Create app.py

app.py

@@ -0,0 +1,33 @@
+import streamlit as st
+import numpy as np
+import pickle
+import pandas as pd
+
+# Load the trained model
+def load_model():
+    with open("walmart_sales_model.pkl", "rb") as f:
+        model = pickle.load(f)
+    return model
+
+# Load the model
+model = load_model()
+
+# Streamlit UI
+def main():
+    st.title("🛒 Walmart Sales Prediction")
+    st.write("Enter the input features below to predict the weekly sales.")
+    
+    # User inputs
+    temp = st.number_input("Enter Temperature (Celsius)", value=20.0)
+    fuel_price = st.number_input("Enter Fuel Price", value=3.5)
+    cpi = st.number_input("Enter CPI", value=200.0)
+    unemployment = st.number_input("Enter Unemployment Rate", value=5.0)
+    holiday_flag = st.selectbox("Is it a Holiday?", [0, 1])
+    
+    if st.button("Predict Sales"):
+        features = np.array([[temp, fuel_price, cpi, unemployment, holiday_flag]])
+        prediction = model.predict(features)
+        st.success(f"Predicted Weekly Sales: ${prediction[0]:,.2f}")
+
+if __name__ == "__main__":
+    main()