jyh20030112/dsh-visual-plugin 预览 preview

jyh20030112/dsh-visual-plugin

Dsh-visual-plugin。为你的纯文本模型赋予视觉能力:将用户图像转发至任何兼容OpenAI的视觉模型,并在Web UI右侧面板中查看结果。

Project Overview项目介绍

dsh-visual-plugin is a DeepSeek Harness plugin that analyzes images and videos using the currently selected multimodal model in DSH. Core capabilities include native image understanding with a copyable description history, PySceneDetect-based keyframe extraction, H.264/yuv420p video normalization, and a right-side panel for switching between image and video views with a chat draft stage. Use it to perform image question-answering and video content analysis directly inside the DSH web UI through a single configured model. Note: video features require FFmpeg/FFprobe ≥6.1 with libx264 and PySceneDetect 0.7.x installed on the host, and an image-capable model must be selected in DSH before sending media.

dsh-visual-plugin 是 DeepSeek Harness 的视觉插件,复用 DSH 当前已选的多模态模型对图片与视频进行分析。核心能力包括:原生图片理解与可复制描述历史、基于 PySceneDetect 的关键帧抽取、H.264/yuv420p 视频转码以及右侧面板的图/视频切换与草稿暂存。适用场景为在 DSH Web 中通过同一模型完成图文问答与视频内容理解。注意:使用视频功能前需在主机自行安装 FFmpeg/FFprobe ≥6.1(带 libx264)与 PySceneDetect 0.7.x,且必须在 DSH 中选择支持图像的模型。

Or use CLI install (for developers)或使用命令行安装(适合开发者)

CLI Install命令行安装

dsh plugin --profile web add dsh-visual-plugin

jyh20030112/dsh-visual-plugin 加入你的 DSH 配置(web profile)即可启用。

READMEREADME

dsh-visual-plugin

DeepSeek neon pixel whale

npm version npm downloads GitHub stars MIT license
TypeScript zero runtime deps

Analyze images and videos with DSH's native vision models and inspect the results in a Web UI right panel.

English · 简体中文

A plugin for 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

Image and video analysis in the dsh web right panel

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:

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.

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:

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:

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.

    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

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

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

Friendly Links

Thanks

  • HsiangNianian — for their help and insights during development.
  • tingfeng347 — for the build-stability and local-harness-setup fixes.
  • 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

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