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app.py

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+
+import streamlit as st
+import requests
+
+st.title("SuperKart Sales Prediction Model with Random Forest")
+
+# Input fields for product and store data
+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.number_input("Product Allocated Area", min_value=0.0, value=1.0)
+Product_MRP = st.number_input("Product MRP", min_value=0.0, value=300.0)
+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", ["Food Mart", "Departmental Store", "Supermarket Type1", "Supermarket Type2"])
+Product_Code = st.selectbox("Product Category", ["FD", "DR", "NC"])
+Store_Age = st.number_input("Store Age in Years", min_value=0, value=50)
+Product_Category = st.selectbox("Product Category", ["Perishable", "Non-Perishable"])
+
+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_Code": Product_Code,
+    "Store_Age": Store_Age,
+    "Product_Category": Product_Category
+}
+
+if st.button("Predict", type='primary'):
+    response = requests.post("https://ccwizard-SuperKartSalesPredictionRandomForestFrontend.hf.space/v1/predict", json=product_data)    # Complete the code to enter user name and space name to correctly define the endpoint
+    if response.status_code == 200:
+        result = response.json()
+        predicted_sales = result["Sales"]
+        st.write(f"Predicted Product Store Sales Total: ₹{predicted_sales:.2f}")
+    else:
+        st.error("Error in API request")