mirror of
https://github.com/n8n-io/n8n.git
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278 lines
7 KiB
TypeScript
278 lines
7 KiB
TypeScript
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import {
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NodeConnectionType,
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type IExecuteFunctions,
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type INodeExecutionData,
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type INodeType,
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type INodeTypeDescription,
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} from 'n8n-workflow';
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import type { SummarizationChainParams } from 'langchain/chains';
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import { loadSummarizationChain } from 'langchain/chains';
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import type { BaseLanguageModel } from 'langchain/dist/base_language';
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import type { Document } from 'langchain/document';
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import { PromptTemplate } from 'langchain/prompts';
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import { N8nJsonLoader } from '../../../utils/N8nJsonLoader';
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import { N8nBinaryLoader } from '../../../utils/N8nBinaryLoader';
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import { getTemplateNoticeField } from '../../../utils/sharedFields';
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import { REFINE_PROMPT_TEMPLATE, DEFAULT_PROMPT_TEMPLATE } from './prompt';
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export class ChainSummarization implements INodeType {
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description: INodeTypeDescription = {
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displayName: 'Summarization Chain',
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name: 'chainSummarization',
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icon: 'fa:link',
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group: ['transform'],
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version: 1,
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description: 'Transforms text into a concise summary',
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defaults: {
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name: 'Summarization Chain',
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color: '#909298',
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},
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codex: {
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alias: ['LangChain'],
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categories: ['AI'],
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subcategories: {
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AI: ['Chains'],
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},
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resources: {
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primaryDocumentation: [
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{
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url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainsummarization/',
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},
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],
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},
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},
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// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
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inputs: [
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NodeConnectionType.Main,
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{
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displayName: 'Model',
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maxConnections: 1,
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type: NodeConnectionType.AiLanguageModel,
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required: true,
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},
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{
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displayName: 'Document',
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maxConnections: 1,
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type: NodeConnectionType.AiDocument,
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required: true,
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},
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],
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outputs: [NodeConnectionType.Main],
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credentials: [],
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properties: [
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getTemplateNoticeField(1951),
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{
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displayName: 'Type',
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name: 'type',
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type: 'options',
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description: 'The type of summarization to run',
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default: 'map_reduce',
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options: [
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{
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name: 'Map Reduce (Recommended)',
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value: 'map_reduce',
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description:
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'Summarize each document (or chunk) individually, then summarize those summaries',
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},
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{
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name: 'Refine',
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value: 'refine',
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description:
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'Summarize the first document (or chunk). Then update that summary based on the next document (or chunk), and repeat.',
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},
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{
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name: 'Stuff',
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value: 'stuff',
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description: 'Pass all documents (or chunks) at once. Ideal for small datasets.',
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},
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],
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},
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{
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displayName: 'Options',
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name: 'options',
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type: 'collection',
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default: {},
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placeholder: 'Add Option',
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options: [
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{
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displayName: 'Final Prompt to Combine',
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name: 'combineMapPrompt',
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type: 'string',
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hint: 'The prompt to combine individual summaries',
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displayOptions: {
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show: {
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'/type': ['map_reduce'],
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},
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},
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default: DEFAULT_PROMPT_TEMPLATE,
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typeOptions: {
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rows: 6,
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},
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},
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{
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displayName: 'Individual Summary Prompt',
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name: 'prompt',
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type: 'string',
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default: DEFAULT_PROMPT_TEMPLATE,
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hint: 'The prompt to summarize an individual document (or chunk)',
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displayOptions: {
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show: {
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'/type': ['map_reduce'],
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},
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},
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typeOptions: {
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rows: 6,
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},
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},
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{
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displayName: 'Prompt',
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name: 'prompt',
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type: 'string',
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default: DEFAULT_PROMPT_TEMPLATE,
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displayOptions: {
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show: {
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'/type': ['stuff'],
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},
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},
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typeOptions: {
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rows: 6,
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},
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},
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{
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displayName: 'Subsequent (Refine) Prompt',
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name: 'refinePrompt',
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type: 'string',
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displayOptions: {
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show: {
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'/type': ['refine'],
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},
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},
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default: REFINE_PROMPT_TEMPLATE,
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hint: 'The prompt to refine the summary based on the next document (or chunk)',
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typeOptions: {
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rows: 6,
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},
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},
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{
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displayName: 'Initial Prompt',
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name: 'refineQuestionPrompt',
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type: 'string',
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displayOptions: {
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show: {
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'/type': ['refine'],
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},
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},
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default: DEFAULT_PROMPT_TEMPLATE,
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hint: 'The prompt for the first document (or chunk)',
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typeOptions: {
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rows: 6,
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},
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},
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],
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},
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],
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};
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async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
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this.logger.verbose('Executing Vector Store QA Chain');
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const type = this.getNodeParameter('type', 0) as 'map_reduce' | 'stuff' | 'refine';
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const model = (await this.getInputConnectionData(
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NodeConnectionType.AiLanguageModel,
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0,
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)) as BaseLanguageModel;
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const documentInput = (await this.getInputConnectionData(NodeConnectionType.AiDocument, 0)) as
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| N8nJsonLoader
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| Array<Document<Record<string, unknown>>>;
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const options = this.getNodeParameter('options', 0, {}) as {
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prompt?: string;
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refineQuestionPrompt?: string;
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refinePrompt?: string;
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combineMapPrompt?: string;
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};
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const chainArgs: SummarizationChainParams = {
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type,
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};
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// Map reduce prompt override
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if (type === 'map_reduce') {
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const mapReduceArgs = chainArgs as SummarizationChainParams & {
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type: 'map_reduce';
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};
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if (options.combineMapPrompt) {
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mapReduceArgs.combineMapPrompt = new PromptTemplate({
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template: options.combineMapPrompt,
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inputVariables: ['text'],
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});
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}
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if (options.prompt) {
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mapReduceArgs.combinePrompt = new PromptTemplate({
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template: options.prompt,
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inputVariables: ['text'],
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});
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}
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}
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// Stuff prompt override
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if (type === 'stuff') {
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const stuffArgs = chainArgs as SummarizationChainParams & {
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type: 'stuff';
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};
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if (options.prompt) {
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stuffArgs.prompt = new PromptTemplate({
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template: options.prompt,
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inputVariables: ['text'],
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});
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}
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}
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// Refine prompt override
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if (type === 'refine') {
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const refineArgs = chainArgs as SummarizationChainParams & {
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type: 'refine';
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};
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if (options.refinePrompt) {
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refineArgs.refinePrompt = new PromptTemplate({
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template: options.refinePrompt,
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inputVariables: ['existing_answer', 'text'],
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});
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}
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if (options.refineQuestionPrompt) {
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refineArgs.questionPrompt = new PromptTemplate({
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template: options.refineQuestionPrompt,
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inputVariables: ['text'],
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});
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}
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}
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const chain = loadSummarizationChain(model, chainArgs);
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const items = this.getInputData();
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const returnData: INodeExecutionData[] = [];
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for (let itemIndex = 0; itemIndex < items.length; itemIndex++) {
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let processedDocuments: Document[];
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if (documentInput instanceof N8nJsonLoader || documentInput instanceof N8nBinaryLoader) {
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processedDocuments = await documentInput.processItem(items[itemIndex], itemIndex);
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} else {
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processedDocuments = documentInput;
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}
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const response = await chain.call({
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input_documents: processedDocuments,
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});
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returnData.push({ json: { response } });
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}
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return this.prepareOutputData(returnData);
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}
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}
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