270 lines
11 KiB
TypeScript
270 lines
11 KiB
TypeScript
import { flatten } from 'lodash'
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import { Pinecone } from '@pinecone-database/pinecone'
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import { PineconeStoreParams, PineconeStore } from '@langchain/pinecone'
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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 { VectorStore } from '@langchain/core/vectorstores'
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import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams, IndexingResult } from '../../../src/Interface'
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import { FLOWISE_CHATID, getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { addMMRInputParams, howToUseFileUpload, resolveVectorStoreOrRetriever } from '../VectorStoreUtils'
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import { index } from '../../../src/indexing'
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class Pinecone_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 = 'Pinecone'
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this.name = 'pinecone'
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this.version = 5.0
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this.type = 'Pinecone'
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this.icon = 'pinecone.svg'
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this.category = 'Vector Stores'
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this.description = `Upsert embedded data and perform similarity or mmr search using Pinecone, a leading fully managed hosted vector 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: ['pineconeApi']
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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: 'Record Manager',
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name: 'recordManager',
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type: 'RecordManager',
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description: 'Keep track of the record to prevent duplication',
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optional: true
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},
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{
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label: 'Pinecone Index',
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name: 'pineconeIndex',
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type: 'string'
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},
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{
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label: 'Pinecone Namespace',
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name: 'pineconeNamespace',
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type: 'string',
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placeholder: 'my-first-namespace',
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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: '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: 'Pinecone Text Key',
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name: 'pineconeTextKey',
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description: 'The key in the metadata for storing text. Default to `text`',
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type: 'string',
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placeholder: '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: 'Pinecone Metadata Filter',
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name: 'pineconeMetadataFilter',
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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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addMMRInputParams(this.inputs)
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this.outputs = [
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{
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label: 'Pinecone 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: 'Pinecone Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(PineconeStore)]
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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 _index = nodeData.inputs?.pineconeIndex as string
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const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string
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const docs = nodeData.inputs?.document as Document[]
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const recordManager = nodeData.inputs?.recordManager
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const pineconeTextKey = nodeData.inputs?.pineconeTextKey as string
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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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const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
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const client = new Pinecone({ apiKey: pineconeApiKey })
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const pineconeIndex = client.Index(_index)
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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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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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}
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}
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const obj: PineconeStoreParams = {
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pineconeIndex,
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textKey: pineconeTextKey || 'text'
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}
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if (pineconeNamespace) obj.namespace = pineconeNamespace
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try {
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if (recordManager) {
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const vectorStore = (await PineconeStore.fromExistingIndex(embeddings, obj)) as unknown as VectorStore
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await recordManager.createSchema()
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const res = await index({
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docsSource: finalDocs,
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recordManager,
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vectorStore,
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options: {
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cleanup: recordManager?.cleanup,
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sourceIdKey: recordManager?.sourceIdKey ?? 'source',
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vectorStoreName: pineconeNamespace
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}
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})
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return res
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} else {
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await PineconeStore.fromDocuments(finalDocs, embeddings, obj)
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return { numAdded: finalDocs.length, addedDocs: finalDocs }
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}
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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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async delete(nodeData: INodeData, ids: string[], options: ICommonObject): Promise<void> {
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const _index = nodeData.inputs?.pineconeIndex as string
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const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const pineconeTextKey = nodeData.inputs?.pineconeTextKey as string
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const recordManager = nodeData.inputs?.recordManager
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const credentialData = await getCredentialData(nodeData.credential ?? '', options)
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const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
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const client = new Pinecone({ apiKey: pineconeApiKey })
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const pineconeIndex = client.Index(_index)
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const obj: PineconeStoreParams = {
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pineconeIndex,
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textKey: pineconeTextKey || 'text'
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}
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if (pineconeNamespace) obj.namespace = pineconeNamespace
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const pineconeStore = new PineconeStore(embeddings, obj)
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try {
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if (recordManager) {
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const vectorStoreName = pineconeNamespace
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await recordManager.createSchema()
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;(recordManager as any).namespace = (recordManager as any).namespace + '_' + vectorStoreName
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const keys: string[] = await recordManager.listKeys({})
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await pineconeStore.delete({ ids: keys })
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await recordManager.deleteKeys(keys)
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} else {
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const pineconeStore = new PineconeStore(embeddings, obj)
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await pineconeStore.delete({ ids })
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}
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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 index = nodeData.inputs?.pineconeIndex as string
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const pineconeNamespace = nodeData.inputs?.pineconeNamespace as string
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const pineconeMetadataFilter = nodeData.inputs?.pineconeMetadataFilter
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const pineconeTextKey = nodeData.inputs?.pineconeTextKey as string
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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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const pineconeApiKey = getCredentialParam('pineconeApiKey', credentialData, nodeData)
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const client = new Pinecone({ apiKey: pineconeApiKey })
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const pineconeIndex = client.Index(index)
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const obj: PineconeStoreParams = {
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pineconeIndex,
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textKey: pineconeTextKey || 'text'
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}
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if (pineconeNamespace) obj.namespace = pineconeNamespace
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if (pineconeMetadataFilter) {
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const metadatafilter = typeof pineconeMetadataFilter === 'object' ? pineconeMetadataFilter : JSON.parse(pineconeMetadataFilter)
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obj.filter = metadatafilter
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}
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if (isFileUploadEnabled && options.chatId) {
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obj.filter = obj.filter || {}
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obj.filter.$or = [
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...(obj.filter.$or || []),
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{ [FLOWISE_CHATID]: { $eq: options.chatId } },
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{ [FLOWISE_CHATID]: { $exists: false } }
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]
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}
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const vectorStore = (await PineconeStore.fromExistingIndex(embeddings, obj)) as unknown as VectorStore
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return resolveVectorStoreOrRetriever(nodeData, vectorStore, obj.filter)
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}
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}
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module.exports = { nodeClass: Pinecone_VectorStores }
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