import { BaseRetriever } from '@langchain/core/retrievers' import { ContextualCompressionRetriever } from 'langchain/retrievers/contextual_compression' import { getCredentialData, getCredentialParam, handleEscapeCharacters } from '../../../src' import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' import { JinaRerank } from './JinaRerank' class JinaRerankRetriever_Retrievers implements INode { label: string name: string version: number description: string type: string icon: string category: string baseClasses: string[] inputs: INodeParams[] credential: INodeParams badge: string outputs: INodeOutputsValue[] constructor() { this.label = 'Jina AI Rerank Retriever' this.name = 'JinaRerankRetriever' this.version = 1.0 this.type = 'JinaRerankRetriever' this.icon = 'JinaAI.svg' this.category = 'Retrievers' this.description = 'Jina AI Rerank indexes the documents from most to least semantically relevant to the query.' this.baseClasses = [this.type, 'BaseRetriever'] this.credential = { label: 'Connect Credential', name: 'credential', type: 'credential', credentialNames: ['jinaAIApi'] } this.inputs = [ { label: 'Vector Store Retriever', name: 'baseRetriever', type: 'VectorStoreRetriever' }, { label: 'Model Name', name: 'model', type: 'options', options: [ { label: 'jina-reranker-v2-base-multilingual', name: 'jina-reranker-v2-base-multilingual' }, { label: 'jina-colbert-v2', name: 'jina-colbert-v2' } ], default: 'jina-reranker-v2-base-multilingual', optional: true }, { label: 'Query', name: 'query', type: 'string', description: 'Query to retrieve documents from retriever. If not specified, user question will be used', optional: true, acceptVariable: true }, { label: 'Top N', name: 'topN', description: 'Number of top results to fetch. Default to 4', placeholder: '4', default: 4, type: 'number', additionalParams: true, optional: true } ] this.outputs = [ { label: 'Jina AI Rerank Retriever', name: 'retriever', baseClasses: this.baseClasses }, { label: 'Document', name: 'document', description: 'Array of document objects containing metadata and pageContent', baseClasses: ['Document', 'json'] }, { label: 'Text', name: 'text', description: 'Concatenated string from pageContent of documents', baseClasses: ['string', 'json'] } ] } async init(nodeData: INodeData, input: string, options: ICommonObject): Promise { const baseRetriever = nodeData.inputs?.baseRetriever as BaseRetriever const model = nodeData.inputs?.model as string const query = nodeData.inputs?.query as string const credentialData = await getCredentialData(nodeData.credential ?? '', options) const jinaApiKey = getCredentialParam('jinaAIAPIKey', credentialData, nodeData) const topN = nodeData.inputs?.topN ? parseFloat(nodeData.inputs?.topN as string) : 4 const output = nodeData.outputs?.output as string const jinaCompressor = new JinaRerank(jinaApiKey, model, topN) const retriever = new ContextualCompressionRetriever({ baseCompressor: jinaCompressor, baseRetriever: baseRetriever }) if (output === 'retriever') return retriever else if (output === 'document') return await retriever.invoke(query ? query : input) else if (output === 'text') { const docs = await retriever.invoke(query ? query : input) let finaltext = '' for (const doc of docs) finaltext += `${doc.pageContent}\n` return handleEscapeCharacters(finaltext, false) } return retriever } } module.exports = { nodeClass: JinaRerankRetriever_Retrievers }