app.py

import gradio as gr
import joblib

model = joblib.load("iris_model.pkl")

classes = ["Setosa", "Versicolor", "Virginica"]

def predict_flower(sl, sw, pl, pw):
    pred = model.predict([[sl, sw, pl, pw]])
    return classes[pred[0]]

demo = gr.Interface(
    fn=predict_flower,
    inputs=[
        gr.Number(label="Sepal Length"),
        gr.Number(label="Sepal Width"),
        gr.Number(label="Petal Length"),
        gr.Number(label="Petal Width")
    ],
    outputs="text",
    title="Iris Flower Classification AI",
    description="Predict flower species using Machine Learning"
)

demo.launch()