"""Run local, CPU-only inference with the packaged classifier."""

from __future__ import annotations

import argparse
import json
from pathlib import Path

import joblib


ROOT = Path(__file__).resolve().parents[1]


def predict(text: str, top_k: int = 3) -> dict[str, object]:
    if not text.strip():
        raise ValueError("Request text must not be empty")
    model = joblib.load(ROOT / "model.joblib")
    predicted = str(model.predict([text])[0])
    probabilities = model.predict_proba([text])[0]
    ranked = sorted(
        ((str(label), float(probability)) for label, probability in zip(model.classes_, probabilities)),
        key=lambda item: item[1],
        reverse=True,
    )
    return {
        "predicted_intent": predicted,
        "top_probabilities": [
            {"intent": label, "probability": probability} for label, probability in ranked[:top_k]
        ],
        "model_version": "1.0.0",
        "warning": "Educational synthetic-data classifier; retain human review for operational decisions.",
    }


def main() -> None:
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("text", help="Non-sensitive operational request to classify")
    parser.add_argument("--top-k", type=int, default=3, choices=range(1, 9))
    args = parser.parse_args()
    print(json.dumps(predict(args.text, args.top_k), indent=2))


if __name__ == "__main__":
    main()