import type { IDataObject, IExecuteFunctions, INodeExecutionData, INodeParameters, INodeType, INodeTypeDescription, } from 'n8n-workflow'; import { NodeConnectionType } from 'n8n-workflow'; import type { BaseLanguageModel } from '@langchain/core/language_models/base'; import { HumanMessage } from '@langchain/core/messages'; import { SystemMessagePromptTemplate, ChatPromptTemplate } from '@langchain/core/prompts'; import { StructuredOutputParser } from 'langchain/output_parsers'; import { z } from 'zod'; import { getTracingConfig } from '../../../utils/tracing'; const SYSTEM_PROMPT_TEMPLATE = "Please classify the text provided by the user into one of the following categories: {categories}, and use the provided formatting instructions below. Don't explain, and only output the json."; const configuredOutputs = (parameters: INodeParameters) => { const categories = ((parameters.categories as IDataObject)?.categories as IDataObject[]) ?? []; const fallback = (parameters.options as IDataObject)?.fallback as string; const ret = categories.map((cat) => { return { type: NodeConnectionType.Main, displayName: cat.category }; }); if (fallback === 'other') ret.push({ type: NodeConnectionType.Main, displayName: 'Other' }); return ret; }; export class TextClassifier implements INodeType { description: INodeTypeDescription = { displayName: 'Text Classifier', name: 'textClassifier', icon: 'fa:tags', iconColor: 'black', group: ['transform'], version: 1, description: 'Classify your text into distinct categories', codex: { categories: ['AI'], subcategories: { AI: ['Chains', 'Root Nodes'], }, resources: { primaryDocumentation: [ { url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.text-classifier/', }, ], }, }, defaults: { name: 'Text Classifier', }, inputs: [ { displayName: '', type: NodeConnectionType.Main }, { displayName: 'Model', maxConnections: 1, type: NodeConnectionType.AiLanguageModel, required: true, }, ], outputs: `={{(${configuredOutputs})($parameter)}}`, properties: [ { displayName: 'Text to Classify', name: 'inputText', type: 'string', required: true, default: '', description: 'Use an expression to reference data in previous nodes or enter static text', typeOptions: { rows: 2, }, }, { displayName: 'Categories', name: 'categories', placeholder: 'Add Category', type: 'fixedCollection', default: {}, typeOptions: { multipleValues: true, }, options: [ { name: 'categories', displayName: 'Categories', values: [ { displayName: 'Category', name: 'category', type: 'string', default: '', description: 'Category to add', required: true, }, { displayName: 'Description', name: 'description', type: 'string', default: '', description: "Describe your category if it's not obvious", }, ], }, ], }, { displayName: 'Options', name: 'options', type: 'collection', default: {}, placeholder: 'Add Option', options: [ { displayName: 'Allow Multiple Classes To Be True', name: 'multiClass', type: 'boolean', default: false, }, { displayName: 'When No Clear Match', name: 'fallback', type: 'options', default: 'discard', description: 'What to do with items that don’t match the categories exactly', options: [ { name: 'Discard Item', value: 'discard', description: 'Ignore the item and drop it from the output', }, { name: "Output on Extra, 'Other' Branch", value: 'other', description: "Create a separate output branch called 'Other'", }, ], }, { displayName: 'System Prompt Template', name: 'systemPromptTemplate', type: 'string', default: SYSTEM_PROMPT_TEMPLATE, description: 'String to use directly as the system prompt template', typeOptions: { rows: 6, }, }, ], }, ], }; async execute(this: IExecuteFunctions): Promise { const items = this.getInputData(); const llm = (await this.getInputConnectionData( NodeConnectionType.AiLanguageModel, 0, )) as BaseLanguageModel; const categories = this.getNodeParameter('categories.categories', 0) as Array<{ category: string; description: string; }>; const options = this.getNodeParameter('options', 0, {}) as { multiClass: boolean; fallback?: string; systemPromptTemplate?: string; }; const multiClass = options?.multiClass ?? false; const fallback = options?.fallback ?? 'discard'; const schemaEntries = categories.map((cat) => [ cat.category, z .boolean() .describe( `Should be true if the input has category "${cat.category}" (description: ${cat.description})`, ), ]); if (fallback === 'other') schemaEntries.push([ 'fallback', z.boolean().describe('Should be true if none of the other categories apply'), ]); const schema = z.object(Object.fromEntries(schemaEntries)); const parser = StructuredOutputParser.fromZodSchema(schema); const multiClassPrompt = multiClass ? 'Categories are not mutually exclusive, and multiple can be true' : 'Categories are mutually exclusive, and only one can be true'; const fallbackPrompt = { other: 'If no categories apply, select the "fallback" option.', discard: 'If there is not a very fitting category, select none of the categories.', }[fallback]; const returnData: INodeExecutionData[][] = Array.from( { length: categories.length + (fallback === 'other' ? 1 : 0) }, (_) => [], ); for (let itemIdx = 0; itemIdx < items.length; itemIdx++) { const item = items[itemIdx]; item.pairedItem = { item: itemIdx }; const input = this.getNodeParameter('inputText', itemIdx) as string; const inputPrompt = new HumanMessage(input); const systemPromptTemplateOpt = this.getNodeParameter( 'options.systemPromptTemplate', itemIdx, ) as string; const systemPromptTemplate = SystemMessagePromptTemplate.fromTemplate( `${systemPromptTemplateOpt ?? SYSTEM_PROMPT_TEMPLATE} {format_instructions} ${multiClassPrompt} ${fallbackPrompt}`, ); const messages = [ await systemPromptTemplate.format({ categories: categories.map((cat) => cat.category).join(', '), format_instructions: parser.getFormatInstructions(), }), inputPrompt, ]; const prompt = ChatPromptTemplate.fromMessages(messages); const chain = prompt.pipe(llm).pipe(parser).withConfig(getTracingConfig(this)); try { const output = await chain.invoke(messages); categories.forEach((cat, idx) => { if (output[cat.category]) returnData[idx].push(item); }); if (fallback === 'other' && output.fallback) returnData[returnData.length - 1].push(item); } catch (error) { if (this.continueOnFail(error)) { returnData[0].push({ json: { error: error.message }, pairedItem: { item: itemIdx }, }); continue; } throw error; } } return returnData; } }