/* eslint-disable n8n-nodes-base/node-dirname-against-convention */ import { NodeConnectionType, type INodeType, type INodeTypeDescription, type ISupplyDataFunctions, type SupplyData, } from 'n8n-workflow'; import { CohereEmbeddings } from '@langchain/cohere'; import { logWrapper } from '../../../utils/logWrapper'; import { getConnectionHintNoticeField } from '../../../utils/sharedFields'; export class EmbeddingsCohere implements INodeType { description: INodeTypeDescription = { displayName: 'Embeddings Cohere', name: 'embeddingsCohere', icon: { light: 'file:cohere.svg', dark: 'file:cohere.dark.svg' }, group: ['transform'], version: 1, description: 'Use Cohere Embeddings', defaults: { name: 'Embeddings Cohere', }, requestDefaults: { ignoreHttpStatusErrors: true, baseURL: '={{ $credentials.host }}', }, credentials: [ { name: 'cohereApi', required: true, }, ], codex: { categories: ['AI'], subcategories: { AI: ['Embeddings'], }, resources: { primaryDocumentation: [ { url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.embeddingscohere/', }, ], }, }, // 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'], properties: [ getConnectionHintNoticeField([NodeConnectionType.AiVectorStore]), { displayName: 'Each model is using different dimensional density for embeddings. Please make sure to use the same dimensionality for your vector store. The default model is using 768-dimensional embeddings.', name: 'notice', type: 'notice', default: '', }, { displayName: 'Model', name: 'modelName', type: 'options', description: 'The model which will generate the embeddings. Learn more.', default: 'embed-english-v2.0', options: [ { name: 'Embed-English-Light-v2.0 (1024 Dimensions)', value: 'embed-english-light-v2.0', }, { name: 'Embed-English-Light-v3.0 (384 Dimensions)', value: 'embed-english-light-v3.0', }, { name: 'Embed-English-v2.0 (4096 Dimensions)', value: 'embed-english-v2.0', }, { name: 'Embed-English-v3.0 (1024 Dimensions)', value: 'embed-english-v3.0', }, { name: 'Embed-Multilingual-Light-v3.0 (384 Dimensions)', value: 'embed-multilingual-light-v3.0', }, { name: 'Embed-Multilingual-v2.0 (768 Dimensions)', value: 'embed-multilingual-v2.0', }, { name: 'Embed-Multilingual-v3.0 (1024 Dimensions)', value: 'embed-multilingual-v3.0', }, ], }, ], }; async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise { this.logger.debug('Supply data for embeddings Cohere'); const modelName = this.getNodeParameter('modelName', itemIndex, 'embed-english-v2.0') as string; const credentials = await this.getCredentials<{ apiKey: string }>('cohereApi'); const embeddings = new CohereEmbeddings({ apiKey: credentials.apiKey, model: modelName, }); return { response: logWrapper(embeddings, this), }; } }