dsh-vision

1. 安装并启动 DeepSeek Harness：npx @deepseek-ai/dsh web
2. 在终端执行上面的安装命令（CLI 会解析插件并核验来源）
3. 用 dsh plugins list 确认已安装，必要时重启 Harness 生效

插件以当前 dsh 进程的权限运行，安装时可能执行代码。请先通读仓库源码与许可证，确认无破坏性命令与越权访问；本站只做索引，不对第三方插件安全性作担保。

事实信息来自公开插件目录快照（2026-10-01），介绍文案由本站再加工。

以下为插件仓库 README 全文（原始内容，由公开目录抓取整理）。

[图片: dsh-vision: native vision passthrough and a vision bridge for DeepSeek Harness]

  English | 中文

  [图片: CI]

  [图片: MIT License]

  [图片: DeepSeek Harness]

`dsh-vision` is a plugin for DeepSeek Harness. Vision-capable models keep receiving images natively. When the selected main model is text-only, the plugin asks a separate vision model to observe the original images, then lets the original DeepSeek model produce the final answer.

## How it works

| Main model | Image path | Final answer |
| --- | --- | --- |
| Supports images | Original images are sent directly, without preprocessing or OCR | Current model |
| `deepseek-official` or another text-only model | A configured vision model observes the original images; its output is injected as untrusted attachment context | DeepSeek |
| Cloud vision unavailable | Falls back to macOS Vision or Tesseract | DeepSeek |

The plugin does not replace the main model selected in Harness. Multiple image attachments are analyzed together, so comparisons and combined evidence work naturally. The user's task is forwarded unchanged instead of being wrapped in a fixed report template.

## Install

Use the plugin manager built into DeepSeek Harness:

```bash
npx @deepseek-ai/dsh plugin --profile web add github:oil-oil/dsh-vision
```

Restart Harness, then paste or drag images into the composer as usual. The plugin replaces the official `deepseek-official` adapter while preserving its model catalog, settings, and credentials. It also adds a **Vision Recognition** card to **Settings → Plugins → Plugin configuration**.

> DeepSeek Harness is still in Developer Preview. This release targets `0.1.0-rc.6` exactly.

## Configure Vision Recognition

Open **Settings → Plugins → Plugin configuration → Vision Recognition**. Select ZenMux, Alibaba Cloud Model Studio, TokenDance, or OpenRouter, then enter its API key. The same card lets you change the model ID, API endpoint, and image limit.

The API key is stored through Harness's official credential service. It is write-only in the browser: the plugin can report whether a key exists, but never reads it back into the page, chat, settings document, or session log.

Routing follows the user's choice. A provider selected in Vision Recognition is primary for text-only models. Other enabled Harness vision routes, an existing see configuration, and local OCR are failover only. When the current main model supports images, the original images pass through natively and none of these bridge routes are used.

Choose **Automatic** to skip plugin-managed cloud credentials. The bridge then tries image-capable models already configured in Harness, followed by see-compatible private configuration and local OCR. A Harness custom model must declare `image` as an input modality or it remains a text model.

## Advanced file configuration

Most setups should use the UI. The equivalent non-secret fields live in the existing `llm-deepseek` section of `$DSH_HOME/settings.yaml`:

```yaml
llm-deepseek:
  visionBackend: zenmux
  visionBackendModel: qwen/qwen3.7-plus
  visionBackendBaseURL: https://zenmux.ai/api/v1
  maxImages: 8
```

Do not put API keys in this file. Save them in the Vision Recognition card or provide the matching environment variable. Changes apply without a restart.

## see-skill compatibility

If Harness has no usable vision model, the plugin also reads `~/.config/see/config.env`. It supports ZenMux, Alibaba Cloud Model Studio, OpenRouter, and TokenDance. Environment variables override the private config file.

```bash
export SEE_PROVIDER=zenmux
export ZENMUX_API_KEY=your-key
```

`SEE_PROVIDER` selects the primary provider. Other providers with configured keys are failover routes only. If no provider is selected and only one is configured, that provider is used.

When no cloud key is available, or every cloud route fails, the plugin tries local capabilities:

- macOS: built-in Vision OCR, with no extra dependency.
- Linux / Windows: Tesseract with the required language data installed.

Local fallback is primarily OCR and is not equivalent to full multimodal understanding.

## Security boundary

- Original images are sent only to vision services configured by the user.
- Vision output is marked as untrusted observation data; instructions inside an image receive no system authority.
- Generated vision context affects only the current model request and does not rewrite message history.
- API keys are resolved through Harness credentials or the user's private see config and are never written to this repository.

## Development

```bash
pnpm install
pnpm check
```

The project is available under the MIT License. Cloud routing, joint multi-image analysis, and local fallback behavior are based on the MIT-licensed [oil-oil/see-skill](https://github.com/oil-oil/see-skill). The DeepSeek icon comes from the official [deepseek-ai/deepseek-harness](https://github.com/deepseek-ai/deepseek-harness) repository.