#!/usr/bin/env python3
"""
build_index.py -- build (and incrementally update) the FAISS ANN index.

This embeds the *entire* metadata corpus (3.15M papers) once and persists a
FAISS index + metadata sidecar so queries don't have to re-embed anything.

    python build_index.py                 # full corpus, default index "arxiv"
    python build_index.py --category cs.LG # only cs.LG papers (faster demo)
    python build_index.py --index-name demo

Re-running it adds any papers not already in the index (incremental build).
"""

from __future__ import annotations

import argparse
import os
import sys

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from data import DataStore  # noqa: E402
from embed import get_embedder  # noqa: E402
from index import IndexBuilder  # noqa: E402


def main(argv=None) -> int:
    p = argparse.ArgumentParser(description="Build the arxiv ANN index.")
    p.add_argument("--index-name", default="arxiv")
    p.add_argument("--category", default=None, help="Only embed this primary_category.")
    p.add_argument("--year-min", type=int, default=None)
    p.add_argument("--year-max", type=int, default=None)
    p.add_argument("--embedder", default=None, choices=["hashing", "remote"])
    p.add_argument("--parquet", default=None)
    args = p.parse_args(argv)

    source = args.parquet or os.environ.get("ARXIV_METADATA_PARQUET", DataStore().source)
    store = DataStore(source=source)
    embedder = get_embedder(args.embedder)
    builder = IndexBuilder(args.index_name, embedder)

    if os.path.exists(builder.default_path()):
        builder.load()
        print(f"Loaded existing index: {len(builder._ids)} papers.")

    print("Scanning metadata (filtered) ...")
    scan = store.scan_filtered(
        year_min=args.year_min,
        year_max=args.year_max,
        primary_category=args.category,
    )
    added = builder.build(scan, store)
    meta = builder.save()

    print(
        f"Done. Index '{args.index_name}' now holds {len(builder._ids)} papers "
        f"(+{added}), dim={meta.dim}, embedder={meta.embedder}."
    )
    return 0


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