DeepSeek Harness 识图插件：保持 DeepSeek 对话，15+ 供应商视觉模型把图片转译为文字，可在 设置→插件 配置
Pending human review — the facts below come from the source repository.
DeepSeek Harness 识图插件：保持 DeepSeek 对话，15+ 供应商视觉模型把图片转译为文字，可在 设置→插件 配置
Users who want this capability in DSH; check the source and docs before installing.
dsh plugin --profile web add github:kaixinbaba/dsh-vision-recognizer No supported platforms were declared.
vision-recognizer, shown as DeepSeek + 识图 in the model picker) that wraps the real DeepSeek adapter: it declares image input (so the attachment preflight and the read_image gate admit images) and, in the request stream, transcribes every attached image to text through the vision model you select, then delegates the text-only conversation to DeepSeek. DeepSeek still answers; recognition is an add-on. attached image ──▶ vision-recognizer route ──▶ vision-model transcription (OCR + layout + detail) │ │ ▼ ▼ DeepSeek answers ◀── text-only conversation (image replaced by [图片转译] text) ## Features - One-click install: dsh plugin --profile web add dsh-vision-recognizer — no build scripts, no sharp approval (no native dependencies at all). - Configure from Settings → Plugins → Vision: pick a provider, enter an API key, override model / endpoint / token cap / timeout / marker. Saved changes take effect immediately, no restart. - 15+ providers, domestic and international: OpenAI, Anthropic Claude, Google Gemini, OpenRouter, Azure OpenAI, Ollama (local), plus Alibaba DashScope, QwenCloud (Intl), Zhipu GLM, Baidu Qianfan, iFlytek Spark, Moonshot Kimi, Tencent Hunyuan, Volcengine Doubao, SiliconFlow. Any OpenAI-compatible endpoint works via the custom provider. - Two wire protocols: OpenAI-compatible (/chat/completions) and native Anthropic Messages — Claude works out of the box. - No hangs: local/anonymous endpoints get a hard 20s timeout cap, HTTP 429 fails fast, failed endpoints cool down for 60s; without a key and without local Ollama it fails fast with actionable guidance. - Fallback chain: after the primary model fails, each fallbackModels entry is tried in order (each may target a different vendor); only after all fail does the request fail, listing every attempt. - Content-hash cache: the same image is transcribed at most once per process (in-process, capped at 200). - Zero-config local path: autoLocalOllama (default on) probes http://localhost:11434 and prepends a running Ollama to the chain — images never leave your machine. ## Quick start sh dsh plugin --profile web add dsh-vision-recognizer > Slow npm registry? dsh plugin --profile web add dsh-vision-recognizer --registry=https://registry.npmmirror.com Install from a local checkout (development): sh dsh plugin --profile web add file:/path/to/dsh-vision-recognizer > Use the file: prefix (copies the package into node_modules). A bare add . or add link:… makes pnpm symlink the package, in which case the plugin's schemastery dependency resolves from the source checkout and is not found — a general pnpm symlink-install gotcha, not a bug in the plugin. Restart dsh web, then: 1. Pick DeepSeek + 识图 in the model selector; 2. Open Settings → Plugins → Vision, choose a provider, enter an API key, save; 3. Paste an image into any conversation → you should see the [图片转译] marker followed by a DeepSeek answer. With no key and no local Ollama, a turn fails fast in a few seconds with guidance — that is the intended anti-hang behavior. ## Supported providers | Provider | baseURL | Default model | Key env var | Protocol | |---|---|---|---|---| | OpenAI | https://api.openai.com/v1 | gpt-4o-mini | OPENAI_API_KEY | OpenAI | | Anthropic Claude | https://api.anthropic.com/v1 | claude-3-5-sonnet-latest | ANTHROPIC_API_KEY | Anthropic | | Google Gemini | https://generativelanguage.googleapis.com/v1beta/openai | gemini-2.0-flash | GEMINI_API_KEY | OpenAI | | OpenRouter | https://openrouter.ai/api/v1 | qwen/qwen-2.5-vl-72b-instruct | OPENROUTER_API_KEY | OpenAI | | Azure OpenAI | user-supplied (…/openai/deployments/<deployment>) | gpt-4o-mini | AZURE_OPENAI_API_KEY | OpenAI | | Ollama (local) | http://localhost:11434/v1 | auto-detected | none | OpenAI | | Alibaba DashScope | https://dashscope.aliyuncs.com/compatible-mode/v1 | qwen-vl-max | DASHSCOPE_API_KEY | OpenAI | | QwenCloud (Intl) | https://dashscope-intl.aliyuncs.com/compatible-mode/v1 | qwen-vl-plus | DASHSCOPE_API_KEY | OpenAI | | Zhipu GLM | https://open.bigmodel.cn/api/paas/v4 | glm-4v-flash | ZHIPU_API_KEY | OpenAI | | Baidu Qianfan | https://qianfan.baidubce.com/v2 | ernie-4.5-vl-8k | QIANFAN_API_KEY | OpenAI | | iFlytek Spark | https://spark-api-open.xf-yun.com/v1 | generalv3.5 | SPARK_API_KEY | OpenAI | | Moonshot Kimi | https://api.moonshot.cn/v1 | moonshot-v1-8k-vision-preview | MOONSHOT_API_KEY | OpenAI | | Tencent Hunyuan | https://api.hunyuan.cloud.tencent.com/v1 | hunyuan-vision | HUNYUAN_API_KEY | OpenAI | | Volcengine Doubao | https://ark.cn-beijing.volces.com/api/v3 | doubao-1.5-vision-pro-32k-250115 | ARK_API_KEY | OpenAI | | SiliconFlow | https://api.siliconflow.cn/v1 | Qwen/Qwen2.5-VL-72B-Instruct | SILICONFLOW_API_KEY | OpenAI | > Model ids drift over time; the defaults are starting points — override Model in the settings UI. Key resolution order: key entered in the UI → the provider env var → $VISION_API_KEY / $DASHSCOPE_API_KEY. ## Configuration storage Config saved from the UI is written to $DSH_HOME/vision-recognizer.json and merged over the bundle defaults at startup. cordis.patch.yml only carries factory defaults; a user cordis.patch.yml override still works as the composition-time fallback. > ⚠️ patch semantics: the bundle's - insert: appends this row to the entry list. Writing a second - insert: with the same id in your own cordis.patch.yml would register the adapter twice (undefined behavior). To override individual keys, write a single top-level - id: dsh-vision-recognizer entry; better yet, use the Settings UI. ## Implementation notes (for plugin authors) Only stable rc.6 public interfaces are used: - ctx.llm.registration(innerProvider).adapter — fetch the wrapped adapter; - ctx.llm.registerAdapter([providerId], proxyAdapter) — register the new route; - proxying resolveModel overrides inputModalities to ['text', 'image']; - proxying stream transcribes image blocks ({ type: 'image', attachment }, bytes read via ctx.get('attachments').readImage(ref)), then yield* forwards the inner adapter's stream; - the settings UI rides the settings.plugins.tab slot plus custom webServer routes, persisting config to its own JSON file (independent of the api-proxy settings allowlist). ## Privacy Transcription sends image bytes (base64, HTTPS) to the vision endpoint you configure — image data leaves your machine unless the endpoint is local (e.g. Ollama). Nothing beyond the harness's own attachment storage persists any image. For sensitive images, use your own endpoint or a local model, or don't install this plugin. ## License MITNot by stars — picked by hand, one at a time.
A visual settings dashboard for DeepSeek Harness: every registered settings namespace — including third-party plugin ones the official UI never covers — rendered as editable, schema-driven forms. Early, but the right direction: stop hand-editing YAML.
A DIY trajectory visualizer for DeepSeek Harness: watch the agent’s plan and execution unfold as a graph instead of scrolling raw logs. Early, but it fills a real gap — understanding at a glance what the agent is doing.
Dispatch DSH work from Claude Code / Codex: spin up in-host DSH agent sessions with per-tier presets, watch native subagent progress, and borrow a multimodal bridge that lends the text-only harness vision and image generation. An orchestration plugin that turns DSH into a backend for other coding agents.