#!/usr/bin/env python3
"""embed-knowledge Skill CLI。库实现安装为 muse_embed，这里只做入参与出错的壳。"""
import pathlib
import sys

import click
import psycopg
import requests
from muse_db import connect
from muse_embed import EmbeddingOwnershipConflict, _run_bulk, _session, embed_texts

_EVIDENCE = pathlib.Path(__file__).resolve().parents[2] / "record-run-evidence" / "scripts"
if str(_EVIDENCE) not in sys.path:
    sys.path.insert(0, str(_EVIDENCE))


@click.command()
@click.option("--work-id", type=int, help="限定作品/拆书批次；拆书默认按 source_id，章后抽卡按 draft.work_id")
@click.option("--source-type", type=str, help="来源类型；chapter_extract 按作品的 draft.work_id 筛选")
@click.option("--limit", type=click.IntRange(min=0), default=0, help="最多处理条数（0=不限）")
@click.option("--probe", help="自由文本试嵌（打印维度与前 5 维，不落库）")
def main(work_id, source_type, limit, probe):
    sess = _session()
    if probe:
        vecs, bad = embed_texts(sess, [probe])
        if bad:
            raise click.ClickException("试嵌失败")
        v = vecs[0]
        click.echo(f"维度={len(v)} 前5维={[round(x, 4) for x in v[:5]]}")
        return

    with connect() as conn:
        _run_bulk(conn, sess, work_id, limit, source_type)
    from lesson_registry import propose_lesson_dedup  # noqa: WPS433

    run_id = f"embed-{work_id or 0}-{source_type or 'all'}-{limit}"
    lesson = propose_lesson_dedup(
        kind="win",
        title="知识草稿嵌入批次完成",
        detail={
            "skill": "embed-knowledge",
            "work_id": work_id,
            "source_type": source_type,
            "limit": limit,
        },
        work_id=work_id if isinstance(work_id, int) else None,
        run_id=run_id,
        creator="embed-knowledge",
    )
    click.echo(f"嵌入完成 lesson={lesson.get('lesson_id')}")


if __name__ == "__main__":
    try:
        main()
    except (EmbeddingOwnershipConflict, psycopg.Error, requests.RequestException) as e:
        click.echo(f"[错误] {type(e).__name__}: {e}", err=True)
        sys.exit(1)