src/streamlit_app.py

import streamlit as st
import requests

st.title("🛒 SuperKart Sales Predictor")

# Input fields
inputs = {
    'Product_Weight': st.number_input("Weight (kg)", value=12.0),
    'Product_Allocated_Area': st.number_input("Allocated Area", value=0.05),
    'Product_MRP': st.number_input("MRP (₹)", value=150.0),
    'Store_Age': st.number_input("Store Age", value=15),
    'Product_Sugar_Content': st.selectbox("Sugar Content", ['Low', 'Regular', 'No Sugar']),
    'Product_Type': st.selectbox("Product Type", ['Dairy', 'Meat', 'Snack Foods', 'Others']),
    'Store_Size': st.selectbox("Store Size", ['Small', 'Medium', 'High']),
    'Store_Location_City_Type': st.selectbox("City Tier", ['Tier 1', 'Tier 2', 'Tier 3']),
    'Store_Type': st.selectbox("Store Type", ['Departmental Store', 'Supermarket Type1', 'Food Mart'])
}

# Prediction button
if st.button("Predict Sales"):
    try:
        #response = requests.post("http://host.docker.internal:7860/predict", json=inputs)
        response = requests.post("https://labhara-superkart-backend.hf.space/predict", json=inputs)
        if response.ok:
            result = response.json()["predicted_sales"]
            st.success(f"💰 Predicted Sales: ₹{result}")
        else:
            st.error("Failed to get prediction.")
    except:
        st.error("Could not reach backend.")