2023-12-08 04:42:32 -08:00
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import { NodeConnectionType } from 'n8n-workflow';
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import type {
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INodeTypeBaseDescription,
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IExecuteFunctions,
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INodeExecutionData,
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INodeType,
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INodeTypeDescription,
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IDataObject,
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} from 'n8n-workflow';
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import { loadSummarizationChain } from 'langchain/chains';
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2024-03-07 02:36:36 -08:00
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import type { BaseLanguageModel } from '@langchain/core/language_models/base';
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import type { Document } from '@langchain/core/documents';
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2024-05-24 05:43:17 -07:00
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import type { TextSplitter } from '@langchain/textsplitters';
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import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
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2023-12-08 04:42:32 -08:00
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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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import { getChainPromptsArgs } from '../helpers';
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2024-04-08 13:51:49 -07:00
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import { getTracingConfig } from '../../../../utils/tracing';
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2023-12-08 04:42:32 -08:00
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function getInputs(parameters: IDataObject) {
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const chunkingMode = parameters?.chunkingMode;
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const operationMode = parameters?.operationMode;
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const inputs = [
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{ displayName: '', type: 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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if (operationMode === 'documentLoader') {
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inputs.push({
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displayName: 'Document',
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type: NodeConnectionType.AiDocument,
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required: true,
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maxConnections: 1,
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});
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return inputs;
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}
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if (chunkingMode === 'advanced') {
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inputs.push({
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displayName: 'Text Splitter',
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type: NodeConnectionType.AiTextSplitter,
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required: false,
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maxConnections: 1,
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});
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return inputs;
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}
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return inputs;
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}
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export class ChainSummarizationV2 implements INodeType {
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description: INodeTypeDescription;
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constructor(baseDescription: INodeTypeBaseDescription) {
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this.description = {
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...baseDescription,
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version: [2],
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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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// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
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inputs: `={{ ((parameter) => { ${getInputs.toString()}; return getInputs(parameter) })($parameter) }}`,
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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: 'Data to Summarize',
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name: 'operationMode',
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noDataExpression: true,
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type: 'options',
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description: 'How to pass data into the summarization chain',
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default: 'nodeInputJson',
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options: [
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{
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name: 'Use Node Input (JSON)',
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value: 'nodeInputJson',
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description: 'Summarize the JSON data coming into this node from the previous one',
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},
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{
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name: 'Use Node Input (Binary)',
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value: 'nodeInputBinary',
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description: 'Summarize the binary data coming into this node from the previous one',
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},
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{
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name: 'Use Document Loader',
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value: 'documentLoader',
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description: 'Use a loader sub-node with more configuration options',
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},
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],
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},
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{
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displayName: 'Chunking Strategy',
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name: 'chunkingMode',
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noDataExpression: true,
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type: 'options',
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description: 'Chunk splitting strategy',
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default: 'simple',
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options: [
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{
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name: 'Simple (Define Below)',
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value: 'simple',
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},
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{
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name: 'Advanced',
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value: 'advanced',
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description: 'Use a splitter sub-node with more configuration options',
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},
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],
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displayOptions: {
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show: {
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'/operationMode': ['nodeInputJson', 'nodeInputBinary'],
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},
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},
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},
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{
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displayName: 'Characters Per Chunk',
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name: 'chunkSize',
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description:
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'Controls the max size (in terms of number of characters) of the final document chunk',
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type: 'number',
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default: 1000,
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displayOptions: {
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show: {
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'/chunkingMode': ['simple'],
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},
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},
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},
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{
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displayName: 'Chunk Overlap (Characters)',
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name: 'chunkOverlap',
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type: 'number',
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description: 'Specifies how much characters overlap there should be between chunks',
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default: 200,
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displayOptions: {
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show: {
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'/chunkingMode': ['simple'],
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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: 'Input Data Field Name',
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name: 'binaryDataKey',
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type: 'string',
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default: 'data',
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description:
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'The name of the field in the agent or chain’s input that contains the binary file to be processed',
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displayOptions: {
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show: {
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'/operationMode': ['nodeInputBinary'],
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},
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},
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},
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{
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displayName: 'Summarization Method and Prompts',
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name: 'summarizationMethodAndPrompts',
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type: 'fixedCollection',
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default: {
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values: {
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summarizationMethod: 'map_reduce',
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prompt: DEFAULT_PROMPT_TEMPLATE,
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combineMapPrompt: DEFAULT_PROMPT_TEMPLATE,
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},
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},
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placeholder: 'Add Option',
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typeOptions: {},
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options: [
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{
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name: 'values',
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displayName: 'Values',
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values: [
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{
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displayName: 'Summarization Method',
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name: 'summarizationMethod',
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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:
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'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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2024-04-05 06:51:54 -07:00
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displayName: 'Individual Summary Prompt',
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2023-12-08 04:42:32 -08:00
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name: 'combineMapPrompt',
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type: 'string',
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2024-04-05 06:51:54 -07:00
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hint: 'The prompt to summarize an individual document (or chunk)',
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2023-12-08 04:42:32 -08:00
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displayOptions: {
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hide: {
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'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
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'stuff',
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'refine',
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],
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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: 9,
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},
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},
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{
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2024-04-05 06:51:54 -07:00
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displayName: 'Final Prompt to Combine',
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2023-12-08 04:42:32 -08:00
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name: 'prompt',
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type: 'string',
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default: DEFAULT_PROMPT_TEMPLATE,
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2024-04-05 06:51:54 -07:00
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hint: 'The prompt to combine individual summaries',
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2023-12-08 04:42:32 -08:00
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displayOptions: {
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hide: {
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'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
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'stuff',
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'refine',
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],
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},
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},
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typeOptions: {
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rows: 9,
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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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hide: {
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'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
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'refine',
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'map_reduce',
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],
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},
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},
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typeOptions: {
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rows: 9,
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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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hide: {
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'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
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'stuff',
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'map_reduce',
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],
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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: 9,
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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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hide: {
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'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
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'stuff',
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'map_reduce',
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],
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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: 9,
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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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],
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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 Summarization Chain V2');
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const operationMode = this.getNodeParameter('operationMode', 0, 'nodeInputJson') as
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| 'nodeInputJson'
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| 'nodeInputBinary'
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| 'documentLoader';
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const chunkingMode = this.getNodeParameter('chunkingMode', 0, 'simple') as
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| 'simple'
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| 'advanced';
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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 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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2024-04-09 05:06:12 -07:00
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try {
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const summarizationMethodAndPrompts = this.getNodeParameter(
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'options.summarizationMethodAndPrompts.values',
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itemIndex,
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{},
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) as {
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prompt?: string;
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refineQuestionPrompt?: string;
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refinePrompt?: string;
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summarizationMethod: 'map_reduce' | 'stuff' | 'refine';
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combineMapPrompt?: string;
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};
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2023-12-08 04:42:32 -08:00
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2024-04-09 05:06:12 -07:00
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const chainArgs = getChainPromptsArgs(
|
|
|
|
|
summarizationMethodAndPrompts.summarizationMethod ?? 'map_reduce',
|
|
|
|
|
summarizationMethodAndPrompts,
|
|
|
|
|
);
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
const chain = loadSummarizationChain(model, chainArgs);
|
|
|
|
|
const item = items[itemIndex];
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
let processedDocuments: Document[];
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
// Use dedicated document loader input to load documents
|
|
|
|
|
if (operationMode === 'documentLoader') {
|
|
|
|
|
const documentInput = (await this.getInputConnectionData(
|
|
|
|
|
NodeConnectionType.AiDocument,
|
|
|
|
|
0,
|
|
|
|
|
)) as N8nJsonLoader | Array<Document<Record<string, unknown>>>;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
const isN8nLoader =
|
|
|
|
|
documentInput instanceof N8nJsonLoader || documentInput instanceof N8nBinaryLoader;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
processedDocuments = isN8nLoader
|
|
|
|
|
? await documentInput.processItem(item, itemIndex)
|
|
|
|
|
: documentInput;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
const response = await chain.withConfig(getTracingConfig(this)).invoke({
|
|
|
|
|
input_documents: processedDocuments,
|
|
|
|
|
});
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
returnData.push({ json: { response } });
|
|
|
|
|
}
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
// Take the input and use binary or json loader
|
|
|
|
|
if (['nodeInputJson', 'nodeInputBinary'].includes(operationMode)) {
|
|
|
|
|
let textSplitter: TextSplitter | undefined;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
switch (chunkingMode) {
|
|
|
|
|
// In simple mode we use recursive character splitter with default settings
|
|
|
|
|
case 'simple':
|
|
|
|
|
const chunkSize = this.getNodeParameter('chunkSize', itemIndex, 1000) as number;
|
|
|
|
|
const chunkOverlap = this.getNodeParameter('chunkOverlap', itemIndex, 200) as number;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
textSplitter = new RecursiveCharacterTextSplitter({ chunkOverlap, chunkSize });
|
|
|
|
|
break;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
// In advanced mode user can connect text splitter node so we just retrieve it
|
|
|
|
|
case 'advanced':
|
|
|
|
|
textSplitter = (await this.getInputConnectionData(
|
|
|
|
|
NodeConnectionType.AiTextSplitter,
|
|
|
|
|
0,
|
|
|
|
|
)) as TextSplitter | undefined;
|
|
|
|
|
break;
|
|
|
|
|
default:
|
|
|
|
|
break;
|
|
|
|
|
}
|
2023-12-08 04:42:32 -08:00
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
let processor: N8nJsonLoader | N8nBinaryLoader;
|
|
|
|
|
if (operationMode === 'nodeInputBinary') {
|
|
|
|
|
const binaryDataKey = this.getNodeParameter(
|
|
|
|
|
'options.binaryDataKey',
|
|
|
|
|
itemIndex,
|
|
|
|
|
'data',
|
|
|
|
|
) as string;
|
|
|
|
|
processor = new N8nBinaryLoader(this, 'options.', binaryDataKey, textSplitter);
|
|
|
|
|
} else {
|
|
|
|
|
processor = new N8nJsonLoader(this, 'options.', textSplitter);
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
const processedItem = await processor.processItem(item, itemIndex);
|
|
|
|
|
const response = await chain.call({
|
|
|
|
|
input_documents: processedItem,
|
|
|
|
|
});
|
|
|
|
|
returnData.push({ json: { response } });
|
|
|
|
|
}
|
|
|
|
|
} catch (error) {
|
|
|
|
|
if (this.continueOnFail()) {
|
|
|
|
|
returnData.push({ json: { error: error.message }, pairedItem: { item: itemIndex } });
|
|
|
|
|
continue;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
}
|
|
|
|
|
|
2024-04-09 05:06:12 -07:00
|
|
|
|
throw error;
|
2023-12-08 04:42:32 -08:00
|
|
|
|
}
|
|
|
|
|
}
|
|
|
|
|
|
2024-05-22 08:40:52 -07:00
|
|
|
|
return [returnData];
|
2023-12-08 04:42:32 -08:00
|
|
|
|
}
|
|
|
|
|
}
|