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0c96590 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | import streamlit as st
import requests
API_URL = "https://nohafx-superkart-predictor.hf.space/predict"
st.title("🛒 SuperKart Product Sales Predictor")
st.write("Enter product and store details to predict sales.")
product_weight = st.number_input("Product Weight", min_value=0.0, value=12.5)
product_sugar = st.selectbox("Product Sugar Content", ["Low Fat", "Regular", "Low Sugar"])
product_area = st.number_input("Product Allocated Area", min_value=0.0, max_value=1.0, value=0.05)
product_type = st.selectbox("Product Type", [
"Snack Foods", "Dairy", "Fruits and Vegetables",
"Frozen Foods", "Household", "Baking Goods",
"Canned", "Health and Hygiene", "Soft Drinks",
"Meat", "Breads", "Hard Drinks", "Others",
"Starchy Foods", "Breakfast", "Seafood"
])
product_mrp = st.number_input("Product MRP", min_value=0.0, value=150.75)
store_size = st.selectbox("Store Size", ["Small", "Medium", "High"])
store_location = st.selectbox("Store Location City Type", ["Tier 1", "Tier 2", "Tier 3"])
store_type = st.selectbox("Store Type", [
"Supermarket Type1", "Supermarket Type2",
"Supermarket Type3", "Grocery Store"
])
store_age = st.number_input("Store Age (Years)", min_value=0, value=15)
if st.button("🔍 Predict Sales"):
input_data = {
"Product_Weight": product_weight,
"Product_Sugar_Content": product_sugar,
"Product_Allocated_Area": product_area,
"Product_Type": product_type,
"Product_MRP": product_mrp,
"Store_Size": store_size,
"Store_Location_City_Type": store_location,
"Store_Type": store_type,
"Store_Age": store_age
}
try:
response = requests.post(API_URL, json=input_data)
if response.status_code == 200:
prediction = response.json()["prediction"]
st.success(f"✅ Predicted Sales: **${prediction:,.2f}**")
else:
st.error(f"❌ Error: {response.text}")
except Exception as e:
st.error(f"❌ Connection Error: {str(e)}")
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