feat(embeddings): onboarding step + graceful degradation when disabled (#2591)

AGENTS.md

@@ -526,6 +526,7 @@ Follow this order so behavior is **specified**, **proven in Rust**, **proven ove
 - **No dynamic imports** in production **`app/src`** code — use **static** `import` / `import type` at the top of the module. Do **not** use `import()` (async dynamic import), `React.lazy(() => import(...))`, or `await import('…')` to load app modules, Tauri APIs, or RPC clients. **Why:** predictable chunk graph, simpler static analysis, fewer surprises in Tauri + Vite, and easier code review. **If a module must not run at load time** (e.g. heavy optional path), use a static import and **guard the call site** with `try/catch` or an explicit runtime check instead of deferring module load via dynamic import. **Exceptions:** Vitest harness patterns (`vi.importActual`, dynamic imports **only** inside `*.test.ts` / `__tests__` / `test/setup.ts` when required by the runner); ambient `typeof import('…')` in `.d.ts`; config files (e.g. `tailwind.config.js` JSDoc).- **Type-only imports**: `import type` where appropriate.
 - **Dual socket / tool sync**: If you change realtime protocol, keep **frontend** (`socketService` / MCP transport) and **core** socket behavior aligned (see [`gitbooks/developing/architecture.md`](gitbooks/developing/architecture.md) dual-socket section).
 - **i18n for all UI text**: Every user-visible string in `app/src/**` (headings, labels, button text, placeholders, status chips, toasts, dialog copy, `aria-label`, etc.) must go through `useT()` from `app/src/lib/i18n/I18nContext`. Hard-coded literals in JSX or `label=`/`placeholder=`/`aria-label=` props are not allowed. Add the new key to [`app/src/lib/i18n/en.ts`](app/src/lib/i18n/en.ts) in the same PR — other locales fall back to English. **Exceptions:** developer-only debug logs, code identifiers, and non-display data (URLs, slugs, technical sentinel values).
+- **i18n chunk files — update ALL locales**: The source-of-truth translation files are the **chunk files** under `app/src/lib/i18n/chunks/` (`en-{1..5}.ts` plus `<locale>-{1..5}.ts` for each locale). When adding or changing keys in `en.ts`, you **must also** add them to the corresponding English chunk file (`en-N.ts`) **and** to the same chunk number for every non-English locale (use the English value as a placeholder — translators fill in later). CI enforces parity via `pnpm i18n:check`; missing keys in any locale chunk will fail the i18n coverage gate. Locales: `ar`, `bn`, `de`, `es`, `fr`, `hi`, `id`, `it`, `ko`, `pt`, `ru`, `zh-CN`.
 
 ---
 

CLAUDE.md

@@ -322,6 +322,7 @@ Specify → prove in Rust → prove over RPC → surface in the UI → test.
 - **No dynamic imports** in production `app/src` code — static `import` / `import type` only. No `import()`, `React.lazy(() => import(...))`, `await import(...)`. For heavy optional paths, use a static import and guard the call site with `try/catch` or a runtime check. *Exceptions*: Vitest harness patterns in `*.test.ts` / `__tests__` / `test/setup.ts`; ambient `typeof import('…')` in `.d.ts`; config files (e.g. `tailwind.config.js` JSDoc).
 - **Dual socket sync**: when changing the realtime protocol, keep `socketService` / MCP transport aligned with core socket behavior (see `gitbooks/developing/architecture.md` dual-socket section).
 - **i18n for all UI text**: every user-visible string in `app/src/**` (headings, labels, button text, placeholders, status chips, toasts, error messages, dialog copy) must go through `useT()` from `app/src/lib/i18n/I18nContext`. Hard-coded literals in JSX or `label=`/`placeholder=`/`aria-label=` props are not allowed. Add the key to [`app/src/lib/i18n/en.ts`](app/src/lib/i18n/en.ts) in the same PR — other locales fall back to English. Exceptions: developer-only debug logs, code identifiers, and non-display data (URLs, slugs, technical sentinel values).
+- **i18n chunk files — update ALL locales**: the source-of-truth translation files are the **chunk files** under `app/src/lib/i18n/chunks/` (`en-{1..5}.ts` plus `<locale>-{1..5}.ts` for each locale). When adding or changing keys in `en.ts`, you **must also** add them to the corresponding English chunk file (`en-N.ts`) **and** to the same chunk number for every non-English locale (use the English value as a placeholder — translators fill in later). CI enforces parity via `pnpm i18n:check`; missing keys in any locale chunk will fail the i18n coverage gate. Locales: `ar`, `bn`, `de`, `es`, `fr`, `hi`, `id`, `it`, `ko`, `pt`, `ru`, `zh-CN`.
 
 ---
 

app/src/components/settings/panels/EmbeddingsPanel.tsx

@@ -28,7 +28,11 @@ type Status =
   | { kind: 'saved' }
   | { kind: 'error'; message: string };
 
-const EmbeddingsPanel = () => {
+interface EmbeddingsPanelProps {
+  embedded?: boolean;
+}
+
+const EmbeddingsPanel = ({ embedded = false }: EmbeddingsPanelProps = {}) => {
   const { t } = useT();
   const { navigateBack, breadcrumbs } = useSettingsNavigation();
 
@@ -74,13 +78,15 @@ const EmbeddingsPanel = () => {
   if (!settings) {
     return (
       <div className="z-10 relative">
-        <SettingsHeader
-          title={t('settings.embeddings.title')}
-          showBackButton
-          onBack={navigateBack}
-          breadcrumbs={breadcrumbs}
-        />
-        <div className="p-4">
+        {!embedded && (
+          <SettingsHeader
+            title={t('settings.embeddings.title')}
+            showBackButton
+            onBack={navigateBack}
+            breadcrumbs={breadcrumbs}
+          />
+        )}
+        <div className={embedded ? '' : 'p-4'}>
           <div className="rounded-lg border border-stone-200 dark:border-neutral-800 bg-white dark:bg-neutral-900 p-4 text-xs text-stone-500 dark:text-neutral-400">
             {status.kind === 'loading'
               ? t('common.loading')
@@ -318,14 +324,16 @@ const EmbeddingsPanel = () => {
 
   return (
     <div className="z-10 relative">
-      <SettingsHeader
-        title={t('settings.embeddings.title')}
-        showBackButton
-        onBack={navigateBack}
-        breadcrumbs={breadcrumbs}
-      />
+      {!embedded && (
+        <SettingsHeader
+          title={t('settings.embeddings.title')}
+          showBackButton
+          onBack={navigateBack}
+          breadcrumbs={breadcrumbs}
+        />
+      )}
 
-      <div className="p-4 space-y-4">
+      <div className={embedded ? 'space-y-4' : 'p-4 space-y-4'}>
         <p className="text-xs text-stone-500 dark:text-neutral-400 leading-relaxed">
           {t('settings.embeddings.description')}
         </p>
@@ -393,6 +401,15 @@ const EmbeddingsPanel = () => {
           })}
         </div>
 
+        {/* Vector search disabled notice */}
+        {selectedProvider === 'none' && (
+          <div className="rounded-xl border border-amber-200 dark:border-amber-500/30 bg-amber-50 dark:bg-amber-900/10 p-3">
+            <p className="text-xs text-amber-800 dark:text-amber-200 leading-relaxed">
+              {t('settings.embeddings.vectorSearchDisabled')}
+            </p>
+          </div>
+        )}
+
         {/* Model & dimensions (for active provider with catalog models) */}
         {currentModels.length > 0 &&
           selectedProvider !== 'custom' &&

app/src/lib/i18n/chunks/ar-1.ts

@@ -241,6 +241,7 @@ const ar1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'الصوت',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'البحث',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'الذاكرة',
   'onboarding.custom.stepCounter': 'الخطوة {n} من {total}',
   'onboarding.custom.defaultTitle': 'افتراضي',
@@ -277,6 +278,13 @@ const ar1: TranslationMap = {
   'onboarding.custom.search.defaultDesc': 'يستخدم OpenHuman خادم بحث مُدار. لا حاجة لمفاتيح.',
   'onboarding.custom.search.configureDesc':
     'استخدم مفتاح مزود البحث الخاص بك (Tavily أو Brave إلخ). اضبطه من الإعدادات › الأدوات.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'الذاكرة',
   'onboarding.custom.memory.subtitle': 'كيف يتذكر OpenHuman سياقك وتفضيلاتك ومحادثاتك السابقة.',
   'onboarding.custom.memory.defaultDesc':
@@ -515,6 +523,8 @@ const ar1: TranslationMap = {
   'settings.embeddings.setupTitle': 'إعداد {provider}',
   'settings.embeddings.saveAndSwitch': 'حفظ والتبديل',
   'settings.embeddings.optional': 'اختياري',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'مسح مفتاح API',
   'mcp.alphaBadge': 'Alpha',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/bn-1.ts

@@ -244,6 +244,7 @@ const bn1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'ভয়েস',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'সার্চ',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'মেমোরি',
   'onboarding.custom.stepCounter': 'ধাপ {n} / {total}',
   'onboarding.custom.defaultTitle': 'ডিফল্ট',
@@ -283,6 +284,13 @@ const bn1: TranslationMap = {
     'OpenHuman ম্যানেজড সার্চ ব্যাকএন্ড ব্যবহার করে। কোনো কী লাগে না।',
   'onboarding.custom.search.configureDesc':
     'নিজের সার্চ প্রোভাইডার কী আনুন (Tavily, Brave ইত্যাদি)। Settings › Tools-এ কনফিগার করুন।',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'মেমোরি',
   'onboarding.custom.memory.subtitle':
     'OpenHuman কীভাবে আপনার কন্টেক্সট, পছন্দ ও পূর্ববর্তী কথোপকথন মনে রাখে।',
@@ -524,6 +532,8 @@ const bn1: TranslationMap = {
   'settings.embeddings.setupTitle': '{provider} সেটআপ',
   'settings.embeddings.saveAndSwitch': 'সংরক্ষণ এবং স্যুইচ',
   'settings.embeddings.optional': 'ঐচ্ছিক',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'API কী মুছুন',
   'mcp.alphaBadge': 'আলফা',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/de-1.ts

@@ -289,6 +289,7 @@ const de1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Stimme',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Suchen',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Erinnerung',
   'onboarding.custom.stepCounter': 'Schritt {n} von {total}',
   'onboarding.custom.defaultTitle': 'Standard',
@@ -328,6 +329,13 @@ const de1: TranslationMap = {
     'OpenHuman verwendet ein verwaltetes Such-Backend. Keine Schlüssel erforderlich.',
   'onboarding.custom.search.configureDesc':
     'Bring deinen eigenen Suchanbieterschlüssel mit (Tavily, Brave usw.). Konfiguriere unter Einstellungen › Extras.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Erinnerung',
   'onboarding.custom.memory.subtitle':
     'Wie OpenHuman sich deinen Kontext, deine Vorlieben und frühere Gespräche merkt.',
@@ -535,6 +543,8 @@ const de1: TranslationMap = {
   'settings.embeddings.setupTitle': '{provider} einrichten',
   'settings.embeddings.saveAndSwitch': 'Speichern & wechseln',
   'settings.embeddings.optional': 'optional',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'API-Schlüssel löschen',
   'mcp.alphaBadge': 'Alpha',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/en-1.ts

@@ -533,6 +533,7 @@ const en1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Voice',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Search',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Memory',
   'onboarding.custom.stepCounter': 'Step {n} of {total}',
   'onboarding.custom.defaultTitle': 'Default',
@@ -572,6 +573,13 @@ const en1: TranslationMap = {
     'OpenHuman uses a managed search proxy by default. No search API key needed.',
   'onboarding.custom.search.configureDesc':
     'Bring your own search provider key (Tavily, Brave, etc.). Configure in Settings › Tools.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Memory',
   'onboarding.custom.memory.subtitle':
     'How OpenHuman remembers your context, preferences, and prior conversations.',
@@ -1053,6 +1061,8 @@ const en1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Set up {provider}',
   'settings.embeddings.saveAndSwitch': 'Save & switch',
   'settings.embeddings.optional': 'optional',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Clear API key',
   'mcp.alphaBadge': 'Alpha',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/es-1.ts

@@ -251,6 +251,7 @@ const es1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Voz',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Búsqueda',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Memoria',
   'onboarding.custom.stepCounter': 'Paso {n} de {total}',
   'onboarding.custom.defaultTitle': 'Por defecto',
@@ -290,6 +291,13 @@ const es1: TranslationMap = {
     'OpenHuman usa un backend de búsqueda gestionado. Sin claves necesarias.',
   'onboarding.custom.search.configureDesc':
     'Usa tu propia clave de proveedor de búsqueda (Tavily, Brave, etc.). Configura en Configuración › Herramientas.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Memoria',
   'onboarding.custom.memory.subtitle':
     'Cómo OpenHuman recuerda tu contexto, preferencias y conversaciones anteriores.',
@@ -536,6 +544,8 @@ const es1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Configurar {provider}',
   'settings.embeddings.saveAndSwitch': 'Guardar y cambiar',
   'settings.embeddings.optional': 'opcional',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Borrar clave API',
   'mcp.alphaBadge': 'Alfa',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/fr-1.ts

@@ -251,6 +251,7 @@ const fr1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Voix',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Recherche',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Mémoire',
   'onboarding.custom.stepCounter': 'Étape {n} sur {total}',
   'onboarding.custom.defaultTitle': 'Par défaut',
@@ -291,6 +292,13 @@ const fr1: TranslationMap = {
     'OpenHuman utilise un backend de recherche géré. Aucune clé nécessaire.',
   'onboarding.custom.search.configureDesc':
     'Utilise ta propre clé de fournisseur de recherche (Tavily, Brave, etc.). À configurer dans Paramètres › Outils.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Mémoire',
   'onboarding.custom.memory.subtitle':
     'Comment OpenHuman mémorise ton contexte, tes préférences et tes conversations passées.',
@@ -539,6 +547,8 @@ const fr1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Configurer {provider}',
   'settings.embeddings.saveAndSwitch': 'Enregistrer et changer',
   'settings.embeddings.optional': 'optionnel',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Effacer la clé API',
   'mcp.alphaBadge': 'Alpha',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/hi-1.ts

@@ -242,6 +242,7 @@ const hi1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'वॉइस',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'सर्च',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'मेमोरी',
   'onboarding.custom.stepCounter': 'स्टेप {n} / {total}',
   'onboarding.custom.defaultTitle': 'डिफ़ॉल्ट',
@@ -280,6 +281,13 @@ const hi1: TranslationMap = {
     'OpenHuman मैनेज्ड सर्च बैकएंड इस्तेमाल करता है। कोई key नहीं चाहिए।',
   'onboarding.custom.search.configureDesc':
     'अपनी सर्च प्रोवाइडर key लाएं (Tavily, Brave, आदि)। Settings › Tools में कॉन्फिगर करें।',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'मेमोरी',
   'onboarding.custom.memory.subtitle':
     'OpenHuman आपका कॉन्टेक्स्ट, पसंद और पुरानी बातें कैसे याद रखता है।',
@@ -522,6 +530,8 @@ const hi1: TranslationMap = {
   'settings.embeddings.setupTitle': '{provider} सेटअप',
   'settings.embeddings.saveAndSwitch': 'सहेजें और बदलें',
   'settings.embeddings.optional': 'वैकल्पिक',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'API कुंजी साफ़ करें',
   'mcp.alphaBadge': 'अल्फ़ा',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/id-1.ts

@@ -245,6 +245,7 @@ const id1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Suara',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Pencarian',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Memori',
   'onboarding.custom.stepCounter': 'Langkah {n} dari {total}',
   'onboarding.custom.defaultTitle': 'Bawaan',
@@ -284,6 +285,13 @@ const id1: TranslationMap = {
     'OpenHuman menggunakan backend pencarian terkelola. Tidak perlu key.',
   'onboarding.custom.search.configureDesc':
     'Bawa key penyedia pencarian Anda sendiri (Tavily, Brave, dll.). Konfigurasi di Pengaturan › Alat.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Memori',
   'onboarding.custom.memory.subtitle':
     'Cara OpenHuman mengingat konteks, preferensi, dan percakapan sebelumnya.',
@@ -527,6 +535,8 @@ const id1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Siapkan {provider}',
   'settings.embeddings.saveAndSwitch': 'Simpan & ganti',
   'settings.embeddings.optional': 'opsional',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Hapus kunci API',
   'mcp.alphaBadge': 'Alfa',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/it-1.ts

@@ -248,6 +248,7 @@ const it1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Voce',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Ricerca',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Memoria',
   'onboarding.custom.stepCounter': 'Passo {n} di {total}',
   'onboarding.custom.defaultTitle': 'Predefinito',
@@ -287,6 +288,13 @@ const it1: TranslationMap = {
     'OpenHuman usa un backend di ricerca gestito. Nessuna chiave necessaria.',
   'onboarding.custom.search.configureDesc':
     'Porta la tua chiave di provider di ricerca (Tavily, Brave, ecc.). Configura in Impostazioni › Strumenti.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Memoria',
   'onboarding.custom.memory.subtitle':
     'Come OpenHuman ricorda il tuo contesto, le preferenze e le conversazioni precedenti.',
@@ -532,6 +540,8 @@ const it1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Configura {provider}',
   'settings.embeddings.saveAndSwitch': 'Salva e cambia',
   'settings.embeddings.optional': 'opzionale',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Cancella chiave API',
   'mcp.alphaBadge': 'Alfa',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/ko-1.ts

@@ -243,6 +243,7 @@ const ko1: TranslationMap = {
   'onboarding.custom.stepperVoice': '음성',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': '검색',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': '메모리',
   'onboarding.custom.stepCounter': '{total}단계 중 {n}단계',
   'onboarding.custom.defaultTitle': '기본값',
@@ -283,6 +284,13 @@ const ko1: TranslationMap = {
     'OpenHuman은 관리형 검색 백엔드를 사용합니다. 키가 필요 없습니다.',
   'onboarding.custom.search.configureDesc':
     '직접 검색 제공업체 키(Tavily, Brave 등)를 가져오세요. 설정 › 도구에서 구성할 수 있습니다.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': '메모리',
   'onboarding.custom.memory.subtitle':
     'OpenHuman이 사용자의 컨텍스트, 선호도, 이전 대화를 기억하는 방식입니다.',
@@ -524,6 +532,8 @@ const ko1: TranslationMap = {
   'settings.embeddings.setupTitle': '{provider} 설정',
   'settings.embeddings.saveAndSwitch': '저장 및 전환',
   'settings.embeddings.optional': '선택사항',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'API 키 삭제',
   'mcp.alphaBadge': '알파',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/pt-1.ts

@@ -251,6 +251,7 @@ const pt1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Voz',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Pesquisa',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Memória',
   'onboarding.custom.stepCounter': 'Etapa {n} de {total}',
   'onboarding.custom.defaultTitle': 'Padrão',
@@ -290,6 +291,13 @@ const pt1: TranslationMap = {
     'O OpenHuman usa um backend de pesquisa gerenciado. Sem chaves necessárias.',
   'onboarding.custom.search.configureDesc':
     'Traga sua própria chave de provedor de pesquisa (Tavily, Brave, etc.). Configure em Configurações › Ferramentas.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Memória',
   'onboarding.custom.memory.subtitle':
     'Como o OpenHuman se lembra do seu contexto, preferências e conversas anteriores.',
@@ -537,6 +545,8 @@ const pt1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Configurar {provider}',
   'settings.embeddings.saveAndSwitch': 'Salvar e trocar',
   'settings.embeddings.optional': 'opcional',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Limpar chave API',
   'mcp.alphaBadge': 'Alfa',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/ru-1.ts

@@ -245,6 +245,7 @@ const ru1: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Голос',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Поиск',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Память',
   'onboarding.custom.stepCounter': 'Шаг {n} из {total}',
   'onboarding.custom.defaultTitle': 'По умолчанию',
@@ -283,6 +284,13 @@ const ru1: TranslationMap = {
     'OpenHuman использует управляемый поисковый бэкенд. Ключи не нужны.',
   'onboarding.custom.search.configureDesc':
     'Используй свой ключ поискового провайдера (Tavily, Brave и др.). Настрой в Настройки › Инструменты.',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': 'Память',
   'onboarding.custom.memory.subtitle':
     'Как OpenHuman запоминает контекст, предпочтения и предыдущие разговоры.',
@@ -527,6 +535,8 @@ const ru1: TranslationMap = {
   'settings.embeddings.setupTitle': 'Настройка {provider}',
   'settings.embeddings.saveAndSwitch': 'Сохранить и переключить',
   'settings.embeddings.optional': 'необязательно',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Удалить API-ключ',
   'mcp.alphaBadge': 'Альфа',
   'mcp.alphaBannerText':

app/src/lib/i18n/chunks/zh-CN-1.ts

@@ -236,6 +236,7 @@ const zhCN1: TranslationMap = {
   'onboarding.custom.stepperVoice': '语音',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': '搜索',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': '记忆',
   'onboarding.custom.stepCounter': '第 {n} 步，共 {total} 步',
   'onboarding.custom.defaultTitle': '默认',
@@ -271,6 +272,13 @@ const zhCN1: TranslationMap = {
   'onboarding.custom.search.defaultDesc': 'OpenHuman 使用托管搜索后端。无需密钥。',
   'onboarding.custom.search.configureDesc':
     '使用你自己的搜索提供商密钥（Tavily、Brave 等）。在设置 › 工具中配置。',
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
   'onboarding.custom.memory.title': '记忆',
   'onboarding.custom.memory.subtitle': 'OpenHuman 如何记住你的上下文、偏好和历史对话。',
   'onboarding.custom.memory.defaultDesc': 'OpenHuman 会自动管理记忆存储和检索。无需设置。',
@@ -508,6 +516,8 @@ const zhCN1: TranslationMap = {
   'settings.embeddings.setupTitle': '设置 {provider}',
   'settings.embeddings.saveAndSwitch': '保存并切换',
   'settings.embeddings.optional': '可选',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': '清除 API 密钥',
   'mcp.alphaBadge': '阿尔法',
   'mcp.alphaBannerText':

app/src/lib/i18n/en.ts

@@ -356,6 +356,7 @@ const en: TranslationMap = {
   'onboarding.custom.stepperVoice': 'Voice',
   'onboarding.custom.stepperOAuth': 'OAuth',
   'onboarding.custom.stepperSearch': 'Search',
+  'onboarding.custom.stepperEmbeddings': 'Embeddings',
   'onboarding.custom.stepperMemory': 'Memory',
   'onboarding.custom.stepCounter': 'Step {n} of {total}',
   'onboarding.custom.defaultTitle': 'Default',
@@ -404,6 +405,15 @@ const en: TranslationMap = {
   'onboarding.custom.search.configureDesc':
     'Bring your own search provider key (Tavily, Brave, etc.). Configure in Settings › Tools.',
 
+  // Onboarding: Custom > Embeddings
+  'onboarding.custom.embeddings.title': 'Embeddings',
+  'onboarding.custom.embeddings.subtitle':
+    'How OpenHuman generates vector embeddings for semantic memory search.',
+  'onboarding.custom.embeddings.defaultDesc':
+    'OpenHuman uses a managed embedding service. No API key needed.',
+  'onboarding.custom.embeddings.configureDesc':
+    'Bring your own embedding provider (OpenAI, Voyage, Ollama, etc.).',
+
   // Onboarding: Custom > Memory
   'onboarding.custom.memory.title': 'Memory',
   'onboarding.custom.memory.subtitle':
@@ -654,6 +664,8 @@ const en: TranslationMap = {
   'settings.embeddings.setupTitle': 'Set up {provider}',
   'settings.embeddings.saveAndSwitch': 'Save & switch',
   'settings.embeddings.optional': 'optional',
+  'settings.embeddings.vectorSearchDisabled':
+    'Vector search is disabled. Memory recall will use keyword matching and recency only — no semantic ranking.',
   'settings.embeddings.clearKey': 'Clear API key',
   'pages.settings.ai.embeddings': 'Embeddings',
   'pages.settings.ai.embeddingsDesc': 'Vector encoding model for memory retrieval',

app/src/pages/onboarding/Onboarding.tsx

@@ -1,9 +1,10 @@
 import { Navigate, Route, Routes } from 'react-router-dom';
 
 import OnboardingLayout from './OnboardingLayout';
+import CustomEmbeddingsPage from './pages/CustomEmbeddingsPage';
 import CustomInferencePage from './pages/CustomInferencePage';
-// Search + Memory steps are hidden from the flow for now (files kept on
-// disk; uncomment alongside customWizardSteps.ts to re-enable):
+// Memory step is hidden from the flow for now (file kept on disk;
+// uncomment alongside customWizardSteps.ts to re-enable):
 // import CustomMemoryPage from './pages/CustomMemoryPage';
 import CustomOAuthPage from './pages/CustomOAuthPage';
 import CustomSearchPage from './pages/CustomSearchPage';
@@ -16,7 +17,7 @@ import WelcomePage from './pages/WelcomePage';
  *
  *   welcome → runtime-choice
  *     ├── cloud  → /home
- *     └── custom → /custom/inference → voice → oauth → search → memory → /home
+ *     └── custom → /custom/inference → voice → oauth → search → embeddings → memory → /home
  *
  * Each custom step asks Default (let OpenHuman manage it) vs Configure
  * (let me pick). Default is a one-click pick; Configure renders inline
@@ -37,6 +38,7 @@ const Onboarding = () => {
         <Route path="custom/voice" element={<CustomVoicePage />} />
         <Route path="custom/oauth" element={<CustomOAuthPage />} />
         <Route path="custom/search" element={<CustomSearchPage />} />
+        <Route path="custom/embeddings" element={<CustomEmbeddingsPage />} />
         {/* <Route path="custom/memory" element={<CustomMemoryPage />} /> */}
         <Route path="*" element={<Navigate to="welcome" replace />} />
       </Route>

app/src/pages/onboarding/OnboardingContext.tsx

@@ -2,7 +2,7 @@ import { createContext, useContext } from 'react';
 
 export type AiMode = 'cloud' | 'custom';
 
-export type CustomStepKey = 'inference' | 'voice' | 'oauth' | 'search' | 'memory';
+export type CustomStepKey = 'inference' | 'voice' | 'oauth' | 'search' | 'embeddings' | 'memory';
 export type CustomStepChoice = 'default' | 'configure';
 
 export interface OnboardingDraft {

app/src/pages/onboarding/customWizardSteps.ts

@@ -8,6 +8,7 @@ export const CUSTOM_WIZARD_STEPS: CustomStepKey[] = [
   'voice',
   'oauth',
   'search',
+  'embeddings',
   // 'memory',
 ];
 
@@ -16,6 +17,7 @@ export const CUSTOM_WIZARD_ROUTES: Record<CustomStepKey, string> = {
   voice: '/onboarding/custom/voice',
   oauth: '/onboarding/custom/oauth',
   search: '/onboarding/custom/search',
+  embeddings: '/onboarding/custom/embeddings',
   memory: '/onboarding/custom/memory',
 };
 
@@ -26,5 +28,6 @@ export const CUSTOM_WIZARD_SETTINGS_ROUTES: Record<CustomStepKey, string> = {
   voice: '/settings/voice',
   oauth: '/settings/composio-routing',
   search: '/settings/tools',
+  embeddings: '/settings/embeddings',
   memory: '/settings/memory-data',
 };

app/src/pages/onboarding/pages/CustomEmbeddingsPage.tsx

@@ -0,0 +1,83 @@
+import { useEffect, useState } from 'react';
+import { useNavigate } from 'react-router-dom';
+
+import EmbeddingsPanel from '../../../components/settings/panels/EmbeddingsPanel';
+import { useT } from '../../../lib/i18n/I18nContext';
+import { useCoreState } from '../../../providers/CoreStateProvider';
+import { trackEvent } from '../../../services/analytics';
+import { isLocalSessionToken } from '../../../utils/localSession';
+import { CUSTOM_WIZARD_ROUTES, CUSTOM_WIZARD_STEPS } from '../customWizardSteps';
+import { type CustomStepChoice, useOnboardingContext } from '../OnboardingContext';
+import CustomWizardStep from '../steps/CustomWizardStep';
+
+const STEP_KEY = 'embeddings' as const;
+const STEP_INDEX = CUSTOM_WIZARD_STEPS.indexOf(STEP_KEY);
+const LOCAL_DEFAULT_DISABLED_REASON =
+  'Managed setup requires OpenHuman sign-in and is unavailable in local mode.';
+
+const CustomEmbeddingsPage = () => {
+  const { t } = useT();
+  const navigate = useNavigate();
+  const { snapshot } = useCoreState();
+  const { draft, setDraft, completeAndExit } = useOnboardingContext();
+  const isLocalSession = isLocalSessionToken(snapshot.sessionToken);
+
+  const [choice, setChoice] = useState<CustomStepChoice | null>(
+    draft.customChoices?.[STEP_KEY] ?? (isLocalSession ? 'configure' : null)
+  );
+
+  useEffect(() => {
+    if (!isLocalSession) {
+      return;
+    }
+    setChoice('configure');
+    setDraft(prev => ({
+      ...prev,
+      customChoices: { ...prev.customChoices, [STEP_KEY]: 'configure' },
+    }));
+  }, [isLocalSession, setDraft]);
+
+  const persistChoice = (next: CustomStepChoice) => {
+    setChoice(next);
+    setDraft(prev => ({ ...prev, customChoices: { ...prev.customChoices, [STEP_KEY]: next } }));
+  };
+
+  const isLast = STEP_INDEX === CUSTOM_WIZARD_STEPS.length - 1;
+
+  return (
+    <CustomWizardStep
+      testId="onboarding-custom-embeddings-step"
+      stepIndex={STEP_INDEX}
+      stepCount={CUSTOM_WIZARD_STEPS.length}
+      title={t('onboarding.custom.embeddings.title')}
+      subtitle={t('onboarding.custom.embeddings.subtitle')}
+      defaultDescription={t('onboarding.custom.embeddings.defaultDesc')}
+      configureDescription={t('onboarding.custom.embeddings.configureDesc')}
+      configureContent={<EmbeddingsPanel embedded />}
+      defaultDisabled={isLocalSession}
+      defaultDisabledReason={isLocalSession ? LOCAL_DEFAULT_DISABLED_REASON : undefined}
+      hideChoiceCards={isLocalSession}
+      choice={choice}
+      onChoiceChange={persistChoice}
+      onBack={() => navigate(CUSTOM_WIZARD_ROUTES[CUSTOM_WIZARD_STEPS[STEP_INDEX - 1]])}
+      onContinue={async () => {
+        trackEvent('onboarding_step_complete', {
+          step_name: 'custom_embeddings',
+          choice: choice ?? 'default',
+        });
+        if (isLast) {
+          try {
+            await completeAndExit();
+          } catch (err) {
+            console.error('[onboarding:custom-embeddings] completeAndExit failed', err);
+          }
+          return;
+        }
+        navigate(CUSTOM_WIZARD_ROUTES[CUSTOM_WIZARD_STEPS[STEP_INDEX + 1]]);
+      }}
+      continueLabel={isLast ? t('onboarding.custom.finish') : undefined}
+    />
+  );
+};
+
+export default CustomEmbeddingsPage;

app/src/pages/onboarding/steps/CustomWizardStep.tsx

@@ -113,6 +113,7 @@ const CustomWizardStep = ({
     t('onboarding.custom.stepperVoice'),
     t('onboarding.custom.stepperOAuth'),
     t('onboarding.custom.stepperSearch'),
+    t('onboarding.custom.stepperEmbeddings'),
     t('onboarding.custom.stepperMemory'),
   ].slice(0, stepCount);
 

app/src/services/api/embeddingsApi.ts

@@ -32,6 +32,7 @@ export interface EmbeddingsSettings {
   dimensions: number;
   rate_limit_per_min: number;
   providers: EmbeddingProviderEntry[];
+  vector_search_enabled: boolean;
 }
 
 export interface EmbeddingsUpdateResult {

src/openhuman/embeddings/rpc.rs

@@ -43,18 +43,29 @@ pub async fn get_settings(config: &Config) -> Result<RpcOutcome<serde_json::Valu
         })
         .collect();
 
+    let vector_search_enabled = {
+        let slug = if provider.starts_with("custom:") {
+            "custom"
+        } else {
+            provider.as_str()
+        };
+        slug != "none"
+    };
+
     let payload = serde_json::json!({
         "provider": provider,
         "model": model,
         "dimensions": dimensions,
         "rate_limit_per_min": rate_limit,
         "providers": providers,
+        "vector_search_enabled": vector_search_enabled,
     });
 
     tracing::debug!(
         provider = provider.as_str(),
         model = model.as_str(),
         dimensions,
+        vector_search_enabled,
         "{LOG_PREFIX} get_settings"
     );
 

src/openhuman/memory/tree_e2e_test.rs

@@ -28,6 +28,7 @@ use crate::openhuman::memory_sync::canonicalize::chat::{ChatBatch, ChatMessage};
 use crate::openhuman::memory_tree::retrieval::{
     query_global, query_source, query_topic, search_entities,
 };
+use crate::openhuman::memory_tree::score::embed::build_embedder_from_config;
 
 fn test_config() -> (TempDir, Config) {
     let tmp = TempDir::new().unwrap();
@@ -364,3 +365,135 @@ async fn full_pipeline_ingest_to_retrieval() {
     })
     .await;
 }
+
+/// When `embeddings_provider = "none"`, the full ingest → retrieval pipeline
+/// must still work end-to-end. Semantic rerank degrades to recency ordering
+/// (InertEmbedder produces zero vectors → cosine similarity = 0), but chunks
+/// are still written with valid zero-vector embeddings, and source-tree
+/// retrieval succeeds via the recency fallback path.
+///
+/// This guards against regressions where disabling embeddings causes panics,
+/// schema mismatches, or silent data loss in the memory subsystem.
+#[tokio::test]
+async fn pipeline_works_with_embeddings_disabled() {
+    let (_tmp, mut cfg) = test_config();
+    cfg.embeddings_provider = Some("none".into());
+
+    // Verify the factory returns InertEmbedder for this config.
+    let embedder = build_embedder_from_config(&cfg).expect("factory must succeed for 'none'");
+    assert_eq!(
+        embedder.name(),
+        "inert",
+        "embeddings_provider=none must route to InertEmbedder"
+    );
+
+    let provider: Arc<dyn ChatProvider> = Arc::new(StaticChatProvider::new(
+        r#"{"summary":"bob@example.com discussed the quarterly review.","entities":["email:bob@example.com"],"topics":["quarterly","review"]}"#,
+    ));
+
+    test_override::with_provider(Arc::clone(&provider), async {
+        // ── Ingest a heavy batch to cross the seal threshold ────────────
+        let source_id = "slack:#disabled-embed-test";
+        let result = ingest_chat(
+            &cfg,
+            source_id,
+            "bob",
+            vec!["test".into()],
+            heavy_batch("slack", "#disabled-embed-test", 0),
+        )
+        .await
+        .expect("ingest_chat must succeed with embeddings disabled");
+
+        assert!(
+            result.chunks_written >= 1,
+            "ingest must write at least one chunk even with embeddings disabled"
+        );
+
+        log::debug!(
+            "[tree_e2e_test::embeddings_disabled] ingest: chunks_written={} dropped={}",
+            result.chunks_written,
+            result.chunks_dropped
+        );
+
+        // ── Drain the async job queue ───────────────────────────────────
+        drain_until_idle(&cfg)
+            .await
+            .expect("drain_until_idle must succeed with embeddings disabled");
+
+        // ── Source-tree retrieval without a query (recency only) ─────────
+        use crate::openhuman::memory_store::chunks::types::SourceKind;
+        let recency_resp = query_source(&cfg, None, Some(SourceKind::Chat), None, None, 20)
+            .await
+            .expect("query_source (recency) must succeed with embeddings disabled");
+
+        log::debug!(
+            "[tree_e2e_test::embeddings_disabled] query_source (recency): total={} hits={}",
+            recency_resp.total,
+            recency_resp.hits.len()
+        );
+
+        assert!(
+            recency_resp.total >= recency_resp.hits.len(),
+            "query_source total must be >= hits.len()"
+        );
+
+        // ── Source-tree retrieval WITH a query (semantic rerank path) ────
+        // This exercises the codepath where build_embedder_from_config is
+        // called internally. With InertEmbedder, the rerank degrades to
+        // recency ordering but must not error.
+        let semantic_resp = query_source(
+            &cfg,
+            None,
+            Some(SourceKind::Chat),
+            None,
+            Some("quarterly review"),
+            20,
+        )
+        .await
+        .expect(
+            "query_source (semantic) must succeed with embeddings disabled — \
+             InertEmbedder should degrade gracefully to recency ordering",
+        );
+
+        log::debug!(
+            "[tree_e2e_test::embeddings_disabled] query_source (semantic): total={} hits={}",
+            semantic_resp.total,
+            semantic_resp.hits.len()
+        );
+
+        assert!(
+            semantic_resp.total >= semantic_resp.hits.len(),
+            "query_source total must be >= hits.len()"
+        );
+
+        // ── Global digest should also succeed ───────────────────────────
+        let today = Utc::now().date_naive();
+        let digest_outcome = end_of_day_digest(&cfg, today)
+            .await
+            .expect("end_of_day_digest must succeed with embeddings disabled");
+
+        log::debug!(
+            "[tree_e2e_test::embeddings_disabled] digest outcome: {:?}",
+            digest_outcome
+        );
+
+        // ── Entity search (keyword-based, no embeddings needed) ─────────
+        let entity_matches = search_entities(&cfg, "bob", None, 10)
+            .await
+            .expect("search_entities must succeed with embeddings disabled");
+
+        log::debug!(
+            "[tree_e2e_test::embeddings_disabled] search_entities('bob'): {} matches",
+            entity_matches.len()
+        );
+
+        log::info!(
+            "[tree_e2e_test] pipeline_works_with_embeddings_disabled PASSED \
+             recency_hits={} semantic_hits={} entity_matches={}",
+            recency_resp.hits.len(),
+            semantic_resp.hits.len(),
+            entity_matches.len()
+        );
+    })
+    .await;
+}

src/openhuman/memory_tree/score/embed/factory.rs

@@ -80,6 +80,21 @@ pub fn build_embedder_from_config(config: &Config) -> Result<Box<dyn Embedder>>
             )))
         }
         _ => {
+            // If the user explicitly disabled embeddings, return InertEmbedder
+            // so semantic rerank degrades to recency-only ordering.
+            if config
+                .embeddings_provider
+                .as_deref()
+                .map(|s| s.trim())
+                .is_some_and(|s| s == "none")
+            {
+                log::info!(
+                    "[memory_tree::embed::factory] embeddings_provider=none — \
+                     using InertEmbedder (vector search disabled)"
+                );
+                return Ok(Box::new(InertEmbedder::new()));
+            }
+
             // Honour the unified AI settings: `embeddings_provider` is the
             // single source of truth. When it parses as `ollama:<model>` we
             // route locally; otherwise we fall back to the cloud session.
@@ -241,6 +256,15 @@ mod tests {
         assert_eq!(e.name(), "cloud");
     }
 
+    #[test]
+    fn none_provider_returns_inert() {
+        let (_tmp, mut cfg) = test_config();
+        cfg.embeddings_provider = Some("none".into());
+        touch_auth_profile(&cfg);
+        let e = build_embedder_from_config(&cfg).expect("none should build");
+        assert_eq!(e.name(), "inert");
+    }
+
     #[test]
     fn explicit_endpoint_override_wins_over_local_ai_flag() {
         // Power-user override beats the checkbox.