112 lines
4.0 KiB
TypeScript
112 lines
4.0 KiB
TypeScript
import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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import { Embeddings } from 'langchain/embeddings/base'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src'
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import { Client, ClientOptions } from '@elastic/elasticsearch'
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import { ElasticClientArgs, ElasticVectorSearch } from 'langchain/vectorstores/elasticsearch'
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class ElasicsearchExisting_VectorStores implements INode {
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label: string
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name: string
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version: number
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description: string
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type: string
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icon: string
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category: string
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baseClasses: string[]
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inputs: INodeParams[]
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credential: INodeParams
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outputs: INodeOutputsValue[]
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constructor() {
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this.label = 'Elasticsearch Load Existing Index'
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this.name = 'ElasticsearchIndex'
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this.version = 1.0
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this.type = 'Elasticsearch'
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this.icon = 'elasticsearch.png'
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this.category = 'Vector Stores'
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this.description = 'Load existing index from Elasticsearch (i.e: Document has been upserted)'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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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: ['elasticsearchApi', 'elasticSearchUserPassword']
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}
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this.inputs = [
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{
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label: 'Embeddings',
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name: 'embeddings',
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type: 'Embeddings'
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},
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{
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label: 'Index Name',
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name: 'indexName',
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placeholder: '<INDEX_NAME>',
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type: 'string'
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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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description: 'Number of top results to fetch. Default to 4',
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placeholder: '4',
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type: 'number',
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additionalParams: true,
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optional: true
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}
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]
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this.outputs = [
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{
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label: 'Elasticsearch Retriever',
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name: 'retriever',
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baseClasses: this.baseClasses
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},
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{
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label: 'Elasticsearch Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(ElasticVectorSearch)]
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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 credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const endPoint = getCredentialParam('endpoint', credentialData, nodeData)
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const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
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const indexName = nodeData.inputs?.indexName as string
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseFloat(topK) : 4
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const output = nodeData.outputs?.output as string
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// eslint-disable-next-line no-console
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console.log('EndPoint:: ' + endPoint + ', APIKey:: ' + apiKey + ', Index:: ' + indexName)
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const elasticSearchClientOptions: ClientOptions = {
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node: endPoint,
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auth: {
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apiKey: apiKey
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}
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}
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const elasticSearchClientArgs: ElasticClientArgs = {
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client: new Client(elasticSearchClientOptions),
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indexName: indexName
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}
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const vectorStore = await ElasticVectorSearch.fromExistingIndex(embeddings, elasticSearchClientArgs)
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// eslint-disable-next-line no-console
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console.log('vectorStore ::' + vectorStore._vectorstoreType())
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if (output === 'retriever') {
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return vectorStore.asRetriever(k)
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} else if (output === 'vectorStore') {
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;(vectorStore as any).k = k
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return vectorStore
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}
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return vectorStore
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}
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}
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module.exports = { nodeClass: ElasicsearchExisting_VectorStores }
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