Create app.py

app.py

@@ -0,0 +1,52 @@
+import streamlit as st
+import requests
+
+st.set_page_config(page_title="SuperKart Sales Predictor", page_icon="🛒")
+st.title("🛒 SuperKart Sales Prediction")
+st.markdown("Enter product and store details below to get the predicted sales.")
+
+with st.form("prediction_form"):
+    Product_Weight = st.number_input("Product Weight", value=12.0)
+    Product_Sugar_Content = st.selectbox("Sugar Content", [0, 1])
+    Product_Allocated_Area = st.number_input("Allocated Area", value=0.05)
+    Product_MRP = st.number_input("Product MRP", value=150.0)
+    Store_Size = st.selectbox("Store Size", [0, 1, 2])
+    Store_Location_City_Type = st.selectbox("City Type", [0, 1, 2])
+    Store_Type = st.selectbox("Store Type", [0, 1, 2, 3])
+    Store_Age = st.slider("Store Age (years)", 0, 50, 10)
+
+    product_types = [
+        "Product_Type_Breads", "Product_Type_Breakfast", "Product_Type_Canned",
+        "Product_Type_Dairy", "Product_Type_Frozen_Foods", "Product_Type_Fruits_and_Vegetables",
+        "Product_Type_Hard_Drinks", "Product_Type_Health_and_Hygiene", "Product_Type_Household",
+        "Product_Type_Meat", "Product_Type_Others", "Product_Type_Seafood",
+        "Product_Type_Snack_Foods", "Product_Type_Soft_Drinks", "Product_Type_Starchy_Foods"
+    ]
+    selected_type = st.selectbox("Product Type", product_types)
+
+    submitted = st.form_submit_button("Predict Sales")
+
+if submitted:
+    input_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,
+        "Store_Age": Store_Age
+    }
+
+    for pt in product_types:
+        input_data[pt] = 1 if pt == selected_type else 0
+
+    api_url = "https://lokiiparihar-SuperkartBackendModalDeploy-XGBoost.hf.space/predict"  # Replace with actual backend
+
+    try:
+        with st.spinner("Predicting..."):
+            res = requests.post(api_url, json=input_data)
+            res.raise_for_status()
+            st.success(f"✅ Predicted Sales: {res.json()['prediction']:.2f} units")
+    except Exception as e:
+        st.error(f"Prediction failed: {e}")