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https://github.com/farcasclaudiu/Flowise.git
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Chore/update deprecating nodes (#2540)
* update deprecating nodes * add filters use cases to marketplace * update log level
This commit is contained in:
Henry Heng
@@ -29,7 +29,6 @@ class SingleStore_VectorStores implements INode {
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this.description =
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'Upsert embedded data and perform similarity search upon query using SingleStore, a fast and distributed cloud relational database'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.badge = 'NEW'
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this.credential = {
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label: 'Connect Credential',
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name: 'credential',
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@@ -1,148 +0,0 @@
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import { Embeddings } from '@langchain/core/embeddings'
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import { SingleStoreVectorStore, SingleStoreVectorStoreConfig } from '@langchain/community/vectorstores/singlestore'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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class SingleStoreExisting_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 = 'SingleStore Load Existing Table'
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this.name = 'singlestoreExisting'
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this.version = 1.0
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this.type = 'SingleStore'
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this.icon = 'singlestore.svg'
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this.category = 'Vector Stores'
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this.description = 'Load existing document from SingleStore'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.badge = 'DEPRECATING'
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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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description: 'Needed when using SingleStore cloud hosted',
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optional: true,
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credentialNames: ['singleStoreApi']
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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: 'Host',
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name: 'host',
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type: 'string'
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},
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{
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label: 'Database',
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name: 'database',
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type: 'string'
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},
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{
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label: 'Table Name',
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name: 'tableName',
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type: 'string',
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placeholder: 'embeddings',
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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: 'Content Column Name',
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name: 'contentColumnName',
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type: 'string',
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placeholder: 'content',
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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: 'Vector Column Name',
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name: 'vectorColumnName',
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type: 'string',
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placeholder: 'vector',
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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: 'Metadata Column Name',
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name: 'metadataColumnName',
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type: 'string',
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placeholder: 'metadata',
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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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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: 'SingleStore 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: 'SingleStore Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(SingleStoreVectorStore)]
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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 user = getCredentialParam('user', credentialData, nodeData)
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const password = getCredentialParam('password', credentialData, nodeData)
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const singleStoreConnectionConfig = {
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connectionOptions: {
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host: nodeData.inputs?.host as string,
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port: 3306,
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user,
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password,
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database: nodeData.inputs?.database as string
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},
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...(nodeData.inputs?.tableName ? { tableName: nodeData.inputs.tableName as string } : {}),
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...(nodeData.inputs?.contentColumnName ? { contentColumnName: nodeData.inputs.contentColumnName as string } : {}),
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...(nodeData.inputs?.vectorColumnName ? { vectorColumnName: nodeData.inputs.vectorColumnName as string } : {}),
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...(nodeData.inputs?.metadataColumnName ? { metadataColumnName: nodeData.inputs.metadataColumnName as string } : {})
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} as SingleStoreVectorStoreConfig
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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 ? parseFloat(topK) : 4
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let vectorStore: SingleStoreVectorStore
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vectorStore = new SingleStoreVectorStore(embeddings, singleStoreConnectionConfig)
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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: SingleStoreExisting_VectorStores }
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@@ -1,166 +0,0 @@
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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 { SingleStoreVectorStore, SingleStoreVectorStoreConfig } from '@langchain/community/vectorstores/singlestore'
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import { flatten } from 'lodash'
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import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
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import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
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class SingleStoreUpsert_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 = 'SingleStore Upsert Document'
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this.name = 'singlestoreUpsert'
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this.version = 1.0
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this.type = 'SingleStore'
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this.icon = 'singlestore.svg'
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this.category = 'Vector Stores'
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this.description = 'Upsert documents to SingleStore'
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this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever']
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this.badge = 'DEPRECATING'
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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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description: 'Needed when using SingleStore cloud hosted',
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optional: true,
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credentialNames: ['singleStoreApi']
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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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},
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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: 'Host',
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name: 'host',
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type: 'string'
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},
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{
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label: 'Database',
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name: 'database',
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type: 'string'
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},
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{
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label: 'Table Name',
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name: 'tableName',
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type: 'string',
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placeholder: 'embeddings',
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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: 'Content Column Name',
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name: 'contentColumnName',
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type: 'string',
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placeholder: 'content',
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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: 'Vector Column Name',
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name: 'vectorColumnName',
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type: 'string',
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placeholder: 'vector',
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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: 'Metadata Column Name',
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name: 'metadataColumnName',
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type: 'string',
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placeholder: 'metadata',
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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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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: 'SingleStore 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: 'SingleStore Vector Store',
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name: 'vectorStore',
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baseClasses: [this.type, ...getBaseClasses(SingleStoreVectorStore)]
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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 user = getCredentialParam('user', credentialData, nodeData)
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const password = getCredentialParam('password', credentialData, nodeData)
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const singleStoreConnectionConfig = {
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connectionOptions: {
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host: nodeData.inputs?.host as string,
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port: 3306,
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user,
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password,
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database: nodeData.inputs?.database as string
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},
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...(nodeData.inputs?.tableName ? { tableName: nodeData.inputs.tableName as string } : {}),
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...(nodeData.inputs?.contentColumnName ? { contentColumnName: nodeData.inputs.contentColumnName as string } : {}),
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...(nodeData.inputs?.vectorColumnName ? { vectorColumnName: nodeData.inputs.vectorColumnName as string } : {}),
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...(nodeData.inputs?.metadataColumnName ? { metadataColumnName: nodeData.inputs.metadataColumnName as string } : {})
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} as SingleStoreVectorStoreConfig
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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 ? parseFloat(topK) : 4
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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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finalDocs.push(new Document(flattenDocs[i]))
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}
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}
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let vectorStore: SingleStoreVectorStore
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vectorStore = new SingleStoreVectorStore(embeddings, singleStoreConnectionConfig)
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vectorStore.addDocuments.bind(vectorStore)(finalDocs)
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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: SingleStoreUpsert_VectorStores }
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