init

app/static/worker.js

@@ -0,0 +1,58 @@
+import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3/dist/transformers.min.js';
+
+// Disable local model file check — always fetch from HuggingFace Hub
+env.allowLocalModels = false;
+
+let transcriber = null;
+
+async function loadModel(modelId) {
+  transcriber = await pipeline(
+    'automatic-speech-recognition',
+    modelId,
+    {
+      device: 'webgpu',
+      dtype: 'q4',
+      progress_callback: (progress) => {
+        self.postMessage({ type: 'model-progress', progress });
+      },
+    }
+  );
+  self.postMessage({ type: 'model-ready' });
+}
+
+// audioData is a Float32Array of 16kHz mono PCM — decoded in the main thread
+// to avoid the missing AudioContext issue in Web Workers.
+async function transcribe(audioData, language) {
+  if (!transcriber) {
+    self.postMessage({ type: 'error', message: 'Model not loaded' });
+    return;
+  }
+
+  try {
+    const result = await transcriber(audioData, {
+      return_timestamps: true,
+      chunk_length_s: 30,
+      stride_length_s: 5,
+      language: language || null,
+      task: 'transcribe',
+    });
+
+    self.postMessage({ type: 'result', text: result.text, chunks: result.chunks || [] });
+  } catch (err) {
+    self.postMessage({ type: 'error', message: err.message });
+  }
+}
+
+self.onmessage = async (event) => {
+  const { type, modelId, audioData, language } = event.data;
+
+  if (type === 'load') {
+    try {
+      await loadModel(modelId || 'Xenova/whisper-small');
+    } catch (err) {
+      self.postMessage({ type: 'error', message: `Failed to load model: ${err.message}` });
+    }
+  } else if (type === 'transcribe') {
+    await transcribe(audioData, language);
+  }
+};