GLM Models for Raycast

A Raycast extension that exposes Z.ai / BigModel GLM models to Raycast's built-in AI features — AI Chat, Quick AI, and AI Commands — using Raycast's extension AI model provider API.

What it does

• Lists your account's GLM models (GLM-5.3, GLM-5.2, GLM-5.3-Flash, GLM-4.6, GLM-4.5 family, GLM-4.5V/4.6V vision models, …) in Raycast's model picker
• Streams completions straight from Z.ai's OpenAI-compatible API
• Supports reasoning (thinking + reasoning-effort picker), tool/function calling, image attachments on vision models, and system messages
• Works with both platforms: Z.ai international (api.z.ai) and BigModel China (open.bigmodel.cn) — switchable in preferences

Requirements

1. Raycast 1.26.0 or newer, signed in with your Raycast account

2. Raycast Pro — Raycast requires a Pro subscription to use models provided by extensions

3. Node.js 22.22.2+ and npm 7+ (check with node -v — matches @raycast/api's own requirement, also declared in engines)

4. An API key:

   • International: create one at z.ai → API Keys (works with the Z.ai (pay-as-you-go) platform setting)
   • China: create one at open.bigmodel.cn (works with the BigModel (pay-as-you-go) setting)

   Keys are not interchangeable between the two platforms. Pay-as-you-go API keys only — GLM Coding Plan and Team Plan keys are not supported.

Setup

cd glm-models
npm install
npm run dev

Running npm run dev registers the extension locally in Raycast (it appears at the top of root search).

First-run onboarding

The first time Raycast needs the extension's settings, it shows a setup form asking for every required preference together — API Key and Platform — with a help page (from help.md) beside the form. Pick the platform that matches where your key was created; the two platforms' keys are not interchangeable.

Preference	What to enter
API Key	Your Z.ai or BigModel key
Platform	Z.ai (pay-as-you-go) or BigModel (pay-as-you-go) — must match where the key came from. Pay-as-you-go keys only: GLM Coding Plan / Team Plan keys are not supported
Custom Base URL	Only if you picked Custom (any HTTPS OpenAI-compatible endpoint)
Extra Models	Optional comma-separated model IDs to force-include in the picker

After the setup form, validate everything with the Check Setup command: it calls the live API with your saved key and platform and tells you exactly what's wrong if they don't match (401 → key/platform mismatch), the endpoint is unreachable, or all good (N models discovered). It can also test a different key/platform combination before you commit it to preferences — a combination that differs from the saved one is reported as validated, but not applied, since extensions cannot change their own preferences — and its Open Platform Console action deep-links to the selected platform's API-keys page (z.ai or open.bigmodel.cn). Validating the saved combination also refreshes Raycast's model list.

Then opt in to extension models (one-time):

1. Open Raycast Settings → AI (or the model picker in AI Chat)
2. Enable models from extensions ("Allow AI Models" / toggle this extension on)
3. Open AI Chat or Quick AI, open the model picker, and pick a GLM model — glm-4.5-flash is free, a good first smoke test

While developing, keep npm run dev running for hot reload. Press ⌃C to stop; the extension stays in Raycast. Re-run npm run dev after code changes.

The Refresh Models command validates the saved key + platform and re-runs model discovery in one step, reporting the outcome (e.g. "Z.ai (pay-as-you-go): 18 models available") — the one-step way to pick up a platform change from the settings (Raycast also refreshes automatically in the background, but it doesn't notify extensions when preferences change).

How model discovery works

• The extension first calls GET {baseURL}/models with your key to get the models your account can actually use (handles platform differences and new releases automatically).
• Each ID is enriched with metadata (title, context window, vision/tools/reasoning capabilities) from the models.dev community catalog, cached for 24h — BigModel reuses the Z.ai catalog since both platforms serve the same model IDs.
• IDs models.dev doesn't know get conservative defaults, so brand-new GLM models still show up and work.
• If the /models call fails, the models.dev model list is used instead; if that is unreachable too (e.g. first run offline), a small curated fallback keeps the picker populated: GLM-5.3, GLM-5.2, GLM-5.3-Flash, GLM-4.7, GLM-4.6, GLM-4.5-Flash.

Notes:

• Reasoning effort maps to Z.ai's reasoning_effort on GLM-5.x models, and to thinking on/off on GLM-4.x models (none disables thinking).
• Reasoning tokens stream into Raycast's collapsible thinking section (reasoning-delta parts).
• Image attachments are only delivered for models declared with vision (GLM-*-V and Flash multimodal models).

Troubleshooting

• Run "Check Setup" first — it validates your saved key and platform against the live API and classifies the failure (key/platform mismatch, network, endpoint unavailable).
• Changed Platform but the model picker is stale — Raycast doesn't notify extensions when preferences change. Run Refresh Models to validate and refresh in one step. Note that Check Setup only validates: after testing a different platform or key, save it in the extension settings for it to take effect.
• AI_DownloadError: Cannot find module 'undici' when attaching an image — this happened in early versions of this extension: image attachments were converted to data: URLs, which the AI SDK tries to fetch, and that path requires the undici npm package which Raycast's runtime doesn't provide. Fixed by passing image bytes directly; if you see it again, run npm run dev so you're on the latest build.
• No GLM models in the picker — check the npm run dev console: it logs either glm-models: discovered N model ids via …/models (dynamic discovery worked) or glm-models: /models lookup failed … followed by which fallback list was used (models.dev or the curated catalog). Also confirm you toggled the extension on in Raycast Settings → AI.
• 401/403 errors — your API key doesn't match the selected Platform (z.ai vs BigModel keys are not interchangeable).

Publishing to the Raycast Store (optional, later)

This repo is currently a personal extension. If you want to publish it:

1. Have a GitHub account linked to Raycast (npm run publish authenticates with GitHub)
2. npm run build to validate for distribution
3. npm run publish — opens a pull request against the raycast/extensions repository
4. After Raycast team review and merge, the extension is published to the Store automatically

Development

src/models.ts           AI model provider entry point: getModels + streamCompletion
src/lib/catalog.ts      Curated model metadata, /models discovery, preferences
src/check-setup.tsx     Command: validate key + platform against the live API
src/refresh-models.ts   Command: manually refresh the model list

• npm run dev — run in development mode with hot reload
• npm run build — production build / store validation
• npx tsc --noEmit — type check

The provider uses @ai-sdk/openai-compatible + Vercel AI SDK streamText, pointed at Z.ai's OpenAI-compatible endpoint. Provider options under the zai namespace (thinking, reasoning_effort) are forwarded into the request body by the compatible provider.