app.py

import gradio as gr
import jax
import numpy as np
# Import your JAX model here

def predict(x: float, y: float):
    """
    Replace this with your actual JAX model inference
    """
    # This is just a placeholder - replace with your model
    return {
        "prediction": float(np.sin(x * 3.14) * np.cos(y * 3.14)),
        "x": x,
        "y": y
    }

# Create Gradio interface with API endpoint
demo = gr.Interface(
    fn=predict,
    inputs=[
        gr.Number(label="X coordinate", minimum=0, maximum=1),
        gr.Number(label="Y coordinate", minimum=0, maximum=1)
    ],
    outputs=gr.JSON(),
    title="Research Visualization ML Model",
    description="Click on the square to generate predictions",
    allow_flagging="never"
)

# Enable API endpoint
demo.launch()