mirror of
https://github.com/n8n-io/n8n.git
synced 2024-11-15 00:54:06 -08:00
421 lines
12 KiB
TypeScript
421 lines
12 KiB
TypeScript
import { NodeConnectionType } from 'n8n-workflow';
|
||
import type {
|
||
INodeTypeBaseDescription,
|
||
IExecuteFunctions,
|
||
INodeExecutionData,
|
||
INodeType,
|
||
INodeTypeDescription,
|
||
IDataObject,
|
||
} from 'n8n-workflow';
|
||
|
||
import { loadSummarizationChain } from 'langchain/chains';
|
||
import type { BaseLanguageModel } from 'langchain/dist/base_language';
|
||
import type { Document } from 'langchain/document';
|
||
import type { TextSplitter } from 'langchain/text_splitter';
|
||
import { RecursiveCharacterTextSplitter } from 'langchain/text_splitter';
|
||
import { N8nJsonLoader } from '../../../../utils/N8nJsonLoader';
|
||
import { N8nBinaryLoader } from '../../../../utils/N8nBinaryLoader';
|
||
import { getTemplateNoticeField } from '../../../../utils/sharedFields';
|
||
import { REFINE_PROMPT_TEMPLATE, DEFAULT_PROMPT_TEMPLATE } from '../prompt';
|
||
import { getChainPromptsArgs } from '../helpers';
|
||
|
||
function getInputs(parameters: IDataObject) {
|
||
const chunkingMode = parameters?.chunkingMode;
|
||
const operationMode = parameters?.operationMode;
|
||
const inputs = [
|
||
{ displayName: '', type: NodeConnectionType.Main },
|
||
{
|
||
displayName: 'Model',
|
||
maxConnections: 1,
|
||
type: NodeConnectionType.AiLanguageModel,
|
||
required: true,
|
||
},
|
||
];
|
||
|
||
if (operationMode === 'documentLoader') {
|
||
inputs.push({
|
||
displayName: 'Document',
|
||
type: NodeConnectionType.AiDocument,
|
||
required: true,
|
||
maxConnections: 1,
|
||
});
|
||
return inputs;
|
||
}
|
||
|
||
if (chunkingMode === 'advanced') {
|
||
inputs.push({
|
||
displayName: 'Text Splitter',
|
||
type: NodeConnectionType.AiTextSplitter,
|
||
required: false,
|
||
maxConnections: 1,
|
||
});
|
||
return inputs;
|
||
}
|
||
return inputs;
|
||
}
|
||
|
||
export class ChainSummarizationV2 implements INodeType {
|
||
description: INodeTypeDescription;
|
||
|
||
constructor(baseDescription: INodeTypeBaseDescription) {
|
||
this.description = {
|
||
...baseDescription,
|
||
version: [2],
|
||
defaults: {
|
||
name: 'Summarization Chain',
|
||
color: '#909298',
|
||
},
|
||
// eslint-disable-next-line n8n-nodes-base/node-class-description-inputs-wrong-regular-node
|
||
inputs: `={{ ((parameter) => { ${getInputs.toString()}; return getInputs(parameter) })($parameter) }}`,
|
||
outputs: [NodeConnectionType.Main],
|
||
credentials: [],
|
||
properties: [
|
||
getTemplateNoticeField(1951),
|
||
{
|
||
displayName: 'Data to Summarize',
|
||
name: 'operationMode',
|
||
noDataExpression: true,
|
||
type: 'options',
|
||
description: 'How to pass data into the summarization chain',
|
||
default: 'nodeInputJson',
|
||
options: [
|
||
{
|
||
name: 'Use Node Input (JSON)',
|
||
value: 'nodeInputJson',
|
||
description: 'Summarize the JSON data coming into this node from the previous one',
|
||
},
|
||
{
|
||
name: 'Use Node Input (Binary)',
|
||
value: 'nodeInputBinary',
|
||
description: 'Summarize the binary data coming into this node from the previous one',
|
||
},
|
||
{
|
||
name: 'Use Document Loader',
|
||
value: 'documentLoader',
|
||
description: 'Use a loader sub-node with more configuration options',
|
||
},
|
||
],
|
||
},
|
||
{
|
||
displayName: 'Chunking Strategy',
|
||
name: 'chunkingMode',
|
||
noDataExpression: true,
|
||
type: 'options',
|
||
description: 'Chunk splitting strategy',
|
||
default: 'simple',
|
||
options: [
|
||
{
|
||
name: 'Simple (Define Below)',
|
||
value: 'simple',
|
||
},
|
||
{
|
||
name: 'Advanced',
|
||
value: 'advanced',
|
||
description: 'Use a splitter sub-node with more configuration options',
|
||
},
|
||
],
|
||
displayOptions: {
|
||
show: {
|
||
'/operationMode': ['nodeInputJson', 'nodeInputBinary'],
|
||
},
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Characters Per Chunk',
|
||
name: 'chunkSize',
|
||
description:
|
||
'Controls the max size (in terms of number of characters) of the final document chunk',
|
||
type: 'number',
|
||
default: 1000,
|
||
displayOptions: {
|
||
show: {
|
||
'/chunkingMode': ['simple'],
|
||
},
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Chunk Overlap (Characters)',
|
||
name: 'chunkOverlap',
|
||
type: 'number',
|
||
description: 'Specifies how much characters overlap there should be between chunks',
|
||
default: 200,
|
||
displayOptions: {
|
||
show: {
|
||
'/chunkingMode': ['simple'],
|
||
},
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Options',
|
||
name: 'options',
|
||
type: 'collection',
|
||
default: {},
|
||
placeholder: 'Add Option',
|
||
options: [
|
||
{
|
||
displayName: 'Input Data Field Name',
|
||
name: 'binaryDataKey',
|
||
type: 'string',
|
||
default: 'data',
|
||
description:
|
||
'The name of the field in the agent or chain’s input that contains the binary file to be processed',
|
||
displayOptions: {
|
||
show: {
|
||
'/operationMode': ['nodeInputBinary'],
|
||
},
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Summarization Method and Prompts',
|
||
name: 'summarizationMethodAndPrompts',
|
||
type: 'fixedCollection',
|
||
default: {
|
||
values: {
|
||
summarizationMethod: 'map_reduce',
|
||
prompt: DEFAULT_PROMPT_TEMPLATE,
|
||
combineMapPrompt: DEFAULT_PROMPT_TEMPLATE,
|
||
},
|
||
},
|
||
placeholder: 'Add Option',
|
||
typeOptions: {},
|
||
options: [
|
||
{
|
||
name: 'values',
|
||
displayName: 'Values',
|
||
values: [
|
||
{
|
||
displayName: 'Summarization Method',
|
||
name: 'summarizationMethod',
|
||
type: 'options',
|
||
description: 'The type of summarization to run',
|
||
default: 'map_reduce',
|
||
options: [
|
||
{
|
||
name: 'Map Reduce (Recommended)',
|
||
value: 'map_reduce',
|
||
description:
|
||
'Summarize each document (or chunk) individually, then summarize those summaries',
|
||
},
|
||
{
|
||
name: 'Refine',
|
||
value: 'refine',
|
||
description:
|
||
'Summarize the first document (or chunk). Then update that summary based on the next document (or chunk), and repeat.',
|
||
},
|
||
{
|
||
name: 'Stuff',
|
||
value: 'stuff',
|
||
description:
|
||
'Pass all documents (or chunks) at once. Ideal for small datasets.',
|
||
},
|
||
],
|
||
},
|
||
{
|
||
displayName: 'Final Prompt to Combine',
|
||
name: 'combineMapPrompt',
|
||
type: 'string',
|
||
hint: 'The prompt to combine individual summaries',
|
||
displayOptions: {
|
||
hide: {
|
||
'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
|
||
'stuff',
|
||
'refine',
|
||
],
|
||
},
|
||
},
|
||
default: DEFAULT_PROMPT_TEMPLATE,
|
||
typeOptions: {
|
||
rows: 9,
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Individual Summary Prompt',
|
||
name: 'prompt',
|
||
type: 'string',
|
||
default: DEFAULT_PROMPT_TEMPLATE,
|
||
hint: 'The prompt to summarize an individual document (or chunk)',
|
||
displayOptions: {
|
||
hide: {
|
||
'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
|
||
'stuff',
|
||
'refine',
|
||
],
|
||
},
|
||
},
|
||
typeOptions: {
|
||
rows: 9,
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Prompt',
|
||
name: 'prompt',
|
||
type: 'string',
|
||
default: DEFAULT_PROMPT_TEMPLATE,
|
||
displayOptions: {
|
||
hide: {
|
||
'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
|
||
'refine',
|
||
'map_reduce',
|
||
],
|
||
},
|
||
},
|
||
typeOptions: {
|
||
rows: 9,
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Subsequent (Refine) Prompt',
|
||
name: 'refinePrompt',
|
||
type: 'string',
|
||
displayOptions: {
|
||
hide: {
|
||
'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
|
||
'stuff',
|
||
'map_reduce',
|
||
],
|
||
},
|
||
},
|
||
default: REFINE_PROMPT_TEMPLATE,
|
||
hint: 'The prompt to refine the summary based on the next document (or chunk)',
|
||
typeOptions: {
|
||
rows: 9,
|
||
},
|
||
},
|
||
{
|
||
displayName: 'Initial Prompt',
|
||
name: 'refineQuestionPrompt',
|
||
type: 'string',
|
||
displayOptions: {
|
||
hide: {
|
||
'/options.summarizationMethodAndPrompts.values.summarizationMethod': [
|
||
'stuff',
|
||
'map_reduce',
|
||
],
|
||
},
|
||
},
|
||
default: DEFAULT_PROMPT_TEMPLATE,
|
||
hint: 'The prompt for the first document (or chunk)',
|
||
typeOptions: {
|
||
rows: 9,
|
||
},
|
||
},
|
||
],
|
||
},
|
||
],
|
||
},
|
||
],
|
||
},
|
||
],
|
||
};
|
||
}
|
||
|
||
async execute(this: IExecuteFunctions): Promise<INodeExecutionData[][]> {
|
||
this.logger.verbose('Executing Summarization Chain V2');
|
||
const operationMode = this.getNodeParameter('operationMode', 0, 'nodeInputJson') as
|
||
| 'nodeInputJson'
|
||
| 'nodeInputBinary'
|
||
| 'documentLoader';
|
||
const chunkingMode = this.getNodeParameter('chunkingMode', 0, 'simple') as
|
||
| 'simple'
|
||
| 'advanced';
|
||
|
||
const model = (await this.getInputConnectionData(
|
||
NodeConnectionType.AiLanguageModel,
|
||
0,
|
||
)) as BaseLanguageModel;
|
||
|
||
const items = this.getInputData();
|
||
const returnData: INodeExecutionData[] = [];
|
||
|
||
for (let itemIndex = 0; itemIndex < items.length; itemIndex++) {
|
||
const summarizationMethodAndPrompts = this.getNodeParameter(
|
||
'options.summarizationMethodAndPrompts.values',
|
||
itemIndex,
|
||
{},
|
||
) as {
|
||
prompt?: string;
|
||
refineQuestionPrompt?: string;
|
||
refinePrompt?: string;
|
||
summarizationMethod: 'map_reduce' | 'stuff' | 'refine';
|
||
combineMapPrompt?: string;
|
||
};
|
||
|
||
const chainArgs = getChainPromptsArgs(
|
||
summarizationMethodAndPrompts.summarizationMethod ?? 'map_reduce',
|
||
summarizationMethodAndPrompts,
|
||
);
|
||
|
||
const chain = loadSummarizationChain(model, chainArgs);
|
||
const item = items[itemIndex];
|
||
|
||
let processedDocuments: Document[];
|
||
|
||
// 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>>>;
|
||
|
||
const isN8nLoader =
|
||
documentInput instanceof N8nJsonLoader || documentInput instanceof N8nBinaryLoader;
|
||
|
||
processedDocuments = isN8nLoader
|
||
? await documentInput.processItem(item, itemIndex)
|
||
: documentInput;
|
||
|
||
const response = await chain.call({
|
||
input_documents: processedDocuments,
|
||
});
|
||
|
||
returnData.push({ json: { response } });
|
||
}
|
||
|
||
// Take the input and use binary or json loader
|
||
if (['nodeInputJson', 'nodeInputBinary'].includes(operationMode)) {
|
||
let textSplitter: TextSplitter | undefined;
|
||
|
||
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;
|
||
|
||
textSplitter = new RecursiveCharacterTextSplitter({ chunkOverlap, chunkSize });
|
||
break;
|
||
|
||
// 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;
|
||
}
|
||
|
||
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 } });
|
||
}
|
||
}
|
||
|
||
return await this.prepareOutputData(returnData);
|
||
}
|
||
}
|