app.py

import gradio as gr

import pickle
with open('modelo.pkl', 'rb') as file:
  knn = pickle.load(file)

def modelo(sepal_length, sepal_width, petal_length, petal_width):
  species = ['Iris-Setosa', 'Iris-Versicolour', 'Iris-Virginica']
  i = knn.predict([[sepal_length, sepal_width, petal_length, petal_width]])[0]
  return species[i]

interfaz = gr.Interface(
    fn=modelo,
    inputs=[
            gr.inputs.Slider(minimum=0.0, maximum=8.0, step=0.1, default=0.0, label='Sepal Length', optional=False),
            gr.inputs.Slider(minimum=0.0, maximum=8.0, step=0.1, default=0.0, label='Sepal Width', optional=False),
            gr.inputs.Slider(minimum=0.0, maximum=8.0, step=0.1, default=0.0, label='Petal Length', optional=False),
            gr.inputs.Slider(minimum=0.0, maximum=8.0, step=0.1, default=0.0, label='Petal Width', optional=False)
    ],
    outputs= gr.outputs.Textbox(type="email", label='Specie'),
    examples= [[6.7, 3.0, 5.2, 2.3], [4.7, 3.2, 1.3, 0.2], [5.0, 3.6, 1.4, 0.2]],
    title = 'Detector de especies de iris',
    description = 'Este modelo está desarrollado para la clasificación de flores de la especie Iris.',
    article = 'Aplicación desarrollada con fines docentes en el curso Saturdays.ai',
    theme = 'peach'
)

interfaz.launch()