mirror of
https://github.com/n8n-io/n8n.git
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463 lines
16 KiB
TypeScript
463 lines
16 KiB
TypeScript
import { NodeOperationError, NodeConnectionType } from 'n8n-workflow';
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import type { ConnectionTypes, IExecuteFunctions, INodeExecutionData } from 'n8n-workflow';
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import type { Tool } from '@langchain/core/tools';
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import type { BaseMessage } from '@langchain/core/messages';
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import type { InputValues, MemoryVariables, OutputValues } from '@langchain/core/memory';
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import type { BaseChatMessageHistory } from '@langchain/core/chat_history';
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import type { BaseCallbackConfig, Callbacks } from '@langchain/core/callbacks/manager';
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import { Embeddings } from '@langchain/core/embeddings';
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import { VectorStore } from '@langchain/core/vectorstores';
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import type { Document } from '@langchain/core/documents';
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import { TextSplitter } from '@langchain/textsplitters';
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import type { BaseChatMemory } from '@langchain/community/memory/chat_memory';
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import { BaseRetriever } from '@langchain/core/retrievers';
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import { BaseOutputParser, OutputParserException } from '@langchain/core/output_parsers';
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import { isObject } from 'lodash';
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import type { BaseDocumentLoader } from 'langchain/dist/document_loaders/base';
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import { N8nJsonLoader } from './N8nJsonLoader';
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import { N8nBinaryLoader } from './N8nBinaryLoader';
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import { logAiEvent, isToolsInstance, isBaseChatMemory, isBaseChatMessageHistory } from './helpers';
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const errorsMap: { [key: string]: { message: string; description: string } } = {
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'You exceeded your current quota, please check your plan and billing details.': {
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message: 'OpenAI quota exceeded',
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description: 'You exceeded your current quota, please check your plan and billing details.',
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},
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};
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export async function callMethodAsync<T>(
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this: T,
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parameters: {
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executeFunctions: IExecuteFunctions;
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connectionType: ConnectionTypes;
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currentNodeRunIndex: number;
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method: (...args: any[]) => Promise<unknown>;
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arguments: unknown[];
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},
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): Promise<unknown> {
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try {
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return await parameters.method.call(this, ...parameters.arguments);
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} catch (e) {
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// Langchain checks for OutputParserException to run retry chain
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// for auto-fixing the output so skip wrapping in this case
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if (e instanceof OutputParserException) throw e;
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// Propagate errors from sub-nodes
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if (e.functionality === 'configuration-node') throw e;
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const connectedNode = parameters.executeFunctions.getNode();
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const error = new NodeOperationError(connectedNode, e, {
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functionality: 'configuration-node',
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});
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if (errorsMap[error.message]) {
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error.description = errorsMap[error.message].description;
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error.message = errorsMap[error.message].message;
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}
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parameters.executeFunctions.addOutputData(
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parameters.connectionType,
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parameters.currentNodeRunIndex,
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error,
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);
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if (error.message) {
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error.description = error.message;
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throw error;
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}
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throw new NodeOperationError(
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connectedNode,
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`Error on node "${connectedNode.name}" which is connected via input "${parameters.connectionType}"`,
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{ functionality: 'configuration-node' },
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);
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}
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}
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export function callMethodSync<T>(
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this: T,
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parameters: {
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executeFunctions: IExecuteFunctions;
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connectionType: ConnectionTypes;
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currentNodeRunIndex: number;
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method: (...args: any[]) => T;
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arguments: unknown[];
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},
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): unknown {
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try {
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return parameters.method.call(this, ...parameters.arguments);
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} catch (e) {
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// Propagate errors from sub-nodes
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if (e.functionality === 'configuration-node') throw e;
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const connectedNode = parameters.executeFunctions.getNode();
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const error = new NodeOperationError(connectedNode, e);
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parameters.executeFunctions.addOutputData(
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parameters.connectionType,
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parameters.currentNodeRunIndex,
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error,
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);
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throw new NodeOperationError(
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connectedNode,
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`Error on node "${connectedNode.name}" which is connected via input "${parameters.connectionType}"`,
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{ functionality: 'configuration-node' },
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);
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}
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}
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export function logWrapper(
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originalInstance:
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| Tool
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| BaseChatMemory
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| BaseChatMessageHistory
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| BaseOutputParser
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| BaseRetriever
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| Embeddings
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| Document[]
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| Document
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| BaseDocumentLoader
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| TextSplitter
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| VectorStore
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| N8nBinaryLoader
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| N8nJsonLoader,
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executeFunctions: IExecuteFunctions,
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) {
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return new Proxy(originalInstance, {
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get: (target, prop) => {
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let connectionType: ConnectionTypes | undefined;
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// ========== BaseChatMemory ==========
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if (isBaseChatMemory(originalInstance)) {
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if (prop === 'loadMemoryVariables' && 'loadMemoryVariables' in target) {
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return async (values: InputValues): Promise<MemoryVariables> => {
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connectionType = NodeConnectionType.AiMemory;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { action: 'loadMemoryVariables', values } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [values],
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})) as MemoryVariables;
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const chatHistory = (response?.chat_history as BaseMessage[]) ?? response;
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executeFunctions.addOutputData(connectionType, index, [
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[{ json: { action: 'loadMemoryVariables', chatHistory } }],
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]);
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return response;
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};
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} else if (prop === 'saveContext' && 'saveContext' in target) {
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return async (input: InputValues, output: OutputValues): Promise<MemoryVariables> => {
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connectionType = NodeConnectionType.AiMemory;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { action: 'saveContext', input, output } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [input, output],
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})) as MemoryVariables;
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const chatHistory = await target.chatHistory.getMessages();
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executeFunctions.addOutputData(connectionType, index, [
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[{ json: { action: 'saveContext', chatHistory } }],
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]);
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return response;
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};
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}
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}
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// ========== BaseChatMessageHistory ==========
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if (isBaseChatMessageHistory(originalInstance)) {
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if (prop === 'getMessages' && 'getMessages' in target) {
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return async (): Promise<BaseMessage[]> => {
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connectionType = NodeConnectionType.AiMemory;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { action: 'getMessages' } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [],
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})) as BaseMessage[];
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const payload = { action: 'getMessages', response };
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executeFunctions.addOutputData(connectionType, index, [[{ json: payload }]]);
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void logAiEvent(executeFunctions, 'n8n.ai.memory.get.messages', { response });
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return response;
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};
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} else if (prop === 'addMessage' && 'addMessage' in target) {
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return async (message: BaseMessage): Promise<void> => {
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connectionType = NodeConnectionType.AiMemory;
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const payload = { action: 'addMessage', message };
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const { index } = executeFunctions.addInputData(connectionType, [[{ json: payload }]]);
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await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [message],
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});
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void logAiEvent(executeFunctions, 'n8n.ai.memory.added.message', { message });
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executeFunctions.addOutputData(connectionType, index, [[{ json: payload }]]);
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};
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}
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}
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// ========== BaseOutputParser ==========
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if (originalInstance instanceof BaseOutputParser) {
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if (prop === 'parse' && 'parse' in target) {
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return async (text: string | Record<string, unknown>): Promise<unknown> => {
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connectionType = NodeConnectionType.AiOutputParser;
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const stringifiedText = isObject(text) ? JSON.stringify(text) : text;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { action: 'parse', text: stringifiedText } }],
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]);
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try {
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [stringifiedText],
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})) as object;
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void logAiEvent(executeFunctions, 'n8n.ai.output.parser.parsed', { text, response });
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executeFunctions.addOutputData(connectionType, index, [
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[{ json: { action: 'parse', response } }],
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]);
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return response;
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} catch (error) {
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void logAiEvent(executeFunctions, 'n8n.ai.output.parser.parsed', {
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text,
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response: error.message ?? error,
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});
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executeFunctions.addOutputData(connectionType, index, [
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[{ json: { action: 'parse', response: error.message ?? error } }],
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]);
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throw error;
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}
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};
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}
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}
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// ========== BaseRetriever ==========
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if (originalInstance instanceof BaseRetriever) {
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if (prop === 'getRelevantDocuments' && 'getRelevantDocuments' in target) {
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return async (
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query: string,
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config?: Callbacks | BaseCallbackConfig,
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): Promise<Document[]> => {
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connectionType = NodeConnectionType.AiRetriever;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { query, config } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [query, config],
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})) as Array<Document<Record<string, any>>>;
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void logAiEvent(executeFunctions, 'n8n.ai.retriever.get.relevant.documents', { query });
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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}
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// ========== Embeddings ==========
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if (originalInstance instanceof Embeddings) {
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// Docs -> Embeddings
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if (prop === 'embedDocuments' && 'embedDocuments' in target) {
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return async (documents: string[]): Promise<number[][]> => {
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connectionType = NodeConnectionType.AiEmbedding;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { documents } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [documents],
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})) as number[][];
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void logAiEvent(executeFunctions, 'n8n.ai.embeddings.embedded.document');
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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// Query -> Embeddings
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if (prop === 'embedQuery' && 'embedQuery' in target) {
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return async (query: string): Promise<number[]> => {
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connectionType = NodeConnectionType.AiEmbedding;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { query } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [query],
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})) as number[];
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void logAiEvent(executeFunctions, 'n8n.ai.embeddings.embedded.query');
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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}
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// ========== N8n Loaders Process All ==========
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if (
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originalInstance instanceof N8nJsonLoader ||
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originalInstance instanceof N8nBinaryLoader
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) {
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// Process All
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if (prop === 'processAll' && 'processAll' in target) {
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return async (items: INodeExecutionData[]): Promise<number[]> => {
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connectionType = NodeConnectionType.AiDocument;
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const { index } = executeFunctions.addInputData(connectionType, [items]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [items],
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})) as number[];
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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// Process Each
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if (prop === 'processItem' && 'processItem' in target) {
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return async (item: INodeExecutionData, itemIndex: number): Promise<number[]> => {
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connectionType = NodeConnectionType.AiDocument;
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const { index } = executeFunctions.addInputData(connectionType, [[item]]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [item, itemIndex],
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})) as number[];
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void logAiEvent(executeFunctions, 'n8n.ai.document.processed');
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executeFunctions.addOutputData(connectionType, index, [
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[{ json: { response }, pairedItem: { item: itemIndex } }],
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]);
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return response;
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};
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}
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}
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// ========== TextSplitter ==========
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if (originalInstance instanceof TextSplitter) {
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if (prop === 'splitText' && 'splitText' in target) {
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return async (text: string): Promise<string[]> => {
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connectionType = NodeConnectionType.AiTextSplitter;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { textSplitter: text } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [text],
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})) as string[];
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void logAiEvent(executeFunctions, 'n8n.ai.text.splitter.split');
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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}
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// ========== Tool ==========
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if (isToolsInstance(originalInstance)) {
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if (prop === '_call' && '_call' in target) {
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return async (query: string): Promise<string> => {
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connectionType = NodeConnectionType.AiTool;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { query } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [query],
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})) as string;
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void logAiEvent(executeFunctions, 'n8n.ai.tool.called', { query, response });
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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}
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// ========== VectorStore ==========
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if (originalInstance instanceof VectorStore) {
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if (prop === 'similaritySearch' && 'similaritySearch' in target) {
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return async (
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query: string,
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k?: number,
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// @ts-ignore
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filter?: BiquadFilterType | undefined,
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_callbacks?: Callbacks | undefined,
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): Promise<Document[]> => {
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connectionType = NodeConnectionType.AiVectorStore;
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const { index } = executeFunctions.addInputData(connectionType, [
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[{ json: { query, k, filter } }],
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]);
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const response = (await callMethodAsync.call(target, {
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executeFunctions,
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connectionType,
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currentNodeRunIndex: index,
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method: target[prop],
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arguments: [query, k, filter, _callbacks],
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})) as Array<Document<Record<string, any>>>;
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void logAiEvent(executeFunctions, 'n8n.ai.vector.store.searched', { query });
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executeFunctions.addOutputData(connectionType, index, [[{ json: { response } }]]);
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return response;
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};
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}
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}
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// eslint-disable-next-line @typescript-eslint/no-unsafe-return
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return (target as any)[prop];
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},
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});
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}
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