#!/usr/bin/env python
"""
Build FAISS indices from library vectors. Plan §1.3: index_smi, index_chem.
"""
from __future__ import annotations

import argparse
import sys
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]
if str(ROOT) not in sys.path:
    sys.path.insert(0, str(ROOT))

from spec_rag.faiss_index import build_hnsw_index, save_index
from spec_rag.io import ensure_dir


def parse_args():
    p = argparse.ArgumentParser(description="Build index_smi.faiss, index_chem.faiss, and index_flare.faiss")
    p.add_argument("--library-dir", required=True, help="Directory with vectors_smi.npy, vectors_chem.npy, and/or vectors_flare.npy")
    p.add_argument("--out-dir", default=None, help="Defaults to library-dir")
    p.add_argument("--metric", choices=["cosine", "l2"], default="cosine")
    p.add_argument("--m", type=int, default=32)
    p.add_argument("--ef-construction", type=int, default=200)
    p.add_argument("--ef-search", type=int, default=256, help="HNSW ef_search; higher improves recall")
    p.add_argument("--smi-only", action="store_true", help="Only build index_smi")
    p.add_argument("--chem-only", action="store_true", help="Only build index_chem")
    p.add_argument("--flare-only", action="store_true", help="Only build index_flare")
    return p.parse_args()


def main():
    args = parse_args()
    lib = Path(args.library_dir)
    out = ensure_dir(args.out_dir or lib)

    import numpy as np

    if args.flare_only:
        targets = [("flare", "vectors_flare.npy", "index_flare.faiss")]
    else:
        targets = []
        if not args.chem_only:
            targets.append(("smi", "vectors_smi.npy", "index_smi.faiss"))
            targets.append(("flare", "vectors_flare.npy", "index_flare.faiss"))
        if not args.smi_only:
            targets.append(("chem", "vectors_chem.npy", "index_chem.faiss"))

    for label, vec_name, index_name in targets:
        vec_path = lib / vec_name
        if not vec_path.exists():
            print(f"Skip index_{label}: {vec_path} not found")
            continue
        v = np.load(vec_path).astype(np.float32)
        idx = build_hnsw_index(
            v, m=args.m, ef_construction=args.ef_construction,
            ef_search=args.ef_search, metric=args.metric,
        )
        save_index(idx, out / index_name)
        print(f"Saved {index_name} ({v.shape[0]} vectors)")


if __name__ == "__main__":
    main()