chore: fetch Lovable AI Gateway model catalog in the daily sync

.github/workflows/sync-models.yml

@@ -44,7 +44,7 @@ jobs:
         run: |
           git config user.name "github-actions[bot]"
           git config user.email "github-actions[bot]@users.noreply.github.com"
-          git add packages/ scripts/openrouter.models.json scripts/openrouter.video-models.json scripts/vercel-gateway.models.json scripts/.sync-models-last-run .changeset/
+          git add packages/ scripts/openrouter.models.json scripts/openrouter.video-models.json scripts/vercel-gateway.models.json scripts/lovable-gateway.models.json scripts/.sync-models-last-run .changeset/
           git commit -m "chore: sync model metadata"
           # GITHUB_TOKEN pushes do not start the PR Test / E2E workflows.
           # After this job, a maintainer must run those checks from the
@@ -68,6 +68,7 @@ jobs:
 
           - Fetches the latest model list from OpenRouter (chat + `GET /api/v1/videos/models`)
           - Fetches the latest model list from Vercel AI Gateway
+          - Fetches the latest model list from Lovable AI Gateway
           - Converts to the internal adapter format
           - Syncs provider-specific model metadata for affected packages
           - Creates a patch changeset for all changed packages

CONTRIBUTING.md

@@ -51,7 +51,7 @@ For deeper architecture details (adapter system, isomorphic tools, framework int
 
 `pnpm generate:models` is the maintainer command behind the daily **Sync Model Metadata** workflow (branch `automated/sync-models`). It:
 
-1. Fetches OpenRouter and Vercel AI Gateway catalogs.
+1. Fetches OpenRouter, Vercel AI Gateway, and Lovable AI Gateway catalogs.
 2. Regenerates `packages/ai-openrouter/src/model-meta.ts` and the Vercel Gateway model list.
 3. Inserts **new** native-provider models into `packages/ai-openai`, `ai-anthropic`, `ai-gemini`, and `ai-grok`.
 4. Writes a patch changeset for the packages that changed.

package.json

@@ -44,7 +44,7 @@
     "generate-docs": "node scripts/generate-docs.ts && pnpm run copy:readme",
     "generate:fal-image-fields": "tsx scripts/generate-fal-image-field-map.ts",
     "generate:models": "pnpm generate:models:fetch && pnpm regenerate:models && tsx scripts/sync-provider-models.ts && pnpm format",
-    "generate:models:fetch": "tsx scripts/fetch-openrouter-models.ts && tsx scripts/fetch-vercel-gateway-models.ts",
+    "generate:models:fetch": "tsx scripts/fetch-openrouter-models.ts && tsx scripts/fetch-vercel-gateway-models.ts && tsx scripts/fetch-lovable-gateway-models.ts",
     "regenerate:models": "tsx scripts/convert-openrouter-models.ts && tsx scripts/convert-vercel-gateway-models.ts",
     "sync-docs-config": "node scripts/sync-docs-config.ts",
     "copy:readme": "node scripts/copy-readme.js",

scripts/fetch-lovable-gateway-models.ts

@@ -0,0 +1,80 @@
+/**
+ * Fetches models from the Lovable AI Gateway API and writes them to
+ * lovable-gateway.models.json.
+ *
+ * Usage:
+ *   pnpm tsx scripts/fetch-lovable-gateway-models.ts
+ *
+ * The endpoint is public — no API key required.
+ *
+ * The output is plain JSON so a malicious or compromised upstream response
+ * cannot smuggle executable code into the build (JSON.stringify cannot produce
+ * a JS expression). The committed wrapper at `lovable-gateway.models.ts`
+ * re-exports this JSON typed as `Array<LovableGatewayCatalogModel>`.
+ */
+
+import { writeFile } from 'node:fs/promises'
+import { dirname, resolve } from 'node:path'
+import { fileURLToPath } from 'node:url'
+
+const __dirname = dirname(fileURLToPath(import.meta.url))
+const OUTPUT_PATH = resolve(__dirname, 'lovable-gateway.models.json')
+const API_URL = 'https://ai.gateway.lovable.dev/v1/models'
+
+interface ApiModel {
+  id: string
+  [key: string]: unknown
+}
+
+function isValidModel(model: unknown): model is ApiModel {
+  return (
+    typeof model === 'object' &&
+    model !== null &&
+    typeof (model as { id?: unknown }).id === 'string' &&
+    (model as { id: string }).id.length > 0
+  )
+}
+
+async function main() {
+  console.log(`Fetching models from ${API_URL}...`)
+
+  const response = await fetch(API_URL, {
+    headers: { Accept: 'application/json' },
+    signal: AbortSignal.timeout(30_000),
+  })
+
+  if (!response.ok) {
+    throw new Error(
+      `Failed to fetch Lovable AI Gateway models: ${response.status} ${response.statusText}`,
+    )
+  }
+
+  const json = (await response.json()) as { data?: unknown }
+  if (!Array.isArray(json.data)) {
+    throw new Error(
+      'Lovable AI Gateway /v1/models response is missing a data array',
+    )
+  }
+
+  const allModels = json.data
+  const validModels = allModels.filter(isValidModel)
+  const skipped = allModels.length - validModels.length
+  if (skipped > 0) {
+    console.log(`Skipped ${skipped} models missing a string id`)
+  }
+
+  validModels.sort((a, b) => a.id.localeCompare(b.id))
+
+  await writeFile(
+    OUTPUT_PATH,
+    JSON.stringify(validModels, null, 2) + '\n',
+    'utf-8',
+  )
+  console.log(`Fetched ${validModels.length} models`)
+  console.log(`Written to ${OUTPUT_PATH}`)
+}
+
+main().catch((error) => {
+  console.error(error)
+  process.exit(1)
+})