#!/usr/bin/env python3
"""回填 chapters.evidence_bundle_json（Phase 九：历史 chapter 无快照时可批量物化）。

用法（需在已执行 Alembic 0009+ 的库上）::

    cd api && uv run python scripts/backfill_chapter_evidence_snapshots.py
    cd api && uv run python scripts/backfill_chapter_evidence_snapshots.py --user-id <uuid>
"""

from __future__ import annotations

import argparse

from sqlalchemy import select

from app.features.auth import models as _auth_models  # noqa: F401
from app.features.conversation import models as _conv_models  # noqa: F401
from app.features.memory import models as _memory_models  # noqa: F401
from app.features.memoir import models as _memoir_models  # noqa: F401
from app.features.payment import models as _payment_models  # noqa: F401
from app.features.story import models as _story_models  # noqa: F401
from app.features.user import models as _user_models  # noqa: F401

from app.core.db import SessionLocal
from app.features.memoir.chapter_evidence_snapshot import (
    refresh_chapter_evidence_snapshot_sync,
)
from app.features.memoir.models import Chapter


def main() -> None:
    p = argparse.ArgumentParser()
    p.add_argument("--user-id", default="", help="仅刷新该用户的章节；默认全表")
    p.add_argument("--limit", type=int, default=0, help="最多处理条数，0 表示不限制")
    args = p.parse_args()

    uid = (args.user_id or "").strip()
    session = SessionLocal()
    n_ok = 0
    try:
        stmt = select(Chapter.id)
        if uid:
            stmt = stmt.where(Chapter.user_id == uid)
        if args.limit > 0:
            stmt = stmt.limit(args.limit)
        ids = list(session.execute(stmt).scalars().all())
        for cid in ids:
            if refresh_chapter_evidence_snapshot_sync(session, str(cid)):
                n_ok += 1
        session.commit()
        print(f"refreshed_snapshots={n_ok} chapter_rows={len(ids)}")
    finally:
        session.close()


if __name__ == "__main__":
    main()