import streamlit as st import requests st.set_page_config(page_title="SuperKart Sales Predictor", page_icon="🛒") st.title("🛒 SuperKart Sales Prediction") st.markdown("Enter product and store details below to get the predicted sales.") with st.form("prediction_form"): Product_Weight = st.number_input("Product Weight", value=12.0) Product_Sugar_Content = st.selectbox("Sugar Content", [0, 1]) Product_Allocated_Area = st.number_input("Allocated Area", value=0.05) Product_MRP = st.number_input("Product MRP", value=150.0) Store_Size = st.selectbox("Store Size", [0, 1, 2]) Store_Location_City_Type = st.selectbox("City Type", [0, 1, 2]) Store_Type = st.selectbox("Store Type", [0, 1, 2, 3]) Store_Age = st.slider("Store Age (years)", 0, 50, 10) product_types = [ "Product_Type_Breads", "Product_Type_Breakfast", "Product_Type_Canned", "Product_Type_Dairy", "Product_Type_Frozen_Foods", "Product_Type_Fruits_and_Vegetables", "Product_Type_Hard_Drinks", "Product_Type_Health_and_Hygiene", "Product_Type_Household", "Product_Type_Meat", "Product_Type_Others", "Product_Type_Seafood", "Product_Type_Snack_Foods", "Product_Type_Soft_Drinks", "Product_Type_Starchy_Foods" ] selected_type = st.selectbox("Product Type", product_types) submitted = st.form_submit_button("Predict Sales") if submitted: input_data = { "Product_Weight": Product_Weight, "Product_Sugar_Content": Product_Sugar_Content, "Product_Allocated_Area": Product_Allocated_Area, "Product_MRP": Product_MRP, "Store_Size": Store_Size, "Store_Location_City_Type": Store_Location_City_Type, "Store_Type": Store_Type, "Store_Age": Store_Age } for pt in product_types: input_data[pt] = 1 if pt == selected_type else 0 api_url = "https://lokiiparihar-SuperkartBackendModalDeploy-XGBoost.hf.space/predict" # Replace with actual backend try: with st.spinner("Predicting..."): res = requests.post(api_url, json=input_data) res.raise_for_status() st.success(f"✅ Predicted Sales: {res.json()['prediction']:.2f} units") except Exception as e: st.error(f"Prediction failed: {e}")