DeepSeek Harness plugin

dsh-local-vision

Local vision bridge for text-only models via llama.cpp, Ollama, LM Studio, or vLLM.

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Source facts

Repository
hyls9527/dsh-local-vision
Latest update
Aug 14, 2026
Category
Vision & Multimodal
GitHub stars
1
Format
bundle
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/hyls9527/dsh-local-vision
Plugin: dsh-local-vision
Author: hyls9527

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer2 files
README.mdSource · read only

dsh-local-vision

> DSH profile bundle · v0.2.0 —— 给纯文本大模型装上「眼睛」

English: Give text-only LLMs (e.g. deepseek-v4-flash) local vision — works with any OpenAI-compatible local inference server (llama.cpp, Ollama, LM Studio, vLLM/SGLang, Jan, GPT4All, llamafile…). Pure Node, no Python, fully offline.

为不具备视觉能力的模型(如 deepseek-v4-flash)提供本地看图能力:兼容所有 OpenAI 兼容的本地推理框架——llama.cpp、Ollama、LM Studio、vLLM/SGLang、Jan、 GPT4All、llamafile 等。纯 Node 实现、零 Python 依赖、全程离线。

一句话用法:local_vision(image="图片路径") —— 自动选端点、自动挑视觉模型、 直接返回图片描述。

功能特性

  • 多端点自动轮询:配置多个本地推理服务,按序选用第一个「健康且含视觉模型」的端点
  • 视觉模型自动探测GET /v1/models 枚举 + 名称启发式过滤(vl/vision/llava/minicpm/internvl/glm-4v/gpt-4o 等关键词)+ Ollama 原生 /api/tags capabilities 增强
  • 仅限视觉模型:端点没有视觉模型时明确报错并列出全部模型,绝不误用纯文本模型
  • 模型参数可选model 可显式指定;缺省自动选择端点上第一个视觉模型
  • health 探测、取消信号、超时控制一应俱全

安装到本机 profile

# 构建(需 node + npm)
npm install && npm run build

# 装入 profile(link 依赖):
#   在 ~/.dsh/profiles/web/package.json 的 dependencies 加:
#     "dsh-local-vision": "link:<本仓库绝对路径>"
#   并在 dsh.profile.bundles 追加 "dsh-local-vision",然后:
cd ~/.dsh/profiles/web && pnpm install -w

工具:local_vision

参数说明
image图片绝对路径(png/jpg/webp/gif/bmp 等),必填
question要问模型的问题;缺省为详细描述图片内容
maxTokens回答长度上限,默认 1024
model视觉模型 id(可选);缺省自动选择端点上第一个视觉模型

返回:{ description, endpoint, model, usage? }

插件配置(cordis.patch.yml 可覆盖)

# ~/.dsh/profiles/web/cordis.patch.yml 中覆盖端点列表示例:
- id: local-vision
  name: dsh-local-vision
  config:
    endpoints:
      - baseUrl: http://127.0.0.1:8090
        alias: llama.cpp
      - baseUrl: http://127.0.0.1:11434
        alias: ollama
      - baseUrl: http://127.0.0.1:1234
        alias: lm-studio
    timeoutMs: 900000

缺省端点:llama.cpp (http://127.0.0.1:8090) + Ollama (http://127.0.0.1:11434)。

与 local-vision 技能的分工

需求用哪个
快速纯文字 OCR、发票、表格、UI 元素坐标local-vision 技能(PaddleOCR / OmniParser)
语义理解:描述场景、看图问答、读懂截图含义本插件(本地视觉模型,全离线)

开发

npm run typecheck   # tsc --noEmit
npm run build       # esbuild → lib/index.js