Upload folder using huggingface_hub

app.py

@@ -16,7 +16,7 @@ Product_Sugar_Content = st.selectbox("Product Sugar Content", options=["Low Suga
 # Product Allocated Area
 Product_Allocated_Area = st.number_input("Product Allocated Area", min_value=0.000, max_value=1.00, value=0.05, step=0.001)
 # Product Type
-Product_Type = st.selectbox(  "Product Type",  options=["Frozen Foods", "Dairy", "Canned", "Baking Goods", "Health and Hygiene"])
+Product_Type = st.selectbox(  "Product Type",  options=["Frozen Foods", "Dairy", "Canned", "Baking Goods", "Health and Hygiene", "Breads", "Fruits and Vegetables", "Meat", "Seafood", "Soft Drinks", "Hard Drinks", "Breakfast", "Starchyfoods"])
 # Product MRP
 Product_MRP = st.number_input("Product MRP", min_value=0.0, max_value=1000.0, value=100.0, step=1.0)
 # Store Establishment Year
@@ -27,7 +27,9 @@ Store_Size = st.selectbox("Store Size", options=["Small", "Medium", "High"])
 Store_Location_City_Type = st.selectbox("Store Location City Type", options=["Tier 1", "Tier 2", "Tier 3"])
 # Store Type
 Store_Type = st.selectbox("Store Type",options=["Supermarket Type1", "Supermarket Type2", "Departmental Store", "Food Mart"])
-
+#Store Id
+Store_id = st.selectbox("Store Id",options=["OUT001", "OUT002", "OUT003", "OUT004"])
+#calculation of store age
 Current_Year = datetime.now().year
 Store_Age = Current_Year - Store_Establishment_Year
 
@@ -41,7 +43,8 @@ input_data = pd.DataFrame([{
     'Store_Age': Store_Age,
     'Store_Size': Store_Size,
     'Store_Location_City_Type': Store_Location_City_Type,
-    'Store_Type': Store_Type
+    'Store_Type': Store_Type,
+    "Store_id": Store_id
 }])
 
 # Make prediction when the "Predict" button is clicked