Create app.py

app.py

@@ -0,0 +1,78 @@
+import streamlit as st
+import pandas as pd
+import joblib
+
+
+def app():
+    st.title('Fraud Prediction')
+    
+    st.header("Transaction Data Input")
+    st.write("Choose to upload a CSV file or manually input transaction data.")
+    
+    # Load pre-trained model
+    with open('model.pkl', 'rb') as file_1:
+        model = joblib.load(file_1)
+
+    # Option to choose upload or manual input
+    option = st.radio("Select input method:", ("Upload CSV", "Manual Input"))
+
+    if option == "Upload CSV":
+        # Option to upload a CSV file
+        file_upload = st.file_uploader("Upload CSV", type=["csv"])
+
+        if file_upload is not None:
+            data = pd.read_csv(file_upload)
+            st.write("Uploaded Data Preview:")
+            st.write(data.head())
+
+            if st.button("Submit CSV"):
+                # Predict using the uploaded CSV data
+                predictions = model.predict(data)
+                data['prediction'] = predictions
+                data['prediction'] = data['prediction'].map({1: 'Fraud Transactions', 0: 'Not Fraud Transactions'})
+
+                st.write("Predictions:")
+                st.write(data[['type','nameOrig', 'nameDest', 'prediction']])
+            
+    elif option == "Manual Input":
+        st.write("Manually input data:")
+        # Manual input of data
+        step = st.number_input("Step", min_value=0)
+        type = st.selectbox("Type", ["TRANSFER", "PAYMENT", "DEBIT", "CASH_OUT", "CASH_IN"])
+        amount = st.number_input("Amount", min_value=0.0)
+        nameOrig = st.text_input("Origin Account Name")
+        oldbalanceOrg = st.number_input("Old Balance (Origin)", min_value=0.0)
+        newbalanceOrig = st.number_input("New Balance (Origin)", min_value=0.0)
+        nameDest = st.text_input("Destination Account Name")
+        oldbalanceDest = st.number_input("Old Balance (Destination)", min_value=0.0)
+        newbalanceDest = st.number_input("New Balance (Destination)", min_value=0.0)
+        isFlaggedFraud = st.selectbox("Is Flagged Fraud?", [0, 1])
+
+        if st.button("Submit"):
+            # Create a DataFrame from manual input
+            manual_data = pd.DataFrame({
+                "step": [step],
+                "type": [type],
+                "amount": [amount],
+                "nameOrig": [nameOrig],
+                "oldbalanceOrg": [oldbalanceOrg],
+                "newbalanceOrig": [newbalanceOrig],
+                "nameDest": [nameDest],
+                "oldbalanceDest": [oldbalanceDest],
+                "newbalanceDest": [newbalanceDest],
+                "isFlaggedFraud": [isFlaggedFraud]
+            })
+
+            st.write("Manual Input Data:")
+            st.write(manual_data)
+
+            # Predict using the manually input data
+            manual_predictions = model.predict(manual_data)
+            manual_data['prediction'] = manual_predictions
+            manual_data['prediction'] = manual_data['prediction'].map({1: 'Fraud Transactions', 0: 'Not Fraud Transactions'})
+
+            st.write("Predictions:")
+            st.write(manual_data[['type','nameOrig', 'nameDest', 'prediction']])
+
+if __name__ == "__main__":
+    app()