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Argonaut790 /

dsh-deepseek-vision

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Image understanding, OCR, and persistent visual evidence for text-only DeepSeek Harness models

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DSH DeepSeek Vision

CI License: MIT

DSH DeepSeek Vision is an open-source DeepSeek Harness (DSH) vision plugin that adds image understanding, full-screen OCR, and persistent visual evidence to text-only DeepSeek models without replacing the parent model.

Unlike provider-pool or CLI interception tools, this plugin keeps DeepSeek Harness in charge of models, attachments, sessions, and UI. It adds:

  • see_image with latest, all, and explicit image selection
  • one conversation-scoped vision analyst with follow-up memory
  • structured summaries, question answers, exhaustive OCR, and uncertainties
  • a read-only Evidence tab and per-call evidence cards
  • a global Vision: … provider/model picker beside Choose Model
  • live route changes; changing the route starts a new analyst

Screenshots

Vision-enabled DeepSeek Harness composer

DeepSeek Harness composer using Grok Latest as the vision model and DeepSeek V4 Pro High as the parent model

The parent DeepSeek model stays in control while the separate Vision route handles image understanding and OCR.

Compact vision model selector

Compact DSH Vision model selector beside the DeepSeek parent model selector

The global selector makes the active image-capable model visible and lets users change the visual-analysis route without changing the conversation model.

Evidence card in a conversation

Vision analysis reply with an evidence card in a DeepSeek Harness conversation

Each see_image call renders an evidence card with the structured summary, question answers, and any uncertainties, so the analysis stays reviewable in the conversation.

GitHub project overview

The open-source DSH DeepSeek Vision repository on GitHub

Requirements

  • Node.js ^22.19.0 or >=24
  • DeepSeek Harness 0.1.0-rc.6
  • an image-capable model registered in the Harness catalog
  • the DSH spawn subagent provider

The Harness must provide delegated-image prompt admission, model input modalities, the see-image-model settings namespace, and the Web conversation slots. This plugin cannot retrofit those contracts into an older release.

Do not mount this package while equivalent in-tree see-image-model, tool-subagent-image, or vision-picker rows are enabled. Duplicate services and tools will conflict.

Install from GitHub

This project is not published to npm. Build a checkout and add that local package to the Web profile:

git clone https://github.com/Argonaut790/dsh-deepseek-vision.git
cd dsh-deepseek-vision
corepack yarn install --frozen-lockfile
corepack yarn build
dsh plugin --profile web add .

The included cordis.patch.yml mounts the global route service and see_image; its package metadata exposes the Web picker and Evidence UI.

Configure

Open a conversation and select an image-capable route from the Vision: … chip. Models are listed only when the Harness catalog explicitly declares image input.

For a headless profile, configure the same global route in $DSH_HOME/settings.yaml:

see-image-model:
  provider: openrouter
  model: '~x-ai/grok-latest'
  maxTokens: 8192

The provider and model names are examples. They must match routes registered in your Harness. The supported output-token range is 1–32768.

An optional static fallback may be set on the tool row:

- id: deepseek-vision-tool
  name: dsh-deepseek-vision/tool
  config:
    provider: spawn
    agentOptions:
      provider: openrouter
      model: '~x-ai/grok-latest'
      maxTokens: 8192

The global picker takes precedence when it contains a complete route.

How it works

  1. Harness retains pasted images as durable delegated-image attachments.
  2. The text-only parent calls see_image with questions and an image selection.
  3. The plugin reuses the newest matching vision analyst for that conversation, forwarding only images the analyst has not already received.
  4. The analyst receives no tools, uses a fixed anti-prompt-injection persona, and must return strict JSON.
  5. The parent receives concise model-facing text while the complete structured record is retained for evidence cards and the Evidence tab.
  6. If durable continuation is unavailable, the plugin performs an isolated one-shot structured readback.

Calls are serialized per conversation by the Harness tool runtime. A route change creates a new analyst rather than mutating the model behind an existing child.

Privacy, trust, and cost

  • Selected images are sent to the configured vision provider. Review that provider's retention, region, and privacy terms before use.
  • Each analyst turn consumes the selected model's tokens and may incur provider charges. Follow-ups can reuse visual context but are still model calls.
  • OCR and visual conclusions are model-generated evidence, not guaranteed facts. Verify high-impact decisions independently.
  • Text found inside images is treated as untrusted data, never as instructions. The analyst has no tools or external-action authority.
  • Evidence records keep attachment identifiers and derived text in the conversation history; they do not embed image bytes.

Image selection

see_image supports:

  • latest (default): images from the newest conversation event containing delegated images
  • all: the de-duplicated conversation image catalog
  • ids: exact attachment IDs already present in that catalog

A call accepts up to 12 questions, 2,000 characters per question, and 8,000 characters in total.

Development

Use Corepack-managed Yarn:

corepack yarn install --frozen-lockfile
corepack yarn typecheck
corepack yarn build
corepack yarn test

The build emits Host entries at lib/index.js and lib/tool.js, declarations under lib/types, and a browser __ModuleLoader__ bundle at lib/client.js. See CONTRIBUTING.md, SECURITY.md, and CHANGELOG.md.

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