import gradio as gr
import joblib
import numpy as np

# Load trained model and scaler
model = joblib.load("game_model.joblib")
scaler = joblib.load("scaler.joblib")

# Prediction function
def predict_sales(na, eu, jp, other, year):
    X = np.array([[na, eu, jp, other, year]])
    X_scaled = scaler.transform(X)
    pred = model.predict(X_scaled)[0]
    return float(pred)

# Gradio UI
interface = gr.Interface(
    fn=predict_sales,
    inputs=[
        gr.Number(label="NA Sales"),
        gr.Number(label="EU Sales"),
        gr.Number(label="JP Sales"),
        gr.Number(label="Other Sales"),
        gr.Number(label="Year")
    ],
    outputs=gr.Number(label="Predicted Global Sales"),
    title="Game Sales Predictor (KNN Model)",
    description="Enter sales values to predict the total global sales of a game."
)

interface.launch()