dsh-docs

1. 安装并启动 DeepSeek Harness：npx @deepseek-ai/dsh web
2. 在终端执行上面的安装命令（CLI 会解析插件并核验来源）
3. 用 dsh plugins list 确认已安装，必要时重启 Harness 生效

插件以当前 dsh 进程的权限运行，安装时可能执行代码。请先通读仓库源码与许可证，确认无破坏性命令与越权访问；本站只做索引，不对第三方插件安全性作担保。

事实信息来自公开插件目录快照（2026-10-03），介绍文案由本站再加工。

以下为插件仓库 README 全文（原始内容，由公开目录抓取整理）。

# dsh-docs

  [图片: dsh-docs — local document intelligence for DeepSeek Harness: PDF, DOCX, XLSX, PPTX, Markdown, HTML, CSV, OCR, and text]

[中文](README.zh-CN.md) | [Installation prompt](INSTALL.md)

**dsh-docs** gives your DeepSeek Harness agent real document intelligence —
entirely on your own machine. Hand it a PDF, Word, Excel, or PowerPoint file
and get back clean Markdown, plain text, or structured JSON; hand it a scanned
page or image and a fully offline OCR pipeline reads it for you. No Docker, no
HTTP service, no API keys, and no document ever leaves your disk.

It ships a pinned, self-contained Python + [Xberg](https://github.com/xberg-io/xberg)
runtime with offline Tesseract language data (English and Simplified Chinese),
delivering complete PDF/Office/OCR coverage on Windows x64 out of the box. The
native Xberg Node binding serves as a lightweight non-OCR fallback on any
platform, and every file read stays confined to folders you explicitly
authorize.

The published package and plugin id use the `dsh-doc` spelling and the tools
use `dshdoc_*`; they were renamed from the initial `dsh-docling` / `docling_*`
release.

## One-prompt install

No local checkout or build toolchain is needed. Paste the following prompt into
a running DSH session (for example `dsh web`) in your own project folder. The
Harness agent installs the published npm package, downloads the pinned offline
OCR runtime, and configures the plugin in one go. The only prerequisite is a
working `dsh` CLI on Node `^22.19` or `>= 24`; every runtime step is plain
Node.js, so any shell works: cmd, PowerShell, pwsh, or Git Bash.

```text
Install the dsh-doc plugin into my DSH web profile, end to end. Do every
step yourself in the terminal and verify the result.

1. Install the published plugin package:
   dsh plugin --profile web add dsh-doc
2. Windows x64 only — download the prebuilt offline OCR runtime. The script
   verifies the pinned archive SHA-256, then verifies every extracted file
   against the bundled manifest:
   node /.dsh/profiles/web/node_modules/dsh-doc/scripts/fetch-runtime-win32-x64.mjs /.dsh/runtimes/dshdoc-runtime-win32-x64
   Replace  with my absolute home directory in this and every later step.
   On any other platform, skip this step and use engine: node below.
3. Edit /.dsh/profiles/web/cordis.patch.yml. Preserve every existing
   entry and add or update this one:
   - id: dsh-doc
     config:
       engine: python
       runtimeDir: /.dsh/runtimes/dshdoc-runtime-win32-x64
       defaultOcr: true
       maxOutputChars: 32000
   The session workspace is readable automatically; add allowedLocalRoots only
   for extra persistent directories such as a shared document vault.
   If you skipped step 2, use `engine: node` and `defaultOcr: false` instead
   and omit runtimeDir.
4. Verify with `dsh --profile web --dump-config` that the composed dsh-doc
   entry carries exactly this config, then report the result and remind me to
   restart `dsh web` so I can call dshdoc_health.

Hard constraints: never install, start, or configure Docling Serve, Docker,
containers, or any remote document-conversion service; never configure a
downloadable OCR backend or allow a model download.
```

After the agent finishes and you restart `dsh web`, check the engine with
`dshdoc_health`, then parse any file below your workspace with
`dshdoc_extract`. [INSTALL.md](INSTALL.md) documents the same flow plus the
manual procedure step by step.

## Supported and tested inputs

- PDF, DOCX, XLSX, PPTX, Markdown, HTML, CSV, and text
- PNG, JPEG, TIFF, WebP, and scanned PDFs through local OCR
- Markdown, plain text, or JSON-shaped Tool Results

The integration suite generates binary documents outside the repository and
verifies PDF, DOCX, XLSX, PPTX, PNG OCR, and scanned-PDF OCR. Test any other
Xberg-supported input against your own corpus before enabling it in production.

## Quick start with `dsh web`

Install the published package into the `web` profile:

```text
dsh plugin --profile web add dsh-doc
```

Windows x64 — fetch the prebuilt offline OCR runtime into a stable directory
outside `node_modules` (so plugin upgrades never delete it):

```text
node ~/.dsh/profiles/web/node_modules/dsh-doc/scripts/fetch-runtime-win32-x64.mjs ~/.dsh/runtimes/dshdoc-runtime-win32-x64
```

Expand `~` to your absolute home directory everywhere, including inside the
YAML below. On other platforms, skip the runtime and use `engine: node` with
`defaultOcr: false`.

Add the plugin entry to the web profile's `cordis.patch.yml`:

```yaml
- id: dsh-doc
  config:
    engine: python
    runtimeDir: ~/.dsh/runtimes/dshdoc-runtime-win32-x64
    maxFileBytes: 52428800
    maxOutputChars: 32000
    # Safe here because the configured runtime carries the local language packs.
    defaultOcr: true
    defaultTableMode: accurate
    defaultOutputFormat: md
```

The session workspace is readable without further configuration. Add
`allowedLocalRoots` only for extra persistent directories the model may read
beyond the workspace, and set `allowWorkspaceFiles: false` only for
allowlist-only lockdown deployments.

Restart `dsh web`, then ask it to read a local document:

```text
Read ./reports/annual-report.pdf and give me the three main risks.
Extract the tables from ./financials.xlsx.
Read the text from ./scanned-invoice.png.
```

Only paths below the session workspace or `allowedLocalRoots` are readable.
Relative paths resolve against the DSH session workspace, not the directory
from which `dsh web` was started.

## Offline embedded Python runtime (Windows x64)

Most users fetch the prebuilt, hash-pinned runtime from the GitHub Release:

```text
node ./scripts/fetch-runtime-win32-x64.mjs
```

To audit and rebuild from source instead, run:

```text
node ./scripts/build-runtime-win32-x64.mjs
```

Either command creates a gitignored `.dsh-runtime/runtime-win32-x64` directory
containing CPython 3.11.9, `xberg==1.0.14`, and pinned `eng` / `chi_sim`
Tesseract data. Every downloaded file is SHA-256 validated; the artifact
contains a manifest, NOTICE, and SPDX inventory. It does not alter a global
Python installation. Run `node ./scripts/verify-runtime-win32-x64.mjs` before
pointing a profile at a copied runtime artifact.

Point the plugin at the runtime:

```yaml
- id: dsh-doc
  config:
    engine: python
    runtimeDir:
```

The Python worker receives only a byte snapshot, display name, MIME type, and
conversion options over stdio. It never receives a user path or URL. It runs
offline, refuses missing OCR language packs, and disables document-derived OCR
caching. `dshdoc_health` reports the available OCR languages. See [the runtime
guide](docs/runtime-win32-x64.md).

### Node-only fallback

Set `engine: node` only when you need PDF/Office/text parsing without the
embedded Python runtime. Its `defaultOcr` is `false`. To enable Node OCR, set
`tessdataPath` to a reviewed local directory containing every requested
`.traineddata` pack; missing data returns `ENGINE_OCR_UNAVAILABLE`
instead of downloading a model. The Python runtime above is the supported
complete offline OCR path.

## Tools

| Tool | Purpose |
| --- | --- |
| `dshdoc_health` | Report readiness of the selected local engine. |
| `dshdoc_convert_file` | Parse an allowlisted local file. |
| `dshdoc_extract` | Preferred local-file convenience tool. |
| `dshdoc_convert_url` | Compatibility stub that returns `UNSUPPORTED_URL`. |

HTTP(S) input is detected only to reject it safely. Download a remote document
through a reviewed workflow into an allowed local root, then parse that file.
The plugin never forwards a URL to Xberg or Python, avoiding redirect and
DNS-rebinding risks.

`page_range` uses inclusive, one-based page numbers for Markdown and plain-text
results. JSON output deliberately retains the complete structured document.

The conversion tools also accept an optional per-request `ocr_languages` array
(for example `["chi_sim", "eng"]`) to override the configured language set for
one document. Results report `OCR: applied` / `OCR: not used` when the engine
exposes whether the OCR pipeline contributed; enabling OCR never replaces a
healthy embedded PDF text layer.

## Configuration

| Field | Default | Meaning |
| --- | --- | --- |
| `engine` | `auto` | `node`, `python`, or `auto`; auto selects configured embedded Python, otherwise Node Xberg. |
| `runtimeDir` | unset | Absolute embedded-runtime directory. |
| `pythonCommand` | unset | Trusted Python executable for a managed runtime. |
| `pythonWorkerPath` | shipped worker | Absolute Python worker override. |
| `tessdataPath` | runtime `ocr/tessdata` | Absolute bundled Tesseract language-data directory. |
| `ocrBackend` | `auto` | `auto` or `tesseract`; both select the pinned local Tesseract backend. |
| `ocrLanguages` | every bundled pack | Ordered local OCR language packs. Unset uses every `.traineddata` pack in the configured runtime. |
| `timeoutMs` | `120000` | Per-conversion deadline. |
| `maxFileBytes` | `52428800` | Authorized input-size cap. |
| `allowedLocalRoots` | `[]` | Extra absolute non-root directories the model may read, beyond the session workspace. |
| `allowWorkspaceFiles` | `true` | Implicitly authorize the session workspace (session cwd) as a readable root; set `false` for allowlist-only lockdown. |
| `defaultOcr` | `false` | OCR default for images and scans; enable it only with a configured local tessdata runtime. |
| `defaultTableMode` | `accurate` | `fast` or `accurate` PDF table behavior. |
| `defaultOutputFormat` | `md` | `md`, `text`, or `json`. |
| `maxOutputChars` | `32000` | Maximum result returned to the model. |
| `debug` | `false` | Logs safe engine metadata only. |

Older `baseUrl`, `apiKey`, `enableRemoteUrls`, and `allowPrivateUrls` profile
fields are accepted only for migration; they do not enable a remote engine.

## Security model

- Paths are realpathed and checked against every configured root and, unless
  `allowWorkspaceFiles` is disabled, the session workspace. Traversal,
  symlink escapes, filesystem roots, non-files, and oversized inputs fail.
- The authorized descriptor is read once into a snapshot before parsing, so a
  later path replacement cannot change the parsed bytes.
- The Node and Python engines accept bytes only. The plugin creates no listener,
  URL fetcher, container, or external parser service.
- OCR is Tesseract-only in this release. All requested language packs are read
  from the configured local artifact; missing packs fail closed rather than
  triggering a model download.
- The descriptor opened for parsing must have the same device/inode identity as
  the post-open allowlisted path, blocking file replacement between authorization
  and the byte snapshot.
- Results are bounded before becoming Tool Results. JSON is limited using the
  same pretty representation shown to the model.

## Development

```text
pnpm install
pnpm lint
pnpm typecheck
pnpm test
pnpm build
pnpm pack --pack-destination .pack
```

Tests create temporary documents only. They cover native Xberg, the Python
stdio worker, local OCR data, Cordis ToolRuntime, and local DSH AgentLoop
context injection.

## Licenses

This project is MIT. Xberg 1.0.14 is MIT. The optional Windows runtime contains
CPython (PSF-2.0) and `tessdata_fast` language data (Apache-2.0), with exact
sources, hashes, and notices recorded in its generated artifact.