Added Google PaLM chat model
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Martin Andrews
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import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { ChatGooglePaLM, GooglePaLMChatInput } from 'langchain/chat_models/googlepalm'
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class ChatGooglePaLM_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 = 'ChatGooglePaLM'
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this.name = 'chatGooglePaLM'
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this.version = 1.0
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this.type = 'ChatGooglePaLM'
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this.icon = 'Google_PaLM_Logo.svg'
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this.category = 'Chat Models'
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this.description = 'Wrapper around Google MakerSuite PaLM large language models using the Chat endpoint'
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this.baseClasses = [this.type, ...getBaseClasses(ChatGooglePaLM)]
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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: ['googleMakerSuite']
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}
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this.inputs = [
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{
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label: 'Model Name',
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name: 'modelName',
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type: 'options',
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options: [
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{
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label: 'models/chat-bison-001',
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name: 'models/chat-bison-001'
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}
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],
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default: 'models/chat-bison-001',
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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: 0.7,
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optional: true,
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description:
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'Controls the randomness of the output.\n' +
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'Values can range from [0.0,1.0], inclusive. A value closer to 1.0 ' +
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'will produce responses that are more varied and creative, while ' +
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'a value closer to 0.0 will typically result in more straightforward ' +
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'responses from the model.'
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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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description:
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'Top-p changes how the model selects tokens for output.\n' +
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'Tokens are selected from most probable to least until ' +
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'the sum of their probabilities equals the top-p value.\n' +
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'For example, if tokens A, B, and C have a probability of .3, .2, and .1 ' +
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'and the top-p value is .5, then the model will select either A or B ' +
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'as the next token (using temperature).'
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},
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{
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label: 'Top-k',
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name: 'topK',
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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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description:
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'Top-k changes how the model selects tokens for output.\n' +
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'A top-k of 1 means the selected token is the most probable among ' +
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'all tokens in the model vocabulary (also called greedy decoding), ' +
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'while a top-k of 3 means that the next token is selected from ' +
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'among the 3 most probable tokens (using temperature).'
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}
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/*
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{
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label: 'Examples',
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name: 'examplesObj',
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type: 'json',
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optional: true,
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additionalParams: true
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//default: { list:[] },
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//description:
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// 'The "examples" field should contain a list of pairs of strings to use as prior turns for this conversation.'
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}
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*/
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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 modelName = nodeData.inputs?.modelName as string
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const temperature = nodeData.inputs?.temperature as string
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const topP = nodeData.inputs?.topP as string
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const topK = nodeData.inputs?.topK as string
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//const examplesObj = nodeData.inputs?.examplesObj
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const googleMakerSuiteKey = getCredentialParam('googleMakerSuiteKey', credentialData, nodeData)
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const obj: Partial<GooglePaLMChatInput> = {
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modelName: modelName,
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temperature: parseFloat(temperature),
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apiKey: googleMakerSuiteKey
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}
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if (topP) obj.topP = parseFloat(topP)
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if (topK) obj.topK = parseFloat(topK)
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/*
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let parsedExamples: any | undefined = undefined
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if (examplesObj) {
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try {
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parsedExamples = typeof examplseObj === 'object' ? examplseObj : JSON.parse(examplseObj)
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obj.examples = parsedExamples.examples || []
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} catch (exception) {
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throw new Error("Invalid JSON in the GooglePaLM's examplseObj: " + exception)
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}
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}
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*/
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const model = new ChatGooglePaLM(obj)
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return model
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}
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}
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module.exports = { nodeClass: ChatGooglePaLM_ChatModels }
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