import streamlit as st import requests st.title("Super Kart Product Pricing Predictor") # Input fields for product and store data Product_Weight = st.number_input("Product Weight", min_value=0.0, value=10.00) Product_Sugar_Content_Options = ["Low Sugar", "Regular", "No Sugar"] Product_Sugar_Content = st.selectbox( "Product Sugar Content: ", Product_Sugar_Content_Options, index = 0, format_func=lambda x: x ) Product_Allocated_Area = st.number_input("Product Allocated Area", min_value=0.0, value = 100.00) Product_MRP = st.number_input("Product MRP", min_value=0.0, value=100.00) Store_Id_Options = ["OUT004", "OUT001", "OUT003", "OUT002"] Store_Id = st.selectbox( "Store Id: ", Store_Id_Options, index = 0, format_func=lambda x: x ) Product_Type_Options = [ 'Dairy', 'Soft Drinks', 'Baking Goods', 'Meat', 'Frozen Foods', 'Snack Foods', 'Hard Drinks', 'Health and Hygiene', 'Breads', 'Fruits and Vegetables', 'Starchy Foods', 'Canned', 'Household', 'Others', 'Seafood', 'Breakfast' ] Product_Type = st.selectbox( "Product Type: ", Product_Type_Options, index = 0, format_func=lambda x: x ) Store_Size_Options = ["Medium", "Large", "Small"] Store_Size = st.selectbox( "Store Size: ", Store_Size_Options, index = 0, format_func=lambda x: x ) Store_Location_City_Type_Options = ["Tier 2", "Tier 1", "Tier 3"] Store_Location_City_Type = st.selectbox( "Store Location City Type: ", Store_Location_City_Type_Options, index = 0, format_func=lambda x: x ) Store_Type_Options = ['Supermarket Type2', 'Supermarket Type1', 'Departmental Store', 'Food Mart'] Store_Type = st.selectbox( "Store Type: ", Store_Type_Options, index = 0, format_func=lambda x: x ) Store_Age_Years_Options = ["1987", "1998", "1999", "2009"] Store_Age_Years = st.selectbox( "Store Opening Year: ", Store_Age_Years_Options ) product_data = { "Product_Weight": Product_Weight, "Product_Sugar_Content": Product_Sugar_Content_Options.index(Product_Sugar_Content), "Product_Allocated_Area": Product_Allocated_Area, "Product_MRP": Product_MRP, "Store_Id": Store_Id_Options.index(Store_Id), "Store_Size": Store_Size_Options.index(Store_Size), "Store_Location_City_Type": Store_Location_City_Type_Options.index(Store_Location_City_Type), "Store_Type": Store_Type_Options.index(Store_Type), "Store_Age_Years": int(Store_Age_Years), "Product_Type": Product_Type_Options.index(Product_Type) } if st.button("Predict", type='primary'): response = requests.post("https://rpeltier-SuperKartPredictorBackend.hf.space/v1/predict", json=product_data) if response.status_code == 200: result = response.json() predicted_sales = result["PredictedPrice"] st.write(f"Predicted Store Sales Total: ${predicted_sales :,.2f}") else: st.error("Error in API request")