HongMing-Huang/dsh-file-upload 预览 preview

HongMing-Huang/dsh-file-upload

插件Plugin 原生Native ⭐ 18 MIT

DeepSeek Harness(dsh)文件消息插件:Claude风格的拖放/回形针上传、内容嗅探、通过微软MarkItDown将文档转换为Markdown(内置JS回退)、文本内联,以及供智能体使用的read_document工具。

项目介绍Project Overview

DSH 文件上传插件为零配置插件,提供拖放、文件夹上传、剪贴板粘贴与多文件支持,附件以 @相对路径 引用(类似 Codex)插入消息而非直接倾倒正文。核心能力是内置 MarkItDown 引擎,支持 20 多种格式(含 PDF/DOCX/PPT/XLS/HTML/CSV/JSON/ZIP/图片 OCR/音频转写)的本地文档转 Markdown,并为只接受文本的模型自动生成图片讲解,同时为代理提供 read_document 工具。适用于需要上传本地文档给 LLM 阅读、又想避免原始内容淹没上下文的场景。注意:单文件默认上限 24 MB;视觉能力走本地 Ollama 优先、OpenAI 兼容端点兜底的发现链。

dsh-file-upload is a zero-config DSH plugin that adds Claude/Codex-style uploads: paperclip picker, drag-and-drop (files and folders), paste-to-attach, and multi-file support. Attachments appear as @relative/path references (Codex-style) rather than dumped text, while a bundled MarkItDown engine converts 20+ formats (PDF, DOCX, PPTX, XLSX, HTML, CSV, JSON, ZIP, OCR, audio transcription) to Markdown locally; images auto-get a description for text-only models. It also exposes a read_document tool with line-paging, an LRU parse cache, and sandbox-aware reads via ctx.fs. Use it when agents must read local files. Caveat: per-file cap is 24 MB and vision falls back to local Ollama then OpenAI-compatible keys.

或使用命令行安装(适合开发者)Or use CLI install (for developers)

命令行安装CLI Install

dsh plugin --profile web add dsh-file-upload

HongMing-Huang/dsh-file-upload 加入你的 DSH 配置(web profile)即可启用。

READMEREADME

dsh-file-upload

File-message plugin for DeepSeek Harness (dsh). Claude/Codex-style uploads — drag-and-drop (files and folders), paperclip picker, paste-to-attach, multi-file support; content sniffing; fully bundled document → Markdown conversion (MarkItDown engine, 20+ formats, image OCR); Codex-style @relative/path references; automatic image explanations for text-only models; and a read_document tool for agents.

npm CI license Awesome DSH Plugin

English | 中文

Zero-config, install-and-use. Every feature works out of the box with sensible defaults — no Python, no downloads, no picking backends. Image explanations auto-discover a vision endpoint (local Ollama → OpenAI-compatible key from the dsh credentials seam).

Features

  • Upload — composer paperclip button plus a global drag-and-drop overlay ("release to attach"), multi-file support.
  • Attachment cards — color-coded type badges (PDF red / DOC blue / XLS green / TXT gray / ZIP purple / JSON gold) with name and size; removable.
  • Codex-style file references — uploaded files appear in the message as @relative/path references (like OpenAI Codex), never as raw content dumped into the composer; the agent reads the file with read_document (converted to Markdown on demand).
  • Codex-style @ mentions — type @ in the composer to pick any uploaded file by its relative path; the reference inserts as a mention.
  • Document → Markdown, fully bundled — the MarkItDown engine ships inside the plugin (Microsoft MarkItDown TypeScript port, markitdown-node): PDF / DOCX / PPTX / XLSX / HTML / CSV / JSON / XML / RSS / Atom / ZIP / Jupyter / image OCR / audio transcription. No Python, no downloads, no setup.
  • Image explanation for text-only models — upload an image and the plugin automatically generates a description ("讲解图片") through a vision discovery chain, so the DeepSeek API (text-only) can reason about the image: explicit visionEndpoint → local Ollama with a VL model (e.g. DeepSeek-VL2, zero-config) → OpenAI-compatible endpoint with a dsh-credentials key. Multimodal routes / vision bridges keep the official read_image path.
  • read_document tool for agents — line-numbered paging (offset/limit), byte-budgeted LRU cache (invalidated on file change), size pre-checks, reads through ctx.fs (inherits sandbox and fs-observation policy).
  • Security — loopback-only uploads, sanitized file names, session-isolated storage (.dsh-uploads/<sessionId>), sha256 content dedup, bounded concurrency, TTL sweep.

Install

dsh plugin --profile web add dsh-file-upload
# restart dsh web

Usage

  1. Click the paperclip in the composer toolbar, or drag files anywhere over the window;
  2. Small text files land directly in the composer; documents appear as attachment cards and their path is sent with the message;
  3. The agent reads documents with read_document <path> — converted to Markdown on demand, pageable with offset/limit.

MarkItDown (fully bundled — no downloads, no setup)

The MarkItDown capability ships inside the plugin. Works out of the box: no Python, no pip, no downloads, no build-script approval.

  • Bundled engine — the Microsoft MarkItDown TypeScript port (markitdown-node) is a regular dependency covering 20+ formats: PDF, DOCX, PPTX, XLSX, HTML, CSV, JSON, XML, RSS, Atom, ZIP, Jupyter notebooks, images (OCR via Tesseract, 110+ languages), and audio transcription (via LLM, needs model credentials).
  • Images — OCR to text by default through the bundled engine.
  • Offline — all parsing runs locally, no network calls.

Optional upgrade: if an official MarkItDown CLI already exists on your machine (or is set via markitdownBin), the plugin prefers it (adds EPUB and more); without one the bundled engine is always available.

- id: file-upload
  config:
    markitdownBin: /path/to/your/markitdown   # optional; empty = bundled engine only

Startup log (bundled mode):

[dsh-file-upload] Document → Markdown ready: bundled MarkItDown engine (20+ formats, image OCR) — fully packaged, no downloads, no Python.

How images are handled (auto-explained)

The plugin detects your session's model capability at upload time:

Detected route What happens
Multimodal model (declares image input, e.g. GPT-4o / Qwen-VL / Claude / Gemini) imageMode: native — the agent uses the official read_image tool; the image enters model context directly
Vision bridge installed (dsh-vision-proxy and similar) detected automatically (they declare image input on their route) — same native path
Text-only model (the DeepSeek API is text-only) an automatic image description is generated via the vision discovery chain and inserted with the message — the model reasons about the image content immediately

Vision discovery chain (zero-config): ① explicit visionEndpoint/visionModel → ② local Ollama at http://localhost:11434 (picks a VL model such as DeepSeek-VL2 — images never leave the machine) → ③ OpenAI standard endpoint using a key from the dsh credentials seam.

Note: DeepSeek's official API does not offer vision input (the multimodal line — DeepSeek-VL2/Janus — is open-source and self-hostable); deploy DeepSeek-VL2 via Ollama for a fully local "official DeepSeek vision" experience.

The route detection mirrors the official read_image gate (ctx.llm.resolveModelInfo + inputModalities).

Configuration

All fields have sensible defaults — you can install and use the plugin without touching any of them. Tune only what you need.

Field Default Description
uploadMaxBytes 25165824 (24 MB) Max bytes per uploaded file
allowedExtensions [] Extension allowlist; empty = all allowed
uploadTtlMs 604800000 (7 days) Unreferenced upload lifetime
sweepIntervalMs 3600000 (1 h) Sweep period; 0 = disabled
maxConcurrentUploads 4 Concurrent upload limit
inlineTextLimit 8192 (8 KB) Text inlined into the composer up to this size
previewTextLimit 2048 (2 KB) Preview length for larger text files
maxFileBytes 25165824 Byte cap for one document read
readLimit 2000 Max lines returned by one read_document call
sheetRowLimit 200 Rows kept per XLSX sheet
maxSheets 5 Sheets read per workbook
cacheEntries 16 Parse-cache entry count
cacheMaxBytes 67108864 (64 MB) Parse-cache byte budget
markitdownBin '' Optional MarkItDown CLI path; empty = auto-detect PATH
markitdownTimeoutMs 120000 Timeout for one CLI invocation
visionEndpoint '' Vision endpoint for image explanations; empty = auto (local Ollama → OpenAI standard)
visionModel '' Vision model id; empty = auto
visionApiKeyEnv OPENAI_API_KEY Credential reference for the vision key (dsh credentials seam)
visionMaxBytes 10485760 (10 MB) Max image bytes sent to the vision endpoint

Development

pnpm install
pnpm build     # tsc (host) + esbuild (client bundle)
pnpm test      # node --test

Architecture

src/
├── index.ts        # entry: apply + Config schema + assembly
├── detect.ts       # content sniffing (never trusts extensions)
├── convert.ts      # MarkItDown engine + optional CLI backend
├── vision.ts       # image explanations (vision discovery chain)
├── upload.ts       # upload route: loopback/session/size/dedup/TTL
├── tool.ts         # read_document: ctx.fs reads + paging + LRU cache
└── client/
    └── index.tsx   # paperclip + drag (files/folders) + paste + cards

Dual-face plugin: dsh.bundle (host) + dsh.client (web UI). No official patches — everything uses official seams (ctx.webServer, ctx.tools, ctx.systemPrompt, ctx.sessions, slash/input-insert-text, slash/input-insert-reference).

Security

  • Uploads are loopback-only and same-origin checked.
  • File names are sanitized (control chars, path separators, dot segments, leading dots stripped).
  • Storage is session-isolated under the session's own workspace; unknown sessions get 403.
  • sha256 content dedup, bounded concurrency (429 on overload), TTL sweep.
  • Text extraction parses bytes, never trusts extensions; binaries are handed to the agent by path only.

License

MIT

上一个 Prev gongwen-skill 下一个 Next dsh-LorebookMD