"""准备标注集评测的输入：S01–S10 转成规范化 PDF，导出带句子编号的全文（给人工标注用）。

用法（在 server/ 下）：
  ../.venv/bin/python ../evals/prepare.py [S01 S02 ...]
输出 evals/out/docs/<ID>/：normalized.pdf、sentences.txt（每行 `[p12s3] 句子`，带格式标记和〔上级：…〕）。
规范化 PDF 生成一次后复用，抽取评测（run_extract.py）也用它作输入，标注和评测看到的是同一份文字层。
"""

from __future__ import annotations

import asyncio
import pathlib
import sys

from bid_doctor.checklist import extract
from bid_doctor.document import formats
from bid_doctor.document.pipeline import convert, structure, text_layer

ROOT = pathlib.Path(__file__).resolve().parent
SAMPLES = ROOT.parent / "samples" / "tenders"
OUT = ROOT / "out" / "docs"


async def prepare(doc_id: str) -> None:
    out = OUT / doc_id
    out.mkdir(parents=True, exist_ok=True)
    pdf_path = out / "normalized.pdf"
    if not pdf_path.exists():
        src = next(p for p in (SAMPLES / doc_id).iterdir() if p.suffix in (".doc", ".docx", ".pdf"))
        raw = src.read_bytes()
        fmt = formats.detect(raw, src.name).format
        pdf_path.write_bytes(raw if fmt == "pdf" else await convert.to_pdf(raw, fmt))
    pages = text_layer.extract("D", pdf_path.read_bytes())
    body = text_layer.body_sentences(pages)
    parents = structure.parents(body)
    notes = extract.marking_notes(body)
    lines = [f"# {doc_id}：{len(pages)} 页，正文句子 {len(body)}", "## 标注规则说明（规则识别）"]
    lines += [f"- [p{n.sentence.page_no}s{n.sentence.seq}] {n.sentence.text}" for n in notes] or ["（无）"]
    page = 0
    for s in body:
        if s.page_no != page:
            page = s.page_no
            lines.append(f"\n=== 第 {page} 页")
        line = f"[p{s.page_no}s{s.seq}] {s.marked}"
        if p := parents.get(s.key):
            line += f"〔上级：{p.text[:40]}〕"
        lines.append(line)
    (out / "sentences.txt").write_text("\n".join(lines) + "\n")
    print(doc_id, len(pages), "页", len(body), "句")


async def main() -> None:
    ids = sys.argv[1:] or [f"S{i:02d}" for i in range(1, 11)]
    for doc_id in ids:
        await prepare(doc_id)


asyncio.run(main())