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OmniVision for DeepSeek Harness: an OmniParser-powered GUI agent plugin — screen capture, element recognition, click/type automation and a browser vision dock with recognition history, diffing and summary

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xiaozhengdeng
stars
2 stars
License
MIT
Updated
Updated 10 days ago

Readme

<div align="center">

# dsh_omnivision

**OmniVision** — OmniParser-powered GUI agent plugin for DeepSeek Harness

English | [中文](#中文)

</div>

---

# English

**OmniVision** is an OmniParser-powered GUI agent plugin for DeepSeek Harness. It turns the desktop or any image into structured elements (text + icons with pixel coordinates), so the model can see and operate the screen **without multimodal vision**.

## Screenshots

| Vision view (智能识别) | Recognition history (识别记录) |
| --- | --- |
| ![Vision view](assets/dock-vision.png) | ![Recognition history](assets/dock-history.png) |

## Features

| Feature | Description |
| --- | --- |
| 🖥 Screen recognition | Capture the desktop (or parse an image) and get interactive elements with pixel coordinates via OmniParser |
| 🖱 Desktop automation | Click, double-click, right-click, drag, type (unicode-safe), key, hotkey, scroll — by element id or raw x/y |
| 👁 Live vision dock | Real-time recognition view with SOM-annotated overlay, hover highlight, click-to-zoom |
| 🕘 Recognition history | Thumbnails per capture, diff vs latest (added / removed / moved) |
| 📋 One-click summary | Sends the recognized elements to the session for the model to summarize |
| 🖼 File parsing | Parse local images from the dock, bypassing model multimodal limits |
| 📊 Call log | Tracks every `gui_*` tool call and action for inspection |

## Tools

The plugin registers these `gui_*` tools into the shared tools registry:

- `gui_capture` — capture the desktop screen and run OmniParser to extract interactive elements (text + icons with pixel coordinates), refreshing the shared vision state and saving the SOM-annotated overlay
- `gui_act` — perform a real mouse/keyboard action on the desktop: click / double-click / right-click / move / type / press / hotkey / scroll / drag
- `gui_find` — search the elements from the last capture by text or type
- `gui_state` — show the current vision state without parsing
- `gui_verify` — re-capture and check whether a text is present or absent, retrying until it settles
- `gui_task` — execute a scripted multi-step UI plan with re-parse between steps and optional assertions
- `gui_open_app` — launch an installed desktop app by name via its Windows AUMID
- `gui_parse_image` — parse a third-party image (from a conversation attachment) into the shared vision state

## Installation

```bash
dsh plugin --profile web add dsh_omnivision
# or a local path:
dsh plugin --profile web add G:\deepseek\plugins\dsh_omnivision
```

Restart the web process after installing. The plugin loads as a profile bundle layer:

- **Host half** registers the `gui_*` tools into the shared `tools` registry and serves the browser half over an HTTP route (`/dsh-omnivision/<method>`)
- **Client half** mounts the OmniVision dock into `shell.overlay` and a toggle into the sidebar footer

## Prerequisites

- Windows with an OmniParser FastAPI server on `http://127.0.0.1:8000` (e.g. via `G:\omni\OmniParser\start_server.bat`)
- The Python venv needs `pyautogui` for screenshots and input automation

## Usage

Call the `gui_*` tools from the model side; the **OmniVision** dock in the browser provides the visual surface:

| Control | Description |
| --- | --- |
| 智能识别 | Live element list + SOM-annotated image (hover to highlight, click to zoom) |
| 🖼 解析图片 | Pick a local image file to parse (bypasses model multimodal limits) |
| 📋 总结 | Send the current recognition info to the session for the model to summarize |
| 识别记录 | History with thumbnails + diff vs latest (added / removed / moved) |
| 调用记录 | Recent `gui_*` tool calls and action log |
| 探测 | Check OmniParser server connectivity |

## Development

```bash
pnpm build      # tsc (host) + tsc (client) + tsdown (client bundle)
pnpm typecheck
```

## License

MIT

---

# 中文

**OmniVision** 是 DeepSeek Harness 的 OmniParser 驱动的 GUI 智能体插件。它把桌面或任意图片变成结构化元素(文本 + 图标 + 像素坐标),让模型**无需多模态能力**就能「看见」并操作屏幕。

## 界面截图

| 智能识别视图 | 识别记录视图 |
| --- | --- |
| ![智能识别](assets/dock-vision.png) | ![识别记录](assets/dock-history.png) |

## 功能

| 功能 | 说明 |
| --- | --- |
| 🖥 屏幕识别 | 截取桌面(或解析图片),经 OmniParser 提取带像素坐标的可交互元素 |
| 🖱 桌面自动化 | 点击 / 双击 / 右键 / 拖拽 / 输入(Unicode 安全)/ 按键 / 热键 / 滚轮,按元素 id 或原始坐标操作 |
| 👁 实时识别 Dock | 实时识别视图 + SOM 标注图(悬停高亮、点击放大) |
| 🕘 识别记录 | 每次识别的缩略图 + 与最新对比(新增 / 移除 / 位移) |
| 📋 一键总结 | 把当前识别信息发到会话,由模型按提示词总结 |
| 🖼 图片解析 | 从 Dock 选择本地图片解析,绕开模型多模态限制 |
| 📊 调用记录 | 记录每次 `gui_*` 工具调用与动作,便于排查 |

## 工具

插件向共享工具注册表注册以下 `gui_*` 工具:

- `gui_capture` — 以原生分辨率截取桌面,运行 OmniParser 提取可交互元素(文本 + 图标 + 像素坐标),刷新共享视觉状态并保存 SOM 标注图
- `gui_act` — 在桌面上执行真实鼠标/键盘操作:点击 / 双击 / 右键 / 移动 / 输入 / 按键 / 热键 / 滚轮 / 拖拽
- `gui_find` — 按文本或类型搜索上一次识别的元素
- `gui_state` — 查看当前视觉状态(不重新解析)
- `gui_verify` — 重新截屏解析,反复确认某文本出现或消失
- `gui_task` — 按脚本执行多步 UI 计划,步骤间重新解析并支持断言
- `gui_open_app` — 通过 Windows AUMID 按名称启动已安装的桌面应用
- `gui_parse_image` — 解析会话中的第三方图片(附件)进入共享视觉状态

## 安装

```bash
dsh plugin --profile web add dsh_omnivision
# 或本地路径:
dsh plugin --profile web add G:\deepseek\plugins\dsh_omnivision
```

安装后重启 web 进程。插件作为 profile bundle 层加载:

- **Host 半**把 `gui_*` 工具注册进共享 `tools` 注册表,并通过 HTTP 路由(`/dsh-omnivision/<method>`)为浏览器半提供数据
- **Client 半**把 OmniVision Dock 挂到 `shell.overlay`,侧栏底部挂开关按钮

## 前置依赖

- Windows + 运行在 `http://127.0.0.1:8000` 的 OmniParser FastAPI 服务(如 `G:\omni\OmniParser\start_server.bat`)
- Python venv 需安装 `pyautogui`(截图与输入自动化)

## 使用

模型侧直接调用 `gui_*` 工具;浏览器里的 **OmniVision** Dock 提供可视化操作:

| 控件 | 说明 |
| --- | --- |
| 智能识别 | 实时元素列表 + SOM 标注图(悬停高亮、点击放大) |
| 🖼 解析图片 | 选择本地图片文件解析(绕开模型多模态限制) |
| 📋 总结 | 把当前识别信息发到会话,由模型按提示词总结 |
| 识别记录 | 历史缩略图 + 与最新对比(新增 / 移除 / 位移) |
| 调用记录 | 最近 `gui_*` 工具调用与动作日志 |
| 探测 | 检查 OmniParser 服务连通性 |

## 开发

```bash
pnpm build      # tsc (host) + tsc (client) + tsdown (client bundle)
pnpm typecheck
```

## 许可证

MIT

Install

dsh plugin --profile web add github:xiaozhengdeng/dsh_omnivision#e62ad43e18cbb1743892eddf18a7624776c29674

Profile: web

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