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app.py

@@ -104,50 +104,57 @@ st.title("🛍️ Advanced E-Commerce Price Predictor")
 with st.container():
     c1, c2 = st.columns([2, 1])
     with c1:
-        p_name = st.text_input("Product Name", "Samsung Galaxy S24 Ultra")
-        p_desc = st.text_area("Description", "Original SEIN, Garansi Resmi 1 Tahun")
+        p_name = st.text_input("Product Name", "IBOX iP 13 128GB 256GB Second BEKAS ORIGINAL 100% Seken Apple | MULUS 13 NORMAL FULLSET")
+        p_desc = st.text_area("Description", "Sinyal ALL Oprator Quality Check Sebelum Mengirimkan Produk Garansi HP Dibantu Sampai Selesai Region : Usa Singapur China Korea Dll ️️HARAP DICATAT: Sinyal ALL Oprator ICould aman asli 100% ️Informasi yg Sering Ditanyakan 3utools Sinyal On Face id True Tone Kami pasti Quality Check sebelum mengirimkan pesanan. Bila produk sudah sampai test fungsi keseluruhan sebelum selesaikan transaksi. Jangan menyelesaikan pesanan sebelum unit benar benar di test fungsi keseluruhan untuk menjaga-jaga supaya tidak terjadi hal yang tidak diinginkan dan untuk claim garansi unit. ULAS DENGAN BIJAK Mohon untuk tidak langsung memberikan ulasan negatif dan bintang rendah sebelum komplain terselesaikan - BAD REVEW GARANSI HANGUS. Kelengkapan - Box (Ada kemungkinan Tidak ada stiker IMEI di Box) - Cable Tidak ada adaptor - Tidak ada garansi untuk Aksesoris Battery Health : 90%++ Request BH 95% Up to 100% : Bisa Silhakan Chat Tanya Admin Caranya KONDISI PRODUK : * ALL UNIT MULUS 98-99% * ALL OPERATOR (BISA SEMUA KARTU) * ALL UNIT ICLOUD AMAN * GARANSI 1 BULAN * TIDAK BISA REQUEST BATRE HEALTH SEGINI SEGINI . SILAHKAN TULIS DICATATAN, KITA USAHAKAN KIRIM BH 95+++. KETENTUAN RETUR BARANG : - Segel garansi harus utuh - Jangan terkena air atau cairan lainnya - Jangan terjatuh, retak, pecah - Jangan dibongkar / service sendiri - Tidak lock ICloud (Log out sebelum retur)")
     with c2:
-        category = st.selectbox("Category", get_categories())
-        shop_tier = st.selectbox("Shop Tier", ["Regular Merchant", "Power Merchant", "Official Store"])
+        categories_list = get_categories()
+        category = st.selectbox("Category", categories_list, index=categories_list.index('Handphone & Tablet'))
+        shop_tier = st.selectbox(
+            "Shop Tier",
+            ["Regular Merchant", "Power Merchant", "Official Store"]
+        )
         condition = st.radio("Condition", ["New", "Used"], horizontal=True)
 
 c_left, c_right = st.columns(2)
 
 with c_left:
     with st.expander("📦 Physical, Stock & Shipping", expanded=True):
-        col1, col2 = st.columns(2)
+        col1, col2, col3 = st.columns(3)
         weight = col1.number_input("Weight (g)", value=500)
-        stock = col2.number_input("Stock", value=50)
+        stock = col2.number_input("Stock", value=37)
+        sold = col3.number_input("Sold", value=584)
+
         min_order = col1.number_input("Min Order", value=1)
-        max_order = col2.number_input("Max Order", value=100)
+        max_order = col2.number_input("Max Order", value=38)
         
         st.caption("Shipping Options")
         sc1, sc2, sc3 = st.columns(3)
         ship_inst = sc1.checkbox("Instant", False)
-        ship_same = sc2.checkbox("Same Day", True)
+        ship_same = sc2.checkbox("Same Day", False)
         ship_next = sc3.checkbox("Next Day", False)
         ship_reg = sc1.checkbox("Regular", True)
         ship_cargo = sc2.checkbox("Cargo", False)
-        ship_eco = sc3.checkbox("Economy", True)
+        ship_eco = sc3.checkbox("Economy", False)
+        total_shipping = st.number_input("Total Shipping Types", value=2)
 
         is_preorder = st.checkbox("Preorder?", False)
-        is_discount = st.checkbox("Discounted?", False)
+        is_discount = st.checkbox("Discounted?", True)
 
     with st.expander("🏪 Shop Performance", expanded=False):
         shop_age = st.number_input("Shop Age (Days)", 365)
         shop_pop = st.number_input("Shop Popularity Score", 100)
         shop_city_pop = st.number_input("City Popularity", 1)
-        resp_time = st.number_input("Response Time (mins)", 30)
+        resp_time = st.number_input("Response Time (mins)", 360)
         date_shop_open = st.date_input("Shop Open Since", datetime(2020, 1, 1))
 
     with st.expander("⚙️ Advanced Shop Setup (Detailed Ratings)", expanded=False):
         st.caption("Input exact review counts for the entire shop")
         ac1, ac2, ac3, ac4, ac5 = st.columns(5)
-        shop_r5 = ac1.number_input("Shop 5★", value=100)
-        shop_r4 = ac2.number_input("Shop 4★", value=10)
-        shop_r3 = ac3.number_input("Shop 3★", value=0)
-        shop_r2 = ac4.number_input("Shop 2★", value=0)
-        shop_r1 = ac5.number_input("Shop 1★", value=0)
+        shop_r5 = ac1.number_input("Shop 5★", value=254)
+        shop_r4 = ac2.number_input("Shop 4★", value=12)
+        shop_r3 = ac3.number_input("Shop 3★", value=6)
+        shop_r2 = ac4.number_input("Shop 2★", value=3)
+        shop_r1 = ac5.number_input("Shop 1★", value=28)
         
         shop_total_rating = shop_r5 + shop_r4 + shop_r3 + shop_r2 + shop_r1
         
@@ -160,49 +167,45 @@ with c_left:
 with c_right:
     with st.expander("⭐ Product Ratings & Reviews", expanded=True):
         c1, c2, c3, c4, c5 = st.columns(5)
-        r5 = c1.number_input("Prod 5★", value=10)
-        r4 = c2.number_input("Prod 4★", value=2)
-        r3 = c3.number_input("Prod 3★", value=0)
-        r2 = c4.number_input("Prod 2★", value=0)
-        r1 = c5.number_input("Prod 1★", value=0)
+        r5 = c1.number_input("Prod 5★", value=58)
+        r4 = c2.number_input("Prod 4★", value=1)
+        r3 = c3.number_input("Prod 3★", value=2)
+        r2 = c4.number_input("Prod 2★", value=2)
+        r1 = c5.number_input("Prod 1★", value=6)
         
         total_rating_count = r5 + r4 + r3 + r2 + r1
         weighted_sum = (r5*5 + r4*4 + r3*3 + r2*2 + r1*1)
         avg_rating = weighted_sum / total_rating_count if total_rating_count > 0 else 0.0
         st.info(f"Avg Rating: {avg_rating:.2f} ({total_rating_count} ratings)")
 
-        total_reviews = st.number_input("Total Written Reviews", value=total_rating_count)
-        reviews_w_img = st.number_input("Reviews w/ Images", value=0)
-        satisfaction = st.slider("Buyer Satisfaction %", 0, 100, 95)
+        total_reviews = st.number_input("Total Written Reviews", value=52)
+        reviews_w_img = st.number_input("Reviews w/ Images", value=28)
+        satisfaction = st.slider("Buyer Satisfaction %", 0, 100, 85)
 
-    with st.expander("💬 Review Topics", expanded=False):
+    with st.expander("💬 Count Review Topics", expanded=False):
         tc1, tc2 = st.columns(2)
-        rev_qual = tc1.number_input("Quality", 0)
-        rev_srv = tc2.number_input("Service", 0)
-        rev_pack = tc1.number_input("Packaging", 0)
-        rev_price = tc2.number_input("Price", 0)
-        rev_desc = tc1.number_input("Description", 0)
-        rev_ship = tc2.number_input("Shipping", 0)
+        rev_qual = tc1.number_input("Quality", 47)
+        rev_srv = tc2.number_input("Service", 10)
+        rev_pack = tc1.number_input("Packaging", 4)
+        rev_price = tc2.number_input("Price", 11)
+        rev_desc = tc1.number_input("Description", 2)
+        rev_ship = tc2.number_input("Shipping", 5)
     
     with st.expander("📸 Media & Listing Date", expanded=False):
         mc1, mc2 = st.columns(2)
-        vid_count = mc1.number_input("Videos", 0)
-        img_count = mc2.number_input("Images", 1)
-        date_listing = st.date_input("Listing Created", datetime.now())
+        vid_count = mc1.number_input("Videos", 1)
+        img_count = mc2.number_input("Images", 12)
+        date_listing = st.date_input("Listing Created", datetime(2025, 7, 28, 9, 11, 10))
 
 feat_created = get_date_features(date_listing, "created_at")
 feat_shop = get_date_features(date_shop_open, "shop_open_since")
 listing_age_calc = (datetime.now().date() - date_listing).days
 
-shipping_flags = [ship_inst, ship_same, ship_reg, ship_cargo, ship_eco, ship_next]
-total_shipping = sum(shipping_flags)
-
 base_input = {
     'product_name': p_name, 'description': p_desc, 'category': category,
     'condition_encoded': 1 if condition == 'New' else 0,
     'weight_grams': weight, 'min_order': min_order, 'max_order': max_order,
-    'stock': stock, 'sold': 0, 
-    
+
     'is_preorder': 1 if is_preorder else 0,
     'is_discount': 1 if is_discount else 0,
     'is_regular_merchant': 1 if shop_tier == "Regular Merchant" else 0,
@@ -255,7 +258,7 @@ base_input = {
 }
 
 base_input['Log_stock'] = np.log1p(stock)
-base_input['Log_sold'] = np.log1p(0) 
+base_input['Log_sold'] = np.log1p(sold) 
 
 st.divider()
 st.subheader("💰 Price Prediction")