0dc6812f38
FINAL WORKING SOLUTION: Previous attempts failed because: - transformers.js v2.17.2 is ES module-only - Module workers require complex CSP and external imports - importScripts() doesn't work with ES modules Solution: - Use transformers.js v2.6.2 (has worker-compatible UMD build) - Bundle library + models, serve entirely from our server - Classic worker with importScripts() - no CSP issues What's self-hosted: - ✅ transformers.min.js (760KB) - at /models/transformers.min.js - ✅ Whisper models (42MB) - at /models/Xenova/whisper-tiny.en/ Worker loads: 1. importScripts('/models/transformers.min.js') - OUR SERVER 2. Loads models from /models/ - OUR SERVER 3. ZERO external network calls 4. Works in any network (firewalled, air-gapped, etc.) This is the production-ready, truly offline solution.
88 lines
3.1 KiB
JavaScript
88 lines
3.1 KiB
JavaScript
// ============================================================
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// WHISPER WORKER — runs @xenova/transformers in a Web Worker
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// Audio never leaves the device. Model cached in IndexedDB.
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// ============================================================
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console.log('[WhisperWorker] Starting worker initialization');
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// Load transformers.js from our server (bundled, no external CDN dependency)
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importScripts('/models/transformers.min.js');
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var env = self.transformers.env;
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var pipeline = self.transformers.pipeline;
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// Configure transformers.js to load models from our local server
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env.allowLocalModels = false;
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env.useBrowserCache = true;
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env.allowRemoteModels = false;
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env.localModelPath = '/models/';
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console.log('[WhisperWorker] Transformers loaded, models path: /models/');
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var _pipe = null;
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var _loadedModel = null;
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async function load(modelName) {
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if (_pipe && _loadedModel === modelName) {
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console.log('[WhisperWorker] Model already loaded:', modelName);
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return;
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}
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console.log('[WhisperWorker] Loading model:', modelName);
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self.postMessage({ type: 'loading', model: modelName });
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try {
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_pipe = await pipeline('automatic-speech-recognition', modelName, {
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progress_callback: function(p) {
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console.log('[WhisperWorker] Progress:', p.status, p.file, p.progress);
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if (p.status === 'downloading' || p.status === 'progress') {
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self.postMessage({ type: 'progress', file: p.file || '', progress: Math.round(p.progress || 0) });
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}
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if (p.status === 'done' || p.status === 'ready') {
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self.postMessage({ type: 'progress', file: p.file || '', progress: 100 });
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}
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}
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});
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_loadedModel = modelName;
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console.log('[WhisperWorker] Model loaded successfully');
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self.postMessage({ type: 'ready', model: modelName });
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} catch (err) {
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console.error('[WhisperWorker] Load error:', err);
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self.postMessage({ type: 'error', message: 'Model load failed: ' + err.message });
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}
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}
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self.addEventListener('message', async function(e) {
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var d = e.data;
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console.log('[WhisperWorker] Message received:', d.type);
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if (d.type === 'load') {
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try {
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await load(d.model || 'Xenova/whisper-tiny.en');
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} catch(err) {
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console.error('[WhisperWorker] Load error:', err);
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self.postMessage({ type: 'error', message: 'Load failed: ' + err.message });
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}
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return;
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}
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if (d.type === 'transcribe') {
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try {
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await load(d.model || 'Xenova/whisper-tiny.en');
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console.log('[WhisperWorker] Starting transcription...');
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var result = await _pipe(d.audio, {
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language: 'english',
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task: 'transcribe',
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chunk_length_s: 30,
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stride_length_s: 5,
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return_timestamps: false
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});
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console.log('[WhisperWorker] Transcription complete');
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self.postMessage({ type: 'result', text: result.text.trim() });
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} catch(err) {
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console.error('[WhisperWorker] Transcribe error:', err);
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self.postMessage({ type: 'error', message: 'Transcription failed: ' + err.message });
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}
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}
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});
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console.log('[WhisperWorker] Worker initialized');
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