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openchamber/packages/web/server/lib/dictation/local/model-catalog.js
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/**
* Catalog of local sherpa-onnx STT models available for dictation.
* Models are downloaded on demand from the k2-fsa GitHub releases and
* extracted under the OpenChamber speech-models directory.
*
* `type` selects the recognizer construction path in the worker:
* - 'nemo_transducer': encoder/decoder/joiner transducer (Parakeet)
* - 'whisper': encoder/decoder Whisper export
* `files` maps logical roles to file names inside the extracted directory.
*/
import path from 'path';
export const LOCAL_STT_MODEL_CATALOG = {
'parakeet-tdt-0.6b-v2-int8': {
type: 'nemo_transducer',
archiveUrl:
'https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2',
extractedDir: 'sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8',
files: {
encoder: 'encoder.int8.onnx',
decoder: 'decoder.int8.onnx',
joiner: 'joiner.int8.onnx',
tokens: 'tokens.txt',
},
description: 'NVIDIA Parakeet TDT v2 (English)',
},
'parakeet-tdt-0.6b-v3-int8': {
type: 'nemo_transducer',
archiveUrl:
'https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8.tar.bz2',
extractedDir: 'sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8',
files: {
encoder: 'encoder.int8.onnx',
decoder: 'decoder.int8.onnx',
joiner: 'joiner.int8.onnx',
tokens: 'tokens.txt',
},
description: 'NVIDIA Parakeet TDT v3 (25 European languages, auto-detected)',
},
'whisper-base-int8': {
type: 'whisper',
archiveUrl:
'https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-base.tar.bz2',
extractedDir: 'sherpa-onnx-whisper-base',
files: {
encoder: 'base-encoder.int8.onnx',
decoder: 'base-decoder.int8.onnx',
tokens: 'base-tokens.txt',
},
description: 'OpenAI Whisper base (multilingual, smaller and lighter)',
},
'whisper-tiny-int8': {
type: 'whisper',
archiveUrl:
'https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-whisper-tiny.tar.bz2',
extractedDir: 'sherpa-onnx-whisper-tiny',
files: {
encoder: 'tiny-encoder.int8.onnx',
decoder: 'tiny-decoder.int8.onnx',
tokens: 'tiny-tokens.txt',
},
description: 'OpenAI Whisper tiny (multilingual, fastest and lightest)',
},
};
/**
* Local text-to-speech models (sherpa-onnx OfflineTts). Downloaded and
* managed through the same pipeline as the STT models.
*/
export const LOCAL_TTS_MODEL_CATALOG = {
'kokoro-en-v0_19': {
type: 'kokoro',
archiveUrl:
'https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/kokoro-en-v0_19.tar.bz2',
extractedDir: 'kokoro-en-v0_19',
files: {
model: 'model.onnx',
voices: 'voices.bin',
tokens: 'tokens.txt',
espeakData: 'espeak-ng-data',
},
description: 'Kokoro TTS (English, natural voices)',
},
};
export const DEFAULT_LOCAL_STT_MODEL = 'parakeet-tdt-0.6b-v2-int8';
export const DEFAULT_LOCAL_TTS_MODEL = 'kokoro-en-v0_19';
export const LOCAL_STT_MODEL_IDS = Object.keys(LOCAL_STT_MODEL_CATALOG);
export const LOCAL_TTS_MODEL_IDS = Object.keys(LOCAL_TTS_MODEL_CATALOG);
/**
* @param {string} modelId
* @returns {boolean}
*/
export function isLocalSttModelId(modelId) {
return typeof modelId === 'string' && Object.hasOwn(LOCAL_STT_MODEL_CATALOG, modelId);
}
/**
* @param {string} modelId
* @returns {boolean}
*/
export function isLocalTtsModelId(modelId) {
return typeof modelId === 'string' && Object.hasOwn(LOCAL_TTS_MODEL_CATALOG, modelId);
}
/**
* Any managed local model (STT or TTS).
* @param {string} modelId
* @returns {boolean}
*/
export function isLocalModelId(modelId) {
return isLocalSttModelId(modelId) || isLocalTtsModelId(modelId);
}
/**
* Spec lookup across both catalogs (STT and TTS).
* @param {string} modelId
*/
export function getLocalSttModelSpec(modelId) {
const spec = LOCAL_STT_MODEL_CATALOG[modelId] ?? LOCAL_TTS_MODEL_CATALOG[modelId];
if (!spec) {
throw new Error(`Unknown local speech model id: ${modelId}`);
}
return {
id: modelId,
...spec,
requiredFiles: Object.values(spec.files),
};
}
/**
* @param {string} modelsDir
* @param {string} modelId
* @returns {string}
*/
export function getLocalSttModelDir(modelsDir, modelId) {
return path.join(modelsDir, getLocalSttModelSpec(modelId).extractedDir);
}