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app.py

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+# app.py
+import streamlit as st
+import joblib
+import pandas as pd
+
+# Load the model
+model = joblib.load("best_sales_model.pkl")
+
+st.title("SuperKart Store Sales Forecasting")
+
+# Input form
+st.subheader("Enter Product and Store Details")
+
+product_weight = st.number_input("Product Weight", value=10.0)
+sugar_content = st.selectbox("Product Sugar Content", ["Low Sugar", "Regular", "No Sugar"])
+allocated_area = st.slider("Product Allocated Area", 0.01, 1.0, 0.1)
+product_type = st.selectbox("Product Type", ["Fruits and Vegetables", "Snack Foods", "Frozen Foods", "Dairy", "Household", "Baking Goods", "Canned", "Health and Hygiene", "Meat", "Soft Drinks", "Breads", "Hard Drinks", "Starchy Foods", "Breakfast", "Seafood", "Others"])
+product_mrp = st.number_input("Product MRP", value=100.0)
+store_size = st.selectbox("Store Size", ["Small", "Medium", "High"])
+store_city = st.selectbox("Store City Type", ["Tier 1", "Tier 2", "Tier 3"])
+store_type = st.selectbox("Store Type", ["Supermarket Type2", "Supermarket Type1", "Departmental Store", "Food Mart"])
+store_id = st.selectbox("Store ID", ["OUT001", "OUT002", "OUT003", "OUT004"])
+store_age = st.slider("Store Age (Years)", 0, 50, 10)
+
+# Predict
+if st.button("Predict Sales"):
+    input_data = pd.DataFrame([{
+        'Product_Weight': product_weight,
+        'Product_Sugar_Content': sugar_content,
+        'Product_Allocated_Area': allocated_area,
+        'Product_Type': product_type,
+        'Product_MRP': product_mrp,
+        'Store_Size': store_size,
+        'Store_Location_City_Type': store_city,
+        'Store_Type': store_type,
+        'Store_Id': store_id,
+        'Store_Age': store_age
+    }])
+    
+    prediction = model.predict(input_data)[0]
+    st.success(f"Predicted Sales: {round(prediction, 2)}")

best_sales_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1e54bbb34d2ac12b359137b917fbcf267b4c191d7b05304baf174c7cf2b9eb25
+size 63810675

requirements.txt

@@ -1,3 +1,11 @@
-altair
-pandas
-streamlit
+pandas==2.2.2
+numpy==2.0.2
+scikit-learn==1.6.1
+xgboost==2.1.4
+joblib==1.4.2
+Werkzeug==2.2.2
+flask==2.2.2
+gunicorn==20.1.0
+requests==2.28.1
+uvicorn[standard]
+streamlit==1.43.2