2026-08-30 02:24:11 +03:00
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import { detectTextLanguage } from '../tts/language-detect.js';
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2026-07-04 02:48:07 +03:00
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/**
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* Dictation service: resolves STT providers, tracks local model download
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* state, and exposes a readiness snapshot for the status route.
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*
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* Providers:
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* - 'local' (default): sherpa-onnx Parakeet running in a worker process.
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* Models auto-download in the background on first use.
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* - 'openai-compatible': any OpenAI-compatible /v1/audio/transcriptions
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* endpoint (faster-whisper, whisper.cpp, OpenAI).
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*/
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import { rm } from 'fs/promises';
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import { DictationWorkerClient, WorkerBackedTranscriptionSession } from './local/worker-client.js';
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import { OpenAICompatibleTranscriptionSession } from './openai-compatible-session.js';
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import {
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DEFAULT_LOCAL_STT_MODEL,
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DEFAULT_LOCAL_TTS_MODEL,
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2026-08-30 02:24:11 +03:00
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getLocalTtsDefaultSpeaker,
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resolveLocalTtsModelForLanguage,
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2026-07-04 02:48:07 +03:00
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LOCAL_STT_MODEL_CATALOG,
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LOCAL_STT_MODEL_IDS,
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LOCAL_TTS_MODEL_CATALOG,
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LOCAL_TTS_MODEL_IDS,
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getLocalSttModelDir,
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isLocalModelId,
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isLocalSttModelId,
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isLocalTtsModelId,
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} from './local/model-catalog.js';
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import { ensureLocalSttModel, isLocalSttModelInstalled } from './local/model-downloader.js';
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export function createDictationService({ modelsDir }) {
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const workerClient = new DictationWorkerClient();
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/** modelId -> 'downloading' | 'error' */
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const downloadStates = new Map();
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/** modelId -> last download error message */
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const downloadErrors = new Map();
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/** modelId -> in-flight ensure promise */
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const downloadPromises = new Map();
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/** modelId -> 0..100 download percent (null while size unknown) */
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const downloadProgress = new Map();
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const startModelDownload = (modelId) => {
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const existing = downloadPromises.get(modelId);
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if (existing) {
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return existing;
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}
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downloadStates.set(modelId, 'downloading');
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downloadErrors.delete(modelId);
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downloadProgress.set(modelId, 0);
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const promise = ensureLocalSttModel({
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modelsDir,
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modelId,
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onProgress: (downloadedBytes, totalBytes) => {
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downloadProgress.set(
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modelId,
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totalBytes ? Math.min(100, Math.round((downloadedBytes / totalBytes) * 100)) : null,
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);
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},
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})
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.then(() => {
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downloadStates.delete(modelId);
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downloadPromises.delete(modelId);
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downloadProgress.delete(modelId);
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})
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.catch((error) => {
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downloadStates.set(modelId, 'error');
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downloadErrors.set(modelId, error?.message || String(error));
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downloadPromises.delete(modelId);
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downloadProgress.delete(modelId);
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});
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downloadPromises.set(modelId, promise);
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return promise;
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};
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const resolveLocalModelId = (requested) => {
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return isLocalSttModelId(requested) ? requested : DEFAULT_LOCAL_STT_MODEL;
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};
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/**
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* Create a connected StreamingTranscriptionSession for one dictation.
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* Returns { session } on success or { error, retryable, reasonCode } when
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* the provider is not ready.
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*
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* @param {{ provider?: string, language?: string, localModel?: string,
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* openaiCompatible?: { baseUrl?: string, model?: string, apiKey?: string } }} options
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*/
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const createSttSession = async (options = {}) => {
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const provider = options.provider === 'openai-compatible' ? 'openai-compatible' : 'local';
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if (provider === 'openai-compatible') {
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const config = options.openaiCompatible || {};
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const session = new OpenAICompatibleTranscriptionSession({
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baseURL: config.baseUrl,
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model: config.model,
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apiKey: config.apiKey || undefined,
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language: options.language || undefined,
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});
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try {
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await session.connect();
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} catch (error) {
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return {
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error: error?.message || String(error),
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retryable: false,
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reasonCode: 'stt_not_configured',
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};
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}
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return { session };
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}
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const modelId = resolveLocalModelId(options.localModel);
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const installed = await isLocalSttModelInstalled(modelsDir, modelId);
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if (!installed) {
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const state = downloadStates.get(modelId);
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if (state === 'error') {
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const message = downloadErrors.get(modelId) || 'Model download failed';
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// Allow a retry on the next attempt.
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downloadStates.delete(modelId);
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return {
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error: `Failed to download dictation model: ${message}`,
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retryable: true,
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reasonCode: 'model_download_failed',
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};
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}
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void startModelDownload(modelId);
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return {
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error: 'Dictation model is downloading',
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retryable: true,
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reasonCode: 'model_download_in_progress',
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};
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}
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const session = new WorkerBackedTranscriptionSession(workerClient, { modelsDir, modelId });
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try {
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await session.connect();
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} catch (error) {
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const message = error?.message || String(error);
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// A model that passes the file-presence check but fails to load is
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// corrupt on disk (e.g. truncated by an interrupted extraction). Remove
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// it so the next attempt re-downloads instead of crashing forever.
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if (/Load model|Protobuf parsing failed/i.test(message)) {
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await rm(getLocalSttModelDir(modelsDir, modelId), { recursive: true, force: true })
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.catch(() => undefined);
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return {
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error: 'Dictation model files were corrupt and have been removed; retry to re-download',
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retryable: true,
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reasonCode: 'model_corrupt',
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};
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}
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return {
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error: message,
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retryable: true,
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reasonCode: 'stt_unavailable',
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};
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}
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return { session };
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};
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/**
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* Readiness snapshot for the status route and UI gating.
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* @param {{ provider?: string, localModel?: string }} [options]
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*/
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const getStatus = async (options = {}) => {
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const provider = options.provider === 'openai-compatible' ? 'openai-compatible' : 'local';
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const modelId = resolveLocalModelId(options.localModel);
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const describeModel = async (id, catalog) => ({
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id,
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description: catalog[id].description,
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installed: await isLocalSttModelInstalled(modelsDir, id),
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downloading: downloadStates.get(id) === 'downloading',
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downloadProgress: downloadProgress.get(id) ?? null,
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downloadError: downloadErrors.get(id) || null,
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});
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const models = await Promise.all(
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LOCAL_STT_MODEL_IDS.map((id) => describeModel(id, LOCAL_STT_MODEL_CATALOG)),
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);
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const ttsModels = await Promise.all(
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LOCAL_TTS_MODEL_IDS.map((id) => describeModel(id, LOCAL_TTS_MODEL_CATALOG)),
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);
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if (provider === 'openai-compatible') {
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return { provider, available: true, models, ttsModels };
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}
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const model = models.find((entry) => entry.id === modelId) || null;
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if (model?.installed) {
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return { provider, available: true, activeModel: modelId, models, ttsModels };
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}
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if (model?.downloading) {
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return {
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provider,
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available: false,
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reasonCode: 'model_download_in_progress',
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activeModel: modelId,
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models,
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ttsModels,
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};
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}
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if (model?.downloadError) {
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return {
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provider,
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available: false,
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reasonCode: 'model_download_failed',
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error: model.downloadError,
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activeModel: modelId,
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models,
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ttsModels,
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};
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}
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return {
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provider,
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available: false,
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reasonCode: 'models_missing',
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activeModel: modelId,
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models,
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ttsModels,
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};
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};
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/**
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* Synthesize speech with the local TTS model. Returns WAV bytes, or a
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* readiness error while the model is missing/downloading.
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2026-08-30 02:24:11 +03:00
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*
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* With `language: 'auto'` the text's language decides the model: the
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* caller's model when it speaks that language, otherwise the catalog
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* model for it (downloaded on first use, reported as in-progress until it
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* lands). The caller's speaker id is kept only on the caller's model; a
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* substitute model starts from its own default speaker for the language.
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* A language no catalog model covers keeps the caller's model, so text is
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* never silently dropped.
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* `languageSample` is the whole message the chunk belongs to (or a prefix
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* of it): the language is judged on that, never on a short chunk alone.
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* @param {{ text: string, model?: string, speakerId?: number, speed?: number, language?: string, languageSample?: string }} options
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2026-07-04 02:48:07 +03:00
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*/
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const synthesizeSpeech = async ({ text, model, speakerId, speed, language, languageSample }) => {
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const requestedModelId = isLocalTtsModelId(model) ? model : DEFAULT_LOCAL_TTS_MODEL;
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let modelId = requestedModelId;
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let resolvedLanguage = null;
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if (language === 'auto') {
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resolvedLanguage = detectTextLanguage(languageSample || text).language;
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const forLanguage = resolveLocalTtsModelForLanguage(resolvedLanguage, requestedModelId);
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if (forLanguage && forLanguage !== requestedModelId) {
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modelId = forLanguage;
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speakerId = getLocalTtsDefaultSpeaker(modelId, resolvedLanguage);
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}
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}
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const installed = await isLocalSttModelInstalled(modelsDir, modelId);
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if (!installed) {
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const state = downloadStates.get(modelId);
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if (state === 'error') {
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const message = downloadErrors.get(modelId) || 'Model download failed';
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downloadStates.delete(modelId);
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return {
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error: `Failed to download TTS model: ${message}`,
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retryable: true,
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reasonCode: 'model_download_failed',
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};
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}
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void startModelDownload(modelId);
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return {
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error: 'TTS model is downloading',
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retryable: true,
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reasonCode: 'model_download_in_progress',
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};
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}
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const result = await workerClient.synthesizeSpeech({
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modelsDir,
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modelId,
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text,
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speakerId,
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speed,
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});
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return { audio: result.audio, format: result.format, modelId, language: resolvedLanguage };
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};
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/**
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* Kick off a background download for a model (used by the status route's
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* download action so Settings can pre-download models).
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*/
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const requestModelDownload = async (modelId) => {
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if (!isLocalModelId(modelId)) {
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return { ok: false, error: 'Unknown model id' };
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}
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if (await isLocalSttModelInstalled(modelsDir, modelId)) {
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return { ok: true, installed: true };
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}
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void startModelDownload(modelId);
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return { ok: true, installed: false };
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};
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/**
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* Delete an installed model from disk. A model that is mid-download cannot
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* be deleted. An engine already loaded in the worker keeps its in-memory
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* copy until the worker's idle shutdown; the files are simply re-downloaded
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* on the next use if the model is selected again.
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*/
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const deleteModel = async (modelId) => {
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if (!isLocalModelId(modelId)) {
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return { ok: false, error: 'Unknown model id' };
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}
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if (downloadStates.get(modelId) === 'downloading') {
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return { ok: false, error: 'Model is downloading' };
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}
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await rm(getLocalSttModelDir(modelsDir, modelId), { recursive: true, force: true });
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downloadErrors.delete(modelId);
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return { ok: true };
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};
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const shutdown = () => {
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workerClient.shutdown();
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};
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return {
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createSttSession,
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synthesizeSpeech,
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getStatus,
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requestModelDownload,
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deleteModel,
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shutdown,
|
|
|
|
|
};
|
|
|
|
|
}
|