174 lines
6.1 KiB
TypeScript
174 lines
6.1 KiB
TypeScript
import { AzureOpenAIInput, OpenAI, OpenAIInput } from '@langchain/openai'
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import { BaseCache } from '@langchain/core/caches'
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import { BaseLLMParams } from '@langchain/core/language_models/llms'
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import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { getModels, MODEL_TYPE } from '../../../src/modelLoader'
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const serverCredentialsExists =
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!!process.env.AZURE_OPENAI_API_KEY &&
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!!process.env.AZURE_OPENAI_API_INSTANCE_NAME &&
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!!process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME &&
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!!process.env.AZURE_OPENAI_API_VERSION
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class AzureOpenAI_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 = 'Azure OpenAI'
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this.name = 'azureOpenAI'
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this.version = 4.0
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this.type = 'AzureOpenAI'
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this.icon = 'Azure.svg'
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this.category = 'LLMs'
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this.description = 'Wrapper around Azure OpenAI large language models'
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this.baseClasses = [this.type, ...getBaseClasses(OpenAI)]
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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: ['azureOpenAIApi'],
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optional: serverCredentialsExists
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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-davinci-003'
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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: 'Max Tokens',
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name: 'maxTokens',
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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: 'Best Of',
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name: 'bestOf',
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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: 'Frequency Penalty',
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name: 'frequencyPenalty',
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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: 'Presence Penalty',
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name: 'presencePenalty',
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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: 'Timeout',
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name: 'timeout',
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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: 'BasePath',
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name: 'basepath',
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type: 'string',
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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, 'azureOpenAI')
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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 maxTokens = nodeData.inputs?.maxTokens as string
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const topP = nodeData.inputs?.topP as string
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const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
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const presencePenalty = nodeData.inputs?.presencePenalty as string
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const timeout = nodeData.inputs?.timeout as string
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const bestOf = nodeData.inputs?.bestOf as string
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const streaming = nodeData.inputs?.streaming as boolean
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const basePath = nodeData.inputs?.basepath as string
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const azureOpenAIApiKey = getCredentialParam('azureOpenAIApiKey', credentialData, nodeData)
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const azureOpenAIApiInstanceName = getCredentialParam('azureOpenAIApiInstanceName', credentialData, nodeData)
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const azureOpenAIApiDeploymentName = getCredentialParam('azureOpenAIApiDeploymentName', credentialData, nodeData)
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const azureOpenAIApiVersion = getCredentialParam('azureOpenAIApiVersion', credentialData, nodeData)
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const cache = nodeData.inputs?.cache as BaseCache
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const obj: Partial<AzureOpenAIInput> & BaseLLMParams & Partial<OpenAIInput> = {
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temperature: parseFloat(temperature),
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modelName,
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azureOpenAIApiKey,
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azureOpenAIApiInstanceName,
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azureOpenAIApiDeploymentName,
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azureOpenAIApiVersion,
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streaming: streaming ?? true
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}
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if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
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if (topP) obj.topP = parseFloat(topP)
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if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
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if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
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if (timeout) obj.timeout = parseInt(timeout, 10)
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if (bestOf) obj.bestOf = parseInt(bestOf, 10)
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if (cache) obj.cache = cache
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if (basePath) obj.azureOpenAIBasePath = basePath
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const model = new OpenAI(obj)
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return model
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}
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}
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module.exports = { nodeClass: AzureOpenAI_LLMs }
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