mirror of
https://github.com/lllin000/PaperForge.git
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231 lines
8.7 KiB
Python
231 lines
8.7 KiB
Python
#!/usr/bin/env python3
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"""Generate minimal pre-install sandbox for testing PaperForge Lite setup wizard.
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Run from repo root:
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python tests/sandbox/generate_sandbox.py
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Creates tests/sandbox/ with:
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- TestZoteroData/ — mock Zotero data dir (wizard creates junction to this)
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- storage/ — 5 PDFs with keys matching exports JSON
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- zotero.sqlite — fake sqlite (satisfies Zotero path detection)
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- exports/ — Better BibTeX JSON exports (keys match storage filenames)
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- 00_TestVault/ — empty vault root (wizard generates everything here)
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Wizard creates inside 00_TestVault/:
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00_System/Zotero -> junction -> TestZoteroData (user points to our TestZoteroData)
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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SANDBOX = Path(__file__).parent
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ZOTERO_DATA = SANDBOX / "TestZoteroData"
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STORAGE = ZOTERO_DATA / "storage"
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EXPORTS = SANDBOX / "exports"
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VAULT = SANDBOX / "00_TestVault"
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# Keys in JSON must match PDF filenames in storage (minus .pdf)
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PAPERS = {
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"骨科": [
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{
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"key": "TSTONE001",
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"title": "Biomechanical Comparison of Suture Anchor Fixations in Rotator Cuff Repair",
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"creators": [{"creatorType": "author", "firstName": "James", "lastName": "Burkhardt"}],
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"date": "2024",
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"publicationTitle": "Journal of Shoulder and Elbow Surgery",
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"DOI": "10.1016/j.jses.2024.01.001",
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"abstractNote": "BACKGROUND: Suture anchor fixation is critical for rotator cuff repair. We compared pull-out strength across 3 anchor types.",
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"has_pdf": True,
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},
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{
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"key": "TSTONE002",
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"title": "Machine Learning Prediction of Anterior Cruciate Ligament Injury Risk in Athletes",
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"creators": [{"creatorType": "author", "firstName": "Wei", "lastName": "Zhang"}],
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"date": "2023",
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"publicationTitle": "American Journal of Sports Medicine",
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"DOI": "10.1177/03635465231123456",
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"abstractNote": "PURPOSE: To develop and validate an ML model for predicting ACL injury risk using biomechanical and demographic features.",
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"has_pdf": True,
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},
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{
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"key": "TSTONE003",
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"title": "Platelet-Rich Plasma for Knee Osteoarthritis: RCT",
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"creators": [{"creatorType": "author", "firstName": "Sarah", "lastName": "Johnson"}],
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"date": "2022",
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"publicationTitle": "Osteoarthritis and Cartilage",
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"DOI": "10.1016/j.joca.2022.03.012",
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"abstractNote": "OBJECTIVE: To evaluate PRP injections vs hyaluronic acid for symptomatic knee OA in a double-blind RCT (n=192).",
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"has_pdf": False,
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},
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],
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"运动医学": [
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{
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"key": "TSTTWO001",
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"title": "Return to Sport After ACL Reconstruction: A Systematic Review",
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"creators": [{"creatorType": "author", "firstName": "Lisa", "lastName": "Park"}],
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"date": "2024",
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"publicationTitle": "Sports Health",
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"DOI": "10.1177/19417381241234567",
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"abstractNote": "DATA SOURCES: PubMed, Embase, Cochrane. 23 studies included. Return-to-sport criteria varied widely across studies.",
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"has_pdf": True,
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},
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{
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"key": "TSTTWO002",
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"title": "Ultrasound-Guided Achilles Tendon Repair: Case Series",
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"creators": [{"creatorType": "author", "firstName": "Carlos", "lastName": "Rodriguez"}],
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"date": "2023",
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"publicationTitle": "Foot and Ankle International",
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"DOI": "10.1177/107110072311234",
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"abstractNote": "CASE SERIES: 28 patients with acute Achilles ruptures. Primary outcomes: AOFAS score, time to weight-bearing, complications.",
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"has_pdf": True,
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},
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],
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}
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def _write_minimal_pdf(path: Path) -> None:
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path.write_bytes(
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b"%PDF-1.4\n"
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b"1 0 obj\n<< /Type /Catalog /Pages 2 0 R >>\nendobj\n"
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b"2 0 obj\n<< /Type /Pages /Kids [3 0 R] /Count 1 >>\nendobj\n"
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b"3 0 obj\n<< /Type /Page /Parent 2 0 R /MediaBox [0 0 612 792] >>\nendobj\n"
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b"xref\n0 4\n"
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b"0000000000 65535 f \n"
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b"0000000009 00000 n \n"
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b"0000000058 00000 n \n"
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b"0000000115 00000 n \n"
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b"trailer\n<< /Size 4 /Root 1 0 R >>\n"
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b"startxref\n199\n"
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b"%%EOF\n"
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)
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def build() -> None:
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import shutil
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for p in [ZOTERO_DATA, EXPORTS, VAULT]:
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if p.exists():
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shutil.rmtree(p)
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print(f"Generating sandbox at: {SANDBOX}")
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# --- TestZoteroData (wizard creates junction inside vault pointing here) ---
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STORAGE.mkdir(parents=True)
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(ZOTERO_DATA / "zotero.sqlite").write_bytes(b"SQLite format 3" * 4)
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for domain, papers in PAPERS.items():
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for paper in papers:
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key = paper["key"]
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if paper["has_pdf"]:
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pdf_dir = STORAGE / key
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pdf_dir.mkdir(parents=True, exist_ok=True)
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_write_minimal_pdf(pdf_dir / f"{key}.pdf")
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# --- exports (BBT JSON, keys must match storage filenames) ---
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EXPORTS.mkdir(parents=True)
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for domain, papers in PAPERS.items():
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items = []
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for paper in papers:
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item = {
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"key": paper["key"],
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"itemType": "journalArticle",
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"title": paper["title"],
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"creators": paper["creators"],
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"date": paper["date"],
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"publicationTitle": paper["publicationTitle"],
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"DOI": paper["DOI"],
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"abstractNote": paper["abstractNote"],
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"collections": [domain],
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}
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if paper["has_pdf"]:
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item["attachments"] = [{"path": f"{paper['key']}/{paper['key']}.pdf", "contentType": "application/pdf"}]
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else:
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item["attachments"] = []
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items.append(item)
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export_path = EXPORTS / f"{domain}.json"
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export_path.write_text(
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json.dumps({"items": items}, ensure_ascii=False, indent=2),
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encoding="utf-8",
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)
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# --- empty vault root (wizard fills everything) ---
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VAULT.mkdir(parents=True)
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# --- README ---
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vault_abs = str(VAULT.resolve())
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zotero_abs = str(ZOTERO_DATA.resolve())
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exports_abs = str(EXPORTS.resolve())
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readme = SANDBOX / "README.md"
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readme.write_text(f"""# PaperForge Lite — Test Sandbox
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## 用途
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测试 PaperForge Lite 安装向导 `setup_wizard.py` 的完整流程。
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## 目录结构
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```
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tests/sandbox/
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TestZoteroData/ ← 模拟 Zotero 数据目录（setup wizard 会在 vault 内建 junction 指向这里）
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storage/ ← 5 PDFs（4篇有附件，1篇无）
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zotero.sqlite ← 伪造（让 Zotero 路径检测通过）
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exports/ ← Better BibTeX JSON 导出（2个域，5篇文献，keys 匹配 storage 文件名）
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00_TestVault/ ← 空目录（安装向导会在这里创建所有子目录）
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README.md ← 本文件
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```
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## 测试步骤
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```powershell
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# 1. 进入仓库根目录
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cd D:\\...\\github-release
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# 2. 运行安装向导，指向空 vault
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python setup_wizard.py --vault {vault_abs}
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# 3. 安装向导中：
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# - Agent 平台：选你的（opencode / cursor / claude 等）
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# - Zotero 数据目录：填 {zotero_abs}
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# （向导会在 vault 内创建 junction: 00_TestVault/00_System/Zotero -> 指向这里）
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# - BBT 导出目录：填 {exports_abs}
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# （向导会检测到 exports/ 下的 JSON 文件）
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# - 其他步骤默认即可
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# 4. 安装完成后，测试 pipeline：
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cd {vault_abs}
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paperforge selection-sync
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paperforge index-refresh
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paperforge ocr run
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paperforge status
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```
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## 预期结果
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| 检查项 | 预期 |
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|--------|------|
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| wizard 检测 TestZoteroData | 通过（有 storage/ 和 zotero.sqlite）|
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| wizard 检测 exports/ | 通过（2个 JSON，keys 有效）|
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| selection-sync | 生成 5 条 library-records |
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| TSTONE003 ocr_status | nopdf（无 PDF） |
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| TSTTWO001/002 有 PDF | ocr_status: pending |
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## 注意
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- 目录名故意和真实 vault 不同，避免硬编码测试不出来
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- PDF 是最小化假文件（pymupdf 可读，内容为空）
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- 不要往 sandbox 加真实数据
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""", encoding="utf-8")
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pdf_count = sum(1 for papers in PAPERS.values() for p in papers if p["has_pdf"])
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paper_count = sum(len(papers) for papers in PAPERS.values())
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print(f"\nSandbox ready: {SANDBOX}")
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print(f" TestZoteroData/storage/ — {pdf_count} PDFs")
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print(f" exports/ — {len(PAPERS)} BBT JSON files ({paper_count} papers)")
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print(f" 00_TestVault/ — EMPTY (wizard fills this)")
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print(f"\nRun:")
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print(f" python setup_wizard.py --vault {VAULT.resolve()}")
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if __name__ == "__main__":
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build()
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