231 lines
8.8 KiB
TypeScript
231 lines
8.8 KiB
TypeScript
import { flatten } from 'lodash'
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import { Embeddings } from '@langchain/core/embeddings'
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import { Document } from '@langchain/core/documents'
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import { CouchbaseVectorStore, CouchbaseVectorStoreArgs } from '@langchain/community/vectorstores/couchbase'
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import { Cluster } from 'couchbase'
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import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams, IndexingResult } from '../../../src/Interface'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { resolveVectorStoreOrRetriever } from '../VectorStoreUtils'
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class Couchbase_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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badge: 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 = 'Couchbase'
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this.name = 'couchbase'
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this.version = 1.0
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this.type = 'Couchbase'
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this.icon = 'couchbase.svg'
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this.category = 'Vector Stores'
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this.description = `Upsert embedded data and load existing index using Couchbase, a award-winning distributed NoSQL database`
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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: ['couchbaseApi']
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}
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this.inputs = [
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{
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label: 'Document',
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name: 'document',
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type: 'Document',
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list: true,
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optional: true
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},
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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: 'Bucket Name',
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name: 'bucketName',
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placeholder: '<DB_BUCKET_NAME>',
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type: 'string'
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},
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{
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label: 'Scope Name',
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name: 'scopeName',
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placeholder: '<SCOPE_NAME>',
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type: 'string'
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},
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{
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label: 'Collection Name',
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name: 'collectionName',
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placeholder: '<COLLECTION_NAME>',
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type: 'string'
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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: '<VECTOR_INDEX_NAME>',
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type: 'string'
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},
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{
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label: 'Content Field',
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name: 'textKey',
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description: 'Name of the field (column) that contains the actual content',
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type: 'string',
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default: 'text',
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additionalParams: true,
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optional: true
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},
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{
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label: 'Embedded Field',
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name: 'embeddingKey',
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description: 'Name of the field (column) that contains the Embedding',
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type: 'string',
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default: 'embedding',
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additionalParams: true,
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optional: true
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},
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{
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label: 'Couchbase Metadata Filter',
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name: 'couchbaseMetadataFilter',
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type: 'json',
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optional: true,
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additionalParams: true,
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acceptVariable: true
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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: 'Couchbase 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: 'Couchbase Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(CouchbaseVectorStore)]
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}
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]
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}
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//@ts-ignore
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vectorStoreMethods = {
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async upsert(nodeData: INodeData, options: ICommonObject): Promise<Partial<IndexingResult>> {
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const bucketName = nodeData.inputs?.bucketName as string
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const scopeName = nodeData.inputs?.scopeName as string
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const collectionName = nodeData.inputs?.collectionName as string
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const indexName = nodeData.inputs?.indexName as string
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let textKey = nodeData.inputs?.textKey as string
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let embeddingKey = nodeData.inputs?.embeddingKey as string
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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let connectionString = getCredentialParam('connectionString', credentialData, nodeData)
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let databaseUsername = getCredentialParam('username', credentialData, nodeData)
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let databasePassword = getCredentialParam('password', credentialData, nodeData)
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const docs = nodeData.inputs?.document as Document[]
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const flattenDocs = docs && docs.length ? flatten(docs) : []
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const finalDocs = []
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for (let i = 0; i < flattenDocs.length; i += 1) {
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if (flattenDocs[i] && flattenDocs[i].pageContent) {
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const document = new Document(flattenDocs[i])
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finalDocs.push(document)
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}
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}
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const couchbaseClient = await Cluster.connect(connectionString, {
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username: databaseUsername,
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password: databasePassword,
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configProfile: 'wanDevelopment'
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})
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const couchbaseConfig: CouchbaseVectorStoreArgs = {
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cluster: couchbaseClient,
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bucketName: bucketName,
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scopeName: scopeName,
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collectionName: collectionName,
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indexName: indexName,
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textKey: textKey,
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embeddingKey: embeddingKey
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}
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try {
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if (!textKey || textKey === '') couchbaseConfig.textKey = 'text'
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if (!embeddingKey || embeddingKey === '') couchbaseConfig.embeddingKey = 'embedding'
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await CouchbaseVectorStore.fromDocuments(finalDocs, embeddings, couchbaseConfig)
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return { numAdded: finalDocs.length, addedDocs: finalDocs }
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} catch (e) {
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throw new Error(e)
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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 bucketName = nodeData.inputs?.bucketName as string
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const scopeName = nodeData.inputs?.scopeName as string
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const collectionName = nodeData.inputs?.collectionName as string
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const indexName = nodeData.inputs?.indexName as string
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let textKey = nodeData.inputs?.textKey as string
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let embeddingKey = nodeData.inputs?.embeddingKey as string
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const couchbaseMetadataFilter = nodeData.inputs?.couchbaseMetadataFilter
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let connectionString = getCredentialParam('connectionString', credentialData, nodeData)
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let databaseUsername = getCredentialParam('username', credentialData, nodeData)
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let databasePassword = getCredentialParam('password', credentialData, nodeData)
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let metadatafilter
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const couchbaseClient = await Cluster.connect(connectionString, {
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username: databaseUsername,
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password: databasePassword,
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configProfile: 'wanDevelopment'
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})
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const couchbaseConfig: CouchbaseVectorStoreArgs = {
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cluster: couchbaseClient,
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bucketName: bucketName,
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scopeName: scopeName,
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collectionName: collectionName,
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indexName: indexName,
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textKey: textKey,
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embeddingKey: embeddingKey
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}
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try {
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if (!textKey || textKey === '') couchbaseConfig.textKey = 'text'
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if (!embeddingKey || embeddingKey === '') couchbaseConfig.embeddingKey = 'embedding'
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if (couchbaseMetadataFilter) {
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metadatafilter = typeof couchbaseMetadataFilter === 'object' ? couchbaseMetadataFilter : JSON.parse(couchbaseMetadataFilter)
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}
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const vectorStore = await CouchbaseVectorStore.initialize(embeddings, couchbaseConfig)
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return resolveVectorStoreOrRetriever(nodeData, vectorStore, metadatafilter)
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} catch (e) {
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throw new Error(e)
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}
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}
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}
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module.exports = { nodeClass: Couchbase_VectorStores }
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