|
|
| import streamlit as st |
| import requests |
|
|
| st.title("SuperKart Sales Forecasting App") |
|
|
| |
| 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=16.0) |
| Product_MRP = st.number_input("Product MRP", min_value=0.0, value=250.0) |
|
|
| Store_Size = st.selectbox("Store Size", ["Small", "Medium", "High"]) |
| Store_Location_City_Type = st.selectbox("Store Location City Type", ["Tier1", "Tier2", "Tier3"]) |
| Store_Type = st.selectbox("Store Type", ["Grocery Store", "Supermarket Type1", "Supermarket Type2", "Supermarket Type3", "Food Mart"]) |
|
|
| Product_Id_char = st.selectbox("Product Id Char", ["FD", "DR", "NC"]) |
| Store_Age_Years = st.number_input("Store Age (Years)", min_value=0, value=14, step=1) |
| Store_Age_Years = int(Store_Age_Years) |
| Product_Type_Category = st.selectbox("Product Type 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_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://nimerml-backend.hf.space/v1/predict", |
| json=product_data |
| ) |
| 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") |
|
|
