#!/usr/bin/env python3
"""kb/eval - recall@5 gate for the brain.

  bin/kb/eval [--json]

Control questions are answered from the graph; recall@5 >= 0.95 gates CI.
Each question maps to leaf ids that MUST appear in the top 5 hits.
"""
from __future__ import annotations

import json
import sys
from pathlib import Path

ROOT = Path(__file__).resolve().parents[2]
sys.path.insert(0, str(ROOT / "tools"))

from kblib import open_readonly, query_fts  # noqa: E402
from yamlout import to_yaml  # noqa: E402

RECALL_THRESHOLD = 0.95

# (query, expected leaf id)
CONTROL_QUESTIONS: list[tuple[str, str]] = [
    ("which database does the brain use", "facts:ladybug"),
    ("hybrid search weights fts and vector equally", "info:hybrid"),
]


def hit_ids_of(query: str, conn, limit: int = 5) -> list[str]:
    try:
        hits = query_fts(conn, query, limit)
        return [h["id"] for h in hits]
    except Exception:
        return []


def main(argv: list[str]) -> int:
    import argparse
    p = argparse.ArgumentParser(description="recall@5 gate")
    p.add_argument("--json", action="store_true")
    a = p.parse_args(argv)

    db, conn = open_readonly()
    recalled = 0
    detail = []
    for query, expected in CONTROL_QUESTIONS:
        hits = hit_ids_of(query, conn)
        ok = any(expected in h or h in expected for h in hits)
        recalled += int(ok)
        detail.append({"q": query, "expected": expected, "in_top5": ok, "hits": hits[:5]})
    recall = recalled / len(CONTROL_QUESTIONS) if CONTROL_QUESTIONS else 1.0
    passed = recall >= RECALL_THRESHOLD
    out = {"recall@5": round(recall, 3), "passed": passed, "gate": len(CONTROL_QUESTIONS), "details": detail}
    print(json.dumps(out, indent=2) if a.json else to_yaml(out))
    conn.close()
    db.close()
    return 0 if passed else 2


if __name__ == "__main__":
    sys.exit(main(sys.argv[1:]))