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dsh-tool-eyes

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2026-08-15最近推送
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功能简介

DeepSeek Harness (DSH) 本地视觉眼睛插件:screen 工具(截图/图片交给本地视觉模型描述)+ ocr 工具(Windows 内置 OCR 逐字提取文字)。零云端、OCR 零 GPU、图片不出本机。

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未验证 — 尚未实测

DeepSeek Harness (DSH) 本地视觉眼睛插件:screen 工具(截图/图片交给本地视觉模型描述)+ ocr 工具(Windows 内置 OCR 逐字提取文字)。零云端、OCR 零 GPU、图片不出本机。 尚未验证——请自行安装测试。

「未验证」表示我们的自动化 CI 尚未安装过该插件。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。

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README

dsh-tool-eyes

Local vision "eyes" for DeepSeek Harness (DSH).

Give your text-only agent eyes with two model-facing tools:

  • screen — capture the screen (or describe an existing image file) through a
    local OpenAI-compatible vision endpoint (llama.cpp with --mmproj, LM Studio,
    Ollama, ...) and return the vision model's text description.
  • ocr — extract ALL text verbatim with the Windows built-in OCR
    engine
    : zero model, zero GPU, zero cloud, milliseconds.
screen  =  screenshot / image  ->  local VLM  ->  text description (understanding)
ocr     =  screenshot / image  ->  Windows OCR -> verbatim text          (extraction)

Why

DeepSeek's chat-completions line is text-only. Instead of switching your whole
conversation to a vision model, keep the text brain and add eyes as tools:

  • Private by default — point screen at a local endpoint and images never
    leave your machine.
  • Cheap — a 0.8B–4B local VLM is plenty for describing screens; ocr costs
    nothing at all.
  • Honest by default — the screen prompt tells the VLM to describe only
    what is visible
    and never guess app/game/character names unless confirmed by
    on-screen text (this measurably cuts small-model name hallucination).

Requirements

  • Windows 10/11 (the ocr tool uses WinRT OCR; screen uses .NET for capture)
  • Node.js >= 22.19, DeepSeek Harness >= 0.1.0-rc.6
  • screen additionally needs any OpenAI-compatible VLM endpoint, e.g.:
    • llama.cpp: llama-server -m model.gguf --mmproj mmproj.gguf --port 1235
    • LM Studio (loaded vision model), Ollama, or any OpenAI-compatible gateway

Install

This package is published on GitHub only (not on npm).

dsh plugin --profile web add https://github.com/go-farther-and-farther/dsh-tool-eyes

Then restart dsh web. The screen and ocr tools appear in the agent's
toolkit automatically.

Manual install (offline / from source)

Copy this package into the profile's node_modules, then register it in
$DSH_HOME/profiles/<profile>/cordis.patch.yml:

- insert:
    - id: tool-eyes
      name: 'dsh-tool-eyes'
      config:
        baseUrl: http://127.0.0.1:1235/v1
        model: ''
        timeoutMs: 180000

Configuration

Plugin config (all optional):

key default meaning
baseUrl http://127.0.0.1:1235/v1 OpenAI-compatible endpoint for screen
model '' model id to send; empty lets the server decide (llama.cpp serves one model)
timeoutMs 180000 hard cap for one capture call
captureScript bundled capture.ps1 override path to an alternate capture script

Override in your profile's cordis.patch.yml (id-targeted):

- id: tool-eyes
  name: 'dsh-tool-eyes'
  config:
    baseUrl: http://127.0.0.1:1235/v1
    model: qwen3.5-4b
    timeoutMs: 120000

Usage

In a conversation, the agent can now:

  • screen — "what is on my screen?", "describe this image file", with an
    optional prompt to focus on a region or detail.
  • ocr — "read all the text on screen", "transcribe this error dialog".

Both accept an optional image path; without it they capture the screen.
The bundled PowerShell scripts can also be run standalone:

powershell -NoProfile -ExecutionPolicy Bypass -File lib\capture.ps1 -Prompt "..." -BaseUrl http://127.0.0.1:1235/v1
powershell -NoProfile -ExecutionPolicy Bypass -File lib\ocr.ps1 -Image C:\path\x.png

Privacy

  • ocr is fully local (WinRT OCR, no network).
  • screen sends the captured image to the configured baseUrl. Point it at a
    local endpoint (llama.cpp / LM Studio / Ollama) to keep images on your machine.

Related

  • dsh-vision-proxy — automatic
    transcription of attached images in the chat input (Chatbox-style), so you
    don't need to give file paths. Pairs well with this plugin.

Development

npm test    # node --test tests/

License

MIT

安装

🧩 让 Agent 自动装(推荐)

装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:

dsh plugin add dshbase-catalog

然后对 agent 说「帮我装 dsh-tool-eyes」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包

该插件是 GitHub 源码(未发 npm)——直接从仓库装:

Web profile:

dsh plugin --profile web add github:go-farther-and-farther/dsh-tool-eyes

Headless(CLI)profile:

dsh plugin --profile headless add github:go-farther-and-farther/dsh-tool-eyes

实测报告

尚未 L3 验证——若已跑过,见下方失败备注。

状态:pending · 最近测试 2026-08-26
备注:验证: runtime-fail 浏览全部待验证失败 →
安全:尚未扫描——我们的每日静态扫描将很快覆盖它。

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