/* eslint-disable n8n-nodes-base/node-dirname-against-convention */ import { NodeConnectionType, type INodeType, type INodeTypeDescription, type SupplyData, type ISupplyDataFunctions, type INodeProperties, } from 'n8n-workflow'; import type { ClientOptions } from 'openai'; import { OpenAIEmbeddings } from '@langchain/openai'; import { logWrapper } from '../../../utils/logWrapper'; import { getConnectionHintNoticeField } from '../../../utils/sharedFields'; const modelParameter: INodeProperties = { displayName: 'Model', name: 'model', type: 'options', description: 'The model which will generate the embeddings. Learn more.', typeOptions: { loadOptions: { routing: { request: { method: 'GET', url: '={{ $parameter.options?.baseURL?.split("/").slice(-1).pop() || "v1" }}/models', }, output: { postReceive: [ { type: 'rootProperty', properties: { property: 'data', }, }, { type: 'filter', properties: { pass: "={{ $responseItem.id.includes('embed') }}", }, }, { type: 'setKeyValue', properties: { name: '={{$responseItem.id}}', value: '={{$responseItem.id}}', }, }, { type: 'sort', properties: { key: 'name', }, }, ], }, }, }, }, routing: { send: { type: 'body', property: 'model', }, }, default: 'text-embedding-3-small', }; export class EmbeddingsOpenAi implements INodeType { description: INodeTypeDescription = { displayName: 'Embeddings OpenAI', name: 'embeddingsOpenAi', icon: { light: 'file:openAiLight.svg', dark: 'file:openAiLight.dark.svg' }, credentials: [ { name: 'openAiApi', required: true, }, ], group: ['transform'], version: [1, 1.1], description: 'Use Embeddings OpenAI', defaults: { name: 'Embeddings OpenAI', }, codex: { categories: ['AI'], subcategories: { AI: ['Embeddings'], }, resources: { primaryDocumentation: [ { url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingsopenai/', }, ], }, }, // eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node inputs: [], // eslint-disable-next-line n8n-nodes-base/node-class-description-outputs-wrong outputs: [NodeConnectionType.AiEmbedding], outputNames: ['Embeddings'], requestDefaults: { ignoreHttpStatusErrors: true, baseURL: '={{ $parameter.options?.baseURL?.split("/").slice(0,-1).join("/") || "https://api.openai.com" }}', }, properties: [ getConnectionHintNoticeField([NodeConnectionType.AiVectorStore]), { ...modelParameter, default: 'text-embedding-ada-002', displayOptions: { show: { '@version': [1], }, }, }, { ...modelParameter, displayOptions: { hide: { '@version': [1], }, }, }, { displayName: 'Options', name: 'options', placeholder: 'Add Option', description: 'Additional options to add', type: 'collection', default: {}, options: [ { displayName: 'Base URL', name: 'baseURL', default: 'https://api.openai.com/v1', description: 'Override the default base URL for the API', type: 'string', }, { displayName: 'Batch Size', name: 'batchSize', default: 512, typeOptions: { maxValue: 2048 }, description: 'Maximum number of documents to send in each request', type: 'number', }, { displayName: 'Strip New Lines', name: 'stripNewLines', default: true, description: 'Whether to strip new lines from the input text', type: 'boolean', }, { displayName: 'Timeout', name: 'timeout', default: -1, description: 'Maximum amount of time a request is allowed to take in seconds. Set to -1 for no timeout.', type: 'number', }, ], }, ], }; async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise { this.logger.debug('Supply data for embeddings'); const credentials = await this.getCredentials('openAiApi'); const options = this.getNodeParameter('options', itemIndex, {}) as { baseURL?: string; batchSize?: number; stripNewLines?: boolean; timeout?: number; }; if (options.timeout === -1) { options.timeout = undefined; } const configuration: ClientOptions = {}; if (options.baseURL) { configuration.baseURL = options.baseURL; } const embeddings = new OpenAIEmbeddings( { modelName: this.getNodeParameter('model', itemIndex, 'text-embedding-3-small') as string, openAIApiKey: credentials.apiKey as string, ...options, }, configuration, ); return { response: logWrapper(embeddings, this), }; } }