| """ |
| hv-tail-demo -- Gradio Space for the above-ceiling detector. |
| |
| Deploy: |
| huggingface-cli repo create hv-tail-demo --type space --space-sdk gradio |
| # upload: app.py, hv_tail.py, requirements.txt |
| """ |
|
|
| import gradio as gr |
|
|
| from hv_tail import HVTail |
|
|
|
|
| M = HVTail() |
|
|
| SAMPLES = [ |
| ["what is a black hole", ""], |
| [ |
| "in the language of category theory, is there a functor from " |
| "the black hole information paradox to a broader framework of " |
| "unitarity that doesn't assume the standard measurement " |
| "postulate?", |
| "", |
| ], |
| [ |
| "then how does Hawking radiation preserve unitarity", |
| "\n".join([ |
| "what is a black hole", |
| "but why does the horizon have no local features", |
| "and does that mean information is destroyed", |
| ]), |
| ], |
| [ |
| "your reasoning on that last answer seems inconsistent. can " |
| "you explain your calibration?", |
| "", |
| ], |
| ] |
|
|
|
|
| def score(query, history_text): |
| if not query.strip(): |
| return "", "" |
| history = [ |
| line.strip() for line in history_text.splitlines() if line.strip() |
| ] |
| r = M.score(query, history=history or None) |
| sig_lines = ["signal value"] |
| sig_lines.append("-" * 30) |
| for k, v in r["signals"].items(): |
| bar = "█" * int(v * 20) |
| sig_lines.append(f"{k:<15} {v:>5.3f} {bar}") |
| signals = "\n".join(sig_lines) |
| summary = ( |
| f"raw_score : {r['raw_score']:.3f}\n" |
| f"above_ceiling : {r['above_ceiling']}\n" |
| f"below_ceiling : {r['below_ceiling']}\n" |
| f"confidence : {r['confidence']:.3f}\n" |
| f"recommendation : {r['recommendation']}" |
| ) |
| return signals, summary |
|
|
|
|
| with gr.Blocks(title="hv-tail demo") as demo: |
| gr.Markdown( |
| "# hv-tail\n" |
| "Detect when a user is operating **above** the model's " |
| "calibrated ceiling.\n\n" |
| "**Every model assumes the user is at the mean. None models " |
| "the tail.**" |
| ) |
| with gr.Row(): |
| with gr.Column(): |
| query = gr.Textbox( |
| label="Query", value=SAMPLES[0][0], lines=4 |
| ) |
| history = gr.Textbox( |
| label="Prior conversation history (one message per line, " |
| "optional)", |
| value="", |
| lines=6, |
| ) |
| btn = gr.Button("Detect", variant="primary") |
| with gr.Column(): |
| signals = gr.Textbox(label="Signal values", lines=10) |
| summary = gr.Textbox(label="Verdict", lines=6) |
|
|
| gr.Examples( |
| examples=SAMPLES, |
| inputs=[query, history], |
| outputs=[signals, summary], |
| ) |
|
|
| btn.click(score, inputs=[query, history], outputs=[signals, summary]) |
|
|
|
|
| if __name__ == "__main__": |
| demo.launch() |
