MIT 授權的純文字模型視覺橋接外掛，用一道 `dsh plugin add` 指令裝進 DeepSeek Harness（dsh）——貼上圖片即得結構化 JSON 證據（OCR、版面、語義）。
DSH 整合
相容
作者聲明
安全稽核
未稽核
最後核實
2026-08-21
授權條款
MIT
01它能幫你完成什麼？
Read images pasted straight into DeepSeek Harness chats running text-only DeepSeek / GLM models
Grounded answers built on structured JSON evidence — full transcription, reading-order layout regions, entity and relation lists
Developers running text-only DeepSeek or GLM models in dsh who need screenshots, slides, documents and charts understood in-conversation
Analyze dense charts, tweet screenshots and multi-image batches without leaving the dsh conversation
Detail-level readings — axes, log scale, color coding, timestamps, engagement numbers, per-image content and style — delivered one by one
dsh users who paste analytics charts, social screenshots or batches of images and need every element quoted back, not summarized away
Keep native paste thumbnails while adding vision via a wrapped model entry
A `(modlens vision)` model-selector entry per text-only route (choice is remembered); pasted thumbnails stay visible and are converted to structured evidence at request time
dsh users who want a Codex-app-like paste experience — visible thumbnails — instead of temp-file paths in the composer
02如何將外掛接入 DeepSeek Harness？
先決條件
- DeepSeek Harness (dsh) available — the install runs through the official `npx -y @deepseek-ai/dsh` CLI
- At least one vision engine: a free Gemini API key, the free Antigravity CLI (no key), an Anthropic key, any OpenAI-compatible endpoint, or an existing Claude Code / Kimi / Codex / OpenCode / Pi login reused with consent
安裝步驟
- 01
Install the plugin with one command: `npx -y @deepseek-ai/dsh plugin --profile web add @liustack/modlens@3.22.1`
$ npx -y @deepseek-ai/dsh plugin --profile web add @liustack/modlens@3.22.1
- 02
Pick a `(modlens vision)` entry in the model selector (it remembers your choice, so once is enough), or just paste an image on a confirmed text-only model and let `modlens_read_image` take over
- 03
If no vision engine is configured yet, set up a free Gemini API key (about three minutes, no credit card) or install Antigravity CLI and sign in with `agy`
驗證整合成功
作者未說明
復原
- Uninstalling is deleting a folder — no harness config lines are changed, so your agents are back to stock
03DSH 整合程度與能力邊界
Installed inside DeepSeek Harness as exactly one dsh plugin via a single `dsh plugin add` command; adds `(modlens vision)` model-selector entries and reads pasted images through the `modlens_read_image` tool
Direct-paste vision for text-only models
an image pasted straight into the chat, or a dropped file path→structured JSON evidence — full transcription, reading-order layout regions, entity and relation lists — grounding the model's answer
images are sent over the network to an external vision engineon a text-only model a pasted image lands as a private temp file whose path enters the composerTen-engine failover chain
six built-in providers (Gemini, OpenAI-compatible, Anthropic, Antigravity CLI, Claude CLI, Kimi CLI) plus up to four reused local agent CLIs→the first good result wins; `meta.attempts` records every attempt so a fallback is never silent
reused CLI reads spend that CLI owner's quota and are labeled in `meta.warnings`reuse is only enabled after explicit per-harness consent recorded in configUniversal OpenAI-compatible socket
`openai.baseUrl` + `openai.apiKey` + `openai.model` config (e.g. qwen-vl, GLM, SiliconFlow, OpenRouter, self-hosted vLLM/Ollama)→any endpoint speaking the OpenAI chat-completions protocol with image input driven as a vision engine
writes provider keys and endpoints into the modlens config
04適合誰？何時不該用？
適合
- Developers running text-only DeepSeek or GLM models in dsh who need screenshots, slides, documents and charts understood in-conversation
- dsh users who paste analytics charts, social screenshots or batches of images and need every element quoted back, not summarized away
- dsh users who want a Codex-app-like paste experience — visible thumbnails — instead of temp-file paths in the composer
不適合
- ModLens ships no local vision model: every read is routed to an external engine (Gemini / OpenAI-compatible / Anthropic API, Antigravity CLI, or a reused agent CLI), so it needs network access and your use of upstream engines is governed by their own terms and quotas.
05相容性、維護與安全提醒
- ModLens ships no local vision model: every read is routed to an external engine (Gemini / OpenAI-compatible / Anthropic API, Antigravity CLI, or a reused agent CLI), so it needs network access and your use of upstream engines is governed by their own terms and quotas.
- Read speed depends on the engine: API providers take 5-10 seconds per read, while CLI-based engines (Antigravity, Claude CLI, Kimi CLI, reused Codex / OpenCode) take 20-45 seconds.
- Only a model whose metadata positively confirms it is text-only is taken over with a `(modlens vision)` entry; anything unconfirmed is left alone, and the DeepSeek / GLM families' own vision models keep their native paste.
MIT · actively maintained (latest release v3.22.1, 2026-08-20)
06常見問題
如何把 ModLens 安裝到 DeepSeek Harness？
執行一道指令：`npx -y @deepseek-ai/dsh plugin --profile web add @liustack/modlens@3.22.1`。外掛會自動探索所有承載純文字 DeepSeek/GLM 模型的 provider 路由，並為每條路由加上一個 `(modlens vision)` 包裝入口（預設安裝會得到 DeepSeek-V4-Flash 與 DeepSeek-V4-Pro 兩個變體）。在模型選擇器選一次即可（選擇會被記住），之後直接貼上圖片就行。
它是 dsh 原生外掛還是 MCP？
它以 dsh 外掛形式安裝，在 dsh 裡就只是一個外掛：沒有 hooks、沒有 wrapper、沒有本機代理常駐程式，任何 harness 設定檔一行都不改。解除安裝就是刪掉一個資料夾，agent 立即恢復原狀。
需要什麼視覺引擎或前置條件？
任選一個引擎即可：免費 Gemini API key（約三分鐘、免信用卡，推薦預設，單次讀圖 5-10 秒）、任何 OpenAI 相容端點（qwen-vl、GLM、自建閘道）、Anthropic key、免 key 的 Antigravity CLI，或經逐個 harness 明確同意後複用 Claude Code / Kimi / Codex / OpenCode / Pi 的現有登入。
我貼上的圖片會傳送到哪裡？
圖片會透過網路傳送到你設定的故障轉移鏈中的視覺引擎；每次嘗試都記錄在 `meta.attempts`，任何消耗到複用 CLI 配額的讀取都會在 `meta.warnings` 標註花了誰的配額。上游引擎各自的條款與配額由你自行負責。
哪些模型會被接管加上視覺？
只有中繼資料明確確認是純文字的模型才會被加上 `(modlens vision)` 入口；無法確認的模型維持原樣，DeepSeek/GLM 自家的視覺模型也保留原生貼上行為。
07相關的 DSH 工作流程
agent-vision-toolkit
作者 anionex
為純文本模型"看圖“設計更好的視覺工具箱和技能，支援多圖理解，圖片問答，前端UI還原、GUI 自動化等，並可選無縫接入多個主流agent，直接識別貼上圖片｜ A vision toolkit and skill designed for text-only llms — image Q&A, long-screenshot OCR, frontend UI restoration, and GUI automation, with optional seamless integration for Codex, Claude Code, Pi, Oh My Pi, and OpenCode
dsh-vision-router
作者 ysr666
為純文本 DeepSeek Harness 智慧體提供「視覺」能力，內建免金鑰視覺鏈路與畫素級視覺工具，一條命令安裝，無需 Python。
dsh-vision-toolkit
作者 anionex
[dsh]為純文本模型設計更強大的視覺工具箱：一行安裝使用、貼上圖片直接識別、多張圖片問答、截圖到前端UI 還原等｜DeepSeek Harness-native integration for agent-vision-toolkit: image Q&A, long-screenshot OCR, UI restoration, grounding, pixel diff, Artifacts, and Web UI.
dsh-image-gen
作者 shanliuling
直接在 DeepSeek Harness 對話中生成圖片，無需切換外部工具。
08資料與來源
**🥇 The most capable vision plugin for DeepSeek Harness (dsh):** install it instantly with one command: `npx -y @deepse…
on the skill harnesses it is exactly one skill folder, on dsh exactly one plugin. Uninstalling is deleting a folder, and…
The plugin auto-discovers every provider route carrying text-only DeepSeek or GLM models and adds a wrapped entry per ro…
此頁面根據專案公開文件、儲存庫中繼資料與 DSH Plugins 的結構化解析所產生；最後核實於 2026-08-21。發現錯誤？提交更正。
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