Update app.py

app.py

@@ -1,4 +1,29 @@
+# app.py
 import streamlit as st
+from models.fraud_detection_model import load_fraud_detection_model, predict_fraud
+from utils.preprocessing import preprocess_data_for_streamlit, feature_engineering
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Load model
+model_path = 'models/fraud_detection_model.h5'
+fraud_model = load_fraud_detection_model(model_path)
+
+# Load data
+data_path = 'data/dataset.csv'
+df, X_scaled = preprocess_data_for_streamlit(data_path)
+
+# Streamlit App
+st.title('Fraud Detection Web App')
+
+# Sidebar with user input
+selected_index = st.sidebar.selectbox('Select an index:', df.index)
+selected_data = X_scaled[selected_index].reshape(1, -1)
+
+# Display selected data
+st.write('Selected Data:')
+st.write(df.iloc[selected_index])
+
+# Predict fraud
+if st.button('Predict Fraud'):
+    prediction = predict_fraud(fraud_model, selected_data)
+    result = "Fraud" if prediction[0][0] == 1 else "Non-Fraud"
+    st.write(f'Prediction: {result}')