248 lines
9.2 KiB
TypeScript
248 lines
9.2 KiB
TypeScript
import { BaseCache } from '@langchain/core/caches'
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import { ChatVertexAIInput, ChatVertexAI as LcChatVertexAI } from '@langchain/google-vertexai'
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import {
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ICommonObject,
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IMultiModalOption,
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INode,
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INodeData,
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INodeOptionsValue,
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INodeParams,
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IVisionChatModal
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} from '../../../src/Interface'
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import { getModels, getRegions, MODEL_TYPE } from '../../../src/modelLoader'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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const DEFAULT_IMAGE_MAX_TOKEN = 8192
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const DEFAULT_IMAGE_MODEL = 'gemini-1.5-flash-latest'
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class ChatVertexAI extends LcChatVertexAI implements IVisionChatModal {
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configuredModel: string
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configuredMaxToken: number
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multiModalOption: IMultiModalOption
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id: string
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constructor(id: string, fields?: ChatVertexAIInput) {
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// @ts-ignore
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if (fields?.model) {
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fields.modelName = fields.model
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delete fields.model
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}
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super(fields ?? {})
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this.id = id
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this.configuredModel = fields?.modelName || ''
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this.configuredMaxToken = fields?.maxOutputTokens ?? 2048
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}
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revertToOriginalModel(): void {
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this.modelName = this.configuredModel
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this.maxOutputTokens = this.configuredMaxToken
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}
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setMultiModalOption(multiModalOption: IMultiModalOption): void {
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this.multiModalOption = multiModalOption
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}
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setVisionModel(): void {
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if (!this.modelName.startsWith('claude-3')) {
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this.modelName = DEFAULT_IMAGE_MODEL
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this.maxOutputTokens = this.configuredMaxToken ? this.configuredMaxToken : DEFAULT_IMAGE_MAX_TOKEN
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}
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}
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}
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class GoogleVertexAI_ChatModels 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 = 'ChatGoogleVertexAI'
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this.name = 'chatGoogleVertexAI'
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this.version = 5.3
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this.type = 'ChatGoogleVertexAI'
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this.icon = 'GoogleVertex.svg'
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this.category = 'Chat Models'
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this.description = 'Wrapper around VertexAI large language models that use the Chat endpoint'
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this.baseClasses = [this.type, ...getBaseClasses(ChatVertexAI)]
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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: 'Region',
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description: 'Region to use for the model.',
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name: 'region',
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type: 'asyncOptions',
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loadMethod: 'listRegions',
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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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},
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{
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label: 'Custom Model Name',
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name: 'customModelName',
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type: 'string',
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placeholder: 'gemini-1.5-pro-exp-0801',
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description: 'Custom model name to use. If provided, it will override the model selected',
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additionalParams: true,
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optional: true
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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: 0.9,
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optional: true
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},
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{
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label: 'Allow Image Uploads',
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name: 'allowImageUploads',
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type: 'boolean',
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description:
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'Allow image input. Refer to the <a href="https://docs.flowiseai.com/using-flowise/uploads#image" target="_blank">docs</a> for more details.',
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default: false,
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optional: true
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},
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{
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label: 'Streaming',
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name: 'streaming',
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type: 'boolean',
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default: true,
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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: '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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label: 'Top Next Highest Probability Tokens',
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name: 'topK',
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type: 'number',
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description: `Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive`,
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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: 'Thinking Budget',
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name: 'thinkingBudget',
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type: 'number',
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description: 'Number of tokens to use for thinking process (0 to disable)',
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step: 1,
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placeholder: '1024',
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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.CHAT, 'chatGoogleVertexAI')
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},
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async listRegions(): Promise<INodeOptionsValue[]> {
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return await getRegions(MODEL_TYPE.CHAT, 'chatGoogleVertexAI')
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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 credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const googleApplicationCredentialFilePath = getCredentialParam('googleApplicationCredentialFilePath', credentialData, nodeData)
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const googleApplicationCredential = getCredentialParam('googleApplicationCredential', credentialData, nodeData)
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const projectID = getCredentialParam('projectID', credentialData, nodeData)
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const authOptions: ICommonObject = {}
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if (Object.keys(credentialData).length !== 0) {
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if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
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throw new Error('Please specify your Google Application Credential')
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if (!googleApplicationCredentialFilePath && !googleApplicationCredential)
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throw new Error(
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'Error: More than one component has been inputted. Please use only one of the following: Google Application Credential File Path or Google Credential JSON Object'
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)
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if (googleApplicationCredentialFilePath && !googleApplicationCredential)
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authOptions.keyFile = googleApplicationCredentialFilePath
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else if (!googleApplicationCredentialFilePath && googleApplicationCredential)
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authOptions.credentials = JSON.parse(googleApplicationCredential)
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if (projectID) authOptions.projectId = projectID
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}
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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 customModelName = nodeData.inputs?.customModelName 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 topK = nodeData.inputs?.topK as string
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const streaming = nodeData.inputs?.streaming as boolean
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const thinkingBudget = nodeData.inputs?.thinkingBudget as string
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const region = nodeData.inputs?.region as string
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const allowImageUploads = nodeData.inputs?.allowImageUploads as boolean
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const multiModalOption: IMultiModalOption = {
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image: {
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allowImageUploads: allowImageUploads ?? false
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}
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}
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const obj: ChatVertexAIInput = {
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temperature: parseFloat(temperature),
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modelName: customModelName || modelName,
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streaming: streaming ?? true
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}
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if (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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if (topK) obj.topK = parseFloat(topK)
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if (thinkingBudget) obj.thinkingBudget = parseInt(thinkingBudget, 10)
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if (region) obj.location = region
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const model = new ChatVertexAI(nodeData.id, obj)
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model.setMultiModalOption(multiModalOption)
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return model
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}
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}
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module.exports = { nodeClass: GoogleVertexAI_ChatModels }
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