快速了解
它能做什么
面向 DeepSeek Harness Web 配置文件的图像、视频和语音工具插件。
本站提供的是中文说明,不代表该项目或 Plugin 自身提供中文界面;语言支持请以上游文档为准。
Web Profile
Not declared in supplied evidence
证据已验证
核对日期 2026/9/11 UTC 14:05
选择前先看
DSH Omni Workstation 会在 DeepSeek Harness 中注册多模态工具,包括图像分析、六项视觉工具、图像生成、异步视频生成、文本转语音和声音克隆。其网页设置页可管理服务商卡片排序、模型路由和模块开关。
适合谁
使用 Web 配置文件、希望以配置方式获得多模态能力而非维护独立脚本的 DeepSeek Harness 用户。
常见任务
- 通过已配置的视觉模型分析上传的图片或本地图片路径。
- 通过支持的服务商协议或 ComfyUI 工作流生成图片。
- 配置视频生成卡片,并使用文档中的视频工具构建功能。
- 按工作区需要,仅启用视觉、图像、视频或语音模块。
权限与数据
插件会本地持久化配置,并连接到你自行配置的外部服务商。
权限- 在 Harness Web 配置文件中注册全局工具和 /omni/* 网页路由。
- 在插件安装目录中读取和写入 omni-vision.json。
- 配置文件可能包含真实 API 密钥;项目文档称该文件会被 Git 忽略。
- 图片、提示词和语音相关输入可能会发送给已配置的外部服务商;供应商具体的数据处理方式未在所给证据中确认。
- 项目说明支持配置 OpenAI、Anthropic、Gemini、Custom、Ollama、ComfyUI 以及语音/视频服务商工作流。
- 配置适用的云端模型卡片时需要对应服务商的 API 密钥。
局限
- 根据 README,需要安装带 Web 配置文件的 dsh,并且 PATH 中可用 pnpm。
- 所给证据未声明 Harness 版本范围。
- 未找到 npm 注册表发行版;应使用已验证的固定 Git bundle 路径。
- 不要手动再添加 omni-workstation bundle 条目;README 指出这会在启动时触发重复 loader entry 错误。
DSHub 已核对
- 已验证固定 Git 源、包清单和 bundle patch 结构。
- 包清单声明了 Web 客户端注入和 bundle patch。
- README 记录了模块、配置位置和安装流程。
DSHub 未核对
- 未实际执行安装或运行时行为验证。
- 未独立验证服务商凭据、外部服务行为、媒体数据处理或模型兼容性。
固定版本安装
安装 DSH Omni Workstation
这个Plugin Bundle没有 DSH Plugin 安装操作,请根据源码文档使用真实交付方式。
维护者原文
项目 README
dsh-omni-workstation
<p align="center"><img src="docs/images/cover.jpg" alt="dsh-omni-workstation cover" width="720"></p>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.
[!TIP] Card limit defaults to 10; the command errors out when the cap is hit. Custom tools run on the
custom-adapterruntime — see the video docs.
Settings Panel
<p align="center"> <img src="docs/images/omni-panel-vlm.png" width="380" alt="VLM tab"> <img src="docs/images/omni-panel-imggen.png" width="380" alt="Image Gen tab"> </p> <p align="center"> <img src="docs/images/omni-panel-video.png" width="380" alt="Video tab"> <img src="docs/images/omni-panel-voice.png" width="380" alt="Voice tab"> </p>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
dshCLI (DeepSeek Harness) with awebprofile installedpnpmonPATH(or usenpx --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-workstationrow to the profilecordis.patch.yml— the bundle already inserts it. A second insert throwsduplicate loader entry id: omni-workstationat 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 profilepackage.jsondependencies and"dsh-omni-workstation"to thedsh.profile.bundlesarray, runpnpm install, then restartdsh web.
Quick Start
- Restart
dsh weband 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_imagetool 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 persistsomni-vision.json; provider-gated tool registration re-syncs on config changes. - Client half (
lib/client.js) — the browser module (loaded via thedsh.cliententry): registers the Settings → Omni Workstation section and its locale namespace (settings.omni-workstation).
Documentation
- docs/features/vlm.md — VLM analysis, card failover, mirror models, multimodal adaptation (中文)
- docs/features/vision-toolkit.md — the 6 vision tools (中文)
- docs/features/imggen.md — image generation & ComfyUI workflows (中文)
- docs/features/video.md — multi-card video generation &
/build-video-tool(中文) - docs/features/voice.md — TTS & voice cloning (中文)
- docs/reference/api.md —
/omni/*API contract - docs/changelog/changelog.md — changelog
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
有意识地管理
安装与管理
前置条件与目标 Profile
目标: Web Profile
交付方式: Git Bundle — huashenglian/dsh-omni-workstation#071a06665db95e182b9ea999805e1b3a2693c4d6。
验证、更新与移除
显示生命周期命令
dsh plugin --profile web list兼容性与访问范围
Requires DeepSeek Harness dsh with a web profile and pnpm available: Not declared in supplied evidence。
风险事实
证据与编辑审查Manifest、Bundle patch、分发与新鲜度
不可变证据
审查状态与源码活动
源码采用 MIT 许可证。添加生产凭据前,请审查配置的服务商端点并妥善保护本地配置文件。
AI 审查于 2026/9/11 UTC 14:06。GitHub 事实核对日期: 2026/9/11 UTC 14:06。
自当前证据基线以来,没有记录到重要源码变化。