# dsh-visual-plugin

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<p align="center">
  Analyze images and videos with DSH's native vision models and inspect
  the results in a Web UI right panel.
</p>

<p align="center">
  <a href="README.md"><b>English</b></a> · <a href="README.zh.md">简体中文</a>
</p>

A plugin for [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness).

## Features

- **Native image understanding** — uploaded images stay on DSH's native attachment and model path; the plugin does not configure or call a separate vision model.
- **Copyable image history** — the right panel records the current DSH model's final answer beside each image thumbnail, with expandable history and one-click copy.
- **Plugin-owned video upload** — accepts MP4, M4V, MOV, AVI, MPG/MPEG, MKV, and WebM only when extension, signature, and FFprobe agree.
- **Scene-aware video analysis** — normalizes to H.264/yuv420p MP4, extracts keyframes with PySceneDetect, and sends ordered timestamped images to the current DSH vision model.
- **Right-side panel** — switch between image/video views, play normalized videos directly, and stage a selected video in the chat draft.
- **Advanced video settings** — tune upload size, storage quota, duration, output size, FPS, CRF, and keyframe count from the plugin settings card.

## How it works

<p align="center">
  <img src="https://raw.githubusercontent.com/jyh20030112/dsh-visual-plugin/main/assets/vision-bridge-flow.svg" width="720" alt="Image and video analysis in the dsh web right panel">
</p>

```
image → DSH native attachment → current image-capable model → final answer
  → /vision-bridge/recent → panel thumbnail + copyable description

video → container validation → H.264/yuv420p normalization → PySceneDetect
  → timestamped keyframes → DSH native image attachments → current model answers
```

The plugin never rewrites model messages or calls a private vision endpoint. Select an image-capable model in DSH before sending images or asking about a video.

## Quick start

Video support requires FFmpeg/FFprobe `>= 6.1` from the same major release (with `libx264`) and PySceneDetect `>= 0.7.1 < 0.8` installed on the host:

```sh
ffmpeg -version
ffprobe -version
python -m pip install 'scenedetect[opencv]>=0.7.1,<0.8'
scenedetect version
```

The plugin never downloads these tools or runs installers. Image features remain available when they are missing, and the settings card reports each video dependency issue.

```sh
dsh plugin --profile web add dsh-visual-plugin   # or: github:jyh20030112/dsh-visual-plugin
```

When developing this checkout against a local DeepSeek Harness source tree, install the local package instead:

```sh
cd /absolute/path/to/dsh-visual-plugin
npm run bootstrap
dsh plugin --profile web add link:/absolute/path/to/dsh-visual-plugin
```

`bootstrap` automatically finds a sibling or ancestor-adjacent Harness checkout.
For another layout, set its location explicitly:

```sh
HARNESS=/absolute/path/to/deepseek-harness npm run bootstrap
```

Restart `dsh web`, then:

1. Open **Settings → Plugins → Plugin configuration** and expand the **Visual Media** card. Use **Sidebar** to show or hide the right panel, and adjust the advanced video settings when needed.

   <img src="https://raw.githubusercontent.com/jyh20030112/dsh-visual-plugin/main/assets/vision-bridge-config.png" width="560" alt="Visual Media settings card with video dependencies and advanced processing controls">

2. Select an image-capable model in DSH; there is no separate vision-model configuration in this plugin.
3. Send an image. The current model answers natively, and the image panel records the thumbnail and final answer for copying.
4. Upload a video from **Upload video** beside the composer. Once processing finishes, select **Videos** in the right panel to play it; **Ask in chat** stages a draft and never submits automatically.

### Vision model

Image and keyframe understanding use the image-capable model currently selected in DSH. Model providers, endpoints, and credentials are managed by DSH rather than this plugin.

## Uninstall

```sh
dsh plugin --profile web remove dsh-visual-plugin
```

Restart `dsh web`. The command forwards to `pnpm remove` inside the profile, and the bundle layer list reconciles to drop the plugin automatically.

## Project layout

```
src/
  index.ts      native image history, video_describe tool, settings, and HTTP routes
  config.ts     advanced video-processing settings and runtime policy
  video/        upload, container probing, transcoding, scene detection, keyframes, and HTTP Range playback
  client/       image/video panel, upload controls, advanced settings, locales, and CSS
cordis.patch.yml  bundle patch layer
```

## Build

```sh
npm run bootstrap && npm run typecheck && npm run build   # needs a local harness checkout
```

Prebuilt `lib/` is committed, so consumers never build.

## CI/CD

`ci.yml` verifies artifacts and the pack contents on every push/PR. `release.yml` (tag `v*`) checks the version, packs, creates a GitHub Release, and publishes to npm.

## Resources

- [DeepSeek Harness](https://github.com/deepseek-ai/deepseek-harness) — the plugin host this project extends.
- [PySceneDetect](https://www.scenedetect.com/) — scene detection used to select video keyframes.
- [awesome-dsh-plugin](https://github.com/awesome-dsh-plugin/awesome-dsh-plugin) — the curated DSH plugin list where this plugin is registered.

## Friendly Links

- [LINUX DO](https://linux.do)

## Thanks

- [HsiangNianian](https://github.com/HsiangNianian/) — for their help and insights during development.
- [tingfeng347](https://github.com/tingfeng347) — for the build-stability and local-harness-setup fixes.
- [dsh-auto-continue](https://github.com/HsiangNianian/dsh-auto-continue) — a DSH Web UI plugin that auto-resumes interrupted requests with 「继续」 (error classification, adaptive backoff, browser notifications); a handy companion.

## License

[MIT](LICENSE)