dsh-omni-workstation
dsh-omni-workstation cover
English | 中文
An omni-modal workstation plugin for DeepSeek Harness (dsh). It gives the AI eyes, a brush, a camera and a voice: image analysis backed by an ordered multi-card VLM failover chain, a 6-tool local vision toolkit, image generation (incl. ComfyUI workflows), multi-card async video generation with an AI tool builder, and TTS / voice cloning across 3 cloud + 4 local providers — all configured from one auto-saving settings page (English / 中文).
Feature Overview
| Module | Tool | Highlights |
|---|
| VLM | analyze_image | Ordered API card list, single-request failover, per-card timeout, JPEG→PNG fallback, 28 built-in providers, mirror models, dynamic multimodal adaptation |
| Vision Toolkit | zoom_image · sample_colors · image_diff · ocr_image · detect_elements · show_image | 4 tools are pure-local (zero tokens); shared image resolution + card chain; artifact paths only |
| Image Gen | generate_image | OpenAI / DashScope / ComfyUI protocols, multi-workflow management with role mapping, reference-image support, auto verify reminder |
| Video | generate_video (+ per-card names) | Multi-card (limit 10), 7 protocols, /build-video-tool AI builder with custom-adapter runtime |
| Voice | speak · clone_voice | MiMo / MiniMax / Doubao + IndexTTS / GPT-SoVITS / VoxCPM / TTS-WebUI; zero-registration inline & persisted cloning |
Every module has its own switch — turning one off unregisters its tools completely (0 token cost) while keeping your configuration.
Why a plugin instead of a Skill or a fixed script
| Approach | Typical pain | What this plugin does |
|---|
| Long Skill text (official-API recipes) | A big instruction dump every turn — expensive tokens | Config lives only in the settings page / omni-vision.json; tool schemas inject only when a module is on |
| Fixed scripts (hand-written API calls) | Locked in a project folder; you must restate path and usage each time | Tools register into the harness — the AI finds and reuses them automatically |
| Changing config / switching models | Edit scripts or re-paste the Skill body | Change a field in Settings; it takes effect immediately |
In short: less context, ready to use, config without code.
Custom tools (video)
Today you can AI-build a custom video tool: type /build-video-tool in chat. The plugin injects a build guide (card limit, existing tools, hard constraints); the AI collects the platform details and writes a new card plus a callable tool — no hand-written script, no re-pasting API docs.
build-video-tool chat example
[!TIP]
Card limit defaults to 10; the command errors out when the cap is hit. Custom tools run on the custom-adapter runtime — see the video docs.
Settings Panel
VLM tab
Image Gen tab
Video tab
Voice tab
Settings → Omni Workstation — four tabs (VLM / Image Gen / Video / Voice) plus a global settings tab. Every edit auto-saves and takes effect immediately; no Save button.
Requirements
dsh CLI (DeepSeek Harness) with a web profile installedpnpm on PATH (or use npx --yes pnpm@<version>)
Install
The plugin is a bundle: it carries its own cordis.patch.yml and self-activates — one command, no manual patch editing.
# From a local directory
dsh plugin --profile web add ./dsh-omni-workstation
# From GitHub
dsh plugin --profile web add github:huashenglian/dsh-omni-workstation
# From a packed tarball (pnpm pack / npm pack)
dsh plugin --profile web add ./dsh-omni-workstation-0.1.0.tgz
dsh plugin add installs the dependency and appends the bundle to dsh.profile.bundles automatically.
[!NOTE]
Do not add a manual - insert: - id: omni-workstation row to the profile cordis.patch.yml — the bundle already inserts it. A second insert throws duplicate loader entry id: omni-workstation at boot.
Manual alternative: put the package under $DSH_HOME/profiles/web/plugins/dsh-omni-workstation/, add "dsh-omni-workstation": "file:./plugins/dsh-omni-workstation" to the profile package.json dependencies and "dsh-omni-workstation" to the dsh.profile.bundles array, run pnpm install, then restart dsh web.
Quick Start
- Restart
dsh web and open Settings → Omni Workstation.
- On the VLM tab, click Add Model (or edit the default card): pick a provider, paste your API key, fetch and pick a model.
- Send the AI an image (or a local path) and ask about it — the
analyze_image tool is now live.
All configuration lives in a single JSON file, omni-vision.json, stored inside the plugin installation directory (git-ignored; contains real API keys — never commit it). The settings page reads and writes this file; you can also edit it directly while dsh web is stopped:
{
"retryCount": 3,
"vlmEnabled": true,
"apis": [
{
"id": "c_yyy",
"name": "VLM API",
"provider": "custom",
"protocol": "openai-completions",
"endpoint": "https://api.example.com/v1",
"apiKey": "sk-...",
"model": "gpt-4o",
"timeoutMs": 120000
}
]
}
How It Works
The package is dual-face:
- Host half (
lib/index.js) — a cordis plugin: registers tools on the global tools registry and /omni/* web routes; loads and persists omni-vision.json; provider-gated tool registration re-syncs on config changes.
- Client half (
lib/client.js) — the browser module (loaded via the dsh.client entry): registers the Settings → Omni Workstation section and its locale namespace (settings.omni-workstation).
Documentation
Uninstall
dsh plugin --profile web remove dsh-omni-workstation
This removes the dependency and the bundle entry. Your omni-vision.json config file is left untouched.
License
MIT
