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import streamlit as st |
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import requests |
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import pandas as pd |
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st.title(" SuperKart Sales Prediction App") |
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st.write("Predict the **Product_Store_Sales_Total** using Machine Learning!") |
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st.header(" Single Prediction") |
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Product_Weight = st.number_input("Product Weight", min_value=0.0, step=0.1) |
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Product_Allocated_Area = st.number_input("Allocated Area", min_value=0.0, step=1.0) |
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Product_MRP = st.number_input("Product MRP", min_value=0.0, step=1.0) |
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Store_Establishment_Year = st.number_input("Store Establishment Year", min_value=1900, max_value=2025, value=2010) |
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Store_Size = st.selectbox("Store Size", ["Small", "Medium", "High"]) |
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Store_Location_City_Type = st.selectbox("City Type", ["Tier 3", "Tier 2", "Tier 1"]) |
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Product_Sugar_Content = st.selectbox("Sugar Content", ["Low Sugar", "Regular", "No Sugar"]) |
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Product_Type = st.text_input("Product Type (e.g., Snack Foods)") |
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Store_Type = st.text_input("Store Type (e.g., Supermarket Type 1)") |
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data = { |
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"Product_Weight": Product_Weight, |
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"Product_Allocated_Area": Product_Allocated_Area, |
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"Product_MRP": Product_MRP, |
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"Store_Establishment_Year": Store_Establishment_Year, |
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"Store_Size": Store_Size, |
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"Store_Location_City_Type": Store_Location_City_Type, |
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"Product_Sugar_Content": Product_Sugar_Content, |
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"Product_Type": Product_Type, |
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"Store_Type": Store_Type, |
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} |
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if st.button("Predict Sales"): |
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try: |
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response = requests.post("https://rajanan-backend.hf.space/v1/predict", json=data) |
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if response.status_code == 200: |
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result = response.json() |
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st.success(f" Predicted Sales: {result['Predicted_Product_Store_Sales_Total']}") |
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else: |
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st.error(" Error from API!") |
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except: |
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st.error(" Unable to connect to backend API") |
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st.header(" Batch Prediction (Upload CSV)") |
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uploaded_file = st.file_uploader("Upload CSV File", type=['csv']) |
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if uploaded_file: |
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if st.button("Predict Batch Sales"): |
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try: |
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response = requests.post("https://rajanan-backend.hf.space/v1/predict_batch", files={"file": uploaded_file}) |
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if response.status_code == 200: |
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result = pd.read_json(response.text) |
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st.write(result) |
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st.success(" Batch predictions generated!") |
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else: |
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st.error("Error from backend API") |
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except: |
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st.error("Failed to connect to API") |
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