/ai-model-web

name: ai-model-web
description: "Use this skill when a browser/Web app (React, Vue, Next, Nuxt, static sites, SPAs, dashboards, AI chat UI, 页面, 前端, 网页) needs AI models via @cloudbase/js-sdk. Default routing for Web/frontend AI — call directly from the browser, do NOT propose a Node.js proxy. Covers generateText and streamText; models via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*, model id in the `model` field. MUST run two-step preflight before code — see body. NOT for Node.js backend (use ai-model-nodejs), Mini Program (use ai-model-wechat), or image generation (Node SDK only)."
version: 2.34.3
alwaysApply: false

Sibling skills (local only)

Sibling CloudBase skills ship beside this skill. Use local relative paths such as `../auth-tool-cloudbase/SKILL.md`.

If a referenced sibling skill file is missing from this environment, ask the user to install the full CloudBase plugin (or the missing skill). Do **not** HTTP-fetch remote skill or protocol markdown into the agent context.

When to use this skill

Use this skill for **calling AI models in browser/Web applications** via `@cloudbase/js-sdk`.

> 🧭 **Runtime-plane default for Web.** Any time the user's request is framed around a page, a Web app, the frontend, React/Vue/Next/Nuxt, a dashboard UI, or "add AI to my H5", this skill is the default routing target. **Do NOT first propose a Node.js / cloud-function / CloudRun proxy**; `@cloudbase/js-sdk` can call the model from the browser directly. Only switch to `ai-model-nodejs` if the user explicitly asks for a backend/server call, image generation, or a scenario that truly needs server-side keys or long-running work. This decision is independent of which concrete model the user picks — model names (`deepseek-*`, `glm-*`, `hunyuan-*`, `kimi-*`, …) only affect the `model` field, not the routing plane.

**Use it when you need to:**

• Integrate AI text generation into a frontend Web app
• Stream AI responses for a better UX
• Call Hunyuan / DeepSeek / GLM / Kimi / MiniMax models from the browser

**Do NOT use for:**

• Node.js backend or cloud functions → use the `ai-model-nodejs` skill
• WeChat Mini Program → use the `ai-model-wechat` skill
• Image generation → use the `ai-model-nodejs` skill (Node SDK only)
• Runtimes without a CloudBase SDK (native apps, Python, Go, etc.) → use the `http-api-cloudbase` skill (it now includes the `ai_model` OpenAPI spec for direct HTTP calls; do NOT build a custom HTTP proxy)

---

⛔ STOP — `ai.createModel(...)` argument is **not** a vendor / model name

Read this before writing any `createModel(...)` line. The single most common mistake when agents generate code for this SDK is hallucinating the argument. There are **exactly three** legal shapes. Anything else is a bug.

| ✅ Legal `ai.createModel(...)` argument | When to use it | |----------------------------------------|----------------| | `"cloudbase"` | **The main managed group for new projects** (TokenHub-backed, multi-vendor pool). Vendor + concrete model go into the **`model` field** of `generateText` / `streamText`, e.g. `{ model: "deepseek-v4-flash" }`. **No model is enabled by default — always check `DescribeAIModels` first and, if the target model is missing, enable it with `UpdateAIModel` before calling the SDK.** | | `"hunyuan-exp"` | Only if `DescribeAIModels` explicitly returns this legacy builtin group for the current env (mainly the Mini Program Growth Plan — see `ai-model-wechat`). | | `"custom-<your-name>"` | A user-defined GroupName you onboarded via `CreateAIModel`. **Must** start with `custom-` (e.g. `custom-kimi`, `custom-openai-compat`). |

❌ Do NOT write any of these — they are all wrong

ai.createModel("deepseek")                 // wrong — that's a vendor, not a GroupName
ai.createModel("deepseek-v4-flash")        // wrong — that's a model name, goes in the `model` field
ai.createModel("hunyuan")                  // wrong — vendor family, not a GroupName
ai.createModel("hunyuan-2.0-instruct-20251111")  // wrong — model name
ai.createModel("glm") / ai.createModel("kimi") / ai.createModel("minimax")  // wrong — vendor names
ai.createModel("openai") / ai.createModel("moonshot")  // wrong — vendor names
ai.createModel("custom")                   // wrong — placeholder; use your real custom-<name>
ai.createModel(modelName)                  // wrong — do not reuse the variable that holds the model id

✅ Correct pattern — GroupName vs Model are two different fields

const model = ai.createModel("cloudbase");          // ← GroupName
await model.generateText({
  model: "deepseek-v4-flash",                       // ← concrete model id
  messages: [...]
});

Decision procedure (when the user names a specific model)

1. The user says "use DeepSeek v3.2" / "use hunyuan instruct" / "use Kimi k2.6" / "use GLM-5" / … 2. `createModel("cloudbase")` stays the same. 3. Put the model id into the **`model` field**: `{ model: "deepseek-v3.2" }`, `{ model: "hunyuan-2.0-instruct-20251111" }`, `{ model: "kimi-k2.6" }`, `{ model: "glm-5" }`, … 4. **Never assume the model is already enabled.** Before writing the SDK call, verify it is present in `DescribeAIModels({ GroupName: "cloudbase" }).Models[]`. If missing, call `DescribeManagedAIModelList` to confirm the exact `Model` name the platform supports (case-sensitive — do **not** guess the spelling), then enable it via `UpdateAIModel` with `Status: 1` (remember `Models` is a full replacement, so resend everything already enabled + the new one).

> If you are about to type `ai.createModel(` and the thing inside the parentheses is a vendor name, a model name, or a guess — **stop**. It is almost certainly one of the three legal values above.

---

Mandatory Two-Step Preflight (before any SDK code)

Before generating any AI-related SDK code, **run the two-step preflight**: ① eligibility, ② group readiness. Emitting `createModel(...)` straight away and letting the user debug runtime errors