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dsh-qwen-multimodal

Verified · install-tested on dsh wuwangmao

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2026-08-15Last push
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What it does

DSH bundle: Qwen multimodal bridge — vision (qwen3-vl), speech-to-text (qwen3-asr), text-to-image (qwen-image), for DeepSeek Harness

✅
Our take
Works — verified, early-stage project

DSH bundle: Qwen multimodal bridge — vision (qwen3-vl), speech-to-text (qwen3-asr), text-to-image (qwen-image), for DeepSeek Harness It installs cleanly and boots without issues in our testing. It's early-stage but functional.

“Verified” means our automated CI actually ran dsh plugin add in a clean profile and it booted — nothing more. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.

README

dsh-qwen-multimodal

A DSH bundle that gives text-only main models (e.g. DeepSeek) **three multimodal skills in one plugin** through Qwen APIs: vision, speech-to-text, and text-to-image — with a built-in generate-then-verify quality loop. | Tool | Capability | Backend | |---|---|---| | describe_image | Image / screenshot / OCR / chart understanding (multiple images at once) | Qwen VL (default qwen3-vl-flash) | | transcribe_audio | Speech / recording transcription (wav/mp3/m4a/aac/flac/ogg/amr) | Qwen3-ASR (qwen3-asr-flash) | | generate_image | Generate images from text and save them locally | Qwen-Image (qwen-image-plus) | Media never enters the main model context: visual/audio content is converted to text, and generated images are saved to local files with paths returned by the tool.

How it works

All API calls reuse the original Python scripts in skills/deepseek-vision/scripts/*.py and the .env configuration (vision/audio use the Alibaba Cloud Bailian OpenAI-compatible endpoint; image generation uses the native multimodal-generation endpoint). The plugin itself is a pure-JS Cordis bundle depending only on the host's mounted subprocess / tools services — **no build step required for git installs**.

Install

From GitHub

``sh dsh plugin --profile demo add github:wuwangmao/dsh-qwen-multimodal `

Local checkout / tarball

`sh dsh plugin --profile demo add ./dsh-qwen-multimodal

or

pnpm pack # then dsh plugin --profile demo add ./dsh-qwen-multimodal-0.1.0.tgz
` Before first use, configure your API key: copy skills/deepseek-vision/.env.example to skills/deepseek-vision/.env and fill in VISION_API_KEY (create one in the Alibaba Cloud Bailian console; new users get free quota, college students get a ¥300 annual voucher). Vision/audio/image reuse the same key by default, or configure them separately (see .env.example).

Python

**Python 3.10+ is required** (the image-generation script uses
int | None type-annotation syntax). python is resolved from the system PATH by default. If it cannot be resolved, restate the plugin row in your profile's cordis.patch.yml and set config.pythonPath.

Configuration overrides

The plugin uses the bundled skill directory by default. To point it at an external directory (e.g. to reuse an existing
.env and scripts, or to keep your key outside node_modules), restate the row: `yaml - insert: - id: qwen-multimodal name: dsh-qwen-multimodal config: skillDir: 'D:/qwen-vision' pythonPath: 'C:/path/to/python.exe' `

Usage

Once loaded, the model can call the three tools directly: -
describe_image({ images: ['screenshot.png'] }) — verbatim extraction of text/code/errors in images - describe_image({ images: ['chart.png'], prompt: '逐字提取图中所有文字,保留原样' }) — custom prompt - transcribe_audio({ audios: ['recording.m4a'], language: 'zh' }) — specify language for accuracy - generate_image({ prompt: 'a cute orange cat on a windowsill watching the sunset', out_dir: './out' }) — generate and save locally - generate_image({ prompt: '...', out_dir: './out', verify: true }) — generate, then automatically re-check the result with Qwen VL against the prompt (quality loop)

Layout

` dsh-qwen-multimodal/ ├── package.json # dsh.bundle manifest ├── cordis.patch.yml # bundle layer: inserts the plugin row ├── src/index.js # plugin: registers the three model tools (pure JS) ├── scripts/selfcheck.mjs # self-check: node scripts/selfcheck.mjs └── skills/deepseek-vision/ # skill assets: SKILL.md + Python scripts + .env.example ``

License

MIT

Install

🧩 Let your agent install it (recommended)

Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:

dsh plugin add dshbase-catalog

Then say "install dsh-qwen-multimodal for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.

This plugin is GitHub source (not published to npm) — install it straight from the repo:

Web profile:

dsh plugin --profile web add github:wuwangmao/dsh-qwen-multimodal

Headless (CLI) profile:

dsh plugin --profile headless add github:wuwangmao/dsh-qwen-multimodal

Test report

Verified: L1 install + L2 load + L3 runtime from GitHub source on dsh 0.1.0-rc.6.

When to use it

Extend the agent's coding surface — give it a new tool, workflow, or integration so it handles a dev task it couldn't before.

Who it's for

Developers who want dsh to behave like a teammate on real codebases — editing, running, and verifying changes rather than just answering.

For developers — extending it

The tool/command surface is the seam: expose more of the SDK, add smarter context wiring, or tighten the loop between code changes and verification.

Security: not yet scanned — our daily static scan will cover it shortly.

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