DeepSeek Harness plugin

dsh-tool-vision

DeepSeek Harness 外置视觉模型插件:inspect_image 把本地图片或 http(s) 图片 URL 发给任意 OpenAI 兼容端点,视觉模型看图的文字回答直接带回对话;附 Web UI 设置栏。

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Source facts

Repository
Scorp1o117/dsh-tool-vision
Latest update
Aug 21, 2026
Category
Models & Providers
GitHub stars
6
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/Scorp1o117/dsh-tool-vision
Plugin: dsh-tool-vision
Author: Scorp1o117

Check the source files

Read the README and other files from this plugin directory before installing.

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README.mdSource · read only

dsh-tool-vision

![中文文档](README.zh.md)

GitHub: Scorp1o117/dsh-tool-vision · npm: dsh-tool-vision

![Enhancement Suite](https://github.com/Scorp1o117/dsh-enhancement-suite) ![npm](https://www.npmjs.com/package/dsh-enhancement-suite)

Part of the DeepSeek Harness Enhancement Suite — Vision · Soul/Persona · Long-term Memory · Plugin Marketplace.

External vision model for DeepSeek Harness.

DSH 0.1.1 adds native image input for DeepSeek's vision catalog. This plugin remains useful when you want a separate OpenAI-compatible vision endpoint, pixel-level image tools, screenshots, or a text-model bridge. The harness derives every model request strictly from the session log (llm/stream requests must equal the durable derivation — the agent-loop invariant), so the bridge keeps its conversion inside that durable path:

1. inspect_image tool — sends an image (local file, or http(s) URL) to any OpenAI-compatible /chat/completions endpoint that supports image_url content parts, and returns the vision model's textual answer into the agent loop. 2. Image bridge (v0.2.1) — pasted images are turned into inspect_image hints before they enter the durable log, on the agent/pre-step waterfall (the one seam where the harness lets a plugin replace the messages of a proposed step). Images already logged by an older version are repaired lazily with a surface replace on the session's first pre-step. Only models listed in multimodalModels receive image blocks directly; a model's declared inputModalities are never consulted, because profiles routinely declare input: [text, image] on text-only models just to pass the harness's prompt-admission check.

  • Zero dependencies beyond the dsh SDK — works with any compatible endpoint:

OpenAI GPT-4o, Qwen-VL (DashScope), GLM-4V (Zhipu), Moonshot, Gemini compatible endpoints, local Ollama, etc.

  • Registered on the global tools layer: every agent in the process can

call inspect_image.

  • Web UI settings section (v0.3.0): Settings → 视觉模型 edits the

tool-vision namespace (API endpoint, write-only key, model, bridge options) in settings.yaml; changes hot-apply without a restart. The API key lives in settings.yaml, not the profile patch. Mount by package name (name: 'dsh-tool-vision') so the web client bundle is discovered.

Install

Mount in a profile patch ($DSH_HOME/profiles/<name>/cordis.patch.yml):

- insert:
    - id: tool-vision
      name: 'dsh-tool-vision'     # after: pnpm add dsh-tool-vision in the profile
      config:
        baseURL: 'https://api.openai.com/v1'
        apiKeyEnv: 'VISION_API_KEY'
        model: 'gpt-4o-mini'

Or load it from a local path without npm:

    - id: tool-vision
      name: './plugins/dsh-tool-vision/index.js'

Config

FieldDefaultMeaning
baseURLhttps://api.openai.com/v1OpenAI-compatible API base URL.
apiKey''API key (takes precedence over env).
apiKeyEnvVISION_API_KEYEnv var holding the key.
modelgpt-4o-miniVision model id.
maxTokens1024Max output tokens.
timeoutMs60000Per-request timeout.
maxImageBytes10MBLargest accepted local image.
descriptiondefaultTool description shown to the model.
bridgeTextOnlytrueBridge pasted images to text hints on models that cannot see images.
bridgeExportDirtempExport dir for bridged images (os.tmpdir()/dsh-vision-bridge).
multimodalModels[]Model ids that receive image blocks directly (e.g. mimo-v2.5).
bridgePreviewtrueInline preview for bridged images: thumbnail above the hint text in the user bubble (click to zoom).
bridgePreviewScanIntervalMs2000Fallback scan interval for the preview scanner (ms); 0 disables the fallback.
bridgePreviewHideHinttrueHide the bridged hint text once the preview image has loaded (kept on failure — safe degradation).
bridgeAutoImagetrueWhile the bridge is on, report image input capability for every model to the host admission gate, so pasted images are accepted on text-only models without hand-editing provider configs.

Image bridge setup

1. (Optional, usually not needed) If bridgeAutoImage is disabled, declare image input on the models you paste images onto, so the harness admits image messages (pi-ai style): ``yaml llm-pi-ai: providers: your-provider: models: - id: deepseek-v4-flash input: [text, image] ` 2. List genuinely multimodal models in the plugin config so they receive image blocks untouched: `yaml - id: tool-vision name: 'dsh-tool-vision' config: multimodalModels: ['mimo-v2.5', 'grok-4.5'] ``

Then pasting an image while on a text-only model stores a hint like [User sent an image, exported to: <path>. Inspect it with the inspect_image tool...] in the transcript (the pasted image no longer renders as pixels in that message), and the agent inspects it through the configured vision endpoint.

> Why not llm/stream? The harness freezes every request and the agent-loop > invariant fails any request whose messages diverge from the session-log > derivation (log-reconstruction desync), and this cordis waterfall's > next() cannot replace request arguments. The agent/pre-step waterfall is > the supported seam: its decision messages become the durable log, so the > invariant stays satisfied.

Key resolution order: config.apiKeyprocess.env[apiKeyEnv]process.env.OPENAI_API_KEY.

Bridge image preview (v0.4.0)

On text-only models, pasted images become [User sent an image...] hint text in the transcript. With bridgePreview enabled (default), the browser half renders those hints as inline thumbnails in the display layer only:

  • Thumbnail + lightbox: click to zoom full-screen; click anywhere or

press Esc to close;

  • Immediate + fallback: new messages are handled by a MutationObserver;

history is back-filled by a periodic scan (interval via bridgePreviewScanIntervalMs);

  • Hide the hint (P2): with bridgePreviewHideHint on, the hint text is

hidden once the image has loaded, leaving just the image; on load failure the text stays (safe degradation — never "no image AND no text");

  • Precise identification: bridged hints carry an invisible prefix marker

(\u200b[bridge]), so ordinary user text that happens to contain "exported to:" is never misidentified;

  • Display-layer red line: persisted messages, the transcript, the

model-facing text and the inspect_image chain are untouched.

Preview images are served by the same-origin loopback route /plugins/dsh-tool-vision/image: read-only access to the bridge export directory, localhost-only Host, image extensions only, ≤ 20MB per file, path-traversal protected.

Tool: inspect_image

ArgRequiredMeaning
pathImage path (absolute, or relative to the current workspace) or http(s) URL.
questionOptional specific question about the image.
detailauto / low / high resolution hint.

Example endpoints (baseURL):

  • OpenAI: https://api.openai.com/v1gpt-4o, gpt-4o-mini
  • Alibaba DashScope (Qwen-VL): https://dashscope.aliyuncs.com/compatible-mode/v1qwen-vl-plus, qwen-vl-max
  • Zhipu (GLM-4V): https://open.bigmodel.cn/api/paas/v4glm-4v-flash (free tier), glm-4v-plus
  • Moonshot (Kimi): https://api.moonshot.cn/v1moonshot-v1-8k-vision-preview
  • Ollama local: http://localhost:11434/v1llama3.2-vision (no key)

> Note for users > - This plugin is a standard profile bundle (dsh.bundle.patch): > dsh plugin --profile web add dsh-tool-vision installs and mounts it in > one step — no manual cordis.patch.yml edits needed. > - Settings changes hot-apply (no restart needed). > - Version 0.6.3 and newer require DSH 0.1.0-rc.7 or newer and are tested > against 0.1.0-rc.7, 0.1.0-rc.8, and 0.1.1-rc.1. > - DSH 0.1.0-rc.6 users must pin dsh-tool-vision@0.6.1, the last release > carrying the legacy settings-allowlist compatibility patch.

Pixel-level vision tools (v0.6.0, ported from dsh-vision-router)

14 vision_* tools driven by the same configured endpoint as inspect_image (baseURL/apiKey/model) — no provider chain, no local models, no extra settings:

ToolPurpose
vision_describeImage Q&A / multi-image comparison (optional structured JSON)
vision_groundLocate a target and return its ORIGINAL-pixel bounding box
vision_detectEnumerate elements (buttons, inputs, icons…) with numbered boxes
vision_cropCrop a pixel region to a PNG artifact
vision_pixel_diffPer-pixel comparison: ratio, worst regions, heatmap, report
vision_colorsDominant-color quantization for palette matching
vision_ocrVerbatim text transcription (letters only — not scene analysis)
vision_long_screenshot_ocrChunked long-screenshot transcription into Markdown
vision_tracePotrace vectorization into colored SVG (worker-thread, safe)
vision_extract_foregroundSolid-background removal → transparent PNG
vision_html_screenshotHeadless render of a local .html (network blocked)
vision_screenshotDesktop capture (privacy-gated: enable desktopScreenshot in settings; Win: PowerShell / macOS: screencapture / Linux: import/scrot)
vision_presentPublish a generated image to the user via the host attachment store
vision_materializeCopy an attachment/local image into the workspace as a real path

Quality & safety details:

  • Content-hash cache keyed by endpoint+model+image+question (no stale

answers across model switches, failures are never cached).

  • Uniform 4MP downscale before every model call; oversized inputs are

rejected with a clear error (stat pre-check, 20MB cap on both file and attachment paths).

  • Rate-limit / 5xx auto-retry with Retry-After-aware backoff; endpoint

content-safety rejections are surfaced as VISION_CONTENT_FILTERED instead of a generic backend error.

  • Long-OCR bounds: 120s total budget, 40-chunk cap, cancellation checks,

stop-on-first-backend-failure.

  • Path containment for relative inputs; artifacts land in

<workspace>/.dsh-tool-vision/.

Requires sharp / potrace / puppeteer-core (declared as optional dependencies: a failed platform install never blocks the plugin; missing ones degrade lazily with an install hint and never break other tools).

vision_screenshot is privacy-sensitive and therefore not registered by default — set desktopScreenshot: true in the tool-vision settings to enable desktop capture.

Limitations

  • A bridged image enters the conversation as a text hint (a transcript, not

pixels) — pixel-precise in-context reasoning is not available to text-only models; the vision model's description comes back through inspect_image.

  • Images are base64-transferred; mind privacy and size limits.
  • Independent of the dsh-llm routing/retry system; failures return clear

errors to the agent.

License

MIT — bridge preview & integration: xing666173. Pixel vision tools ported from dsh-vision-router (© ysr666, MIT) with gratitude.