SuperKart / app.py
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Deploy Streamlit frontend with model and CSV
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import streamlit as st
import pandas as pd
import requests
st.title("πŸ›’ SuperKart Quarterly Sales Predictor")
# Input form
st.subheader("πŸ” Predict Store's Quarterly Sales")
store_id = st.selectbox("Store ID", ["OUT001", "OUT002", "OUT003", "OUT004"])
product_type = st.selectbox("Product Type", ["Dairy", "Soft Drinks", "Meat", "Canned", "Frozen Foods"])
sugar_content = st.selectbox("Product Sugar Content", ["Low", "Medium", "High", "No Added Sugar"])
store_type = st.selectbox("Store Type", ["Supermarket Type1", "Supermarket Type2", "Grocery Store", "Food Mart"])
city_type = st.selectbox("City Type", ["Urban", "Semi-Urban", "Rural"])
store_size = st.selectbox("Store Size", ["Small", "Medium", "High"])
est_year = st.number_input("Store Establishment Year", min_value=1980, max_value=2025, value=2005)
weight = st.number_input("Product Weight", min_value=0.0, value=12.0)
area = st.number_input("Product Allocated Area", min_value=0.0, value=125.0)
mrp = st.number_input("Product MRP", min_value=0.0, value=120.0)
input_data = pd.DataFrame([{
'Store_Id': store_id,
'Product_Type': product_type,
'Product_Sugar_Content': sugar_content,
'Store_Type': store_type,
'Store_Location_City_Type': city_type,
'Store_Size': store_size,
'Store_Establishment_Year': est_year,
'Product_Weight': weight,
'Product_Allocated_Area': area,
'Product_MRP': mrp
}])
if st.button("Predict Sales"):
api_url = "https://abcabcabc999--superkart.hf.space/v1/storesales"
response = requests.post(api_url, json=input_data.to_dict(orient='records'))
if response.status_code == 200:
result = response.json()
st.success(f"πŸ“¦ Predicted Total Sales: β‚Ή{result['Total_Store_Sales']:,.2f}")
else:
st.error(f"❌ API Error: {response.text}")
st.subheader("πŸ“ Batch Prediction via CSV")
file = st.file_uploader("Upload CSV", type=["csv"])
if file and st.button("Predict Batch"):
response = requests.post("https://abcabcabc999--superkart.hf.space/v1/storesalesbatch", files={"file": file})
if response.status_code == 200:
st.write(pd.DataFrame(response.json()))
else:
st.error(f"❌ Batch API Error: {response.text}")