app.py

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")