mirror of
https://github.com/n8n-io/n8n.git
synced 2025-01-12 13:27:31 -08:00
feat(Pinecone Vector Store Node, Supabase Vector Store Node): Add update operation to vector store nodes (#10060)
This commit is contained in:
parent
c6131859f5
commit
7e1eeb4c31
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@ -9,6 +9,15 @@ import { pineconeIndexSearch } from '../shared/methods/listSearch';
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const sharedFields: INodeProperties[] = [pineconeIndexRLC];
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const pineconeNamespaceField: INodeProperties = {
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displayName: 'Pinecone Namespace',
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name: 'pineconeNamespace',
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type: 'string',
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description:
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'Partition the records in an index into namespaces. Queries and other operations are then limited to one namespace, so different requests can search different subsets of your index.',
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default: '',
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};
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const retrieveFields: INodeProperties[] = [
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{
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displayName: 'Options',
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@ -16,17 +25,7 @@ const retrieveFields: INodeProperties[] = [
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type: 'collection',
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placeholder: 'Add Option',
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default: {},
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options: [
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{
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displayName: 'Pinecone Namespace',
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name: 'pineconeNamespace',
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type: 'string',
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description:
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'Partition the records in an index into namespaces. Queries and other operations are then limited to one namespace, so different requests can search different subsets of your index.',
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default: '',
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},
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metadataFilterField,
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],
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options: [pineconeNamespaceField, metadataFilterField],
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},
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];
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@ -45,17 +44,11 @@ const insertFields: INodeProperties[] = [
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default: false,
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description: 'Whether to clear the namespace before inserting new data',
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},
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{
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displayName: 'Pinecone Namespace',
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name: 'pineconeNamespace',
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type: 'string',
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description:
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'Partition the records in an index into namespaces. Queries and other operations are then limited to one namespace, so different requests can search different subsets of your index.',
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default: '',
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},
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pineconeNamespaceField,
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],
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},
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];
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export const VectorStorePinecone = createVectorStoreNode({
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meta: {
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displayName: 'Pinecone Vector Store',
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@ -70,6 +63,7 @@ export const VectorStorePinecone = createVectorStoreNode({
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required: true,
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},
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],
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operationModes: ['load', 'insert', 'retrieve', 'update'],
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},
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methods: { listSearch: { pineconeIndexSearch } },
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retrieveFields,
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@ -6,6 +6,14 @@ import { metadataFilterField } from '../../../utils/sharedFields';
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import { supabaseTableNameRLC } from '../shared/descriptions';
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import { supabaseTableNameSearch } from '../shared/methods/listSearch';
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const queryNameField: INodeProperties = {
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displayName: 'Query Name',
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name: 'queryName',
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type: 'string',
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default: 'match_documents',
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description: 'Name of the query to use for matching documents',
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};
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const sharedFields: INodeProperties[] = [supabaseTableNameRLC];
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const insertFields: INodeProperties[] = [
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{
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@ -14,17 +22,10 @@ const insertFields: INodeProperties[] = [
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type: 'collection',
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placeholder: 'Add Option',
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default: {},
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options: [
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{
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displayName: 'Query Name',
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name: 'queryName',
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type: 'string',
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default: 'match_documents',
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description: 'Name of the query to use for matching documents',
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},
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],
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options: [queryNameField],
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},
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];
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const retrieveFields: INodeProperties[] = [
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{
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displayName: 'Options',
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@ -32,18 +33,12 @@ const retrieveFields: INodeProperties[] = [
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type: 'collection',
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placeholder: 'Add Option',
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default: {},
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options: [
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{
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displayName: 'Query Name',
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name: 'queryName',
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type: 'string',
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default: 'match_documents',
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description: 'Name of the query to use for matching documents',
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},
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metadataFilterField,
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],
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options: [queryNameField, metadataFilterField],
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},
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];
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const updateFields: INodeProperties[] = [...insertFields];
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export const VectorStoreSupabase = createVectorStoreNode({
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meta: {
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description: 'Work with your data in Supabase Vector Store',
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@ -58,6 +53,7 @@ export const VectorStoreSupabase = createVectorStoreNode({
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required: true,
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},
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],
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operationModes: ['load', 'insert', 'retrieve', 'update'],
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},
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methods: {
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listSearch: { supabaseTableNameSearch },
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@ -66,6 +62,7 @@ export const VectorStoreSupabase = createVectorStoreNode({
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insertFields,
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loadFields: retrieveFields,
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retrieveFields,
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updateFields,
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async getVectorStoreClient(context, filter, embeddings, itemIndex) {
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const tableName = context.getNodeParameter('tableName', itemIndex, '', {
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extractValue: true,
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@ -13,16 +13,21 @@ import type {
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ILoadOptionsFunctions,
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INodeListSearchResult,
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Icon,
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INodePropertyOptions,
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} from 'n8n-workflow';
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import type { Embeddings } from '@langchain/core/embeddings';
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import type { Document } from '@langchain/core/documents';
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import { logWrapper } from '../../../utils/logWrapper';
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import type { N8nJsonLoader } from '../../../utils/N8nJsonLoader';
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import { N8nJsonLoader } from '../../../utils/N8nJsonLoader';
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import type { N8nBinaryLoader } from '../../../utils/N8nBinaryLoader';
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import { getMetadataFiltersValues, logAiEvent } from '../../../utils/helpers';
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import { getConnectionHintNoticeField } from '../../../utils/sharedFields';
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import { processDocument } from './processDocuments';
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type NodeOperationMode = 'insert' | 'load' | 'retrieve' | 'update';
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const DEFAULT_OPERATION_MODES: NodeOperationMode[] = ['load', 'insert', 'retrieve'];
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interface NodeMeta {
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displayName: string;
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name: string;
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@ -30,7 +35,9 @@ interface NodeMeta {
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docsUrl: string;
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icon: Icon;
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credentials?: INodeCredentialDescription[];
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operationModes?: NodeOperationMode[];
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}
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interface VectorStoreNodeConstructorArgs {
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meta: NodeMeta;
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methods?: {
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@ -42,10 +49,12 @@ interface VectorStoreNodeConstructorArgs {
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) => Promise<INodeListSearchResult>;
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};
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};
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sharedFields: INodeProperties[];
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insertFields?: INodeProperties[];
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loadFields?: INodeProperties[];
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retrieveFields?: INodeProperties[];
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updateFields?: INodeProperties[];
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populateVectorStore: (
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context: IExecuteFunctions,
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embeddings: Embeddings,
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@ -60,15 +69,52 @@ interface VectorStoreNodeConstructorArgs {
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) => Promise<VectorStore>;
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}
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function transformDescriptionForOperationMode(
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fields: INodeProperties[],
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mode: 'insert' | 'load' | 'retrieve',
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) {
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function transformDescriptionForOperationMode(fields: INodeProperties[], mode: NodeOperationMode) {
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return fields.map((field) => ({
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...field,
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displayOptions: { show: { mode: [mode] } },
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}));
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}
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function isUpdateSupported(args: VectorStoreNodeConstructorArgs): boolean {
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return args.meta.operationModes?.includes('update') ?? false;
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}
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function getOperationModeOptions(args: VectorStoreNodeConstructorArgs): INodePropertyOptions[] {
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const enabledOperationModes = args.meta.operationModes ?? DEFAULT_OPERATION_MODES;
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const allOptions = [
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{
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name: 'Get Many',
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value: 'load',
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description: 'Get many ranked documents from vector store for query',
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action: 'Get many ranked documents from vector store for query',
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},
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{
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name: 'Insert Documents',
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value: 'insert',
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description: 'Insert documents into vector store',
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action: 'Insert documents into vector store',
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},
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{
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name: 'Retrieve Documents (For Agent/Chain)',
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value: 'retrieve',
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description: 'Retrieve documents from vector store to be used with AI nodes',
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action: 'Retrieve documents from vector store to be used with AI nodes',
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},
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{
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name: 'Update Documents',
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value: 'update',
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description: 'Update documents in vector store by ID',
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action: 'Update documents in vector store by ID',
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},
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];
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return allOptions.filter(({ value }) =>
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enabledOperationModes.includes(value as NodeOperationMode),
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);
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}
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export const createVectorStoreNode = (args: VectorStoreNodeConstructorArgs) =>
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class VectorStoreNodeType implements INodeType {
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description: INodeTypeDescription = {
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@ -101,11 +147,11 @@ export const createVectorStoreNode = (args: VectorStoreNodeConstructorArgs) =>
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const mode = parameters?.mode;
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const inputs = [{ displayName: "Embedding", type: "${NodeConnectionType.AiEmbedding}", required: true, maxConnections: 1}]
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if (['insert', 'load'].includes(mode)) {
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if (['insert', 'load', 'update'].includes(mode)) {
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inputs.push({ displayName: "", type: "${NodeConnectionType.Main}"})
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}
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if (mode === 'insert') {
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if (['insert'].includes(mode)) {
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inputs.push({ displayName: "Document", type: "${NodeConnectionType.AiDocument}", required: true, maxConnections: 1})
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}
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return inputs
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@ -127,26 +173,7 @@ export const createVectorStoreNode = (args: VectorStoreNodeConstructorArgs) =>
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type: 'options',
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noDataExpression: true,
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default: 'retrieve',
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options: [
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{
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name: 'Get Many',
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value: 'load',
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description: 'Get many ranked documents from vector store for query',
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action: 'Get many ranked documents from vector store for query',
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},
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{
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name: 'Insert Documents',
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value: 'insert',
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description: 'Insert documents into vector store',
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action: 'Insert documents into vector store',
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},
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{
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name: 'Retrieve Documents (For Agent/Chain)',
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value: 'retrieve',
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description: 'Retrieve documents from vector store to be used with AI nodes',
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action: 'Retrieve documents from vector store to be used with AI nodes',
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},
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],
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options: getOperationModeOptions(args),
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},
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{
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...getConnectionHintNoticeField([NodeConnectionType.AiRetriever]),
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@ -185,15 +212,30 @@ export const createVectorStoreNode = (args: VectorStoreNodeConstructorArgs) =>
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},
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},
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},
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// ID is always used for update operation
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{
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displayName: 'ID',
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name: 'id',
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type: 'string',
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default: '',
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required: true,
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description: 'ID of an embedding entry',
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displayOptions: {
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show: {
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mode: ['update'],
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},
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},
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},
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...transformDescriptionForOperationMode(args.loadFields ?? [], 'load'),
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...transformDescriptionForOperationMode(args.retrieveFields ?? [], 'retrieve'),
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...transformDescriptionForOperationMode(args.updateFields ?? [], 'update'),
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],
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};
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methods = args.methods;
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async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
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const mode = this.getNodeParameter('mode', 0) as 'load' | 'insert' | 'retrieve';
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const mode = this.getNodeParameter('mode', 0) as NodeOperationMode;
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const embeddings = (await this.getInputConnectionData(
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NodeConnectionType.AiEmbedding,
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@ -208,7 +250,7 @@ export const createVectorStoreNode = (args: VectorStoreNodeConstructorArgs) =>
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const filter = getMetadataFiltersValues(this, itemIndex);
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const vectorStore = await args.getVectorStoreClient(
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this,
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// We'll pass filter to similaritySearchVectorWithScore instaed of getVectorStoreClient
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// We'll pass filter to similaritySearchVectorWithScore instead of getVectorStoreClient
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undefined,
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embeddings,
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itemIndex,
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@ -274,6 +316,60 @@ export const createVectorStoreNode = (args: VectorStoreNodeConstructorArgs) =>
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return [resultData];
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}
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if (mode === 'update') {
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if (!isUpdateSupported(args)) {
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throw new NodeOperationError(
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this.getNode(),
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'Update operation is not implemented for this Vector Store',
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);
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}
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const items = this.getInputData();
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const loader = new N8nJsonLoader(this);
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const resultData = [];
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for (let itemIndex = 0; itemIndex < items.length; itemIndex++) {
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const itemData = items[itemIndex];
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const documentId = this.getNodeParameter('id', itemIndex, '', {
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extractValue: true,
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}) as string;
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const vectorStore = await args.getVectorStoreClient(
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this,
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undefined,
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embeddings,
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itemIndex,
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);
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const { processedDocuments, serializedDocuments } = await processDocument(
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loader,
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itemData,
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itemIndex,
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);
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if (processedDocuments?.length !== 1) {
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throw new NodeOperationError(this.getNode(), 'Single document per item expected');
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}
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resultData.push(...serializedDocuments);
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try {
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// Use ids option to upsert instead of insert
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await vectorStore.addDocuments(processedDocuments, {
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ids: [documentId],
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});
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void logAiEvent(this, 'n8n.ai.vector.store.updated');
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} catch (error) {
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throw error;
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}
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}
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return [resultData];
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}
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throw new NodeOperationError(
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this.getNode(),
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'Only the "load" and "insert" operation modes are supported with execute',
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@ -27,7 +27,7 @@ export function getMetadataFiltersValues(
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ctx: IExecuteFunctions,
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itemIndex: number,
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): Record<string, never> | undefined {
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const options = ctx.getNodeParameter('options', itemIndex);
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const options = ctx.getNodeParameter('options', itemIndex, {});
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if (options.metadata) {
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const { metadataValues: metadata } = options.metadata as {
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@ -2145,6 +2145,7 @@ export const eventNamesAiNodes = [
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'n8n.ai.llm.generated',
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'n8n.ai.llm.error',
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'n8n.ai.vector.store.populated',
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'n8n.ai.vector.store.updated',
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] as const;
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export type EventNamesAiNodesType = (typeof eventNamesAiNodes)[number];
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