pred), "mae": mean_absolute_error(y_test, pred)}, X_test
 
 @st.cache_resource(show_spinner=False)
-def compute_shap(pipe, X_sample, feats_num, feats_cat, shap_sample=1000, seed=42):
+def compute_shap(_pipe, X_sample, feats_num, feats_cat, shap_sample=1000, seed=42):
     np.random.seed(seed)
-    preproc = pipe.named_steps["pre"]
-    rf = pipe.named_steps["rf"]
+    preproc = _pipe.named_steps["pre"]
+    rf = _pipe.named_steps["rf"]
     feature_names = list(preproc.named_transformers_["cat"].get_feature_names_out(feats_cat)) + feats_num
 
     if len(X_sample) > shap_sample: