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Tool Vision Read — DeepSeek Harness 插件(DSH Plugin)
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@deepseek-ai/dsh-tool-vision-read

Tool Vision Read

DSH 插件:vision_read — 将图像读取路由到专用视觉模型(例如 Kimi K3),让仅支持文本的智能体能够查看图像

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add github:Mappedinfo/dsh-tool-vision-read#921d4af1a2333d58d1020703c20b0c2ab93833ab
README兼容性版本
vision_read demo in the DeepSeek Harness GUI

兼容性与来源证明

Tool Vision Read 以 @deepseek-ai/dsh-tool-vision-read 发布,当前版本为 0.1.0-rc.6。Plugin Hub 会校验它的 manifest,并保存精确安装来源,便于复现安装结果。

DSH 兼容范围
*
运行环境
any
发布来源
github
Registry 更新时间
2026/8/21

版本

0.1.0-rc.6prerelease
2026/8/21

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0.1.0-rc.6
DSH
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未提供
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any
许可证
MIT
发布源
github
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最近提交
2026/8/21
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README

dsh-tool-vision-read

Unofficial community plugin. Independently developed and maintained; not part of the official DeepSeek Harness distribution.

A lightweight DeepSeek Harness plugin that registers a vision_read tool: it reads an image file through a dedicated vision model route and returns a text description — so a text-only agent (a model whose route does not declare image input, e.g. a chat model without vision) can still "see" images.

It is the same idea as routing different roles to different models (e.g. oh-my-pi's modelRoles), applied to one narrow capability: image description. No third-party CLI (modlens etc.), no manual delegation — the plugin does it in one call.

How it works

ModeBehaviorCost
direct (default)The plugin reads the file, commits it through the attachment service, and makes one llm.stream call to the configured vision provider/model with a text+image message.One round trip, no agent loop.
subagentThe plugin starts an in-process subagent pinned to the vision route (agentOptions), which calls read_image itself and can iterate (zoom, OCR, follow-ups).Full agent loop, more flexible.

The tool always routes to the configured vision route, regardless of the calling model. Configuration parsing fails when either route id is omitted; a call resolves the route before image I/O and fails with guidance when the resolved route does not declare image input (declare it in the provider settings, e.g. defaultInput: [text, image] for pi-ai routes).

Requirements

  • A DeepSeek Harness deployment (source checkout or out-of-tree profile install).
  • A vision-capable model route. The plugin was verified against Kimi Coding API (k3-256k, which accepts image input) — any provider that supports image content blocks works.

Install

Option A: inside the deepseek-harness monorepo (recommended for development)

Copy this package under packages/vision/tool-vision-read (or install from git), then:

pnpm install

Register the package in tsconfig.base.json (add ./packages/vision/*/src to the @deepseek-ai/dsh-* wildcard and the @deepseek-ai/dsh-*/invariant wildcard) and in tsconfig.host.json references, then mount it — see the official adding-a-package cookbook.

Option B: install the Profile Bundle (recommended)

Install the Git repository into a profile through the DSH plugin manager:

dsh plugin --profile web add github:Mappedinfo/dsh-tool-vision-read

For local development, link the checkout instead:

dsh plugin --profile web add link:/absolute/path/to/dsh-tool-vision-read

The package declares a DSH Profile Bundle, so a successful install adds it to dsh.profile.bundles. Restart dsh web; its bundled cordis.patch.yml mounts vision_read automatically. The default route is kimi-coding / k3-256k. Override it for one launch without editing the package:

DSH_VISION_PROVIDER=my-provider DSH_VISION_MODEL=my-vision-model dsh web

The profile's own cordis.patch.yml is applied after the Bundle. Use an id-targeted override when the route or other options must be durable:

- id: tool-vision-read
  config:
    provider: my-provider
    model: my-vision-model
    mode: direct

Do not insert a second tool-vision-read row in the profile. Remove the Bundle with dsh plugin --profile web remove @deepseek-ai/dsh-tool-vision-read. The @deepseek-ai/* peer packages are satisfied by the DSH installation's module closure ($DSH_HOME/profiles/node_modules flat fallback) — autoInstallPeers: false keeps pnpm from pulling older registry copies.

Configuration

KeyTypeDefaultMeaning
providerstring— (required)Registered provider route owning the vision model.
modelstring— (required)Vision model id on that route.
toolNamestringvision_readModel-facing tool name.
mode'direct' | 'subagent''direct'Execution mode.
maxImageBytesnumberattachment limitsCap on image bytes sent to the vision route.
maxOutputTokensnumber1024Cap on the vision route's output tokens.
promptstringsee sourceInstruction sent beside the image; {{path}} and {{focus}} placeholders.

Tool contract

vision_read(file_path: string, focus?: string)

Returns { path, provider, model, description } — the vision model's text description of the image. Accepts PNG/JPEG/WebP/GIF paths only; paths resolve against the calling session's workspace cwd.

Example

A text-only agent (deepseek-v4-flash) calling vision_read on a campus-gate photo, with the description produced by Kimi K3-256K through the kimi-coding route:

vision_read demo in the DeepSeek Harness GUI

user: 请用 vision_read 看一下 /Users/shiqi/Downloads/微信图片_20260816082109_883_131.jpg 并描述内容
agent: (vision_read) → "这是一张横构图、白天拍摄的现代城市/园区街景照片……天空与云约占画面上方 2/3……
        左侧一栋多层建筑转角呈弧形……中右一座较低的建筑带弧形屋顶边缘和竖向格栅外立面……"

Layout

src/index.ts          # plugin (name/inject/apply/Config) + vision_read tool
src/invariant.ts      # package invariant companion (no runtime invariant)
cordis.patch.yml      # auto-mounted DSH Profile Bundle layer
lib/                  # reference build emitted from the deepseek-harness monorepo
tests/                # vitest spec (runs in the monorepo context)
docs/dsh-discussion-draft.md   # DeepSeek Harness "Show Your Plugins!" draft

Notes

  • lib/ is the reference build generated from the package inside the deepseek-harness monorepo (packages/vision/tool-vision-read); the tests run against the monorepo toolchain. The git dependency installs the committed lib/ directly.
  • Developed and verified end-to-end: a text-only agent (deepseek-v4-flash) calling vision_read on a JPEG received a correct description from Kimi K3-256K.

License

MIT