import requests
import streamlit as st
import pandas as pd

st.title("SmartKart Total Sales Prediction")
st.subheader("Online Prediction")

# ── Numeric fields ─────────────────────────────────────────────────────────────
Product_Weight          = st.number_input("Product Weight (kg)",          min_value=0.0, value=1.0)
Product_Allocated_Area  = st.number_input("Product Allocated Area (sq ft)", min_value=0.0, value=10.0)
Product_MRP             = st.number_input("Product MRP ($)",              min_value=0.0, value=100.0)
Store_Age               = st.number_input("Store Age (years)",            min_value=0,   value=10)

# ── Ordinal fields ─────────────────────────────────────────────────────────────
Product_Sugar_Content = st.selectbox("Product Sugar Content", ["No Sugar", "Low Sugar", "Regular"])
sugar_map = {"No Sugar": 0, "Low Sugar": 1, "Regular": 2}

Store_Size = st.selectbox("Store Size", ["Small", "Medium", "Large"])
size_map = {"Small": 1, "Medium": 2, "Large": 3}

Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier 1", "Tier 2", "Tier 3"])
tier_map = {"Tier 1": 1, "Tier 2": 2, "Tier 3": 3}

# ── Categorical fields (dropdowns with correct options) ────────────────────────
Store_Type = st.selectbox("Store Type", [
    "Departmental Store", "Food Mart",
    "Supermarket Type1", "Supermarket Type2"
])

Product_Type = st.selectbox("Product Type", [
    "Baking Goods", "Breads", "Breakfast", "Canned", "Dairy",
    "Frozen Foods", "Fruits and Vegetables", "Hard Drinks",
    "Health and Hygiene", "Household", "Meat", "Others",
    "Seafood", "Snack Foods", "Soft Drinks", "Starchy Foods"
])

# ── Build payload (send raw strings — backend handles encoding) ────────────────
payload = {
    "Product_Weight":               Product_Weight,
    "Product_Allocated_Area":       Product_Allocated_Area,
    "Product_MRP":                  Product_MRP,
    "Store_Age":                    Store_Age,
    "Product_Sugar_Content_Ord":    sugar_map[Product_Sugar_Content],
    "Store_Size_Ord":               size_map[Store_Size],
    "Store_Location_City_Type_Ord": tier_map[Store_Location_City_Type],
    "Store_Type":                   Store_Type,
    "Product_Type":                 Product_Type
}

# ── Predict ────────────────────────────────────────────────────────────────────
if st.button("Predict Total Sales", type="primary"):
    response = requests.post(
        "https://tifischer-smartkart-prediction-backend.hf.space/v1/predict",
        json=payload,
        timeout=30
    )
    if response.status_code == 200:
        result = response.json()
        st.success(f"Predicted Total Sales: ${result['Predicted_Total_Sales']}")
    else:
        st.error(f"Error in API request: {response.status_code}")