agnes-ai-for-dsh
Agnes AI integration for DeepSeek Harness —
an LLM provider with multimodal support, image/video generation tools, and a
settings panel.
中文说明
What it provides
| Piece | Description |
|---|
| Provider | agnes-ai, registered with the llm-pi-ai adapter (OpenAI-compatible Chat Completions) |
| Chat models | agnes-2.5-flash, agnes-3.0-flash, agnes-2.5-pro, agnes-2.5-pro-beta — all accept image input |
| Tools | agnes_image_generation, agnes_video_generation, agnes_record_generation |
| Settings panel | An Agnes AI section in Settings listing the live configuration and the model catalogue |
Install
dsh plugin install agnes-ai-for-dsh
Or add it to a profile's package.json and reinstall:
{
"dependencies": {
"agnes-ai-for-dsh": "git+https://github.com/wangyemen/agnes-ai-for-dsh.git"
}
}
Then add the bundle to dsh.profile.bundles and restart DSH.
Configure
The provider is pre-declared by cordis.patch.yml, so the only required step is
the API key:
- Open Settings → Models.
- Find Agnes AI and enter your API key.
- The key is stored by DSH's credential system under
AGNES_AI_API_KEY.
The default endpoint is the China region:
https://api.agnes-ai.cn/v1
To use the Global endpoint, change baseURL to
https://apihub.agnes-ai.com/v1 either in cordis.patch.yml or directly in
Settings → Models.
Usage
Once enabled, the two media tools are available to the model:
agnes_image_generation — text-to-image, image-to-image and multi-image
editing. Parameters: model, prompt, size (1K–4K), optional ratio,
optional image (input URLs), optional return_base64.agnes_video_generation — asynchronous video generation with polling.
Parameters: model, prompt, optional seconds, mode, size,
aspect_ratio, and the mode-specific media fields.
Video generation is asynchronous: the tool creates a task and then polls
GET /agnesapi?video_id=…&model_name=… until it settles. agnes-video-2.5-flash
accepts only 720P; agnes-video-2.5 accepts 720P, 1080P, 1K and 2K.
Notes for maintainers
Tool schemas
The host's defineTool does not accept raw JSON Schema — it requires a
property-map DSL whose entries may carry their own required: true, and it
compiles that into object-rooted JSON Schema itself.
That DSL is not valid JSON Schema. If it ever reaches a provider unconverted, the
provider rejects the entire request (WorkBuddy returns HTTP 400, code 11129,
"工具定义不合规"), so every model reply in the session fails — not merely the one
tool. This is not hypothetical: it is exactly what happened when a bare
require() threw inside an ESM module and a silent identity fallback registered
the raw DSL.
The defence is in src/tools.ts:
compileParameters() compiles the DSL here, so the plugin does not depend on
the host helper for correctness.assertValidCompiledSchema() / assertAllToolSchemas() verify the compiled
form at load and throw on the invalid shape, so a mistake stops the plugin
instead of poisoning every request.- Registration re-checks the parameters
defineTool actually produced and
refuses to register if the raw DSL survived.
verify.mjs exercises all of this against the real defineTool.
Build
npm install
npm run build
lib/ is committed, because the package installs from git and the consuming
profile does not run build scripts. Rebuild before committing any src/
change, or the stale lib/ is what ships.
License
MIT
