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Image Studio — DSH Plugin for DeepSeek Harness
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dsh-image-studio

Image Studio

DeepSeek Harness plugin: local text-to-image with a canvas-style GUI, inpainting, DeepSeek vision review, OpenAI-compatible API option, and a Python Stable Diffusion worker (diffusers/MPS).

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add dsh-image-studio@0.1.7
READMECompatibilityVersions

Compatibility and provenance

Image Studio is published as dsh-image-studio and currently resolves to version 0.1.7. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
web
Release source
npm
Registry updated
9/20/2026

Versions

0.1.7stable
9/1/2026
0.1.6stable
9/1/2026
0.1.5stable
9/1/2026
Show 5 more versionsCollapse versions
0.1.4stable
8/31/2026
0.1.3stable
8/31/2026
0.1.2stable
8/31/2026
0.1.1stable
8/31/2026
0.1.0stable
8/31/2026

Related plugins

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Latest
0.1.7
DSH
*
HMR
Process restart
Tree shaking
Safe tree shaking not declared
Unpacked size
58.9 kB
Files
11
Surface
web
License
MIT
Source
npm
GitHub
★ 0
Weekly downloads
64
Last push
8/31/2026
View source ↗Project homepage ↗
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README

dsh-image-studio

Language: English · Česky

DeepSeek Harness plugin for local text-to-image and image editing, with a settings GUI and a model-callable dsh_image tool.

Features

  • Generate images from a prompt — locally via Stable Diffusion (diffusers + PyTorch MPS on Apple Silicon) or an OpenAI-compatible image API.
  • Inpaint — edit a region of an existing image using a mask.
  • Review — check a generated image with a vision model: the DeepSeek vision API (deepseek-v4-flash-vision-exp) or a local Ollama vision model (qwen2.5vl:3b).
  • Settings section "Image Studio" — backend, model, API key, vision model, and generation parameters.
  • Cooperates with dsh-resource-guard: local generation reserves memory first.

Requirements (local backend)

  • macOS with Apple Silicon (MPS) or a CPU-only fallback.
  • python3 on PATH (creates ~/.dsh/image-studio-venv automatically).
  • First local run downloads model weights (runwayml/stable-diffusion-v1-5, runwayml/stable-diffusion-inpainting).

Install

dsh plugin --profile web add dsh-image-studio

Then add dsh-image-studio to dsh.profile.bundles and dependencies in ~/.dsh/profiles/web/package.json, and run dsh plugin --profile web install.

Usage

Ask the agent:

  • dsh_image action=generate prompt="a lighthouse at dusk" — generate locally.
  • dsh_image action=inpaint prompt="a red door" image=/abs/img.png mask=/abs/mask.png — edit a region.
  • dsh_image action=check image=/abs/img.png — vision review.

Outputs are written to ~/.dsh/image-studio-outputs/.

Settings

FieldDefaultMeaning
backendlocallocal (Stable Diffusion) or api (OpenAI-compatible).
modelrunwayml/stable-diffusion-v1-5Local model id or API image model.
apiBaseUrlhttps://api.openai.com/v1API base URL (backend api).
apiKey``Bearer token (backend api / vision).
visionBackenddeepseekdeepseek or local.
visionModeldeepseek-v4-flash-vision-expVision model id.
steps / guidanceScale / width / height25 / 7.5 / 512 / 512Generation parameters.

Architecture

  • Host (lib/index.js) — spawns worker/image_worker.py (a stdlib HTTP server on 127.0.0.1:7861) into ~/.dsh/image-studio-venv, calls its /generate and /inpaint endpoints, and implements the vision review.
  • Client (lib/client.js) — settings.section with configuration, prompt input, and Generate / Inpaint / Review buttons (via the action namespace).

License

MIT