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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}")
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