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dsh-llm-autorouter

autorouter0-ai/dsh-llm-autorouter

DeepSeek Harness plugin: use AutoRouter as your LLM provider — unified routing, failover, and model discovery

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安装参考

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dsh plugin --profile web add github:autorouter0-ai/dsh-llm-autorouter

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PROJECT README

README

dsh-llm-autorouter

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DeepSeek Harness LLM adapter for AutoRouter — a model routing gateway that unifies access to multiple upstream channels. AutoRouter supports mainstream API formats (OpenAI-compatible, Anthropic, Gemini, and others) and handles routing, channel failover, billing, and observability inside the gateway.

This plugin mounts on the Harness so every model call goes through your AutoRouter deployment instead of hitting providers directly. It registers one provider route (autorouter by default) on ctx.llm; first fetch and import the models exposed by the gateway, then use those imported model ids in your agent config.

Tested with DeepSeek Harness 0.1.0-rc.5. Harness is still Developer Preview — later versions may break compatibility.

Requirements

  • An AutoRouter API key.
  • A working DeepSeek Harness environment.

Install

Choose the installation method that matches how you run DeepSeek Harness.

Direct install from npm (recommended)

If you use DeepSeek Harness directly from npm:

npx @deepseek-ai/dsh plugin --profile web add dsh-llm-autorouter

Direct install from git

If you want to install the plugin from a git repository:

npx @deepseek-ai/dsh plugin --profile web add github:autorouter0-ai/dsh-llm-autorouter

A git install fetches sources and runs the prepare build. If the first attempt fails, follow the allowBuilds instructions printed by the command.

Install from source

If you are developing this plugin locally, build the package first and then install it into a Web profile:

pnpm install
pnpm build
pnpm pack    # produces dsh-llm-autorouter-0.1.0.tgz

npx @deepseek-ai/dsh plugin --profile web add ./dsh-llm-autorouter-0.1.0.tgz

Configuration

The bundle has two entries with one installation: the Host entry supplies the LLM adapter, settings namespace, and model discovery; the browser entry supplies the AutoRouter card on the Web Plugins page.

Web UI (recommended)

After install, open the AutoRouter card under Plugins. Enter the gateway URL and API key. The key is stored only through the credentials service (AUTOROUTER_API_KEY by default) — never in settings.yaml or the browser.

Use Fetch models and Import selected to populate the models allowlist that chat selectors read from.

Headless / CLI profiles

Headless profiles load only the Host entry. Set AUTOROUTER_API_KEY in the launching environment, or store the key through the credentials service.

Config fields

Defaults apply when the bundle is installed with no extra config. Override any field in your profile's cordis.patch.yml or a --patch overlay:

Field Default Meaning
baseURL $AUTOROUTER_BASE_URLhttps://api.autorouter.top Gateway origin, without a trailing slash.
apiKeyEnv AUTOROUTER_API_KEY Credential reference resolved per request through the credentials service.
providers ['autorouter'] Provider routes this adapter owns.
thinking (neutral) 'enabled' / 'disabled'. Neutral: nothing is sent; upstream keeps its own default.
reasoningEffort (neutral) 'off' / 'low' / 'high' / 'max'. When set, materialized into requests that omit one.
defaultContextWindow 128000 Context capacity when the selected model has no exact value.
models [] Saved chat-model allowlist ({ id, name?, description?, contextWindow?, maxTokens?, inputModalities? }).
streamIdleTimeoutMs 300000 Max idle time while one stream read is outstanding.
discoveryTimeoutMs 10000 Network timeout for model listing.
retryPolicy normal defaults Provider-owned request retry policy.

Example cordis.patch.yml:

- insert:
    - id: llm-autorouter
      name: dsh-llm-autorouter
      config:
        baseURL: https://gateway.example.com
        apiKeyEnv: AUTOROUTER_API_KEY
        thinking: enabled
        reasoningEffort: high
        models:
          - id: deepseek-v4-flash
            contextWindow: 1000000

Environment overrides for local overlays:

  • AUTOROUTER_BASE_URL — gateway origin
  • AUTOROUTER_API_KEY_ENV — credential env var name

Usage

Point an agent at the autorouter provider:

- id: agent-loop
  name: '@deepseek-ai/dsh-agent-loop'
  config:
    agents:
      - id: main
        provider: autorouter
        model: deepseek-v4-flash   # any model id your gateway routes

Thinking mode

Neutral by default: with no thinking / reasoningEffort configured, neither field is sent on the wire and each upstream channel keeps its own default. AutoRouter relays the request body per channel (including DeepSeek-V4 thinking inferred from model-name suffixes).

  • Set reasoningEffort: high (etc.) to send thinking + reasoning effort on every request.
  • Set thinking: disabled to force thinking off on every request.
  • reasoning_content from DeepSeek-family channels is streamed back as reasoning blocks.

Model discovery

Chat selectors list only the saved models allowlist — they never probe the gateway on their own. The Web card's Fetch models action queries the gateway with your token and returns up to 1000 candidates grouped by capability. Import selected saves the chosen ids and their advertised modalities / token limits into the allowlist. Re-import after a gateway upgrade to pick up new fields. A failed discovery leaves the existing catalog unchanged.

Known limitations

  • Discovery failures fall back silently; misconfiguration usually surfaces on the first chat request.
  • Image input requires the Host attachment service (included in the Web profile) and a gateway route that accepts image payloads.

Development

pnpm install
pnpm typecheck
pnpm build

For a local Host overlay without installing the bundle:

pnpm build
pnpm dev:overlay          # writes dev-cordis.local.yml
pnpm dsh web --patch ./dev-cordis.local.yml

Peer packages (@deepseek-ai/*) must be linked from a deepseek-harness checkout:

DSH_HARNESS_DIR=/path/to/deepseek-harness pnpm dev:link-peers
pnpm build && pnpm smoke

License

MIT. Portions adapted from @deepseek-ai/dsh-llm-deepseek (MIT, deepseek-harness).

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