import gradio as gr
import joblib
import numpy as np

model = joblib.load("knn_model.pkl")
scaler = joblib.load("scaler.pkl")


def predict_iris(sepal_length, sepal_width, petal_length, petal_width):

    data = np.array([[
        sepal_length,
        sepal_width,
        petal_length,
        petal_width
    ]])

    data_scaled = scaler.transform(data)

    prediction = model.predict(data_scaled)

    return prediction[0]


demo = gr.Interface(
    fn=predict_iris,
    inputs=[
        gr.Number(label="Sepal Length (cm)"),
        gr.Number(label="Sepal Width (cm)"),
        gr.Number(label="Petal Length (cm)"),
        gr.Number(label="Petal Width (cm)")
    ],
    outputs=gr.Textbox(label="Predicted Species"),
    title="Iris Flower Classification using KNN"
)

demo.launch()