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