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app.py

@@ -209,7 +209,8 @@ base_input = {
     'is_power_merchant': 1 if shop_tier == "Power Merchant" else 0,
     'is_official_store': 1 if shop_tier == "Official Store" else 0,
 
-    'video_count': vid_count, 'image_count': img_count,
+    'video_count': vid_count,
+    'image_count': img_count,
 
     'can_shipping_instant': 1 if ship_inst else 0,
     'can_shipping_sameday': 1 if ship_same else 0,
@@ -260,11 +261,8 @@ st.divider()
 st.subheader("💰 Price Prediction")
 
 if price_models:
-    col_model, col_btn = st.columns([1, 1])
-    with col_model:
-        model_name = st.selectbox("Select Model", list(price_models.keys()), label_visibility="collapsed")
-    with col_btn:
-        predict_btn = st.button("Predict Price", type="primary", use_container_width=True)
+    model_name = st.selectbox("Select Model", list(price_models.keys()), label_visibility="collapsed")
+    predict_btn = st.button("Predict Price", type="primary", use_container_width=True)
 
     if predict_btn:
         raw_df = prepare_raw_dataframe(base_input, price_cols, vectorizer)
@@ -280,7 +278,7 @@ if price_models:
 
         st.success(f"Estimated Price: **Rp {price_pred:,.0f}**")
         
-        with st.expander("Feature Importance Analysis"):
-            load_and_plot_importance(model_name, "price")
+    with st.expander("Feature Importance Analysis"):
+        load_and_plot_importance(model_name, "price")
 else:
     st.error("Models failed to load.")