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/* eslint-disable no-restricted-globals */
import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@latest'
class MyTextGenerationPipeline {
static task = 'text-generation'
static instance = null
static currentGeneration = 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
})
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
})
return this.instance
} catch (wasmError) {
throw new Error(
`Both WebGPU and WASM failed. WebGPU error: ${webgpuError.message}. WASM error: ${wasmError.message}`
)
}
}
}
static stopGeneration() {
if (this.currentGeneration) {
this.currentGeneration.abort()
this.currentGeneration = null
}
}
}
// Listen for messages from the main thread
self.addEventListener('message', async (event) => {
try {
const { type, model, dtype, messages, prompt, hasChatTemplate, config } =
event.data
if (type === 'stop') {
MyTextGenerationPipeline.stopGeneration()
self.postMessage({ status: 'ready' })
return
}
if (!model) {
self.postMessage({
status: 'error',
output: 'No model provided'
})
return
}
// Retrieve the pipeline. This will download the model if not already cached.
const generator = await MyTextGenerationPipeline.getInstance(
model,
dtype,
(x) => {
self.postMessage({ status: 'loading', output: x })
}
)
if (type === 'load') {
self.postMessage({
status: 'ready',
output: `Model ${model}, dtype ${dtype} loaded`
})
return
}
if (type === 'generate') {
let inputText = ''
if (hasChatTemplate && messages && messages.length > 0) {
inputText = messages
} else if (!hasChatTemplate && prompt) {
inputText = prompt
} else {
self.postMessage({ status: 'ready' })
return
}
const options = {
max_new_tokens: config.max_new_tokens || 100,
temperature: config.temperature || 0.7,
do_sample: config.do_sample !== false,
...(config.top_p && { top_p }),
...(config.top_k && { top_k })
}
// Create an AbortController for this generation
const abortController = new AbortController()
MyTextGenerationPipeline.currentGeneration = abortController
try {
const output = await generator(inputText, {
...options,
signal: abortController.signal
})
if (hasChatTemplate) {
// For chat mode, extract only the assistant's response
self.postMessage({
status: 'output',
output: output[0].generated_text.slice(-1)[0]
})
} else {
self.postMessage({
status: 'output',
output: {
role: 'assistant',
content: output[0].generated_text
}
})
}
self.postMessage({ status: 'ready' })
} catch (error) {
if (error.name === 'AbortError') {
self.postMessage({ status: 'ready' })
} else {
throw error
}
} finally {
MyTextGenerationPipeline.currentGeneration = null
}
}
} catch (error) {
self.postMessage({
status: 'error',
output: error.message || 'An error occurred during text generation'
})
}
})
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