import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' import { OpenSearchVectorStore } from 'langchain/vectorstores/opensearch' import { Embeddings } from 'langchain/embeddings/base' import { Client } from '@opensearch-project/opensearch' import { getBaseClasses } from '../../../src/utils' class OpenSearch_Existing_VectorStores implements INode { label: string name: string version: number description: string type: string icon: string category: string badge: string baseClasses: string[] inputs: INodeParams[] outputs: INodeOutputsValue[] constructor() { this.label = 'OpenSearch Load Existing Index' this.name = 'openSearchExistingIndex' this.version = 1.0 this.type = 'OpenSearch' this.icon = 'opensearch.svg' this.category = 'Vector Stores' this.description = 'Load existing index from OpenSearch (i.e: Document has been upserted)' this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever'] this.badge = 'DEPRECATING' this.inputs = [ { label: 'Embeddings', name: 'embeddings', type: 'Embeddings' }, { label: 'OpenSearch URL', name: 'opensearchURL', type: 'string', placeholder: 'http://127.0.0.1:9200' }, { label: 'Index Name', name: 'indexName', type: 'string' }, { label: 'Top K', name: 'topK', description: 'Number of top results to fetch. Default to 4', placeholder: '4', type: 'number', additionalParams: true, optional: true } ] this.outputs = [ { label: 'OpenSearch Retriever', name: 'retriever', baseClasses: this.baseClasses }, { label: 'OpenSearch Vector Store', name: 'vectorStore', baseClasses: [this.type, ...getBaseClasses(OpenSearchVectorStore)] } ] } async init(nodeData: INodeData): Promise { const embeddings = nodeData.inputs?.embeddings as Embeddings const opensearchURL = nodeData.inputs?.opensearchURL as string const indexName = nodeData.inputs?.indexName as string const output = nodeData.outputs?.output as string const topK = nodeData.inputs?.topK as string const k = topK ? parseFloat(topK) : 4 const client = new Client({ nodes: [opensearchURL] }) const vectorStore = new OpenSearchVectorStore(embeddings, { client, indexName }) if (output === 'retriever') { const retriever = vectorStore.asRetriever(k) return retriever } else if (output === 'vectorStore') { ;(vectorStore as any).k = k return vectorStore } return vectorStore } } module.exports = { nodeClass: OpenSearch_Existing_VectorStores }