Deploy Streamlit UI (connects to singhina/superkart-backend)

streamlit_app.py

@@ -2,33 +2,39 @@ import streamlit as st
 import pandas as pd
 import requests, os
 
+# Page config
 st.set_page_config(page_title="SuperKart Forecast", layout="centered")
 st.title("🛒 SuperKart Quarterly Sales Forecast")
 
-BACKEND_URL = os.getenv(
-    "BACKEND_URL",
-    "https://singhina-superkart-backend.hf.space"
-)
+# Point to your Flask backend
+BACKEND_URL = os.getenv("BACKEND_URL", "$BACKEND_URL")
 
-c1, c2 = st.columns(2)
-with c1:
-    pw  = st.number_input("Product Weight",           0.0,100.0,12.5,0.1)
-    pa  = st.number_input("Allocated Area Ratio",     0.0,  1.0,0.08,0.005)
-    mrp = st.number_input("Product MRP (₹)",          0.0,1000.0,50.0,1.0)
-    year= st.number_input("Store Established Year",1900,2025,2015,1)
-    size= st.selectbox("Store Size", ["Low","Medium","High"])
-with c2:
-    city = st.selectbox("City Tier", ["Tier 1","Tier 2","Tier 3"])
-    stype= st.selectbox("Store Type", [
-        "Departmental Store","Supermarket Type 1",
-        "Supermarket Type 2","Food Mart"
-    ])
-    prefix=st.text_input("Product Prefix","FD")
-    pnum  =st.number_input("Product Numeric ID", 0,100000,6114,1)
-    age   =st.number_input("Store Age (yrs)",    0,   50,   int(pd.Timestamp.now().year-year),1)
+# Input form
+with st.form("forecast_form"):
+    c1, c2 = st.columns(2)
+    with c1:
+        pw   = st.number_input("Product Weight (kg)", 0.0, 100.0, 12.5, 0.1)
+        pa   = st.number_input("Allocated Area Ratio", 0.0, 1.0,   0.08, 0.005)
+        mrp  = st.number_input("Product MRP (₹)",      0.0, 1000.0,50.0,  1.0)
+        year = st.number_input("Store Established Year",1900,2025,2015,1)
+        size = st.selectbox("Store Size", ["low","medium","high"])
+    with c2:
+        city   = st.selectbox("City Tier", ["Tier 1","Tier 2","Tier 3"])
+        stype  = st.selectbox("Store Type", [
+            "Departmental Store","Supermarket Type 1",
+            "Supermarket Type 2","Food Mart"
+        ])
+        prefix = st.text_input("Product Prefix","FD")
+        pnum   = st.number_input("Product Numeric ID", 0, 100000, 6114, 1)
+        age    = st.number_input(
+            "Store Age (yrs)", 0, 50,
+            int(pd.Timestamp.now().year - year), 1
+        )
+    submitted = st.form_submit_button("🔮 Predict")
 
-if st.button(" Predict"):
-    payload={"data":[{
+# Submit & show result
+if submitted:
+    payload = {"data":[{
         "Product_Weight":pw,
         "Product_Allocated_Area":pa,
         "Product_MRP":mrp,
@@ -40,7 +46,10 @@ if st.button(" Predict"):
         "Product_Num":pnum,
         "Store_Age":age
     }]}
-    r = requests.post(f"{BACKEND_URL}/predict", json=payload)
-    r.raise_for_status()
-    pred = r.json()["predictions"][0]
-    st.success(f" Forecasted Sales: ₹{pred:,.2f}")
+    try:
+        r = requests.post(f"{BACKEND_URL}/predict", json=payload, timeout=10)
+        r.raise_for_status()
+        pred = r.json()["predictions"][0]
+        st.success(f"🚀 Forecasted Sales: ₹{pred:,.2f}")
+    except Exception as e:
+        st.error(f"❌ Error: {e}")