"""
CLI entry point for Feature 1/4/15's retrieval pipeline - fetches
verified nutrition data (Open Food Facts) for every product in the
catalog, computes transparent scores/insights, and persists them.

Usage:
    python scripts/enrich_nutrition.py
    python scripts/enrich_nutrition.py --max-products 200 --no-narrative
    python scripts/enrich_nutrition.py --force   # re-fetch even already-verified products

Equivalent to POST /api/admin/nutrition-intelligence/enrich.
"""
from __future__ import annotations

import argparse
import logging
import sys
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))

from app.services.nutrition_db import ensure_nutrition_schema  # noqa: E402
from app.services.nutrition_enrichment_service import enrich_all_products  # noqa: E402

logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
logger = logging.getLogger(__name__)


def _progress(done: int, total: int) -> None:
    if total and (done % 25 == 0 or done == total):
        logger.info(f"Enrichment progress: {done}/{total}")


def main() -> None:
    parser = argparse.ArgumentParser(description="Enrich the catalog with verified nutrition data")
    parser.add_argument("--force", action="store_true", help="Re-fetch even products already marked 'verified'")
    parser.add_argument("--no-narrative", action="store_true", help="Skip the LLM narrative step (facts/scores/tags only)")
    parser.add_argument("--max-products", type=int, default=None, help="Cap the number of products processed (for a quick test run)")
    args = parser.parse_args()

    ensure_nutrition_schema()
    result = enrich_all_products(
        skip_if_verified=not args.force,
        generate_narrative=not args.no_narrative,
        progress_cb=_progress,
        max_products=args.max_products,
    )

    logger.info(
        f"Done in {result.duration_seconds}s - "
        f"{result.verified} verified, {result.partial} partial, {result.unavailable} unavailable "
        f"of {result.total_products} total products"
    )
    if result.errors:
        logger.warning(f"{len(result.errors)} errors (showing up to 10): {result.errors[:10]}")


if __name__ == "__main__":
    main()