app.py

import streamlit as st
import requests

st.title("SuperKart Sales Prediction Model with Random Forest")

# Input fields for product and store data
Product_Weight = st.number_input("Product Weight", min_value=0.0, value=0.01)
Product_Sugar_Content = st.selectbox("Product Sugar Content", ["Low Sugar", "Regular", "No Sugar"])
Product_Allocated_Area = st.number_input("Product Allocated Area", min_value=0.0, value=0.01)
Product_MRP = st.number_input("Product MRP", min_value=0.0, value=0.01)
Store_Size = st.selectbox("Store Size", ["Small", "Medium", "High"])
Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier 1", "Tier 2", "Tier 3"])
Store_Type = st.selectbox("Store Type", ["Food Mart", "Departmental Store", "Supermarket Type1", "Supermarket Type2"])
Product_Code = st.selectbox("Product Category", ["FD", "DR", "NC"])
Store_Age = st.number_input("Store Age in Years", min_value=0, value=1)
Product_Category = st.selectbox("Product Category", ["Perishable", "Non-Perishable"])

product_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,
    "Product_Code": Product_Code,
    "Store_Age": Store_Age,
    "Product_Category": Product_Category
}

if st.button("Predict", type='primary'):
    response = requests.post("https://ccwizard-SuperKartSalesPredictionRandomForestBackend.hf.space/v1/predict", json=product_data)
    if response.status_code == 200:
        result = response.json()
        predicted_sales = result["Sales"]
        st.write(f"Predicted Product Store Sales Total: {predicted_sales:,.2f}")
    else:
        st.error("Error in API request")