@n8n/n8n-nodes-langchain/dist/nodes/retrievers/RetrieverVectorStore/RetrieverVectorStore.node.js


"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.RetrieverVectorStore = void 0;
const vectorstores_1 = require("@langchain/core/vectorstores");
const contextual_compression_1 = require("@langchain/classic/retrievers/contextual_compression");
const n8n_workflow_1 = require("n8n-workflow");
const ai_utilities_1 = require("@n8n/ai-utilities");
class RetrieverVectorStore {
    constructor() {
        this.description = {
            displayName: 'Vector Store Retriever',
            name: 'retrieverVectorStore',
            icon: 'node:vector-store-retriever',
            iconColor: 'black',
            group: ['transform'],
            version: 1,
            description: 'Use a Vector Store as Retriever',
            defaults: {
                name: 'Vector Store Retriever',
            },
            codex: {
                categories: ['AI'],
                subcategories: {
                    AI: ['Retrievers'],
                },
                resources: {
                    primaryDocumentation: [
                        {
                            url: 'https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.retrievervectorstore/',
                        },
                    ],
                },
            },
            inputs: [
                {
                    displayName: 'Vector Store',
                    maxConnections: 1,
                    type: n8n_workflow_1.NodeConnectionTypes.AiVectorStore,
                    required: true,
                },
            ],
            outputs: [n8n_workflow_1.NodeConnectionTypes.AiRetriever],
            outputNames: ['Retriever'],
            builderHint: {
                relatedNodes: [
                    {
                        nodeType: '@n8n/n8n-nodes-langchain.vectorStoreInMemory',
                        relationHint: 'Connect to provide vectors for retrieval in RAG workflows',
                    },
                ],
                inputs: {
                    ai_vectorStore: { required: true },
                },
            },
            properties: [
                {
                    displayName: 'Limit',
                    name: 'topK',
                    type: 'number',
                    default: 4,
                    description: 'The maximum number of results to return',
                },
            ],
        };
    }
    async supplyData(itemIndex) {
        this.logger.debug('Supplying data for Vector Store Retriever');
        const topK = this.getNodeParameter('topK', itemIndex, 4);
        const vectorStore = (await this.getInputConnectionData(n8n_workflow_1.NodeConnectionTypes.AiVectorStore, itemIndex));
        let retriever = null;
        if (vectorStore instanceof vectorstores_1.VectorStore) {
            retriever = vectorStore.asRetriever(topK);
        }
        else {
            retriever = new contextual_compression_1.ContextualCompressionRetriever({
                baseCompressor: vectorStore.reranker,
                baseRetriever: vectorStore.vectorStore.asRetriever(topK),
            });
        }
        return {
            response: (0, ai_utilities_1.logWrapper)(retriever, this),
        };
    }
}
exports.RetrieverVectorStore = RetrieverVectorStore;
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