app.py

import gradio as gr
from datasets import load_dataset
import numpy as np
from PIL import Image

def show_first():
    ds = load_dataset("MultimodalUniverse/jwst", split="train", streaming=True)
    rec = next(iter(ds))
    img = rec["image"]

    # convert the flux array to a viewable grayscale image
    flux = np.array(img["flux"], dtype=np.float32)
    lo = np.percentile(flux, 1)
    hi = np.percentile(flux, 99)
    if hi <= lo:  # fallback if data is odd
        lo, hi = float(flux.min()), float(flux.max())
    norm = np.clip((flux - lo) / (hi - lo + 1e-9), 0, 1)
    arr = (norm * 255).astype(np.uint8)
    pil = Image.fromarray(arr, mode="L")

    caption = f"object_id: {rec.get('object_id')}, band: {img.get('band')}"
    return pil, caption

demo = gr.Interface(
    fn=show_first,
    inputs=None,
    outputs=[gr.Image(type="pil", label="Preview"), gr.Textbox(label="Info", lines=2)],
    title="JWST sample preview",
    description="First streamed record as image + a little metadata."
)

demo.launch()