111 lines
3.7 KiB
TypeScript
111 lines
3.7 KiB
TypeScript
import { BaseCache } from '@langchain/core/caches'
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import { VertexAI, VertexAIInput } from '@langchain/google-vertexai'
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import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
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import { getBaseClasses } from '../../../src/utils'
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import { getModels, MODEL_TYPE } from '../../../src/modelLoader'
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import { buildGoogleCredentials } from '../../../src/google-utils'
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class GoogleVertexAI_LLMs implements INode {
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label: string
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name: string
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version: number
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type: string
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icon: string
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category: string
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description: string
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baseClasses: string[]
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credential: INodeParams
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inputs: INodeParams[]
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constructor() {
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this.label = 'GoogleVertexAI'
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this.name = 'googlevertexai'
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this.version = 3.0
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this.type = 'GoogleVertexAI'
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this.icon = 'GoogleVertex.svg'
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this.category = 'LLMs'
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this.description = 'Wrapper around GoogleVertexAI large language models'
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this.baseClasses = [this.type, ...getBaseClasses(VertexAI)]
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this.credential = {
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label: 'Connect Credential',
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name: 'credential',
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type: 'credential',
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credentialNames: ['googleVertexAuth'],
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optional: true,
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description:
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'Google Vertex AI credential. If you are using a GCP service like Cloud Run, or if you have installed default credentials on your local machine, you do not need to set this credential.'
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}
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this.inputs = [
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{
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label: 'Cache',
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name: 'cache',
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type: 'BaseCache',
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optional: true
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},
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{
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label: 'Model Name',
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name: 'modelName',
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type: 'asyncOptions',
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loadMethod: 'listModels',
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default: 'text-bison'
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},
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{
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label: 'Temperature',
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name: 'temperature',
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type: 'number',
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step: 0.1,
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default: 0.7,
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optional: true
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},
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{
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label: 'max Output Tokens',
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name: 'maxOutputTokens',
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type: 'number',
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step: 1,
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optional: true,
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additionalParams: true
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},
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{
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label: 'Top Probability',
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name: 'topP',
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type: 'number',
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step: 0.1,
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optional: true,
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additionalParams: true
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}
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]
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}
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//@ts-ignore
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loadMethods = {
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async listModels(): Promise<INodeOptionsValue[]> {
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return await getModels(MODEL_TYPE.LLM, 'googlevertexai')
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}
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}
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async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
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const temperature = nodeData.inputs?.temperature as string
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const modelName = nodeData.inputs?.modelName as string
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const maxOutputTokens = nodeData.inputs?.maxOutputTokens as string
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const topP = nodeData.inputs?.topP as string
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const cache = nodeData.inputs?.cache as BaseCache
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const obj: Partial<VertexAIInput> = {
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temperature: parseFloat(temperature),
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model: modelName
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}
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const authOptions = await buildGoogleCredentials(nodeData, options)
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if (authOptions && Object.keys(authOptions).length !== 0) obj.authOptions = authOptions
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if (maxOutputTokens) obj.maxOutputTokens = parseInt(maxOutputTokens, 10)
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if (topP) obj.topP = parseFloat(topP)
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if (cache) obj.cache = cache
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const model = new VertexAI(obj)
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return model
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}
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}
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module.exports = { nodeClass: GoogleVertexAI_LLMs }
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