from __future__ import annotations

import argparse
from pathlib import Path

from engine.refinement.reflexion import (
    REFLEXION_CSV_PATH,
    REFLEXION_MODEL_PATH,
    train_reflexion_model,
)


def main() -> None:
    parser = argparse.ArgumentParser(
        description=(
            "Entrena el model KNN de 'reflexion' a partir de les parelles "
            "(MoE/Salamandra, HITL) a demo/temp/audiodescriptions.db."
        )
    )
    parser.add_argument(
        "--max-examples",
        type=int,
        default=None,
        help=(
            "Nombre màxim de mostres d'entrenament a processar. "
            "Per defecte es processen totes."
        ),
    )
    args = parser.parse_args()

    train_reflexion_model(max_examples=args.max_examples)

    n_rows = 0
    if REFLEXION_CSV_PATH.exists():
        try:
            text = REFLEXION_CSV_PATH.read_text(encoding="utf-8")
            # descomptar la capçalera
            n_rows = max(0, len([l for l in text.splitlines() if l.strip()]) - 1)
        except Exception:
            n_rows = 0

    model_str = "creat" if REFLEXION_MODEL_PATH.exists() else "no creat"

    print(
        f"✅ Entrenament de reflexion completat. "
        f"Mostres al CSV: {n_rows}, fitxer de model: {model_str} ({REFLEXION_MODEL_PATH})."
    )


if __name__ == "__main__":
    main()