200 lines
5.4 KiB
TypeScript
200 lines
5.4 KiB
TypeScript
/**
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* @module tensorrt-llm-extension/src/index
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*/
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import {
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Compatibility,
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DownloadEvent,
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DownloadRequest,
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DownloadState,
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GpuSetting,
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InstallationState,
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Model,
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baseName,
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downloadFile,
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events,
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executeOnMain,
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joinPath,
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showToast,
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systemInformation,
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LocalOAIEngine,
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fs,
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MessageRequest,
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ModelEvent,
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getJanDataFolderPath,
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SystemInformation,
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ModelFile,
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} from '@janhq/core'
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/**
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* TensorRTLLMExtension - Implementation of LocalOAIEngine
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* @extends BaseOAILocalInferenceProvider
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* Provide pre-populated models for TensorRTLLM
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*/
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export default class TensorRTLLMExtension extends LocalOAIEngine {
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/**
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* Override custom function name for loading and unloading model
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* Which are implemented from node module
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*/
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override provider = PROVIDER
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override inferenceUrl = INFERENCE_URL
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override nodeModule = NODE
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private supportedGpuArch = ['ampere', 'ada']
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override compatibility() {
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return COMPATIBILITY as unknown as Compatibility
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}
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override async onLoad(): Promise<void> {
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super.onLoad()
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if ((await this.installationState()) === 'Installed') {
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const models = MODELS as unknown as Model[]
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this.registerModels(models)
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}
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}
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override async install(): Promise<void> {
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await this.removePopulatedModels()
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const info = await systemInformation()
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if (!this.isCompatible(info)) return
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const janDataFolderPath = await getJanDataFolderPath()
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const engineVersion = TENSORRT_VERSION
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const executableFolderPath = await joinPath([
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janDataFolderPath,
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'engines',
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this.provider,
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engineVersion,
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info.gpuSetting?.gpus[0].arch,
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])
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if (!(await fs.existsSync(executableFolderPath))) {
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await fs.mkdir(executableFolderPath)
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}
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const placeholderUrl = DOWNLOAD_RUNNER_URL
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const tensorrtVersion = TENSORRT_VERSION
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const url = placeholderUrl
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.replace(/<version>/g, tensorrtVersion)
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.replace(/<gpuarch>/g, info.gpuSetting!.gpus[0]!.arch!)
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const tarball = await baseName(url)
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const tarballFullPath = await joinPath([executableFolderPath, tarball])
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const downloadRequest: DownloadRequest = {
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url,
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localPath: tarballFullPath,
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extensionId: this.name,
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downloadType: 'extension',
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}
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downloadFile(downloadRequest)
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const onFileDownloadSuccess = async (state: DownloadState) => {
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// if other download, ignore
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if (state.fileName !== tarball) return
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events.off(DownloadEvent.onFileDownloadSuccess, onFileDownloadSuccess)
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await executeOnMain(
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this.nodeModule,
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'decompressRunner',
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tarballFullPath,
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executableFolderPath
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)
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events.emit(DownloadEvent.onFileUnzipSuccess, state)
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// Prepopulate models as soon as it's ready
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const models = MODELS as unknown as Model[]
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this.registerModels(models).then(() => {
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showToast(
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'Extension installed successfully.',
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'New models are added to Model Hub.'
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)
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})
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}
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events.on(DownloadEvent.onFileDownloadSuccess, onFileDownloadSuccess)
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}
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private async removePopulatedModels(): Promise<void> {
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const models = MODELS as unknown as Model[]
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console.debug(`removePopulatedModels`, JSON.stringify(models))
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const janDataFolderPath = await getJanDataFolderPath()
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const modelFolderPath = await joinPath([janDataFolderPath, 'models'])
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for (const model of models) {
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const modelPath = await joinPath([modelFolderPath, model.id])
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try {
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await fs.rm(modelPath)
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} catch (err) {
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console.error(`Error removing model ${modelPath}`, err)
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}
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}
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events.emit(ModelEvent.OnModelsUpdate, {})
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}
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override async loadModel(model: ModelFile): Promise<void> {
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if ((await this.installationState()) === 'Installed')
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return super.loadModel(model)
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throw new Error('EXTENSION_IS_NOT_INSTALLED::TensorRT-LLM extension')
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}
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override async installationState(): Promise<InstallationState> {
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const info = await systemInformation()
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if (!this.isCompatible(info)) return 'NotCompatible'
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const firstGpu = info.gpuSetting?.gpus[0]
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const janDataFolderPath = await getJanDataFolderPath()
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const engineVersion = TENSORRT_VERSION
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const enginePath = await joinPath([
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janDataFolderPath,
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'engines',
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this.provider,
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engineVersion,
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firstGpu.arch,
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info.osInfo.platform === 'win32' ? 'nitro.exe' : 'nitro',
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])
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// For now, we just check the executable of nitro x tensor rt
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return (await fs.existsSync(enginePath)) ? 'Installed' : 'NotInstalled'
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}
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override stopInference() {
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if (!this.loadedModel) return
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showToast(
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'Unable to Stop Inference',
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'The model does not support stopping inference.'
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)
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return Promise.resolve()
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}
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override async inference(data: MessageRequest) {
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if (!this.loadedModel) return
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// TensorRT LLM Extension supports streaming only
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if (data.model) data.model.parameters.stream = true
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super.inference(data)
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}
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isCompatible(info: SystemInformation): info is Required<SystemInformation> & {
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gpuSetting: { gpus: { arch: string }[] }
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} {
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const firstGpu = info.gpuSetting?.gpus[0]
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return (
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!!info.osInfo &&
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!!info.gpuSetting &&
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!!firstGpu &&
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info.gpuSetting.gpus.length > 0 &&
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this.compatibility().platform.includes(info.osInfo.platform) &&
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!!firstGpu.arch &&
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firstGpu.name.toLowerCase().includes('nvidia') &&
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this.supportedGpuArch.includes(firstGpu.arch)
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)
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}
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}
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