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/* eslint-disable no-restricted-globals */
import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@latest'
import { KokoroTTS } from 'https://cdn.jsdelivr.net/npm/kokoro-js@1.2.1/dist/kokoro.web.js'
class MyTextToSpeechPipeline {
static task = 'text-to-speech'
static instance = null
static async getInstance(model, dtype = 'fp32', progress_callback = null) {
try {
// Try WebGPU first
this.instance = await pipeline(this.task, model, {
dtype,
device: 'webgpu',
progress_callback,
quantized: false
})
return this.instance
} catch (webgpuError) {
// Fallback to WASM if WebGPU fails
if (progress_callback) {
progress_callback({
status: 'fallback',
message: 'WebGPU failed, falling back to WASM'
})
}
try {
this.instance = await pipeline(this.task, model, {
dtype,
device: 'wasm',
progress_callback,
quantized: false
})
return this.instance
} catch (wasmError) {
throw new Error(
`Both WebGPU and WASM failed. WebGPU error: ${webgpuError.message}. WASM error: ${wasmError.message}`
)
}
}
}
}
class MyKokoroTTSPipeline {
static instance = null
static async getInstance(model, dtype = 'fp32', progress_callback = null) {
try {
const device = 'webgpu'
if (progress_callback) {
progress_callback({
status: 'loading',
message: `Loading Kokoro TTS model with ${device} device`
})
}
this.instance = await KokoroTTS.from_pretrained(model, {
dtype,
device,
progress_callback: progress_callback
? (data) => {
progress_callback({
status: 'loading',
...data
})
}
: null
})
return this.instance
} catch (webgpuError) {
// Fallback to WASM if WebGPU fails
if (progress_callback) {
progress_callback({
status: 'fallback',
message: 'WebGPU failed, falling back to WASM'
})
}
try {
this.instance = await KokoroTTS.from_pretrained(model, {
dtype,
device: 'wasm',
progress_callback: progress_callback
? (data) => {
progress_callback({
status: 'loading',
...data
})
}
: null
})
return this.instance
} catch (wasmError) {
throw new Error(
`Both WebGPU and WASM failed for Kokoro TTS. WebGPU error: ${webgpuError.message}. WASM error: ${wasmError.message}`
)
}
}
}
}
self.addEventListener('message', async (event) => {
try {
const { type, model, dtype, text, isStyleTTS2, config } = event.data
if (!model) {
self.postMessage({
status: 'error',
output: 'No model provided'
})
return
}
let synthesizer
if (isStyleTTS2) {
// Use Kokoro TTS for StyleTTS2 models
synthesizer = await MyKokoroTTSPipeline.getInstance(
model,
dtype || 'q8',
(x) => {
self.postMessage({ status: 'loading', output: x })
}
)
} else {
// Use standard transformers pipeline
synthesizer = await MyTextToSpeechPipeline.getInstance(
model,
dtype || 'fp32',
(x) => {
self.postMessage({ status: 'loading', output: x })
}
)
}
if (type === 'load') {
self.postMessage({
status: 'ready',
output: `Model ${model}${isStyleTTS2 ? ' StyleTTS2' : ''}, dtype ${dtype} loaded`
})
return
}
if (type === 'synthesize') {
if (!text || typeof text !== 'string' || text.trim() === '') {
self.postMessage({
status: 'error',
output: 'No text provided for synthesis'
})
return
}
try {
let output
if (isStyleTTS2) {
const options = {}
options.voice = config.voice
const audioResult = await synthesizer.generate(text.trim(), options)
output = {
audio: Array.from(audioResult.audio),
sampling_rate: audioResult.sampling_rate || 24000 // Default for Kokoro
}
} else {
const options = {}
if (config?.speakerEmbeddings) {
try {
const response = await fetch(config.speakerEmbeddings)
if (response.ok) {
const embeddings = await response.arrayBuffer()
options.speaker_embeddings = new Float32Array(embeddings)
}
} catch (error) {
console.warn('Failed to load speaker embeddings:', error)
}
}
const result = await synthesizer(text.trim(), options)
output = {
audio: Array.from(result.audio),
sampling_rate: result.sampling_rate
}
}
self.postMessage({
status: 'output',
output
})
self.postMessage({ status: 'ready' })
} catch (error) {
throw error
}
}
} catch (error) {
self.postMessage({
status: 'error',
output:
error.message || 'An error occurred during text-to-speech synthesis'
})
}
})
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