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spark-ai-models

Use when adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.

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查看安装方法

包含的文件(2)

  • SKILL.md3.2 KB
  • reference.md4.4 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Spark AI model catalog

Owner: packages/spark-llm-providers. Catalog, gateway rewrites, and measured windows live in baidu-oneapi.ts. Do not guess vendor ids, context, or prices.

Workflow

  1. Identify the change: new model, metric correction, or both.
  2. Research current vendor docs (and gateway ids). Record source URLs and the exact numbers. If docs conflict with a live gateway, keep both in comments and register the gateway ceiling for contextWindow.
  3. Edit the existing provider owner. For Baidu, follow reference.md. Do not add a second catalog or public alias.
  4. If this is a successor model, replace the predecessor in default enable (see Baidu OneAPI). Update tests and packages/spark-llm-providers/README.md.
  5. Run the package and registry tests listed in the reference.

Research rules

  • Prefer the vendor's current model and pricing pages over training memory, blogs, or aggregator tables.
  • Model id uses a dot when the vendor does (grok-4.6, not grok-4-6).
  • contextWindow is the prompt+output ceiling Spark compact/preflight uses. On Baidu, measured provider input beats advertised vendor context.
  • maxTokens is Spark's output budget, not always the vendor max. If the vendor lists no output cap, keep the same-family budget unless measurement says otherwise.
  • Spark cost is USD per million tokens: { input, output, cacheRead, cacheWrite }. Use headline rates (Baidu/Spark do not model xAI ≥200k 2× long-context pricing). If the vendor has no cache-write fee, set cacheWrite to the input rate like existing Grok rows.
  • thinkingLevelMap only remaps Spark levels that differ from the transport. Confirm whether xhigh is real, aliased to high, or invalid.

Baidu OneAPI

  • Claude and DeepSeek → anthropic-messages. GPT-5.6 and Grok → openai-responses (BAIDU_ONEAPI_OPENAI_RESPONSES_MODEL_IDS).
  • Local id and gateway id can differ (claude-opus-5 → Opus 5). GPT/Grok are currently 1:1.
  • Adding a model also requires GATEWAY_MODEL_BY_ID plus the models[] row.
  • Catalog and default enable are separate. Keep the predecessor catalog row unless the user asks to delete it. Default enabledModels is the current frontier only: when a successor ships (grok-4.5 → grok-4.6), replace the old id in DEFAULT_SPARK_ENABLED_MODEL_PATTERNS with the new one. Do not leave both enabled, and do not use baidu-oneapi/*.
  • Add the previous bundled default (including baidu-oneapi/*) as a legacy set that migrates onto the new list. A user's custom scope, such as baidu-oneapi/* alone, must not be rewritten.
  • Prove default enable with membership tests: new id in enabledModelIds, old id out. Do not freeze the whole catalog as the scope contract.

Metric edits

Changing only windows or prices still needs tests and README notes. Do not advertise a round number (1M, 256k) when the gateway hard-fails earlier.

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