fix(frontend): align Vertex Gemini endpoint controls

frontend/src/features/providers/components/__tests__/endpoint-default-paths.spec.ts

@@ -0,0 +1,47 @@
+import { describe, expect, it } from 'vitest'
+
+import { getDefaultEndpointPath } from '../endpoint-default-paths'
+
+const apiFormats = [
+  { value: 'gemini:generate_content', default_path: '/v1beta/models/{model}:{action}' },
+  { value: 'gemini:embedding', default_path: '/v1beta/models/{model}:{action}' },
+  { value: 'openai:responses', default_path: '/v1/responses' },
+]
+
+describe('endpoint default paths', () => {
+  it('uses Gemini Developer API paths for custom Gemini endpoints', () => {
+    expect(getDefaultEndpointPath({
+      apiFormat: 'gemini:generate_content',
+      providerType: 'custom',
+      apiFormats,
+    })).toBe('/v1beta/models/{model}:{action}')
+
+    expect(getDefaultEndpointPath({
+      apiFormat: 'gemini:embedding',
+      providerType: 'custom',
+      apiFormats,
+    })).toBe('/v1beta/models/{model}:{action}')
+  })
+
+  it('uses Vertex AI project/location paths for Vertex provider Gemini endpoints', () => {
+    expect(getDefaultEndpointPath({
+      apiFormat: 'gemini:generate_content',
+      providerType: 'vertex_ai',
+      apiFormats,
+    })).toBe('/v1/projects/{project_id}/locations/{region}/publishers/google/models/{model}:{action}')
+
+    expect(getDefaultEndpointPath({
+      apiFormat: 'gemini:embedding',
+      providerType: 'vertex_ai',
+      apiFormats,
+    })).toBe('/v1/projects/{project_id}/locations/{region}/publishers/google/models/{model}:predict')
+  })
+
+  it('keeps Codex Responses root path without duplicating /v1', () => {
+    expect(getDefaultEndpointPath({
+      apiFormat: 'openai:responses',
+      providerType: 'codex',
+      apiFormats,
+    })).toBe('/responses')
+  })
+})

frontend/src/features/providers/components/__tests__/provider-key-concurrent_limit.spec.ts

@@ -350,6 +350,27 @@ describe('provider key concurrent_limit form behavior', () => {
     }))
   })
 
+  it('keeps Gemini embedding selectable for Vertex AI keys', async () => {
+    const root = mountDialog(KeyFormDialog, {
+      open: true,
+      endpoint: null,
+      editingKey: null,
+      providerId: 'provider-vertex',
+      providerType: 'vertex_ai',
+      availableApiFormats: ['gemini:generate_content', 'gemini:embedding', 'claude:messages'],
+    })
+    await settle()
+
+    expect(root.textContent).toContain('Gemini Embedding')
+
+    const serviceAccountOption = root.querySelector<HTMLButtonElement>('[data-select-item="service_account"]')
+    expect(serviceAccountOption).not.toBeNull()
+    serviceAccountOption?.click()
+    await settle()
+
+    expect(root.textContent).toContain('Gemini Embedding')
+  })
+
   it('hydrates and serializes a positive concurrent_limit number from the normal key form', async () => {
     const root = mountDialog(KeyFormDialog, {
       open: true,