Update src/streamlit_app.py

src/streamlit_app.py

@@ -12,8 +12,8 @@ product_weight = st.number_input("Product Weight (kg)", min_value=0.0, step=0.1,
 product_sugar = st.selectbox("Product Sugar Content", [0, 1])
 product_alloc_area = st.number_input("Allocated Display Area (sq. m)", min_value=0.0, step=0.01, value=0.05)
 product_mrp = st.number_input("Product MRP", min_value=1.0, step=0.5, value=150.0)
-store_size = st.selectbox("Store Size", [0, 1, 2])  # small/medium/high
-store_city_type = st.selectbox("Store Location City Type", [0, 1, 2])  # a/b/c
+store_size = st.selectbox("Store Size", [0, 1, 2])
+store_city_type = st.selectbox("Store Location City Type", [0, 1, 2])
 store_type = st.selectbox("Store Type", [0, 1, 2, 3])
 store_age = st.slider("Store Age (Years)", 0, 30, 10)
 
@@ -51,18 +51,23 @@ if st.button("Predict Sales"):
     with st.spinner("Fetching prediction from backend..."):
         try:
             response = requests.post(
-                "https://lokiiparihar-SuperkartBackendModalDeploy-XGBoost.hf.space/predict",
+                "https://lokiiparihar-superkartbackendmodaldeploy-xgboost.hf.space/predict",
                 json=input_data
             )
             if response.status_code == 200:
                 result = response.json()
-                prediction = result.get("prediction", "N/A")
-                try:
-                    prediction = float(prediction)
-                    st.success(f"✅ Predicted Sales: **{prediction:.2f} units**")
-                except ValueError:
-                    st.error(f"❌ Prediction format error: {prediction}")
+                prediction = result.get("prediction")
+
+                if prediction is not None:
+                    try:
+                        prediction = float(prediction)
+                        st.success(f"✅ Predicted Sales: **{prediction:.2f} units**")
+                    except (ValueError, TypeError):
+                        st.error(f"❌ Prediction format error: {prediction}")
+                else:
+                    st.error("❌ Prediction not returned by backend.")
             else:
                 st.error(f"❌ API Error: Status code {response.status_code}")
+                st.text(f"Response: {response.text}")
         except Exception as e:
             st.error(f"❌ Request failed: {e}")