app.py

import gradio as gr
from predict_impulse import predict_impulse

def run(category, amount, payment_method, day):
    result = predict_impulse(
        category=category,
        amount=amount,
        payment_method=payment_method,
        day=day
    )

    if result["impulsive"]:
        return f"🚨 Impulsive Spend Detected\nConfidence: {result['confidence']}"
    else:
        return f"✅ Normal Spend\nConfidence: {result['confidence']}"

demo = gr.Interface(
    fn=run,
    inputs=[
        gr.Dropdown(
            ["Dining", "Entertainment", "Subscriptions", "Groceries", "Transport", "Utilities"],
            label="Category"
        ),
        gr.Number(label="Amount"),
        gr.Dropdown(
            ["Cash", "Debit Card", "Credit Card", "Bank Transfer"],
            label="Payment Method"
        ),
        gr.Dropdown(
            ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"],
            label="Day of Week"
        )
    ],
    outputs=gr.Textbox(label="Impulse Analysis"),
    title="Sensei Budget AI – Impulse Detection",
    description="Detects impulsive spending behavior using a trained ML model + Opik observability."
)

demo.launch()