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Bundle Vision — DeepSeek Harness 插件(DSH Plugin)
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dsh-bundle-vision

Bundle Vision

DeepSeek Harness 的视觉套件 + 插件:describe_image 工具读取本地图片,并请求任意已配置的多模态路由,无需修改核心

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add dsh-bundle-vision@0.1.0
README兼容性版本

兼容性与来源证明

Bundle Vision 以 dsh-bundle-vision 发布,当前版本为 0.1.0。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
npm
Registry 更新时间
2026/9/20

版本

0.1.0stable
2026/8/15

相关插件

正在加载相关插件…

最新版
0.1.0
DSH
*
HMR
重启进程
Tree shaking
未声明可安全裁剪
解包体积
18.5 kB
文件数
7
Surface
any
许可证
MIT
发布源
npm
GitHub
★ 0
周下载
45
最近提交
2026/8/15
查看源码 ↗项目主页 ↗
README Badge

点击下方 Badge 复制 Markdown,粘贴到 README 即可。

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相关插件

继续浏览 vision-media 分类下经过校验的插件。

Tool Describe Image@linxin666/dsh-tool-describe-image面向模型的 describe_image 工具,用于 dsh Web GUI:通过在兼容 OpenAI 的端点调用视觉语言模型,为文本模型提供图像理解能力,以描述一张图像(本地路径、http(s) URL 或附件引用)。可热插拔 —Modlens@liustack/modlens面向仅支持文本的 LLM 的插件视觉能力,由免费的 Antigravity CLI 提供支持Vision Toolkit@anionex/dsh-vision-toolkit面向 Harness 原生集成的 DeepSeek 与 agent-vision-toolkit:图像问答、OCR、定位、UI 还原、像素差异、Artifacts 和 Web UI。Deepseek Ivideodeepseek-ivideoiPolloWork HyperFrames Video Studio,以及 27 个可编辑视频模板,以原生 DeepSeek Harness 对话视图呈现。

README

dsh-bundle-vision

A zero-core-change vision capability for DeepSeek Harness, shipped as one installable npm package that is both a profile bundle and a plugin:

  • the plugin registers the model-facing describe_image tool;
  • the bundle patch mounts that plugin on any profile.

The tool reads a local PNG/JPEG/WebP/GIF file, commits the bytes through the shipped attachment service, and asks the named multimodal route about it in one direct LLM request (provider / model are tool arguments). The result is text only — no image block ever enters the calling session, so a text-only main model gains vision without any change to dsh itself.

How it works against the shipped seams

Everything the tool uses already ships with every dsh profile:

  • ctx.fs (bounded byte read, session-workspace resolution) — filesystem capability;
  • ctx.attachments (saveImage, image limits, magic-byte validation) — durable image storage;
  • ctx.llm (resolveModelInfo + stream) with the pi-ai multi-provider adapter — the multimodal request itself.

The one per-deployment prerequisite is the same as for any vision use of dsh: the multimodal model must declare image input in the llm-pi-ai settings section, e.g.:

llm-pi-ai:
  providers:
    my-vision:
      apiKeyEnv: MY_VISION_API_KEY
      api: openai-completions
      baseURL: https://example.invalid/v1
      models:
        - id: my-vision-model
          input: [text, image]

(On releases whose Models page has the input-modality control, the same declaration is one dropdown.)

Install (installed dsh, no source checkout)

From the npm registry:

dsh plugin --profile <name> add dsh-bundle-vision

Or from a packed tarball (e.g. before the first publish, or for a pinned version):

dsh plugin --profile <name> add ./dsh-bundle-vision-0.1.0.tgz

dsh plugin forwards to pnpm inside the profile directory and reconciles the profile's bundle layers automatically — a dependency declaring dsh.bundle joins the layer stack. Restart dsh <name>; the tool registers for every agent (profile-root registrations are visible to all preset scopes).

Use

Ask the main model, naming the route:

Use describe_image with file_path /path/to/photo.jpg, provider my-vision, model my-vision-model, and prompt "OCR the text in this image".

The main model supplies provider/model per call — configure several multimodal routes and switch per call, no profile edits. Refusals name the failing gate (unknown extension, deployment media types, a route whose model does not declare image input, a missing file, a type-mismatched file, an errored stream).

Version floor

The package declares >=0.1.0-rc.6 peer dependencies on the dsh seam packages. Bump the floor if a later release is required.

Development

npm install          # dev deps resolve the seam packages from the npm registry
npm run typecheck    # tsc --noEmit over src + tests
npm test             # vitest
npm run build        # tsdown (lib/index.js) + tsc declarations (lib/types)
npm pack             # the installable tarball