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OperationCondition
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# -*- coding: utf-8 -*-
"""Clustering Use_model_cloud.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/19dFamN4Td92NqjpOmSrTE7L1kyiZtmTk
"""

import os
import joblib

"""# **Web/API deployment**

## **Serialize the Model**
"""

saved_model_path = "files/prueba_clustering.joblib"

os.path.getsize(saved_model_path)

saved_model = joblib.load("files/prueba_clustering.joblib")

saved_model

"""## **Write a Model Server**"""


"""### Define Function for Prediction"""

import numpy as np

def predict_cluster(RPM, Aceleraci贸n_LA, Velocidad_LA, Envolvente_LA, Aceleraci贸n_LI, Velocidad_LI, Envolvente_LI, Horas_Op):
    # Asume que el modelo necesita un array de numpy con una fila de features
    input_features = np.array([RPM, Aceleraci贸n_LA, Velocidad_LA, Envolvente_LA, Aceleraci贸n_LI, Velocidad_LI, Envolvente_LI, Horas_Op]).reshape(1, -1)
    cluster_number = saved_model.predict(input_features)[0]
    # Mapeo de n煤mero de cluster a nombre de cluster
    cluster_names = {0: "Operaci贸n Cr铆tica", 1: "Operaci贸n Sub-贸ptima", 2: "Operaci贸n Normal"}
    cluster_name = cluster_names.get(cluster_number, "Cluster no identificado")
    return f"El cluster predicho es: {cluster_name}"

"""### Create Interface"""

import gradio as gr

iface = gr.Interface(
    fn=predict_cluster,
    inputs=[
        gr.Number(label="RPM"),
        gr.Number(label="Aceleraci贸n_LA"),
        gr.Number(label="Velocidad_LA"),
        gr.Number(label="Envolvente_LA"),
        gr.Number(label="Aceleraci贸n_LI"),
        gr.Number(label="Velocidad_LI"),
        gr.Number(label="Envolvente_LI"),
        gr.Number(label="Horas_Op")
    ],
    outputs="text",
    title="Predicci贸n de Condici贸n de Operaci贸n del Activo",
    description="Introduce los valores de las caracter铆sticas del motor para predecir la condici贸n."
)

# Lanzar la aplicaci贸n de Gradio
iface.launch()