#!/usr/bin/env python3
"""CLI-Testtool – Erkennung direkt auf einer lokalen Bilddatei (ohne API/DB).

    python test_recognition.py /pfad/zum/bild.jpg
    python test_recognition.py /pfad/zum/bild.jpg --pretty

Gibt das JSON-Ergebnis der Pipeline aus. Ideal zum schnellen Pruefen der
Modelle/Postprocessing auf dem Server.
"""
import json
import sys
import uuid
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parent))

from app.config import settings  # noqa: E402
from app.services import image_service  # noqa: E402
from app.services.recognition_pipeline import get_pipeline  # noqa: E402


def main() -> int:
    args = [a for a in sys.argv[1:] if not a.startswith("--")]
    if not args:
        print("Usage: python test_recognition.py <bild> [--pretty]")
        return 2
    img_path = Path(args[0])
    if not img_path.exists():
        print(f"Datei nicht gefunden: {img_path}")
        return 2

    raw = img_path.read_bytes()
    try:
        prepared = image_service.prepare_image(
            raw,
            allowed_types=settings.allowed_image_types_list,
            max_dimension=settings.max_image_dimension,
            min_dimension=settings.min_image_dimension,
        )
    except image_service.ImageValidationError as exc:
        print(json.dumps({"success": False, "error": "invalid_image", "detail": str(exc)}))
        return 1

    response = get_pipeline().run(prepared.rgb, request_id=str(uuid.uuid4()))
    indent = 2 if "--pretty" in sys.argv else None
    print(json.dumps(response.model_dump(), ensure_ascii=False, indent=indent))
    return 0


if __name__ == "__main__":
    raise SystemExit(main())