import gradio as gr
import joblib
import numpy as np

# Load model
model = joblib.load("model.joblib")
labels = ["setosa", "versicolor", "virginica"]

def predict_iris(sepal_length, sepal_width, petal_length, petal_width):
    X = np.array([[sepal_length, sepal_width, petal_length, petal_width]])
    probs = model.predict_proba(X)[0]
    idx = probs.argmax()
    return f"{labels[idx]} (Confidence: {probs[idx]:.2f})"

# Gradio UI
interface = 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="Prediction"),
    title="🌸 Iris Flower Classification",
    description="Enter flower measurements to predict the Iris species"
)

interface.launch()