2024-02-15 08:38:05 +07:00

219 lines
6.4 KiB
TypeScript

/**
* @file This file exports a class that implements the InferenceExtension interface from the @janhq/core package.
* The class provides methods for initializing and stopping a model, and for making inference requests.
* It also subscribes to events emitted by the @janhq/core package and handles new message requests.
* @version 1.0.0
* @module inference-nvidia-triton-trt-llm-extension/src/index
*/
import {
ChatCompletionRole,
ContentType,
MessageRequest,
MessageStatus,
ModelSettingParams,
ThreadContent,
ThreadMessage,
events,
fs,
Model,
BaseExtension,
MessageEvent,
ModelEvent,
} from '@janhq/core'
import { requestInference } from './helpers/sse'
import { ulid } from 'ulid'
import { join } from 'path'
import { EngineSettings } from './@types/global'
/**
* A class that implements the InferenceExtension interface from the @janhq/core package.
* The class provides methods for initializing and stopping a model, and for making inference requests.
* It also subscribes to events emitted by the @janhq/core package and handles new message requests.
*/
export default class JanInferenceTritonTrtLLMExtension extends BaseExtension {
private static readonly _homeDir = 'file://engines'
private static readonly _engineMetadataFileName = 'triton_trtllm.json'
static _currentModel: Model
static _engineSettings: EngineSettings = {
base_url: '',
}
controller = new AbortController()
isCancelled = false
/**
* Subscribes to events emitted by the @janhq/core package.
*/
async onLoad() {
if (!(await fs.existsSync(JanInferenceTritonTrtLLMExtension._homeDir)))
JanInferenceTritonTrtLLMExtension.writeDefaultEngineSettings()
// Events subscription
events.on(MessageEvent.OnMessageSent, (data) =>
JanInferenceTritonTrtLLMExtension.handleMessageRequest(data, this)
)
events.on(ModelEvent.OnModelInit, (model: Model) => {
JanInferenceTritonTrtLLMExtension.handleModelInit(model)
})
events.on(ModelEvent.OnModelStop, (model: Model) => {
JanInferenceTritonTrtLLMExtension.handleModelStop(model)
})
}
/**
* Stops the model inference.
*/
onUnload(): void {}
/**
* Initializes the model with the specified file name.
* @param {string} modelId - The ID of the model to initialize.
* @returns {Promise<void>} A promise that resolves when the model is initialized.
*/
async initModel(
modelId: string,
settings?: ModelSettingParams
): Promise<void> {
return
}
static async writeDefaultEngineSettings() {
try {
const engine_json = join(
JanInferenceTritonTrtLLMExtension._homeDir,
JanInferenceTritonTrtLLMExtension._engineMetadataFileName
)
if (await fs.existsSync(engine_json)) {
const engine = await fs.readFileSync(engine_json, 'utf-8')
JanInferenceTritonTrtLLMExtension._engineSettings =
typeof engine === 'object' ? engine : JSON.parse(engine)
} else {
await fs.writeFileSync(
engine_json,
JSON.stringify(
JanInferenceTritonTrtLLMExtension._engineSettings,
null,
2
)
)
}
} catch (err) {
console.error(err)
}
}
/**
* Stops the model.
* @returns {Promise<void>} A promise that resolves when the model is stopped.
*/
async stopModel(): Promise<void> {}
/**
* Stops streaming inference.
* @returns {Promise<void>} A promise that resolves when the streaming is stopped.
*/
async stopInference(): Promise<void> {
this.isCancelled = true
this.controller?.abort()
}
private static async handleModelInit(model: Model) {
if (model.engine !== 'triton_trtllm') {
return
} else {
JanInferenceTritonTrtLLMExtension._currentModel = model
JanInferenceTritonTrtLLMExtension.writeDefaultEngineSettings()
// Todo: Check model list with API key
events.emit(ModelEvent.OnModelReady, model)
}
}
private static async handleModelStop(model: Model) {
if (model.engine !== 'triton_trtllm') {
return
}
events.emit(ModelEvent.OnModelStopped, model)
}
/**
* Handles a new message request by making an inference request and emitting events.
* Function registered in event manager, should be static to avoid binding issues.
* Pass instance as a reference.
* @param {MessageRequest} data - The data for the new message request.
*/
private static async handleMessageRequest(
data: MessageRequest,
instance: JanInferenceTritonTrtLLMExtension
) {
if (data.model.engine !== 'triton_trtllm') {
return
}
const timestamp = Date.now()
const message: ThreadMessage = {
id: ulid(),
thread_id: data.threadId,
assistant_id: data.assistantId,
role: ChatCompletionRole.Assistant,
content: [],
status: MessageStatus.Pending,
created: timestamp,
updated: timestamp,
object: 'thread.message',
}
events.emit(MessageEvent.OnMessageResponse, message)
instance.isCancelled = false
instance.controller = new AbortController()
requestInference(
data?.messages ?? [],
this._engineSettings,
{
...JanInferenceTritonTrtLLMExtension._currentModel,
parameters: data.model.parameters,
},
instance.controller
).subscribe({
next: (content) => {
const messageContent: ThreadContent = {
type: ContentType.Text,
text: {
value: content.trim(),
annotations: [],
},
}
message.content = [messageContent]
events.emit(MessageEvent.OnMessageUpdate, message)
},
complete: async () => {
message.status = message.content.length
? MessageStatus.Ready
: MessageStatus.Error
events.emit(MessageEvent.OnMessageUpdate, message)
},
error: async (err) => {
if (instance.isCancelled || message.content.length) {
message.status = MessageStatus.Error
events.emit(MessageEvent.OnMessageUpdate, message)
return
}
const messageContent: ThreadContent = {
type: ContentType.Text,
text: {
value: 'Error occurred: ' + err.message,
annotations: [],
},
}
message.content = [messageContent]
message.status = MessageStatus.Ready
events.emit(MessageEvent.OnMessageUpdate, message)
},
})
}
}