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HenryHengZJHenryHengZJ
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Merge pull request #409 from govind-kumarr/feature/Qdrant-VectorStore-Integration
Feature/Qdrant vector store integration
2 parents f475594 + ab029a8 commit 4765464

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‎packages/components/nodes/vectorstores/Qdrant_Existing/Qdrant_Existing.ts

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import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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import { QdrantClient } from '@qdrant/js-client-rest'
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import { QdrantVectorStore, QdrantLibArgs } from 'langchain/vectorstores/qdrant'
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import { Embeddings } from 'langchain/embeddings/base'
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import { getBaseClasses } from '../../../src/utils'
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class Qdrant_Existing_VectorStores implements INode {
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label: string
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name: string
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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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outputs: INodeOutputsValue[]
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constructor() {
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this.label = 'Qdrant Load Existing Index'
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this.name = 'qdrantExistingIndex'
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this.type = 'Qdrant'
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this.icon = 'qdrant_logo.svg'
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this.category = 'Vector Stores'
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this.description = 'Load existing index from Qdrant (i.e., documents have been upserted)'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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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: 'Qdrant Server URL',
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name: 'qdrantServerUrl',
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type: 'string',
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placeholder: 'http://localhost:6333'
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},
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{
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label: 'Qdrant Collection Name',
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name: 'qdrantCollection',
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type: 'string'
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},
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{
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label: 'Qdrant API Key',
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name: 'qdrantApiKey',
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type: 'password',
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optional: true
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},
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{
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label: 'Qdrant Collection Cofiguration',
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name: 'qdrantCollectionCofiguration',
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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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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: 'Qdrant 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: 'Qdrant Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(QdrantVectorStore)]
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}
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]
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}
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async init(nodeData: INodeData): Promise<any> {
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const qdrantServerUrl = nodeData.inputs?.qdrantServerUrl as string
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const collectionName = nodeData.inputs?.qdrantCollection as string
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const qdrantApiKey = nodeData.inputs?.qdrantApiKey as string
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let qdrantCollectionCofiguration = nodeData.inputs?.qdrantCollectionCofiguration
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const embeddings = nodeData.inputs?.embeddings as Embeddings
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const output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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// connect to Qdrant Cloud
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const client = new QdrantClient({
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url: qdrantServerUrl,
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apiKey: qdrantApiKey
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})
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const dbConfig: QdrantLibArgs = {
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client,
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collectionName
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}
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if (qdrantCollectionCofiguration) {
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qdrantCollectionCofiguration =
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typeof qdrantCollectionCofiguration === 'object' ? qdrantCollectionCofiguration : JSON.parse(qdrantCollectionCofiguration)
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dbConfig.collectionConfig = qdrantCollectionCofiguration
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}
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const vectorStore = await QdrantVectorStore.fromExistingCollection(embeddings, dbConfig)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever(k)
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return retriever
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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: Qdrant_Existing_VectorStores }

‎packages/components/nodes/vectorstores/Qdrant_Existing/qdrant_logo.svg

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‎packages/components/nodes/vectorstores/Qdrant_Upsert/Qdrant_Upsert.ts

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import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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import { QdrantClient } from '@qdrant/js-client-rest'
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import { QdrantVectorStore, QdrantLibArgs } from 'langchain/vectorstores/qdrant'
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import { Embeddings } from 'langchain/embeddings/base'
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import { Document } from 'langchain/document'
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import { getBaseClasses } from '../../../src/utils'
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import { flatten } from 'lodash'
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class QdrantUpsert_VectorStores implements INode {
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label: string
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name: string
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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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outputs: INodeOutputsValue[]
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constructor() {
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this.label = 'Qdrant Upsert Document'
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this.name = 'qdrantUpsert'
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this.type = 'Qdrant'
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this.icon = 'qdrant_logo.svg'
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this.category = 'Vector Stores'
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this.description = 'Upsert documents to Qdrant'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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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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},
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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: 'Qdrant Server URL',
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name: 'qdrantServerUrl',
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type: 'string',
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placeholder: 'http://localhost:6333'
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},
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{
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label: 'Qdrant Collection Name',
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name: 'qdrantCollection',
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type: 'string'
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},
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{
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label: 'Qdrant API Key',
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name: 'qdrantApiKey',
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type: 'password',
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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 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: 'Qdrant 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: 'Qdrant Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(QdrantVectorStore)]
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}
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]
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}
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async init(nodeData: INodeData): Promise<any> {
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const qdrantServerUrl = nodeData.inputs?.qdrantServerUrl as string
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const collectionName = nodeData.inputs?.qdrantCollection as string
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const qdrantApiKey = nodeData.inputs?.qdrantApiKey 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 output = nodeData.outputs?.output as string
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const topK = nodeData.inputs?.topK as string
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const k = topK ? parseInt(topK, 10) : 4
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// connect to Qdrant Cloud
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const client = new QdrantClient({
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url: qdrantServerUrl,
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apiKey: qdrantApiKey
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})
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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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finalDocs.push(new Document(flattenDocs[i]))
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}
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const dbConfig: QdrantLibArgs = {
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client,
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url: qdrantServerUrl,
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collectionName
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}
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const vectorStore = await QdrantVectorStore.fromDocuments(finalDocs, embeddings, dbConfig)
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if (output === 'retriever') {
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const retriever = vectorStore.asRetriever(k)
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return retriever
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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: QdrantUpsert_VectorStores }

‎packages/components/nodes/vectorstores/Qdrant_Upsert/qdrant_logo.svg

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‎packages/components/package.json

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"@getzep/zep-js": "^0.3.1",
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"@huggingface/inference": "1",
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"@pinecone-database/pinecone": "^0.0.12",
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"@qdrant/js-client-rest": "^1.2.2",
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"@supabase/supabase-js": "^2.21.0",
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"@types/js-yaml": "^4.0.5",
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"axios": "^0.27.2",

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