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| import streamlit as st | |
| import requests | |
| st.title("Welcome to SuperKart Revenue Forecast") #Complete the code to define the title of the app. | |
| # 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=0.004, max_value = 0.298, value=0.1) #Complete the code to define the UI element for Product_Allocated_Area | |
| Product_MRP = st.number_input("Product MRP", min_value=31, max_value = 266, value=160) #Complete the code to define the UI element for Product_MRP | |
| Store_Size = st.selectbox("Store Size", ["High", "Medium", "Small"]) #Complete the code to define the UI element for Store_Size | |
| Store_Location_City_Type = st.selectbox("Store Location Type", ["Tier 1", "Tier 2", "Tier 3"]) #Complete the code to define the UI element for Store_Location_City_Type | |
| Store_Type = st.selectbox("Store Type", ["Departmental Store", "Food Mart", "Supermarket Type1", "Supermarket Type2"]) #Complete the code to define the UI element for Store_Type | |
| Product_Id_char = st.selectbox("DR", ["FD", "NC"]) #Complete the code to define the UI element for Product_Id_char | |
| Store_Age_Years = st.number_input("Store_Age_Years", min_value=16, max_value = 38, value=20) #Complete the code to define the UI element for Store_Age_Years | |
| Product_Type_Category = st.selectbox("Product Type/Category", ["Baking Goods", "Breads", "Breakfast", "Canned", "Dairy", "Frozen Foods", "Fruits & Vegetables", "Hard Drinks", | |
| "Health & Hygiene", "Household", "Meat", "Others", "Seafood", "Snack Foods", "Soft Drinks", | |
| "Starchy Foods"]) #Complete the code to define the UI element for Product_Type_Category | |
| 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", type='primary'): | |
| response = requests.post("https://nu99-SuperKartRevenueForecastingNU.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") |