Paper Desk · 论文工作台

A Zotero-shaped paper desk for DeepSeek Harness. It adds a Papers entry to the DSH sidebar and a three-pane reader to the main panel: the normal DSH sidebar on the left, the PDF in the middle, and a DeepSeek co-reading chat / Markdown notebook on the right.

本项目也适合中文用户：界面、AI 精读笔记和共读对话默认使用中文。

Features

• Projects — create a project such as Scaling inference for SBI. Each project keeps its papers, tags, annotations, chats and notes together.
• Drop PDFs in — uploads, parses, and files PDFs into a Zotero-style folder (Author et al. - Year - Title). Title, authors and year are read from the PDF metadata and first page.
• Double-click to read — click the Read button, or double-click any non-interactive part of a paper row.
• Zotero-shaped paper rows — expand a paper to see paper.pdf, notes.md and any appendix or supplementary files. Extra files are stored verbatim and never parsed.
• PDF reading — PDF.js viewer with fit-width/zoom, page navigation, selectable text, four highlight colours, paragraph-anchored notes, one-click selection translation, and “ask AI” with the selected passage.
• Math-aware Markdown — $...$, $$...$$, \(...\) and \[...\] render in notes and chat using KaTeX's HTML layout with embedded KaTeX fonts. Code spans and currency are left alone.
• AI deep-read note — on first open DeepSeek writes a structured Markdown note: TL;DR, core problem, prior work pros/cons, how this paper fixes the cons, motivation + key idea + example, how to read the experiments, strengths, limitations and future work. The note is a normal Markdown file you edit in the right pane, with preview, autosave and “AI rewrite”.
• Co-reading chat — a dedicated DeepSeek conversation per paper. It receives the paper text, generated note, highlights and the quoted passage, so follow-up questions have context. The conversation is persisted.
• Tags and search — Zotero-style tag chips; filter by one or more tags and search titles, authors, tags and note excerpts.
• Your data is plain files — no database, no lock-in.

paper-desk/
  projects/
    scaling-inference-for-sbi/
      project.json
      papers/
        kuhmichel-et-al-2026-high-dimensional-simulation-based-inference/
          paper.pdf
          paper.txt          # extracted text (AI context)
          notes.md           # Markdown notebook
          annotations.json   # highlights + paragraph notes
          chat.json          # co-reading conversation
          attachments/       # appendix, supplementary material, ...

Requirements

• DeepSeek Harness 0.2.x with the Web GUI and a DeepSeek provider.
• A modern Chromium-based Web renderer (the DSH Desktop app is supported).
• Node.js 22+ for development builds.

Paper Desk uses the active DSH profile's provider/model. It does not ask for a separate API key. When provider/model are not configured explicitly it selects the first DeepSeek Flash/Chat route available in the profile.

Install from GitHub

In DSH, open Settings → Plugins, install the bundle from GitHub (fexas/dsh-paper-desk), and enable it. Restart DSH if the host asks for a restart after installing a new package.

If your DSH version exposes the plugin command directly, the equivalent local checkout flow is:

git clone https://github.com/fexas/dsh-paper-desk.git
cd dsh-paper-desk
npm ci
npm run build

Then add this directory as a file: dependency of the active DSH profile and select dsh-paper-desk in that profile's bundle list (see the DSH plugin documentation). The host half has no build step; client.js is the pre-built browser half.

Data location

The default data directory depends on how the plugin is installed:

Install	Default projects/ location
Linked local checkout	<plugin-root>/projects/
Managed plugin (under node_modules)	$DSH_HOME/paper-desk/projects/ (usually ~/.dsh/paper-desk/projects/)

Override it in the plugin row:

- id: dsh-paper-desk
  name: dsh-paper-desk
  config:
    provider: deepseek-account
    model: deepseek-flash
    # dataDir: /absolute/path/to/paper-desk-projects

The data directory contains project.json plus one folder per paper. Deleting a project or paper moves it to projects/.trash/ rather than destroying it. PDFs, text, notes, annotations and chat history are local files; nothing is sent anywhere except the model requests made by DeepSeek.

How it works

browser (client.js)                         host (host/service.js)
──────────────────                         ───────────────────────
React slot UI                              Typert Remote `paperDesk`
PDF.js viewer + KaTeX                      projects/, uploads, files
highlight / note state          <──RPC──>  annotations.json, notes.md
DeepSeek chat + note UI                    chat.json, paper.txt
                                           DeepSeek call via ctx.llm

• client.js is a single browser module built from client/ with esbuild. PDF.js and KaTeX fonts are bundled, so no CDN or extra asset route is needed.
• The host exposes a small paperDesk Remote namespace. The browser never gets direct filesystem access.
• Every paper is a directory with human-readable JSON/Markdown files; the UI can be removed without losing the research library.

Performance notes

The reader shell opens as soon as the paper record arrives. PDF bytes are read in eight parallel range requests, page 1 renders before the remaining page boxes and text layer are resolved, and recently opened PDFs stay in a small in-memory LRU cache. PDF.js runs its worker bundle on the page thread, which avoids a Chromium/Electron worker handshake failure that can otherwise hang the viewer. AI note generation runs alongside PDF loading; a compact progress card shows the live stage and disappears when the note is written.

Development

npm ci
npm run build      # rebuild client.js
npm run check      # syntax-check host and built client

Source layout:

• host/service.js — projects, chunked uploads, annotations, notes, LLM calls
• client/App.jsx — project library, paper rows, reader shell, chat and notes
• client/PdfViewer.jsx — PDF.js canvas/text/highlight viewer
• client/markdown.js — Markdown + KaTeX formula rendering
• client/styles.css — DSH-token-based UI styles
• build.mjs — esbuild bundle, PDF.js worker embedding, inline KaTeX fonts

Pull requests are welcome. Please keep the UI on DSH theme tokens (--dsw-alias-*) and do not add a separate app shell, CDN dependency or a second filesystem root.

Known limitations

• No OCR: image-only PDFs will not have selectable text or AI full-text context.
• The AI note is generated from extracted PDF text; complex multi-column or scanned layouts may lose structure.
• The co-reading chat is a focused paper assistant, not a general-purpose DSH agent with tool access.
• Data is local to one machine; there is no sync or multi-user layer.

License

MIT. See LICENSE and THIRD_PARTY_NOTICES.md. Bundled third-party code includes PDF.js (Apache-2.0), KaTeX (MIT), marked, DOMPurify and lucide.