"""Gradio app for the PIRD AI-text detector (Hugging Face Spaces).

Expects the trained checkpoint in ./pird_deploy (pird.pt + config.json) and the `pird/` package
present in the Space. Runs on CPU (free Spaces tier) — RoBERTa inference on one text is ~1-2s.
"""
import os
from pird.detectors.pird import PIRDDetector

CKPT = os.environ.get("PIRD_CKPT", "pird_deploy")
detector = PIRDDetector(CKPT)


def classify(text: str):
    text = (text or "").strip()
    n_words = len(text.split())
    if n_words < 20:
        return ({"enter ≥ 20 words": 1.0},
                "Please paste at least ~20 words for a reliable estimate.")
    p = float(detector.predict_proba([text])[0])
    label = {"AI-generated": p, "Human-written": 1.0 - p}
    verdict = (f"P(AI-generated) = {p*100:.1f}%   "
               f"— {'likely AI' if p >= 0.5 else 'likely human'} "
               f"(calibrated; {n_words} words)")
    return label, verdict


import gradio as gr

DESCRIPTION = (
    "**PIRD** is a paraphrase-robust, cross-domain detector for AI-generated text. Unlike "
    "perplexity-based detectors, it stays reliable when AI text is paraphrased to evade detection. "
    "Paste a passage (≥ 20 words) to get a calibrated probability that it was AI-generated.\n\n"
    "_Research demo — predictions are probabilistic and not infallible; do not use as sole "
    "evidence of misconduct._"
)
EXAMPLES = [
    ["The proposed framework leverages a robust architecture to efficiently process large-scale data, "
     "demonstrating significant improvements across all evaluated benchmarks and establishing a new "
     "state of the art for the task under consideration."],
    ["honestly i wasn't sure the trip was gonna happen at all — the flight got delayed twice, my bag "
     "nearly didn't make it, and then it rained the whole first day. but somehow it turned out great."],
]

demo = gr.Interface(
    fn=classify,
    inputs=gr.Textbox(lines=12, label="Paste text", placeholder="Paste a passage (≥ 20 words)..."),
    outputs=[gr.Label(num_top_classes=2, label="Prediction"),
             gr.Textbox(label="Calibrated probability")],
    title="PIRD — Paraphrase-Robust AI-Text Detector",
    description=DESCRIPTION,
    examples=EXAMPLES,
    flagging_mode="never",   # Gradio 5/6 renamed allow_flagging -> flagging_mode
)

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