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app.py

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+import streamlit as st
+import requests
+
+API_URL = "https://Hunagypsy-superkart-backend-api.hf.space/v1/predict"
+
+st.title("Product Store Sales Prediction App")
+
+# User Inputs
+Product_Weight = st.number_input("Product Weight", min_value=0.0, value=12.66)
+Product_Sugar_Content = st.selectbox("Product Sugar Content", ["Low Sugar", "Regular", "No Sugar"])
+Product_Allocated_Area = st.selectbox("Product Allocated Area", ["Small", "Medium", "Large"])
+Product_MRP = st.number_input("Product MRP", min_value=0.0, value=100.0)
+Store_Size = st.selectbox("Store Size", ["Small", "Medium", "High"])
+Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier 1", "Tier 2", "Tier 3"])
+Store_Type = st.selectbox("Store Type", ["Type 1", "Type 2", "Type 3", "Type 4"])
+Product_Id_char = st.text_input("Product ID (char)", value="FDX")
+Store_Age_Years = st.number_input("Store Age (Years)", min_value=0, value=5)
+Product_Type_Category = st.selectbox("Product Type Category", ["Food", "Non-Food", "Drinks"])
+
+product_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,
+    "Product_Id_char": Product_Id_char,
+    "Store_Age_Years": Store_Age_Years,
+    "Product_Type_Category": Product_Type_Category
+}
+
+if st.button("Predict"):
+    try:
+        response = requests.post(API_URL, json=product_data)
+        if response.status_code == 200:
+            result = response.json()
+            st.success(f"Predicted Product Store Sales Total: ₹{{result['Sales']:.2f}}")
+        else:
+            st.error(f"API request failed: {{response.status_code}}")
+    except Exception as e:
+        st.error(f"Error: {{e}}")

requirements.txt

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+streamlit==1.45.0
+requests==2.32.3