import { RecursiveCharacterTextSplitter, type TextSplitter } from '@langchain/textsplitters'; import { NodeConnectionTypes, type INodeType, type INodeTypeDescription, type ISupplyDataFunctions, type SupplyData, type IDataObject, type INodeInputConfiguration, } from 'n8n-workflow'; import { logWrapper } from '@utils/logWrapper'; import { N8nBinaryLoader } from '@utils/N8nBinaryLoader'; import { N8nJsonLoader } from '@utils/N8nJsonLoader'; import { metadataFilterField } from '@utils/sharedFields'; // Dependencies needed underneath the hood for the loaders. We add them // here only to track where what dependency is sued // import 'd3-dsv'; // for csv import 'mammoth'; // for docx import 'epub2'; // for epub import 'pdf-parse'; // for pdf function getInputs(parameters: IDataObject) { const inputs: INodeInputConfiguration[] = []; const textSplittingMode = parameters?.textSplittingMode; // If text splitting mode is 'custom' or does not exist (v1), we need to add an input for the text splitter if (!textSplittingMode || textSplittingMode === 'custom') { inputs.push({ displayName: 'Text Splitter', maxConnections: 1, type: 'ai_textSplitter', required: true, }); } return inputs; } export class DocumentDefaultDataLoader implements INodeType { description: INodeTypeDescription = { displayName: 'Default Data Loader', name: 'documentDefaultDataLoader', icon: 'file:binary.svg', group: ['transform'], version: [1, 1.1], defaultVersion: 1.1, description: 'Load data from previous step in the workflow', defaults: { name: 'Default Data Loader', }, codex: { categories: ['AI'], subcategories: { AI: ['Document Loaders'], }, resources: { primaryDocumentation: [ { url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.documentdefaultdataloader/', }, ], }, }, inputs: `={{ ((parameter) => { ${getInputs.toString()}; return getInputs(parameter) })($parameter) }}`, outputs: [NodeConnectionTypes.AiDocument], outputNames: ['Document'], properties: [ { displayName: 'This will load data from a previous step in the workflow. Example', name: 'notice', type: 'notice', default: '', }, { displayName: 'Type of Data', name: 'dataType', type: 'options', default: 'json', required: true, noDataExpression: true, options: [ { name: 'JSON', value: 'json', description: 'Process JSON data from previous step in the workflow', }, { name: 'Binary', value: 'binary', description: 'Process binary data from previous step in the workflow', }, ], }, { displayName: 'Mode', name: 'jsonMode', type: 'options', default: 'allInputData', required: true, displayOptions: { show: { dataType: ['json'], }, }, options: [ { name: 'Load All Input Data', value: 'allInputData', description: 'Use all JSON data that flows into the parent agent or chain', }, { name: 'Load Specific Data', value: 'expressionData', description: 'Load a subset of data, and/or data from any previous step in the workflow', }, ], }, { displayName: 'Mode', name: 'binaryMode', type: 'options', default: 'allInputData', required: true, displayOptions: { show: { dataType: ['binary'], }, }, options: [ { name: 'Load All Input Data', value: 'allInputData', description: 'Use all Binary data that flows into the parent agent or chain', }, { name: 'Load Specific Data', value: 'specificField', description: 'Load data from a specific field in the parent agent or chain', }, ], }, { displayName: 'Data Format', name: 'loader', type: 'options', default: 'auto', required: true, displayOptions: { show: { dataType: ['binary'], }, }, options: [ { name: 'Automatically Detect by Mime Type', value: 'auto', description: 'Uses the mime type to detect the format', }, { name: 'CSV', value: 'csvLoader', description: 'Load CSV files', }, { name: 'Docx', value: 'docxLoader', description: 'Load Docx documents', }, { name: 'EPub', value: 'epubLoader', description: 'Load EPub files', }, { name: 'JSON', value: 'jsonLoader', description: 'Load JSON files', }, { name: 'PDF', value: 'pdfLoader', description: 'Load PDF documents', }, { name: 'Text', value: 'textLoader', description: 'Load plain text files', }, ], }, { displayName: 'Data', name: 'jsonData', type: 'string', typeOptions: { rows: 6, }, default: '', required: true, description: 'Drag and drop fields from the input pane, or use an expression', displayOptions: { show: { dataType: ['json'], jsonMode: ['expressionData'], }, }, }, { displayName: 'Input Data Field Name', name: 'binaryDataKey', type: 'string', default: 'data', required: true, description: 'The name of the field in the agent or chain’s input that contains the binary file to be processed', displayOptions: { show: { dataType: ['binary'], }, hide: { binaryMode: ['allInputData'], }, }, }, { displayName: 'Text Splitting', name: 'textSplittingMode', type: 'options', default: 'simple', required: true, noDataExpression: true, displayOptions: { show: { '@version': [1.1], }, }, options: [ { name: 'Simple', value: 'simple', description: 'Splits every 1000 characters with a 200 character overlap', }, { name: 'Custom', value: 'custom', description: 'Connect a custom text-splitting sub-node', }, ], }, { displayName: 'Options', name: 'options', type: 'collection', placeholder: 'Add Option', default: {}, options: [ { displayName: 'JSON Pointers', name: 'pointers', type: 'string', default: '', description: 'Pointers to extract from JSON, e.g. "/text" or "/text, /meta/title"', displayOptions: { show: { '/loader': ['jsonLoader', 'auto'], }, }, }, { displayName: 'CSV Separator', name: 'separator', type: 'string', description: 'Separator to use for CSV', default: ',', displayOptions: { show: { '/loader': ['csvLoader', 'auto'], }, }, }, { displayName: 'CSV Column', name: 'column', type: 'string', default: '', description: 'Column to extract from CSV', displayOptions: { show: { '/loader': ['csvLoader', 'auto'], }, }, }, { displayName: 'Split Pages in PDF', description: 'Whether to split PDF pages into separate documents', name: 'splitPages', type: 'boolean', default: true, displayOptions: { show: { '/loader': ['pdfLoader', 'auto'], }, }, }, { ...metadataFilterField, displayName: 'Metadata', description: 'Metadata to add to each document. Could be used for filtering during retrieval', placeholder: 'Add property', }, ], }, ], }; async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise { const node = this.getNode(); const dataType = this.getNodeParameter('dataType', itemIndex, 'json') as 'json' | 'binary'; let textSplitter: TextSplitter | undefined; if (node.typeVersion === 1.1) { const textSplittingMode = this.getNodeParameter('textSplittingMode', itemIndex, 'simple') as | 'simple' | 'custom'; if (textSplittingMode === 'simple') { textSplitter = new RecursiveCharacterTextSplitter({ chunkSize: 1000, chunkOverlap: 200 }); } else if (textSplittingMode === 'custom') { textSplitter = (await this.getInputConnectionData(NodeConnectionTypes.AiTextSplitter, 0)) as | TextSplitter | undefined; } } else { textSplitter = (await this.getInputConnectionData(NodeConnectionTypes.AiTextSplitter, 0)) as | TextSplitter | undefined; } const binaryDataKey = this.getNodeParameter('binaryDataKey', itemIndex, '') as string; const processor = dataType === 'binary' ? new N8nBinaryLoader(this, 'options.', binaryDataKey, textSplitter) : new N8nJsonLoader(this, 'options.', textSplitter); return { response: logWrapper(processor, this), }; } }