"""Gradio demo: linear slope y = wx + b via ONNX Runtime."""

import gradio as gr
import numpy as np
import onnxruntime as ort

session = ort.InferenceSession("slope.onnx")


def predict(x_val: float) -> float:
    x = np.array([[x_val]], dtype=np.float32)
    outputs = session.run(None, {"x": x})
    return float(outputs[0][0, 0])


demo = gr.Interface(
    fn=predict,
    inputs=gr.Number(label="x", value=2.0),
    outputs=gr.Number(label="y = wx + b"),
    title="ONNX Slope Demo",
    description=(
        "PyTorch-trained linear model exported to ONNX. "
        "Trained on y ≈ 2x + 1; enter x to get the predicted y."
    ),
)

demo.launch()