Fix post-transcribe freeze: batch embeddings off the main thread + guard load

Two reported symptoms — the transcript screen sitting on its loading spinner
after a transcription, and a follow-up transcription stuck at 0% — both trace
to the same cause: after a transcript saves, embedOne() embeds the whole
lecture in ONE synchronous WASM call on the MAIN thread. Measured in a browser
harness: embedding 150 segments blocks the thread for ~1.86s straight (a 50ms
heartbeat fired once instead of ~35x); on a phone or a long lecture that's many
seconds of total UI freeze. During it the just-navigated transcript screen
can't run its get() callback (looks "stuck loading") and a concurrent
transcription's progress UI is frozen at 0%.

- embeddingStore.embedTranscript: embed in batches of 16, yielding to the event
  loop between batches, so the UI stays responsive. Per-text vectors are
  identical (e5 pools each text independently); this only changes scheduling.
- transcript/[id].tsx: the get() load had NO error handling, so a rejected load
  (or a long freeze) left the spinner up forever. Add .catch -> show a real
  "couldn't load" message instead of an infinite spinner; also catch the
  (non-fatal) media-url load.

Ruled out (via harness) the theory that the e5 embedding model hits the same
WASM MatMulNBits load failure as Whisper — e5 (encoder-only) loads fine at both
q8 and fp32 on WASM, so its dtype is left unchanged.

Proper long-term fix (separate, larger): run embeddings in a Web Worker.

Validated: tsc clean, 282 tests, web export OK.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

src/app/transcript/[id].tsx

@@ -17,6 +17,7 @@ import { MaxContentWidth, Spacing } from '@/constants/theme';
 import { useTheme } from '@/hooks/use-theme';
 import { getRepo, type Transcript } from '@/lib/db';
 import { downloadText } from '@/lib/download';
+import { errorMessage } from '@/lib/errorMessage';
 import {
   detectCitations,
   detectEvents,
@@ -52,6 +53,7 @@ export default function TranscriptScreen() {
   }, [t]);
 
   const [transcript, setTranscript] = useState<Transcript | null | undefined>(undefined);
+  const [loadError, setLoadError] = useState<string | null>(null);
   const [title, setTitle] = useState('');
   const [segments, setSegments] = useState<Segment[]>([]);
   const [dirty, setDirty] = useState(false);
@@ -99,6 +101,9 @@ export default function TranscriptScreen() {
         if (!alive) return;
         url = u;
         setPersistedUrl(u);
+      })
+      .catch(() => {
+        // Missing/failed media is non-fatal — playback just stays unavailable.
       });
     return () => {
       alive = false;
@@ -115,6 +120,12 @@ export default function TranscriptScreen() {
         setTranscript(t ?? null);
         setTitle(t?.title ?? '');
         setSegments(t?.segments ?? []);
+      })
+      .catch((e) => {
+        // Without this, a rejected load left the screen on its spinner forever.
+        if (!alive) return;
+        setLoadError(errorMessage(e));
+        setTranscript(null);
       });
     return () => {
       alive = false;
@@ -277,7 +288,9 @@ export default function TranscriptScreen() {
   if (transcript === null)
     return (
       <Centered>
-        <ThemedText type="small" themeColor="textSecondary">Transcript not found.</ThemedText>
+        <ThemedText type="small" themeColor="textSecondary">
+          {loadError ? `Couldn't load this transcript: ${loadError}` : 'Transcript not found.'}
+        </ThemedText>
       </Centered>
     );
 

src/stores/embeddingStore.ts

@@ -40,10 +40,21 @@ async function embedTranscript(transcriptId: string): Promise<void> {
     return;
   }
   const eng = getEmbeddingEngine();
-  const vecs = await eng.embed(
+  // Embed in small batches, yielding to the event loop between them. The WASM
-    t.segments.map((s) => s.text),
+  // backend runs synchronously on the MAIN thread, so embedding a whole lecture
-    'passage',
+  // (100s of segments) in one call froze the UI for seconds — which, right after
-  );
+  // a transcription, looked like the transcript screen was "stuck loading" and
+  // starved any follow-up transcription. Per-text vectors are identical
+  // regardless of batch size (e5 pools each text independently).
+  const texts = t.segments.map((s) => s.text);
+  const BATCH = 16;
+  const vecs: Float32Array[] = [];
+  for (let i = 0; i < texts.length; i += BATCH) {
+    const out = await eng.embed(texts.slice(i, i + BATCH), 'passage');
+    for (const v of out) vecs.push(v);
+    // Hand the thread back so navigation, rendering and other work can run.
+    await new Promise<void>((resolve) => setTimeout(resolve, 0));
+  }
   await repo.upsertVectors(
     transcriptId,
     EMBED_MODEL,