59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
#!/usr/bin/env python3
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"""embed-knowledge Skill CLI。库实现安装为 muse_embed，这里只做入参与出错的壳。"""
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import pathlib
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import sys
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import click
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import psycopg
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import requests
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from muse_db import connect
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from muse_embed import EmbeddingOwnershipConflict, _run_bulk, _session, embed_texts
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_EVIDENCE = pathlib.Path(__file__).resolve().parents[2] / "record-run-evidence" / "scripts"
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if str(_EVIDENCE) not in sys.path:
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sys.path.insert(0, str(_EVIDENCE))
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@click.command()
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@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")
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@click.option("--source-type", type=str, help="来源类型；chapter_extract 按作品的 draft.work_id 筛选")
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@click.option("--limit", type=click.IntRange(min=0), default=0, help="最多处理条数（0=不限）")
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@click.option("--probe", help="自由文本试嵌（打印维度与前 5 维，不落库）")
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def main(work_id, source_type, limit, probe):
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sess = _session()
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if probe:
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vecs, bad = embed_texts(sess, [probe])
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if bad:
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raise click.ClickException("试嵌失败")
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v = vecs[0]
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click.echo(f"维度={len(v)} 前5维={[round(x, 4) for x in v[:5]]}")
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return
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with connect() as conn:
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_run_bulk(conn, sess, work_id, limit, source_type)
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from lesson_registry import propose_lesson_dedup # noqa: WPS433
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run_id = f"embed-{work_id or 0}-{source_type or 'all'}-{limit}"
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lesson = propose_lesson_dedup(
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kind="win",
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title="知识草稿嵌入批次完成",
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detail={
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"skill": "embed-knowledge",
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"work_id": work_id,
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"source_type": source_type,
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"limit": limit,
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},
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work_id=work_id if isinstance(work_id, int) else None,
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run_id=run_id,
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creator="embed-knowledge",
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)
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click.echo(f"嵌入完成 lesson={lesson.get('lesson_id')}")
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if __name__ == "__main__":
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try:
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main()
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except (EmbeddingOwnershipConflict, psycopg.Error, requests.RequestException) as e:
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click.echo(f"[错误] {type(e).__name__}: {e}", err=True)
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sys.exit(1)
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