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91 lines
2.4 KiB
TypeScript
91 lines
2.4 KiB
TypeScript
/* eslint-disable n8n-nodes-base/node-dirname-against-convention */
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import {
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NodeConnectionType,
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type INodeType,
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type INodeTypeDescription,
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type ISupplyDataFunctions,
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type SupplyData,
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} from 'n8n-workflow';
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import { ContextualCompressionRetriever } from 'langchain/retrievers/contextual_compression';
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import { LLMChainExtractor } from 'langchain/retrievers/document_compressors/chain_extract';
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import type { BaseLanguageModel } from '@langchain/core/language_models/base';
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import type { BaseRetriever } from '@langchain/core/retrievers';
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import { logWrapper } from '../../../utils/logWrapper';
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export class RetrieverContextualCompression implements INodeType {
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description: INodeTypeDescription = {
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displayName: 'Contextual Compression Retriever',
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name: 'retrieverContextualCompression',
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icon: 'fa:box-open',
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group: ['transform'],
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version: 1,
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description: 'Enhances document similarity search by contextual compression.',
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defaults: {
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name: 'Contextual Compression Retriever',
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},
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codex: {
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categories: ['AI'],
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subcategories: {
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AI: ['Retrievers'],
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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/sub-nodes/n8n-nodes-langchain.retrievercontextualcompression/',
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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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{
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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: 'Retriever',
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maxConnections: 1,
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type: NodeConnectionType.AiRetriever,
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required: true,
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},
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],
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outputs: [
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{
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displayName: 'Retriever',
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maxConnections: 1,
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type: NodeConnectionType.AiRetriever,
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},
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],
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properties: [],
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};
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async supplyData(this: ISupplyDataFunctions, itemIndex: number): Promise<SupplyData> {
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this.logger.debug('Supplying data for Contextual Compression Retriever');
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const model = (await this.getInputConnectionData(
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NodeConnectionType.AiLanguageModel,
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itemIndex,
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)) as BaseLanguageModel;
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const baseRetriever = (await this.getInputConnectionData(
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NodeConnectionType.AiRetriever,
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itemIndex,
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)) as BaseRetriever;
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const baseCompressor = LLMChainExtractor.fromLLM(model);
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const retriever = new ContextualCompressionRetriever({
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baseCompressor,
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baseRetriever,
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});
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return {
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response: logWrapper(retriever, this),
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};
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}
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}
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