371 lines
13 KiB
TypeScript
371 lines
13 KiB
TypeScript
import { flatten } from 'lodash'
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import { Document } from '@langchain/core/documents'
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import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams, IndexingResult } from '../../../src/Interface'
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import { FLOWISE_CHATID, getBaseClasses, parseJsonBody } from '../../../src/utils'
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import { index } from '../../../src/indexing'
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import { howToUseFileUpload } from '../VectorStoreUtils'
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import { VectorStore } from '@langchain/core/vectorstores'
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import { VectorStoreDriver } from './driver/Base'
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import { TypeORMDriver } from './driver/TypeORM'
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// import { PGVectorDriver } from './driver/PGVector'
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import { getContentColumnName, getDatabase, getHost, getPort, getTableName } from './utils'
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const serverCredentialsExists = !!process.env.POSTGRES_VECTORSTORE_USER && !!process.env.POSTGRES_VECTORSTORE_PASSWORD
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// added temporarily to fix the base class return for VectorStore when postgres node is using TypeORM
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function getVectorStoreBaseClasses() {
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// Try getting base classes through the utility function
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const baseClasses = getBaseClasses(VectorStore)
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// If we got results, return them
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if (baseClasses && baseClasses.length > 0) {
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return baseClasses
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}
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// If VectorStore is recognized as a class but getBaseClasses returned nothing,
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// return the known inheritance chain
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if (VectorStore instanceof Function) {
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return ['VectorStore']
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}
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// Fallback to minimum required class
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return ['VectorStore']
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}
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class Postgres_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 = 'Postgres'
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this.name = 'postgres'
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this.version = 7.1
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this.type = 'Postgres'
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this.icon = 'postgres.svg'
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this.category = 'Vector Stores'
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this.description = 'Upsert embedded data and perform similarity search upon query using pgvector on Postgres'
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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: ['PostgresApi'],
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optional: serverCredentialsExists
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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: 'Host',
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name: 'host',
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type: 'string',
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placeholder: getHost(),
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optional: !!getHost()
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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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placeholder: getDatabase(),
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optional: !!getDatabase()
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},
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{
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label: 'Port',
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name: 'port',
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type: 'number',
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placeholder: getPort(),
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optional: true
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},
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{
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label: 'SSL',
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name: 'ssl',
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description: 'Use SSL to connect to Postgres',
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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: 'Table Name',
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name: 'tableName',
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type: 'string',
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placeholder: getTableName(),
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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: 'Driver',
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name: 'driver',
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type: 'options',
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default: 'typeorm',
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description: 'Different option to connect to Postgres',
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options: [
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{
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label: 'TypeORM',
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name: 'typeorm'
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},
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{
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label: 'PGVector',
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name: 'pgvector'
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}
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],
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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: 'Distance Strategy',
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name: 'distanceStrategy',
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description: 'Strategy for calculating distances between vectors',
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type: 'options',
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options: [
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{
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label: 'Cosine',
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name: 'cosine'
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},
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{
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label: 'Euclidean',
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name: 'euclidean'
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},
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{
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label: 'Inner Product',
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name: 'innerProduct'
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}
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],
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additionalParams: true,
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default: 'cosine',
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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: 'Upsert Batch Size',
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name: 'batchSize',
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type: 'number',
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step: 1,
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description: 'Upsert in batches of size N',
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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: 'Additional Configuration',
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name: 'additionalConfig',
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type: 'json',
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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 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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label: 'Postgres Metadata Filter',
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name: 'pgMetadataFilter',
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type: 'json',
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additionalParams: true,
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optional: true,
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acceptVariable: 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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description: 'Column name to store the text content (PGVector Driver only, others use pageContent)',
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type: 'string',
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placeholder: getContentColumnName(),
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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: 'Postgres 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: 'Postgres Vector Store',
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name: 'vectorStore',
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baseClasses: [
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this.type,
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// ...getBaseClasses(VectorStore), // disabled temporarily for using TypeORM
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...getVectorStoreBaseClasses() // added temporarily for using TypeORM
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]
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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 tableName = getTableName(nodeData)
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const docs = nodeData.inputs?.document as Document[]
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const recordManager = nodeData.inputs?.recordManager
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const isFileUploadEnabled = nodeData.inputs?.fileUpload as boolean
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const _batchSize = nodeData.inputs?.batchSize
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const vectorStoreDriver: VectorStoreDriver = Postgres_VectorStores.getDriverFromConfig(nodeData, options)
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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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try {
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if (recordManager) {
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const vectorStore = await vectorStoreDriver.instanciate()
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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: tableName
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}
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})
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return res
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} else {
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if (_batchSize) {
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const batchSize = parseInt(_batchSize, 10)
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for (let i = 0; i < finalDocs.length; i += batchSize) {
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const batch = finalDocs.slice(i, i + batchSize)
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await vectorStoreDriver.fromDocuments(batch)
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}
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} else {
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await vectorStoreDriver.fromDocuments(finalDocs)
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}
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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 vectorStoreDriver: VectorStoreDriver = Postgres_VectorStores.getDriverFromConfig(nodeData, options)
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const tableName = getTableName(nodeData)
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const recordManager = nodeData.inputs?.recordManager
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const vectorStore = await vectorStoreDriver.instanciate()
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try {
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if (recordManager) {
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const vectorStoreName = tableName
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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 filterKeys: ICommonObject = {}
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if (options.docId) {
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filterKeys.docId = options.docId
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}
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const keys: string[] = await recordManager.listKeys(filterKeys)
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await vectorStore.delete({ ids: keys })
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await recordManager.deleteKeys(keys)
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} else {
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await vectorStore.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 vectorStoreDriver: VectorStoreDriver = Postgres_VectorStores.getDriverFromConfig(nodeData, options)
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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 _pgMetadataFilter = nodeData.inputs?.pgMetadataFilter
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const isFileUploadEnabled = nodeData.inputs?.fileUpload as boolean
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let pgMetadataFilter: any
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if (_pgMetadataFilter) {
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pgMetadataFilter = typeof _pgMetadataFilter === 'object' ? _pgMetadataFilter : parseJsonBody(_pgMetadataFilter)
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}
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if (isFileUploadEnabled && options.chatId) {
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pgMetadataFilter = {
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...(pgMetadataFilter || {}),
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[FLOWISE_CHATID]: options.chatId
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}
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}
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const vectorStore = await vectorStoreDriver.instanciate(pgMetadataFilter)
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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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if (pgMetadataFilter) {
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;(vectorStore as any).filter = pgMetadataFilter
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}
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return vectorStore
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}
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return vectorStore
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}
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static getDriverFromConfig(nodeData: INodeData, options: ICommonObject): VectorStoreDriver {
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/*switch (nodeData.inputs?.driver) {
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case 'typeorm':
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return new TypeORMDriver(nodeData, options)
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case 'pgvector':
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return new PGVectorDriver(nodeData, options)
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default:
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return new TypeORMDriver(nodeData, options)
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}*/
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return new TypeORMDriver(nodeData, options)
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}
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}
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module.exports = { nodeClass: Postgres_VectorStores }
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