@pzqian123/dsh-tool-vision
DSH 插件：当主模型路由无法接受图像输入时，通过用户配置的具备视觉能力的模型读取图像
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add @pzqian123/dsh-tool-vision@0.1.3Tool Vision 以 @pzqian123/dsh-tool-vision 发布，当前版本为 0.1.3。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
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A DeepSeek Harness (DSH) plugin that gives a text-only model route (e.g. deepseek-v4-flash) an image-reading capability by routing the image to a user-configured, vision-capable LLM route.
When the main model needs to see an image, it calls the plugin's read_image_vision tool. The plugin reads the image file and sends the image + a task-specific prompt (written by the main model per task) to the configured vision model, then returns the textual description as the tool result. No image block is ever injected into the session, so the text-only main route keeps working.
lib/ committed — installs from GitHub, npm, or a tarball with no build scripts, no allowBuilds permission needed.llm-pi-ai.providers.<name>).image input, before any bytes leave the machine.main model (no vision) ──read_image_vision(file_path, prompt)──▶ dsh-tool-vision
│
│ read file → attachments.saveImage (validate/persist)
│ llm.stream({provider, model, messages:[image+prompt]})
▼
configured vision model (e.g. xiaomi/mimo-v2.5)
│
▼ text description
main model ◀──────────── tool result (path / provider / model / description) ──┘
The vision model sees only the image and the prompt — it has no access to the conversation, so the main model must put everything needed to answer into the prompt argument.
dsh CLI on PATH)image input. Built-in example: the xiaomi route with mimo-v2.5 (configured via the Web Models page or settings.yaml → llm-pi-ai.providers.xiaomi, with its apiKeyEnv credential set, e.g. XIAOMI_API_KEY).Choose one — the profile commands below use web as an example; pass --profile <name> for any other profile.
# From npm
dsh plugin --profile web add @pzqian123/dsh-tool-vision
# From GitHub (no build step, so no allowBuilds is required)
dsh plugin --profile web add github:pzqian123/dsh-tool-vision
# From a local tarball
npm pack
dsh plugin --profile web add .\pzqian123-dsh-tool-vision-<version>.tgz
Restart
dsh web(or the profile's process) after installing — the bundle list is read at startup.
Configuration lives in three layers, all in your own files — the package ships no defaults and refuses to call the tool until the vision route is configured.
settings.yamlRoutes are registered under llm-pi-ai.providers.<name> in ~/.dsh/settings.yaml (or via the Web Models page, see below).
Catalog route — if pi-ai ships a catalog for the provider (e.g. xiaomi, openai, anthropic), only the credential reference is needed; endpoint and models come from the built-in catalog:
llm-pi-ai:
providers:
xiaomi:
apiKeyEnv: XIAOMI_API_KEY
Custom OpenAI-compatible endpoint — hand-declare the route, its protocol, endpoint, and model list. The vision model's input must include image, or the tool's capability check refuses the call before any bytes leave the machine:
llm-pi-ai:
providers:
my-vision:
displayName: My Vision Gateway
apiKeyEnv: MY_VISION_API_KEY
api: openai-completions
baseURL: https://gateway.example.com/v1
models:
- id: vision-1
name: Vision Model 1
contextWindow: 131072
maxTokens: 8192
input: [text, image] # ← required for vision
~/.dsh/.credentials.yaml (or an environment variable)Keys are stored by the credentials service, never in settings.yaml. The apiKeyEnv reference from Layer 1 names the key:
MY_VISION_API_KEY: sk-your-key-here
…or export the same name as an environment variable instead of writing the file.
cordis.patch.ymlAdd the vision route to the tool-vision row in your profile's patch layer (~/.dsh/profiles/web/cordis.patch.yml):
- id: tool-vision
config:
provider: my-vision # route name from Layer 1
model: vision-1 # model id from Layer 1
# maxTokens: 1024 # optional: vision model max output tokens (default 1024)
# timeoutMs: 120000 # optional: total timeout per vision call in ms (default 120000)
Config changes take effect via HMR — no restart needed.
Settings → Models covers Layers 1 and 2 with a form instead of YAML:
apiKeyEnv reference (derived <ROUTE>_API_KEY) for you.input field; for a hand-declared custom vision model, add input: [text, image] to settings.yaml afterwards.dsh plugin add, write the tool-vision row, and store the API key through the credentials service. Mention the key in the same message; it goes into ~/.dsh/.credentials.yaml, not into chat history.dsh web (it runs inside that process); a restart is needed after install/uninstall.tool-vision row needs no restart; only install/uninstall does.read_image_vision whenever it needs to see an image.maxTokens.read_image_vision refuses and points you to read_image, so the image is never redundantly sent to the configured vision provider.settings.yaml — keys live in ~/.dsh/.credentials.yaml (or an environment variable); the credential name is referenced by apiKeyEnv in the provider profile.Just ask the main model to read an image:
Read D:\images\screenshot.png and tell me, character by character, what text is in it.
The model will call read_image_vision with a task-specific prompt. The harness's built-in read_image tool coexists in the tool catalog; the system prompt and the tools' own behavior keep the two straight.
deepseek-v4-flash): the built-in read_image refuses (the route cannot carry images); the model uses read_image_vision, which forwards the image to the configured vision model and returns a text description.read_image. In this case read_image_vision refuses — forwarding would be redundant and would ship the image to another provider — with an error pointing back to read_image.file_path | path to a PNG/JPEG/WebP/GIF image, resolved by the DSH filesystem backend |
prompt | required; your instruction to the vision model about the image (it sees only the image and this prompt) |
| output | { path, provider, model, prompt, description, truncated } |
The image bytes are sent to the configured vision provider (the same provider/credential you configure in DSH model settings). Nothing else from the session is sent. The description is stored in the session as plain text.
| Symptom | Cause / fix |
|---|---|
| "read_image_vision is not configured" | The tool-vision row config is missing provider/model — add it as shown above |
| "no adapter registered for provider" | Provider route not registered — configure llm-pi-ai.providers.<name> in settings.yaml / Web Models page |
| "does not declare image input" | The target model has no vision capability — switch to a model whose entry declares image input |
| "no credential for provider route" | The provider's apiKeyEnv credential is missing — set it on the Web Models page or in ~/.dsh/.credentials.yaml |
| "exceeds the X-byte attachment limit" | Image larger than the attachment cap (default 5MB) — compress first |
| "extension declares ... but the bytes use a different image format" | Extension does not match the real format — rename or convert |
| Vision model returns empty / times out | Check network and quota; raise timeoutMs; raise maxTokens or ask the main model to retry with a narrower prompt when truncated |
dsh-tool-vision/
├── package.json # declares dsh.bundle (bundle manifest)
├── cordis.patch.yml # the patch layer that inserts the tool-vision row
├── lib/index.js # the plugin implementation (plain ESM, no build step)
├── README.md
└── README.zh-CN.md
Iterate locally:
npm pack
dsh plugin --profile web remove @pzqian123/dsh-tool-vision
dsh plugin --profile web add .\pzqian123-dsh-tool-vision-<version>.tgz
Note: pnpm symlinks local-directory dependencies, which breaks runtime resolution — always install from the tarball (or GitHub/npm) rather than a local path.
| Field | Type | Default | Description |
|---|---|---|---|
provider | string | "" | Vision provider route name (required) |
model | string | "" | Vision model id, must declare image input (required) |
maxTokens | number | 1024 | Vision model max output tokens |
timeoutMs | number | 120000 | Total timeout per vision call, ms |
MIT