Create predict.py

predict.py

@@ -0,0 +1,37 @@
+import pandas as pd
+import joblib
+
+# Load model and encoders
+model = joblib.load("model/model.pkl")
+encoders = joblib.load("model/encoders.pkl")
+
+def predict_transaction(data_dict):
+    # Convert dict to dataframe
+    df = pd.DataFrame([data_dict])
+
+    # Process time
+    df["hour"] = pd.to_datetime(df["time"], format="%H:%M").dt.hour
+    df.drop(columns=["check_id", "time"], inplace=True)
+
+    # Encode categorical features
+    for col in ["employee_id", "terminal_id"]:
+        df[col] = encoders[col].transform(df[col])
+
+    # Predict
+    prediction = model.predict(df)[0]
+    return "Suspicious" if prediction == 1 else "Not Suspicious"
+
+# Example usage
+if __name__ == "__main__":
+    sample = {
+        "check_id": 1005,
+        "employee_id": "E101",
+        "total": 100,
+        "discount_amount": 90,
+        "item_count": 1,
+        "time": "12:10",
+        "terminal_id": "T1"
+    }
+
+    result = predict_transaction(sample)
+    print("Prediction:", result)