"""
hv-mode-demo -- Gradio Space for the hv-mode cognitive delivery router.

Deploy:
    huggingface-cli repo create hv-mode-demo --type space --space-sdk gradio
    # then upload this file + hv_mode.py + requirements.txt
"""

import gradio as gr

from hv_mode import HVMode


MODEL = HVMode()


SAMPLES = [
    [
        "A black hole is a region of spacetime where gravity is so strong "
        "that nothing - no particles or even electromagnetic radiation such "
        "as light - can escape from it. The theory of general relativity "
        "predicts that a sufficiently compact mass can deform spacetime to "
        "form a black hole. The boundary of the region from which no escape "
        "is possible is called the event horizon. Although the event horizon "
        "has profound effects on the fate of an object that crosses it, it "
        "has no locally detectable features. A black hole acts as a perfect "
        "black body, and moreover, it emits Hawking radiation. Note: results "
        "may vary depending on the observer's frame of reference.",
        "show me a picture of what a black hole is",
    ],
    [
        "To change a flat tire: first, park on level ground and engage the "
        "parking brake. Second, loosen the lug nuts slightly with the wrench. "
        "Third, jack up the car until the tire clears the ground. Fourth, "
        "remove the lug nuts and take off the tire. Fifth, mount the spare "
        "tire and hand-tighten the lug nuts. Finally, lower the car and "
        "tighten the lug nuts fully. Note: check the spare's pressure first.",
        "how do I change a flat tire",
    ],
    [
        "Approach A costs 40 USD and takes 3 hours. Approach B costs 120 USD "
        "and takes 1 hour. Approach C costs 60 USD and takes 2 hours. Mean "
        "cost is about 73 USD.",
        "compare the options in color",
    ],
]


def render(llm_text: str, query: str, mode: str):
    if not llm_text.strip():
        return "<p style='color:#888'>Enter some text above.</p>", ""
    meaning = MODEL.extract(llm_text)
    if mode == "auto":
        mode = MODEL.best_mode(query or llm_text, meaning=meaning)
    content, mime = MODEL.render(meaning, mode)
    dist = MODEL.detect(query or llm_text, meaning=meaning)
    dist_str = "\n".join(
        f"{m:<14} {p:.3f}" for m, p in
        sorted(dist.items(), key=lambda kv: -kv[1])
    )
    return content, dist_str


with gr.Blocks(title="hv-mode demo") as demo:
    gr.Markdown(
        "# hv-mode\n"
        "LLM text in, reader-mode-matched output out.\n\n"
        "**Storage is not delivery.**"
    )
    with gr.Row():
        with gr.Column():
            text = gr.Textbox(
                label="LLM response",
                lines=10,
                value=SAMPLES[0][0],
            )
            query = gr.Textbox(
                label="Original query (optional)",
                value=SAMPLES[0][1],
            )
            mode = gr.Dropdown(
                choices=[
                    "auto", "text", "card_deck", "svg_tree",
                    "svg_strip", "pacman", "color_field", "rhythm",
                ],
                value="auto",
                label="Output mode",
            )
            btn = gr.Button("Render", variant="primary")
        with gr.Column():
            output = gr.HTML(label="Rendered output")
            dist = gr.Textbox(label="Mode distribution", lines=8)

    gr.Examples(
        examples=SAMPLES,
        inputs=[text, query],
        outputs=[output, dist],
    )

    btn.click(render, inputs=[text, query, mode], outputs=[output, dist])


if __name__ == "__main__":
    demo.launch()