Feat/aws kendra vector search (#5088)
* Add AWS Kendra vector store integration * Fix import paths in Kendra vector store * Add AWS Kendra dependencies to package.json * Update pnpm-lock.yaml with AWS Kendra dependencies * Fix linter warnings in Kendra vector store * Fix code formatting in Kendra vector store * Update pnpm-lock.yaml --------- Co-authored-by: Henry Heng <henryheng@flowiseai.com> Co-authored-by: Henry <hzj94@hotmail.com>
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anatolii burtsev
GitHub
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import { flatten } from 'lodash'
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import { AmazonKendraRetriever } from '@langchain/aws'
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import { KendraClient, BatchPutDocumentCommand, BatchDeleteDocumentCommand } from '@aws-sdk/client-kendra'
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import { Document } from '@langchain/core/documents'
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import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeOutputsValue, INodeParams, IndexingResult } from '../../../src/Interface'
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import { FLOWISE_CHATID, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { howToUseFileUpload } from '../VectorStoreUtils'
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import { MODEL_TYPE, getRegions } from '../../../src/modelLoader'
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class Kendra_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 = 'AWS Kendra'
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this.name = 'kendra'
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this.version = 1.0
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this.type = 'Kendra'
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this.icon = 'kendra.svg'
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this.category = 'Vector Stores'
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this.description = `Use AWS Kendra's intelligent search service for document retrieval and semantic search`
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.credential = {
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label: 'AWS Credential',
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name: 'credential',
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type: 'credential',
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credentialNames: ['awsApi'],
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optional: true
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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: 'Region',
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name: 'region',
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type: 'asyncOptions',
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loadMethod: 'listRegions',
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default: 'us-east-1'
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},
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{
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label: 'Kendra Index ID',
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name: 'indexId',
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type: 'string',
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placeholder: 'xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx',
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description: 'The ID of your AWS Kendra index'
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},
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{
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label: 'File Upload',
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name: 'fileUpload',
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description: 'Allow file upload on the chat',
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hint: {
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label: 'How to use',
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value: howToUseFileUpload
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},
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type: 'boolean',
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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: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to 10',
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placeholder: '10',
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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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label: 'Attribute Filter',
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name: 'attributeFilter',
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description: 'Optional filter to apply when retrieving documents',
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type: 'json',
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optional: true,
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additionalParams: true
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}
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]
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// Note: Kendra doesn't support MMR search, but keeping the structure consistent
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this.outputs = [
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{
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label: 'Kendra 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: 'Kendra Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, 'BaseRetriever']
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}
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]
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}
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loadMethods = {
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async listRegions(): Promise<INodeOptionsValue[]> {
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return await getRegions(MODEL_TYPE.CHAT, 'awsChatBedrock')
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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 indexId = nodeData.inputs?.indexId as string
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const region = nodeData.inputs?.region as string
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const docs = nodeData.inputs?.document as Document[]
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const isFileUploadEnabled = nodeData.inputs?.fileUpload as boolean
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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let clientConfig: any = { region }
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if (credentialData && Object.keys(credentialData).length !== 0) {
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const accessKeyId = getCredentialParam('awsKey', credentialData, nodeData)
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const secretAccessKey = getCredentialParam('awsSecret', credentialData, nodeData)
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const sessionToken = getCredentialParam('awsSession', credentialData, nodeData)
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if (accessKeyId && secretAccessKey) {
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clientConfig.credentials = {
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accessKeyId,
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secretAccessKey,
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...(sessionToken && { sessionToken })
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}
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}
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}
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const client = new KendraClient(clientConfig)
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const flattenDocs = docs && docs.length ? flatten(docs) : []
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const finalDocs = []
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const kendraDocuments = []
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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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if (isFileUploadEnabled && options.chatId) {
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flattenDocs[i].metadata = { ...flattenDocs[i].metadata, [FLOWISE_CHATID]: options.chatId }
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}
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finalDocs.push(new Document(flattenDocs[i]))
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// Prepare document for Kendra
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const docId = `doc_${Date.now()}_${i}`
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const docTitle = flattenDocs[i].metadata?.title || flattenDocs[i].metadata?.source || `Document ${i + 1}`
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kendraDocuments.push({
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Id: docId,
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Title: docTitle,
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Blob: new Uint8Array(Buffer.from(flattenDocs[i].pageContent, 'utf-8')),
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ContentType: 'PLAIN_TEXT' as any
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})
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}
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}
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try {
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if (kendraDocuments.length > 0) {
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// Kendra has a limit of 10 documents per batch
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const batchSize = 10
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for (let i = 0; i < kendraDocuments.length; i += batchSize) {
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const batch = kendraDocuments.slice(i, i + batchSize)
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const command = new BatchPutDocumentCommand({
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IndexId: indexId,
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Documents: batch
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})
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const response = await client.send(command)
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if (response.FailedDocuments && response.FailedDocuments.length > 0) {
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console.error('Failed documents:', response.FailedDocuments)
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throw new Error(`Failed to index some documents: ${JSON.stringify(response.FailedDocuments)}`)
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}
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}
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}
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return { numAdded: finalDocs.length, addedDocs: finalDocs }
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} catch (error) {
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throw new Error(`Failed to index documents to Kendra: ${error}`)
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}
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},
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async delete(nodeData: INodeData, ids: string[], options: ICommonObject): Promise<void> {
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const indexId = nodeData.inputs?.indexId as string
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const region = nodeData.inputs?.region as string
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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let clientConfig: any = { region }
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if (credentialData && Object.keys(credentialData).length !== 0) {
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const accessKeyId = getCredentialParam('awsKey', credentialData, nodeData)
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const secretAccessKey = getCredentialParam('awsSecret', credentialData, nodeData)
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const sessionToken = getCredentialParam('awsSession', credentialData, nodeData)
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if (accessKeyId && secretAccessKey) {
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clientConfig.credentials = {
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accessKeyId,
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secretAccessKey,
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...(sessionToken && { sessionToken })
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}
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}
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}
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const client = new KendraClient(clientConfig)
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try {
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// Kendra has a limit of 10 documents per batch delete
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const batchSize = 10
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for (let i = 0; i < ids.length; i += batchSize) {
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const batch = ids.slice(i, i + batchSize)
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const command = new BatchDeleteDocumentCommand({
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IndexId: indexId,
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DocumentIdList: batch
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})
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await client.send(command)
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}
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} catch (error) {
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throw new Error(`Failed to delete documents from Kendra: ${error}`)
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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 indexId = nodeData.inputs?.indexId as string
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const region = nodeData.inputs?.region as string
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const topK = nodeData.inputs?.topK as string
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const attributeFilter = nodeData.inputs?.attributeFilter
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const isFileUploadEnabled = nodeData.inputs?.fileUpload as boolean
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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let clientOptions: any = {}
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if (credentialData && Object.keys(credentialData).length !== 0) {
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clientOptions.credentials = {
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accessKeyId: getCredentialParam('awsKey', credentialData, nodeData),
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secretAccessKey: getCredentialParam('awsSecret', credentialData, nodeData),
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sessionToken: getCredentialParam('awsSession', credentialData, nodeData)
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}
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}
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let filter = undefined
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if (attributeFilter) {
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filter = typeof attributeFilter === 'object' ? attributeFilter : JSON.parse(attributeFilter)
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}
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// Add chat-specific filtering if file upload is enabled
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if (isFileUploadEnabled && options.chatId) {
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if (!filter) {
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filter = {}
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}
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filter.OrAllFilters = [
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...(filter.OrAllFilters || []),
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{
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EqualsTo: {
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Key: FLOWISE_CHATID,
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Value: {
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StringValue: options.chatId
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}
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}
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}
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]
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}
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const retriever = new AmazonKendraRetriever({
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topK: topK ? parseInt(topK) : 10,
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indexId,
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region,
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attributeFilter: filter,
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clientOptions
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})
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const output = nodeData.outputs?.output as string
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if (output === 'retriever') {
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return retriever
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} else if (output === 'vectorStore') {
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// Kendra doesn't have a traditional vector store interface,
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// but we can return the retriever with additional properties
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;(retriever as any).k = topK ? parseInt(topK) : 10
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;(retriever as any).filter = filter
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return retriever
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}
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}
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}
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module.exports = { nodeClass: Kendra_VectorStores }
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 80 80">
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<defs>
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<linearGradient id="kendraGradient" x1="0%" y1="0%" x2="100%" y2="100%">
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<stop offset="0%" style="stop-color:#FF9900;stop-opacity:1" />
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<stop offset="100%" style="stop-color:#FF6600;stop-opacity:1" />
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</linearGradient>
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</defs>
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<!-- Background -->
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<rect width="80" height="80" rx="4" fill="#232F3E"/>
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<!-- AWS Kendra Icon representation -->
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<!-- Main search/document icon -->
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<g transform="translate(42, 35) scale(1.5)">
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<!-- Document stack -->
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<rect x="-18" y="-12" width="24" height="28" rx="2" fill="#FF9900" opacity="0.3" transform="translate(3, -3)"/>
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<rect x="-18" y="-12" width="24" height="28" rx="2" fill="#FF9900" opacity="0.6" transform="translate(1.5, -1.5)"/>
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<rect x="-18" y="-12" width="24" height="28" rx="2" fill="url(#kendraGradient)"/>
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<!-- Search lines on document -->
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<line x1="-12" y1="-4" x2="0" y2="-4" stroke="white" stroke-width="2" stroke-linecap="round"/>
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<line x1="-12" y1="2" x2="-2" y2="2" stroke="white" stroke-width="2" stroke-linecap="round"/>
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<line x1="-12" y1="8" x2="0" y2="8" stroke="white" stroke-width="2" stroke-linecap="round"/>
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<!-- Magnifying glass -->
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<circle cx="10" cy="5" r="7" fill="none" stroke="white" stroke-width="2.5"/>
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<line x1="15" y1="10" x2="20" y2="15" stroke="white" stroke-width="2.5" stroke-linecap="round"/>
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</g>
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<!-- AWS Kendra text (optional, small) -->
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<text x="40" y="74" font-family="Arial, sans-serif" font-size="14" fill="#FF9900" text-anchor="middle">Kendra</text>
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</svg>
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After Width: | Height: | Size: 1.6 KiB |
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@ -25,6 +25,7 @@
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"@arizeai/openinference-instrumentation-langchain": "^2.0.0",
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"@aws-sdk/client-bedrock-runtime": "3.422.0",
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"@aws-sdk/client-dynamodb": "^3.360.0",
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"@aws-sdk/client-kendra": "^3.750.0",
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"@aws-sdk/client-s3": "^3.844.0",
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"@aws-sdk/client-secrets-manager": "^3.699.0",
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"@aws-sdk/client-sns": "^3.699.0",
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621
pnpm-lock.yaml
621
pnpm-lock.yaml
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