Scorp1o117/dsh-tool-vision ↗★ 8

dsh-tool-vision

调用外置OpenAI兼容端点进行图片分析 适合需要让不支持视觉的模型通过外置接口实现看图回答的用户。

包名
dsh-tool-vision
兼容性
待验证
Harness 依赖范围
>=0.2.0-rc.2 <0.3.0
版本
0.10.0
许可证
NOASSERTION
最近更新
2026年9月30日

同名包的其他仓库

安装

$npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Scorp1o117/dsh-tool-vision

Configuration page (DSH 0.2.0-rc.2 and later)

Open Plugins → Installed → dsh-tool-vision from the homepage sidebar to configure and save this plugin. The page uses the official plugins.bundle.config interface, without a duplicate entry in global Settings. Web and Desktop share the page. This version requires DSH 0.2.0-rc.2 or a later 0.2.x host; existing configuration is retained.

中文文档

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

Enhancement Suite npm

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 the active Profile patch; changes hot-apply without a restart. The API key lives in that patch. Mount by package name (name: 'dsh-tool-vision') so the web client bundle is discovered.