import streamlit as st import pandas as pd import joblib # Load trained model pipeline model = joblib.load('SuperKart_Mode_v1_0.joblib') # Streamlit app title st.title("🛒 Product Store Sales Prediction App") st.markdown("Enter product and store details below to predict sales.") # Input form with st.form("prediction_form"): product_weight = st.number_input("Product Weight (in kg)", min_value=1.0, max_value=50.0, value=13.5) product_allocated_area = st.number_input("Allocated Area (0 to 1)", min_value=0.001, max_value=1.0, value=0.08) product_mrp = st.number_input("Product MRP (₹)", min_value=1.0, max_value=1000.0, value=250.75) store_age = st.number_input("Store Age (in years)", min_value=1, max_value=100, value=20) product_sugar_content = st.selectbox("Product Sugar Content", ["Low Sugar", "Regular", "No Sugar", "High Sugar"]) product_type = st.selectbox("Product Type", [ "Meat", "Snack Foods", "Hard Drinks", "Dairy", "Canned", "Soft Drinks", "Health and Hygiene", "Baking Goods", "Bread", "Breakfast", "Frozen Foods", "Fruits and Vegetables", "Household", "Seafood", "Starchy Foods", "Others" ]) store_size = st.selectbox("Store Size", ["Small", "Medium", "High"]) store_location = st.selectbox("City Tier", ["Tier 1", "Tier 2", "Tier 3"]) store_type = st.selectbox("Store Type", ["Departmental Store", "Supermarket Type1", "Supermarket Type2", "Food Mart"]) submit = st.form_submit_button("Predict Sales") # Prediction logic if submit: input_dict = { "Product_Weight": [product_weight], "Product_Allocated_Area": [product_allocated_area], "Product_MRP": [product_mrp], "Store_Age": [store_age], "Product_Sugar_Content": [product_sugar_content], "Product_Type": [product_type], "Store_Size": [store_size], "Store_Location_City_Type": [store_location], "Store_Type": [store_type] } input_df = pd.DataFrame(input_dict) # Predict using loaded model prediction = model.predict(input_df)[0] # Show result st.success(f"📈 Predicted Product Store Sales: ₹{prediction:,.2f}")