dsh-multi-model-provider

dsh-multi-model-provider

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This plugin has three capabilities:

1. Register models — language models stay in @deepseek-ai/dsh-llm-pi-ai; image, speech, audio, video, embedding, and reranking models live in this plugin's task-model catalog. The built-in realtimeModelRuntime owns effective Realtime route selection, credential references, adapter/profile registries, and bounded session assembly. Provider plugins register wire adapters; product plugins register role profiles.
2. Assist with portraits — evidence-backed profiles plus an explicit eight-token speed probe. Settings owns these writes.
3. Select the Agent model — selectAgentModel() / select_default_model picks the primary language model for newly created Agents from the live language catalog. It does not auto-route task models.

Peer plugins inject modelCatalog and call snapshot() to read every registered model, portrait, and last probe. Installing this package does not make image, speech, or realtime models callable; dsh-realtime-voice supplies the GPT and Doubao full-duplex adapters.

Capabilities

1. Registration

Language routes use configure_model_route / list_model_routes. Task routes use register_task_model / list_task_models. A task-model registration describes a route; a separate runtime adapter is still required to invoke it. select_task_models with ids: [] disables every route on that connection without fallback.

For a declared language route, contextWindow describes model capacity. Leave requestMaxTokens unset unless the deployment intentionally wants that exact output limit sent on every request. Discovery-only maxTokens metadata is validated but is not persisted as a request default; this prevents large advertised capacities from becoming invalid max_output_tokens values at compatible gateways.

2. Portraits

prepare_model_portraits returns seed facts, gaps, and official documentation URLs. The Agent opens those pages and calls ingest_portrait_research with http(s) source URLs; price rates must cite that evidence. lastProbe is recorded only by an explicitly approved Agent call to validate_model_portrait(liveProbe=true), never copied from documentation. get_model_portrait, upsert_model_portrait, and validate_model_portrait manage the stored profile.

The catalog ships a source-backed starter set without a fixed model-count cap. Its provider-priced routes cover GPT-5.6 Sol / Terra, Claude Opus 5 / Sonnet 5, Gemini 3.1 Pro Preview / 3.7 Flash, DeepSeek V4 Pro / Flash, Kimi K3 / K2.6, GLM-5.3 / 5-Turbo / 5V-Turbo, Grok 4.5 / 4.3, MiniMax M3 / M2.7, and Mistral Small 4 / Ministral 8B. It also carries provider-independent capability portraits for Qwen 3.8 Max Preview / 3.7 Plus, Qwen 3.5 4B / 9B / 27B, Qwen 3.6 35B-A3B, Qwen3-Coder-Next, and the open-weight MiniMax and Mistral checkpoints. Selection is current-generation first, then accounts for usage, specialization, private-deployment adoption, and hardware footprint. These are exact-id fallbacks, not registrations. A stored user portrait always wins. Route portraits may contain effective-dated provider prices; portable portraits deliberately leave pricing empty because API and infrastructure cost depend on the selected deployment. Neither kind fabricates benchmark scores, latency ranges, or lastProbe results.

Specialized task routes are a separate layer. The video starter set covers Google Gemini Omni Flash Preview and Veo 3.1 Standard / Fast / Lite; MiniMax H3 and Hailuo 2.3 / Fast; and OpenAI Sora 2 / Pro. It also includes MiniMax Speech 2.8 HD / Turbo, Music 3.0, and image-01. Every route keeps exact task, modality, execution, price, and source-backed capability boundaries. H3 is therefore a video-generation candidate with native audio output, not an Agent LLM. These routes remain registered-only until their declared runtime adapters and credentials are available. Google’s current video routes are enabled as candidates; Sora 2 / Pro are disabled because OpenAI now marks them Legacy. Music 3.0 is disabled because its paid API stopped accepting new users on August 20, 2026; its portrait remains visible for existing paying users and open-weight deployment decisions.

3. Agent model

Selection is built on the catalog, not a parallel list:

export const inject = ['modelCatalog']

const snapshot = await ctx.modelCatalog.snapshot()
await ctx.modelCatalog.selectAgentModel({
  provider: 'volcengine',
  model: 'doubao-seed-1-6',
})

snapshot().languageModels is the live Agent-model candidate list, with stored or exact-match bundled portraits attached when they exist. portraitSource reports stored or bundled. selectAgentModel() refuses task models and unknown ids. It only affects newly created Agents.

Other plugins that only need the directory can stop at snapshot(). Do not scrape settings.yaml, and do not ask the Agent to call tools just to read the catalog.

Agent tools

• list_model_routes, configure_model_route, and select_default_model manage primary language models through llm-pi-ai.
• inspect_volcengine_provider returns safe credential state, the authenticated Ark catalog, selections, task routes, and correct invocation paths.
• select_volcengine_language_models replaces the Ark language/VLM selection; an empty array explicitly disables the route.
• list_task_models inspects non-language registrations and reports registration separately from callability.
• discover_task_models queries a connection's authenticated provider catalog without registering anything.
• select_task_models replaces the enabled set; ids: [] explicitly disables every route on that connection.
• register_task_model creates or updates a task-model route and its reusable connection profile.
• prepare_model_portraits expands a short “build initial portraits” request into seed facts, gaps, and official documentation URLs.
• ingest_portrait_research merges Agent-researched facts that have http(s) source URLs.
• get_model_portrait, upsert_model_portrait, and validate_model_portrait manage evidence-backed model profiles.
• invoke_task_model invokes a callable non-Realtime request/response route through its runtime adapter. Realtime speech uses realtimeModelRuntime and a provider-owned session transport.
• summarize_model_usage aggregates native LLM and task-model observations from the current durable session.

Registration tools accept credential references such as OPENAI_API_KEY, never API-key values. Doubao Realtime uses the single DOUBAO_API_KEY reference. The user enters actual values only in secure Settings credential fields; the Agent can fill provider, URL, model catalog, and profile metadata.

Settings UI and data model

Installation adds Volcengine Ark and Doubao Speech as two independent providers in the built-in Models Settings section and retains inline portrait results on language-model rows. It also adds a flat, read-only Model portraits Settings page with two tabs: collect and view. Each collection creates a visible Session inside the configurable Temporary Workspace provided by dsh-temporary-session. The collection tab therefore requires that profile bundle; catalog and Agent-tool features remain available without it. It does not add a separate top-level Volcengine settings page.

Ark uses ARK_API_KEY and the official https://ark.cn-beijing.volces.com/api/v3 base URL. On upgrade, a legacy VOLCENGINE_API_KEY value is safely copied to the standard ARK_API_KEY reference when the latter is missing; the legacy reference is retained and the secret is never logged or written to ordinary settings. Doubao shows the fixed Realtime protocol model 1.2.6.1 and voice as separate fields. “Validate API key and load voices” first creates a minimal live Realtime session with the draft DOUBAO_API_KEY; the documented O/SC voice catalog is exposed only after session.created succeeds. Each provider is configured and saved from its own Models editor card; users never need to edit YAML.

The UI creates no parallel source of truth. Ark language models are written to llm-pi-ai.providers.volcengine; Doubao Speech task models and all portrait bindings are written to multi-model-provider; credential values only cross the write-only Credentials API and never enter ordinary settings.yaml. ChatVoice only selects registered Realtime routes and does not own provider credentials.

Ark, DeepSeek, and Doubao can be edited or removed independently from Models. Removing an active DeepSeek or Doubao user configuration clears its user-layer settings and page-managed credential, while leaving the built-in provider definition available for later reconfiguration. Environment-sourced credentials are never deleted by the page.

The conversation model dropdown is searchable by provider, model id, display name, and description, so a large registry does not turn into an unscannable list.

Example task-model registration:

multi-model-provider:
  connections:
    openai:
      provider: openai
      displayName: OpenAI
      credentialRef: OPENAI_API_KEY
      baseURL: https://api.openai.com/v1
      profile: {}
    doubao-speech:
      provider: doubao-speech
      displayName: Doubao Speech
      credentialRef: DOUBAO_API_KEY
      credentialRefs:
        apiKey: DOUBAO_API_KEY
        realtimeApiKey: DOUBAO_API_KEY
      profile:
        product: doubao-speech
  models:
    openai/gpt-image-2:
      connection: openai
      model: gpt-image-2
      displayName: GPT Image 2
      task: image-generation
      runtimeAdapter: openai-images
      input: [text, image]
      output: [image]
      execution: request-response
      capabilities: [image.generate]
      operations: [generate, edit]
      roles: [image-generator]
      profile: {}

The visible built-in catalog includes Google Gemini Omni Flash Preview and Veo 3.1 Standard / Fast / Lite; OpenAI Sora 2 / Pro, gpt-image-2, and gpt-realtime; MiniMax H3, Hailuo 2.3 / Fast, Speech 2.8 HD / Turbo, Music 3.0, and image-01; plus 25 documented Realtime S2S-O/SC 2.0 voice profiles. Doubao fixes session.model to 1.2.6.1; the Models page displays that protocol model independently from the selectable voice profile, and the runtime maps the selected voice automatically. The routes belong to independent provider connections and appear in list_task_models, not in the language-model picker. Generative-media routes remain registered-only until their adapters are installed; legacy Sora and Music API routes are disabled by default. Doubao routes start disabled until selected in Models settings; former ASR/TTS entries remain migration-only and are not shown by this Provider.

Supported tasks cover image understanding/generation, speech synthesis/transcription/translation/analysis, voice conversion/cloning/design, podcasts, realtime speech, audio/video generation, embedding, and reranking. Routes also declare Lore-compatible capability ids such as speech.transcribe.file, speech.synthesize.short, and speech.realtime_session; file is a distinct input modality. Input/output modalities, operations, and execution lifecycle remain separate so task semantics are not conflated with modality.

volcengine and doubao-speech are separate providers because their protocols, credentials, catalogs, and probes differ. Ark catalog discovery uses ARK_API_KEY; Realtime Duplex uses the new Speech console's single DOUBAO_API_KEY. Ark /models is not a speech-entitlement catalog, while Volcengine's ListSpeakers/ServiceStatus OpenAPI requires cloud-account AK/SK and cannot use the Speech API Key. The one-key provider therefore carries the documented Realtime catalog and verifies access with a minimal session probe.

Every task route has an explicit enabled state. Selection is replacement-based, and an empty selection remains empty: it never falls back to the full provider catalog. Disabled routes stay inspectable for portrait work but are not callable.

Portraits, invocation, and routing evidence

A portrait keeps one sectioned qualitative Markdown description, structured pricing, and an explicit performance.lastProbe observation separate from long-term measured usage. Portraits cover task route ids and LLM ids in llm:<provider>/<model> form. Price rates carry operation, billing unit, currency, effective dates, and an evidence id so stale claims can be detected. Registration remains authoritative for capabilities, input/output modalities, execution mode, and operations.

The starter set is intentionally selective but has no fixed size: cover widely adopted providers, then include current flagships, workhorses, specialized models, and commonly self-hosted models with distinct hardware footprints. Usage, open-weight adoption, and deployment form are selection signals; every model claim and price cites first-party documentation. Matching has two exact layers: provider/model route profiles may carry route pricing, while an explicitly enumerated exact model id may receive a provider-independent capability profile. There is no fuzzy alias guessing and no price transfer across providers. Runtime reachability, time to first token, and latency remain separate probe/usage observations.

The Model portraits page collects or refreshes the currently selected model. Each job creates a distinct visible background Agent Session whose cwd is the configured dsh-temporary-session Workspace root, then durably attaches that Session to the same UI group. The root defaults to $DSH_HOME/temporary-sessions and can be changed in Temporary Workspace Settings. The active Agent handle is disposed when the job finishes, while the Session remains recoverable so Settings can open the research record later. The collection Agent has no filesystem tools, keeping the shared scratch root isolated from both project work and model-portrait persistence. The plugin supplies immutable registration seeds and the full research/acceptance contract, and requires the Agent to gather current official documentation or benchmark evidence, save findings through ingest_portrait_research / upsert_model_portrait, and run validate_model_portrait(liveProbe=false). Settings displays job status and the resulting portrait, evidence, validation, and latest probe. Paid or traffic-producing live probes are not started by collection; they require a separate explicit user approval before the Agent may call validate_model_portrait(liveProbe=true).

Request/response providers implement TaskModelRuntimeAdapter; full-duplex speech providers implement RealtimeModelSessionAdapter against realtimeModelRuntime. invoke_task_model records privacy-safe task metrics. LLM observations reuse native durable Harness request/header, step/start, and assistant/message.usage events, so no wrapper or duplicate content log is added. summarize_model_usage aggregates counts, success, latency, tokens, and cost without copying prompts, responses, media, or credentials.

Runtime boundary

• This plugin owns registration, portraits, Settings schemas, safe credential references, request/response task invocation, realtimeModelRuntime, and privacy-safe invocation observations.
• llm-pi-ai owns language-model protocol adaptation and execution.
• Independent provider adapters execute image/audio/video routes and handle binary artifacts through TaskModelRuntimeAdapter; routes without one remain registered-only.
• A peer plugin should inject modelCatalog and call snapshot(). It must not scrape settings.yaml, and it should not ask the Agent to call these tools just to read the catalog.
• selectAgentModel() / select_default_model chooses the Agent language model from snapshot().languageModels. It does not auto-route task models and only affects newly created Agents.

Install

This is a community composition bundle for DeepSeek Harness 0.1.1-rc.2. It is not an official DeepSeek package. Host and Web runtime files are committed, so a Git install does not need prepare or allowBuilds.

dsh-temporary-session is optional and is used only by portrait collection. DSH does not automatically install, activate, or update peer plugins; install it as a direct profile dependency when that workflow is needed.

For a reproducible Git install, append the reviewed release commit SHA to the GitHub spec (#<release-commit-sha>). Do not pin an earlier commit merely because it reports the same prerelease version.

Follow main (moves when the branch moves):

dsh plugin --profile web add github:AlexKaiqi/dsh-multi-model-provider

Install from a local checkout while developing:

git clone https://github.com/AlexKaiqi/dsh-multi-model-provider.git
cd dsh-multi-model-provider
dsh plugin --profile web add "$PWD"

After the package is published to npm:

dsh plugin --profile web add 'dsh-multi-model-provider@0.1.0-rc.11'

Through dsh.pub, once listed:

npx dshpub add AlexKaiqi/dsh-multi-model-provider --profile web

Verify the bundle layer, then restart Web and open a new Agent task so tools and system-prompt guidance load:

dsh --profile web --dump-config   # look for "# == dsh-multi-model-provider"
dsh web --profile web

Remove it from the profile:

dsh plugin --profile web remove dsh-multi-model-provider

Updates are explicit:

dsh plugin --profile web update dsh-multi-model-provider dsh-temporary-session

Development

pnpm install --frozen-lockfile --ignore-scripts
pnpm check

Requires Node.js ^22.19.0 || >=24.0.0 and pnpm 11.7.0.