Update app.py

app.py

@@ -1,19 +1,21 @@
-import gradio as gr
 import pandas as pd
 import joblib
 
-# Load your trained model
-model = joblib.load("model.pkl")
+# Load trained model
+model = joblib.load("fraud_model.pkl")
 
-def detect_fraud(file):
+def predict_fraud(file):
     df = pd.read_csv(file.name)
-    # Drop 'Class' if it exists
-    if 'Class' in df.columns:
-        df = df.drop(columns=['Class'])
+    predictions = model.predict(df.drop("Class", axis=1))  # Drop target column
+    df["Prediction"] = predictions
+    return df[df["Prediction"] == 1]  # Return only fraudulent predictions
 
-    prediction = model.predict(df)
-    df['Prediction'] = prediction
-    return df
 
-iface = gr.Interface(fn=detect_fraud, inputs=gr.File(label="Upload CSV"), outputs="dataframe")
-iface.launch()
+interface = gr.Interface(
+
+    fn=predict_fraud,
+    inputs=gr.File(label="Upload CSV File"),
+    outputs=gr.Dataframe(label="Fraudulent Transactions"),
+    title="Fraud Detection System",
+    description="Upload a bank transaction CSV file to detect fraud. Ensure the format matches the training dataset (columns V1-V28, Time, Amount, Class)."
+)