app.py

import gradio as gr
import joblib
import pandas as pd

# Model ve scaler'ı yükle
model = joblib.load("xgb_model.pkl")
scaler = joblib.load("scaler.pkl")

def predict_quality(pressure, temp_x_pressure, fusion_metric):
    input_df = pd.DataFrame([[pressure, temp_x_pressure, fusion_metric]], 
                            columns=["Pressure (kPa)", "Temperature x Pressure", "Material Fusion Metric"])
    scaled = scaler.transform(input_df)
    prediction = model.predict(scaled)[0]
    return float(prediction)

iface = gr.Interface(
    fn=predict_quality,
    inputs=[
        gr.Number(label="Pressure (kPa)"),
        gr.Number(label="Temperature x Pressure"),
        gr.Number(label="Material Fusion Metric")
    ],
    outputs=gr.Number(label="Kalite Skoru"),
    title="Kalite Skoru Tahmin Modeli",
    description="Pressure, Temperature x Pressure ve Material Fusion Metric değerlerini giriniz, kalite skorunu tahmin eder."
)

# Spaces için doğrudan launch() çağrısı
iface.launch(server_name="0.0.0.0", server_port=7860)