app.py

# Import necessary libraries
import gradio as gr
import numpy as np
import pandas as pd
import tensorflow as tf
from joblib import load


try:
   
    custom_objects = {'mae': tf.keras.losses.MeanAbsoluteError()}
    model = tf.keras.models.load_model('elevator_health_model.h5', custom_objects=custom_objects)
    
    scaler = load('elevator_data_scaler.joblib')
    print("Model and scaler loaded successfully.")
except Exception as e:
    print(f"Error loading model or scaler: {e}")
   
    model = None
    scaler = None


def predict_health(ball_bearing, humidity, vibration):
    """
    This function takes the user's input, processes it, and returns the health score.
    """
    if model is None or scaler is None:
        return "Error: Model or scaler not loaded. Please check the logs."

   
    input_df = pd.DataFrame([[ball_bearing, humidity, vibration]], 
                            columns=['ball-bearing', 'humidity', 'vibration'])

    # load data scaler
    input_scaled = scaler.transform(input_df)

    # prediksi engan model
    reconstruction = model.predict(input_scaled)

    
    health_index = np.mean(np.abs(input_scaled - reconstruction), axis=1)[0]

    
    threshold = 0.1
    
    if health_index < threshold:
        status = "HEALTHY"
        explanation = "The elevator is operating within normal parameters."
    else:
        status = "WARNING! ANOMALY DETECTED"
        explanation = "The elevator is showing signs of abnormal behavior. An inspection is recommended."

    # Format output string
    result = (
        f"Health Index Score: {health_index:.4f}\n"
        f"Status: {status}\n\n"
        f"Explanation: {explanation}"
    )
    
    return result


demo = gr.Interface(
    fn=predict_health,
    inputs=[
        gr.Number(label="Ball Bearing Value"),
        gr.Number(label="Humidity Value"),
        gr.Number(label="Vibration Value")
    ],
    outputs=gr.Textbox(label="Health Status Result", lines=5),
    title="Elevator Health Monitoring",
    description="Enter the current sensor readings from the elevator to get its real-time health index. A low score indicates normal operation, while a high score suggests an anomaly."
)


if __name__ == "__main__":
    demo.launch(server_port=7685)