import { flatten } from 'lodash' import { createClient } from '@supabase/supabase-js' import { Document } from 'langchain/document' import { Embeddings } from 'langchain/embeddings/base' import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' import { SupabaseLibArgs, SupabaseVectorStore } from 'langchain/vectorstores/supabase' class Supabase_VectorStores implements INode { label: string name: string version: number description: string type: string icon: string category: string badge: string baseClasses: string[] inputs: INodeParams[] credential: INodeParams outputs: INodeOutputsValue[] constructor() { this.label = 'Supabase' this.name = 'supabase' this.version = 1.0 this.type = 'Supabase' this.icon = 'supabase.svg' this.category = 'Vector Stores' this.description = 'Upsert embedded data and perform similarity search upon query using Supabase via pgvector extension' this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever'] this.badge = 'NEW' this.credential = { label: 'Connect Credential', name: 'credential', type: 'credential', credentialNames: ['supabaseApi'] } this.inputs = [ { label: 'Document', name: 'document', type: 'Document', list: true, optional: true }, { label: 'Embeddings', name: 'embeddings', type: 'Embeddings' }, { label: 'Supabase Project URL', name: 'supabaseProjUrl', type: 'string' }, { label: 'Table Name', name: 'tableName', type: 'string' }, { label: 'Query Name', name: 'queryName', type: 'string' }, { label: 'Supabase Metadata Filter', name: 'supabaseMetadataFilter', type: 'json', optional: true, additionalParams: true }, { label: 'Top K', name: 'topK', description: 'Number of top results to fetch. Default to 4', placeholder: '4', type: 'number', additionalParams: true, optional: true } ] this.outputs = [ { label: 'Supabase Retriever', name: 'retriever', baseClasses: this.baseClasses }, { label: 'Supabase Vector Store', name: 'vectorStore', baseClasses: [this.type, ...getBaseClasses(SupabaseVectorStore)] } ] } //@ts-ignore vectorStoreMethods = { async upsert(nodeData: INodeData, options: ICommonObject): Promise { const supabaseProjUrl = nodeData.inputs?.supabaseProjUrl as string const tableName = nodeData.inputs?.tableName as string const queryName = nodeData.inputs?.queryName as string const docs = nodeData.inputs?.document as Document[] const embeddings = nodeData.inputs?.embeddings as Embeddings const credentialData = await getCredentialData(nodeData.credential ?? '', options) const supabaseApiKey = getCredentialParam('supabaseApiKey', credentialData, nodeData) const client = createClient(supabaseProjUrl, supabaseApiKey) const flattenDocs = docs && docs.length ? flatten(docs) : [] const finalDocs = [] for (let i = 0; i < flattenDocs.length; i += 1) { if (flattenDocs[i] && flattenDocs[i].pageContent) { finalDocs.push(new Document(flattenDocs[i])) } } try { await SupabaseVectorStore.fromDocuments(finalDocs, embeddings, { client, tableName: tableName, queryName: queryName }) } catch (e) { throw new Error(e) } } } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { const supabaseProjUrl = nodeData.inputs?.supabaseProjUrl as string const tableName = nodeData.inputs?.tableName as string const queryName = nodeData.inputs?.queryName as string const embeddings = nodeData.inputs?.embeddings as Embeddings const supabaseMetadataFilter = nodeData.inputs?.supabaseMetadataFilter const output = nodeData.outputs?.output as string const topK = nodeData.inputs?.topK as string const k = topK ? parseFloat(topK) : 4 const credentialData = await getCredentialData(nodeData.credential ?? '', options) const supabaseApiKey = getCredentialParam('supabaseApiKey', credentialData, nodeData) const client = createClient(supabaseProjUrl, supabaseApiKey) const obj: SupabaseLibArgs = { client, tableName, queryName } if (supabaseMetadataFilter) { const metadatafilter = typeof supabaseMetadataFilter === 'object' ? supabaseMetadataFilter : JSON.parse(supabaseMetadataFilter) obj.filter = metadatafilter } const vectorStore = await SupabaseVectorStore.fromExistingIndex(embeddings, obj) if (output === 'retriever') { const retriever = vectorStore.asRetriever(k) return retriever } else if (output === 'vectorStore') { ;(vectorStore as any).k = k return vectorStore } return vectorStore } } module.exports = { nodeClass: Supabase_VectorStores }