Show Piper startup and download stages

piper-worker.js

@@ -7,15 +7,27 @@ const VOICE_ID = 'sv_SE-nst-medium';
 const ASSET_ROOT = '/static/piper-wasm-v1';
 const localFetch = self.fetch.bind(self);
 
+function reportStage(id, stage) {
+  if (Number.isSafeInteger(id)) self.postMessage({id, type: 'progress', progress: {stage}});
+}
+
 // Keep the TTS library's OPFS cache logic, but serve models/config from the
 // same-origin static asset service instead of its built-in external model URL.
 self.fetch = async (resource, options) => {
   const requestedUrl = resource instanceof Request ? resource.url : String(resource);
   const localModelUrl = localPiperModelUrl(requestedUrl, self.location.origin);
-  if (!localModelUrl) return localFetch(resource, options);
+  if (!localModelUrl) {
+    if (activeRequestId && requestedUrl.includes('/static/piper-wasm-v1/onnx/')) {
+      reportStage(activeRequestId, 'loading-runtime-assets');
+    }
+    return localFetch(resource, options);
+  }
+  const isModel = localModelUrl.endsWith('.onnx');
+  if (activeRequestId) reportStage(activeRequestId, isModel ? 'loading-model' : 'loading-model-info');
   const redirected = resource instanceof Request ? new Request(localModelUrl, resource) : localModelUrl;
   const response = await localFetch(redirected, options);
-  if (!activeRequestId || !localModelUrl.endsWith('.onnx')) return response;
+  if (!activeRequestId || !isModel) return response;
+  reportStage(activeRequestId, 'reading-model');
   return trackModelDownload(response, {
     id: activeRequestId,
     postMessage: message => self.postMessage(message),
@@ -47,9 +59,10 @@ async function synthesizeMessage(event) {
   const {id, text} = event.data || {};
   if (!Number.isSafeInteger(id) || typeof text !== 'string') return;
   activeRequestId = id;
-  self.postMessage({id, type: 'progress', progress: {stage: 'starting'}});
+  reportStage(id, 'loading-runtime');
   try {
     const session = await getSession();
+    reportStage(id, 'model-ready');
     const blob = await session.predict(text);
     const audio = await blob.arrayBuffer();
     self.postMessage({id, type: 'audio', audio}, [audio]);