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Compression Retriever: Reciprocal Rank Fusion
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import { INode, INodeData, INodeParams } from '../../../src/Interface'
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import { BaseLanguageModel } from 'langchain/base_language'
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import { ContextualCompressionRetriever } from 'langchain/retrievers/contextual_compression'
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import { BaseRetriever } from 'langchain/schema/retriever'
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import { ReciprocalRankFusion } from './ReciprocalRankFusion'
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import { VectorStoreRetriever } from 'langchain/vectorstores/base'
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class RRFRetriever_Retrievers implements INode {
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label: string
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name: string
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version: number
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description: string
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type: string
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icon: string
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category: string
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baseClasses: string[]
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inputs: INodeParams[]
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badge: string
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constructor() {
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this.label = 'Reciprocal Rank Fusion Retriever'
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this.name = 'RRFRetriever'
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this.version = 2.0
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this.type = 'RRFRetriever'
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this.badge = 'NEW'
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this.icon = 'compressionRetriever.svg'
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this.category = 'Retrievers'
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this.description = 'Reciprocal Rank Fusion to re-rank search results by multiple query generation.'
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this.baseClasses = [this.type, 'BaseRetriever']
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this.inputs = [
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{
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label: 'Base Retriever',
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name: 'baseRetriever',
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type: 'VectorStoreRetriever'
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},
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{
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label: 'Language Model',
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name: 'model',
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type: 'BaseLanguageModel'
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},
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{
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label: 'Query Count',
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name: 'queryCount',
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description: 'Number of synthetic queries to generate. Default to 4',
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placeholder: '4',
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type: 'number',
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default: 4,
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additionalParams: true,
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optional: true
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},
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{
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label: 'Top K',
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name: 'topK',
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description: 'Number of top results to fetch. Default to the TopK of the Base Retriever',
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placeholder: '0',
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type: 'number',
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default: 0,
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additionalParams: true,
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optional: true
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}
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]
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}
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async init(nodeData: INodeData): Promise<any> {
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const llm = nodeData.inputs?.model as BaseLanguageModel
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const baseRetriever = nodeData.inputs?.baseRetriever as BaseRetriever
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const queryCount = nodeData.inputs?.queryCount as string
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const q = queryCount ? parseFloat(queryCount) : 4
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const topK = nodeData.inputs?.topK as string
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let k = topK ? parseFloat(topK) : 4
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if (k <= 0) {
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k = (baseRetriever as VectorStoreRetriever).k
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}
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const ragFusion = new ReciprocalRankFusion(llm, baseRetriever as VectorStoreRetriever, q, k)
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return new ContextualCompressionRetriever({
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baseCompressor: ragFusion,
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baseRetriever: baseRetriever
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})
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}
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}
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module.exports = { nodeClass: RRFRetriever_Retrievers }
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