feat: switch embeddings from Voyage AI to Google Gemini text-embedding-004

- embedText: call Gemini REST API (768-dim) instead of Voyage (1024-dim)
- Migration: drop+recreate incidents.embedding as vector(768), update
  match_incidents function, swap VOYAGE_API_KEY → GOOGLE_AI_API_KEY in app_settings
- Settings UI: relabel to "Google AI API Key (Embeddings)"
- All call sites updated (incidents POST, similar GET)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CPf5Rc8QPx6V8KLEEgfKEQ

app/api/incidents/[id]/similar/route.ts

@@ -18,7 +18,7 @@ export async function GET(
   if (!profile || !['hse', 'admin'].includes(profile.role))
     return NextResponse.json({ error: 'Forbidden' }, { status: 403 })
 
-  const voyageKey = await getApiKey(supabase, 'VOYAGE_API_KEY')
+  const googleAiKey = await getApiKey(supabase, 'GOOGLE_AI_API_KEY')
 
   const { data: incident } = await supabase
     .from('incidents')
@@ -34,7 +34,7 @@ export async function GET(
     if (inc.embedding) {
       embeddingVec = JSON.parse(inc.embedding) as number[]
     } else {
-      embeddingVec = await embedText(inc.description, voyageKey)
+      embeddingVec = await embedText(inc.description, googleAiKey)
       // Closed incidents are locked at the DB level — the trigger would reject
       // this backfill. The vector still serves the similarity query below.
       if (inc.status !== 'closed') {

app/api/incidents/route.ts

@@ -182,9 +182,9 @@ export async function POST(request: Request) {
   // Embed description asynchronously for future similarity search
   const supabaseForEmbed = supabase
   import('@/lib/settings').then(({ getApiKey }) =>
-    getApiKey(supabaseForEmbed, 'VOYAGE_API_KEY').then(voyageKey =>
+    getApiKey(supabaseForEmbed, 'GOOGLE_AI_API_KEY').then(googleAiKey =>
       import('@/lib/claude/embed').then(({ embedText }) =>
-        embedText(input.description.trim(), voyageKey).then(embedding =>
+        embedText(input.description.trim(), googleAiKey).then(embedding =>
           supabase.from('incidents').update({
             embedding: `[${embedding.join(',')}]` as unknown as string,
           }).eq('id', incident.id)

app/api/settings/route.ts

@@ -6,7 +6,7 @@ import { createClient } from '@/lib/supabase/server'
 const ALLOWED_KEYS = [
   'ANTHROPIC_API_KEY',
   'DEEPSEEK_API_KEY',
-  'VOYAGE_API_KEY',
+  'GOOGLE_AI_API_KEY',
   'META_WHATSAPP_PHONE_NUMBER_ID',
   'META_WHATSAPP_ACCESS_TOKEN',
 ] as const

components/settings/api-key-form.tsx

@@ -10,13 +10,13 @@ interface Props {
 
 const KEY_LABELS: Record<string, string> = {
   DEEPSEEK_API_KEY: 'DeepSeek API Key (AI)',
-  VOYAGE_API_KEY: 'Voyage AI API Key (Embeddings)',
+  GOOGLE_AI_API_KEY: 'Google AI API Key (Embeddings)',
 }
 
 export function ApiKeyForm({ settings }: Props) {
   const [values, setValues] = useState<Record<string, string>>({
     DEEPSEEK_API_KEY: '',
-    VOYAGE_API_KEY: '',
+    GOOGLE_AI_API_KEY: '',
   })
   const [saving, setSaving] = useState<Record<string, boolean>>({})
   const [results, setResults] = useState<Record<string, 'ok' | 'error'>>({})

lib/claude/embed.ts

@@ -1,15 +1,18 @@
 export async function embedText(text: string, apiKey?: string): Promise<number[]> {
-  const key = apiKey ?? process.env.VOYAGE_API_KEY
+  const key = apiKey ?? process.env.GOOGLE_AI_API_KEY
-  if (!key) throw new Error('VOYAGE_API_KEY is not set')
+  if (!key) throw new Error('GOOGLE_AI_API_KEY is not set')
-  const res = await fetch('https://api.voyageai.com/v1/embeddings', {
+  const res = await fetch(
-    method: 'POST',
+    `https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:embedContent?key=${key}`,
-    headers: {
+    {
-      'Content-Type': 'application/json',
+      method: 'POST',
-      'Authorization': `Bearer ${key}`,
+      headers: { 'Content-Type': 'application/json' },
-    },
+      body: JSON.stringify({
-    body: JSON.stringify({ input: [text], model: 'voyage-3-lite' }),
+        model: 'models/text-embedding-004',
-  })
+        content: { parts: [{ text }] },
-  if (!res.ok) throw new Error(`Voyage embed failed: ${res.status}`)
+      }),
-  const json = await res.json() as { data: Array<{ embedding: number[] }> }
+    }
-  return json.data[0].embedding
+  )
+  if (!res.ok) throw new Error(`Gemini embed failed: ${res.status}`)
+  const json = await res.json() as { embedding: { values: number[] } }
+  return json.embedding.values
 }

supabase/migrations/20260713000001_gemini_embeddings.sql

@@ -0,0 +1,49 @@
+-- Migrate embeddings from Voyage AI (1024-dim) to Gemini text-embedding-004 (768-dim)
+
+-- Drop dependent objects first
+drop index if exists incidents_embedding_idx;
+drop function if exists match_incidents;
+
+-- Replace column (dimension change requires drop+add)
+alter table incidents drop column if exists embedding;
+alter table incidents add column embedding vector(768);
+
+-- Recreate index
+create index incidents_embedding_idx
+  on incidents using ivfflat (embedding vector_cosine_ops)
+  with (lists = 10);
+
+-- Recreate similarity function at 768-dim
+create or replace function match_incidents(
+  query_embedding vector(768),
+  exclude_id      uuid,
+  match_count     int default 5
+)
+returns table (
+  id            uuid,
+  reference_no  text,
+  incident_type text,
+  description   text,
+  severity      int,
+  similarity    float
+)
+language sql
+security definer
+as $$
+  select
+    i.id,
+    i.reference_no,
+    i.incident_type,
+    i.description,
+    i.severity,
+    1 - (i.embedding <=> query_embedding) as similarity
+  from incidents i
+  where i.id != exclude_id
+    and i.embedding is not null
+  order by i.embedding <=> query_embedding
+  limit match_count;
+$$;
+
+-- Register Gemini key slot, remove Voyage slot
+insert into app_settings (key, value) values ('GOOGLE_AI_API_KEY', '') on conflict (key) do nothing;
+delete from app_settings where key = 'VOYAGE_API_KEY';

tests/lib/claude/embed.test.ts

@@ -2,36 +2,36 @@ import { describe, it, expect, vi, beforeEach, afterEach } from 'vitest'
 
 describe('embedText', () => {
   beforeEach(() => {
-    process.env.VOYAGE_API_KEY = 'test-key'
+    process.env.GOOGLE_AI_API_KEY = 'test-key'
   })
 
   afterEach(() => {
     vi.restoreAllMocks()
   })
 
-  it('returns 1024-element embedding array', async () => {
+  it('returns 768-element embedding array', async () => {
-    const mockEmbedding = Array.from({ length: 1024 }, (_, i) => i / 1024)
+    const mockEmbedding = Array.from({ length: 768 }, (_, i) => i / 768)
     vi.stubGlobal('fetch', vi.fn().mockResolvedValue({
       ok: true,
-      json: () => Promise.resolve({ data: [{ embedding: mockEmbedding }] }),
+      json: () => Promise.resolve({ embedding: { values: mockEmbedding } }),
     }))
     const { embedText } = await import('@/lib/claude/embed')
     const result = await embedText('forklift hit racking in zone B')
-    expect(result).toHaveLength(1024)
+    expect(result).toHaveLength(768)
     expect(result[0]).toBeCloseTo(0)
-    expect(result[1023]).toBeCloseTo(1023 / 1024)
+    expect(result[767]).toBeCloseTo(767 / 768)
   })
 
   it('throws on non-ok response', async () => {
     vi.stubGlobal('fetch', vi.fn().mockResolvedValue({ ok: false, status: 401 }))
     const { embedText } = await import('@/lib/claude/embed')
-    await expect(embedText('test')).rejects.toThrow('Voyage embed failed: 401')
+    await expect(embedText('test')).rejects.toThrow('Gemini embed failed: 401')
   })
 
-  it('throws when VOYAGE_API_KEY is missing', async () => {
+  it('throws when GOOGLE_AI_API_KEY is missing', async () => {
-    delete process.env.VOYAGE_API_KEY
+    delete process.env.GOOGLE_AI_API_KEY
     vi.resetModules()
     const { embedText } = await import('@/lib/claude/embed')
-    await expect(embedText('test')).rejects.toThrow('VOYAGE_API_KEY')
+    await expect(embedText('test')).rejects.toThrow('GOOGLE_AI_API_KEY')
   })
 })