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| import streamlit as st | |
| import pandas as pd | |
| import joblib | |
| import requests | |
| # Title | |
| st.title("π SuperKart Sales Forecasting") | |
| st.markdown("Enter product and store details to predict sales.") | |
| # Input fields | |
| product_weight = st.number_input("Product Weight (kg)", min_value=1.0, step=0.1) | |
| product_sugar_content = st.selectbox("Sugar Content", ["Low Sugar", "Regular", "No Sugar", "Sugar Free"]) | |
| product_allocated_area = st.slider("Display Area (%)", 0.0, 0.3, 0.05) | |
| product_type = st.selectbox("Product Type", [ | |
| "Meat", "Snack Foods", "Hard Drinks", "Dairy", "Canned", "Soft Drinks", "Health and Hygiene", | |
| "Baking Goods", "Bread", "Breakfast", "Frozen Foods", "Fruits and Vegetables", | |
| "Household", "Seafood", "Starchy Foods", "Others" | |
| ]) | |
| product_mrp = st.number_input("Product MRP (βΉ)", min_value=10.0, step=1.0) | |
| store_size = st.selectbox("Store Size", ["Small", "Medium", "High"]) | |
| store_location_city_type = st.selectbox("City Tier", ["Tier 1", "Tier 2", "Tier 3"]) | |
| store_type = st.selectbox("Store Type", [ | |
| "Departmental Store", "Supermarket Type1", "Supermarket Type2", "Food Mart" | |
| ]) | |
| store_age = st.slider("Store Age (Years)", 1, 40, 15) | |
| # Submit | |
| if st.button("Predict Sales"): | |
| input_data = { | |
| "Product_Weight": product_weight, | |
| "Product_Sugar_Content": product_sugar_content, | |
| "Product_Allocated_Area": product_allocated_area, | |
| "Product_Type": product_type, | |
| "Product_MRP": product_mrp, | |
| "Store_Size": store_size, | |
| "Store_Location_City_Type": store_location_city_type, | |
| "Store_Type": store_type, | |
| "Store_Age": store_age | |
| } | |
| # Call the backend API | |
| try: | |
| response = requests.post("https://<your-backend-username>.huggingface.space/<backend-space-name>/predict", json=input_data) | |
| result = response.json() | |
| if "predicted_sales" in result: | |
| st.success(f"π Predicted Sales: βΉ{result['predicted_sales']}") | |
| else: | |
| st.error(f"Error: {result.get('error', 'Unknown')}") | |
| except Exception as e: | |
| st.error(f"API call failed: {e}") | |