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MemberJunction: AI Reranker Service and LLM-based reranking for two-stage retrieval

Package Exports

  • @memberjunction/ai-reranker
  • @memberjunction/ai-reranker/dist/index.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@memberjunction/ai-reranker) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

@memberjunction/ai-reranker

Two-stage retrieval reranking service for MemberJunction's AI agent framework. Provides centralized reranker management and LLM-based reranking capabilities for improving the relevance of vector search results, particularly agent memory notes. Supports configurable reranking models, observability integration, and agent-level configuration.

Architecture

graph TD
    subgraph "@memberjunction/ai-reranker"
        RS["RerankerService<br/>Singleton Manager"]
        style RS fill:#2d8659,stroke:#1a5c3a,color:#fff

        LR["LLMReranker<br/>LLM-Based Reranking"]
        style LR fill:#7c5295,stroke:#563a6b,color:#fff

        CT["Config Types<br/>RerankerConfiguration"]
        style CT fill:#b8762f,stroke:#8a5722,color:#fff
    end

    subgraph "Two-Stage Retrieval"
        S1["Stage 1: Vector Search<br/>Fast approximate retrieval"]
        style S1 fill:#2d6a9f,stroke:#1a4971,color:#fff

        S2["Stage 2: LLM Reranking<br/>Precise relevance scoring"]
        style S2 fill:#7c5295,stroke:#563a6b,color:#fff

        S3["Final Results<br/>Reranked by relevance"]
        style S3 fill:#2d8659,stroke:#1a5c3a,color:#fff
    end

    S1 -->|"Top-K candidates"| RS
    RS --> S2
    S2 -->|"Scored & sorted"| S3

    subgraph Dependencies
        AI["@memberjunction/ai<br/>BaseReranker"]
        style AI fill:#2d6a9f,stroke:#1a4971,color:#fff

        AIP["@memberjunction/ai-prompts<br/>AIPromptRunner"]
        style AIP fill:#2d6a9f,stroke:#1a4971,color:#fff

        AIE["@memberjunction/aiengine<br/>NoteMatchResult"]
        style AIE fill:#2d6a9f,stroke:#1a4971,color:#fff
    end

    AI --> RS
    AIP --> LR
    AIE --> RS

Installation

npm install @memberjunction/ai-reranker

Key Exports

RerankerService (Singleton)

Centralized service for managing reranker instances and performing note reranking. Caches reranker instances by model for efficient reuse.

import { RerankerService, parseRerankerConfiguration } from '@memberjunction/ai-reranker';

// Parse configuration from agent entity
const config = parseRerankerConfiguration(agent.RerankerConfiguration);

if (config?.enabled) {
    const result = await RerankerService.Instance.rerankNotes(
        vectorSearchResults,   // NoteMatchResult[] from vector search
        userQuery,             // The user's query for relevance scoring
        config,                // RerankerConfiguration
        contextUser
    );

    if (result.success) {
        console.log(`Reranked ${result.notes.length} notes in ${result.durationMs}ms`);
    }
}

LLMReranker

LLM-based reranking implementation that uses AI prompts to score document relevance. Extends BaseReranker from @memberjunction/ai.

import { createLLMReranker } from '@memberjunction/ai-reranker';

const reranker = createLLMReranker(modelId, contextUser);

RerankerConfiguration

Configuration type stored as JSON on agent entities:

interface RerankerConfiguration {
    /** Whether reranking is enabled for this agent */
    enabled: boolean;
    /** AI model ID to use for reranking */
    modelId?: string;
    /** Maximum number of results to return after reranking */
    topK?: number;
    /** Minimum relevance score threshold (0-1) */
    minScore?: number;
}

RerankServiceResult

interface RerankServiceResult {
    notes: NoteMatchResult[];     // Reranked notes sorted by relevance
    success: boolean;             // Whether reranking succeeded
    durationMs: number;           // Time taken in milliseconds
    usage?: {                     // Token usage for cost tracking
        promptTokens?: number;
        completionTokens?: number;
        cost?: number;
    };
    runStepID?: string;           // Created run step ID (if observability enabled)
}

RerankObservabilityOptions

Integration with agent run step tracking:

const result = await RerankerService.Instance.rerankNotes(
    notes,
    query,
    config,
    contextUser,
    {
        agentRunID: runId,        // Link to agent run
        parentStepID: stepId,     // Parent step for hierarchy
        stepNumber: 3             // Step sequence number
    }
);

How Two-Stage Retrieval Works

  1. Stage 1 -- Vector Search: Fast approximate nearest-neighbor search using embeddings to retrieve a broad set of candidate notes (e.g., top 50)
  2. Stage 2 -- LLM Reranking: An LLM evaluates each candidate note against the query and assigns a precise relevance score
  3. Result: The top-K most relevant notes are returned, sorted by LLM-determined relevance

This approach combines the speed of vector search with the accuracy of LLM-based understanding, significantly improving retrieval quality for agent memory.

Interaction with Consolidation

The candidate corpus the reranker scores is the in-process vector store (AIEngine._noteVectorService). Since v5.30.x, that store is kept in sync with persisted Status='Active' (see @memberjunction/aiengine README), which has two consequences for reranking:

  • Consolidated source notes drop out immediately. When MemoryManagerAgent's consolidation pipeline merges a cluster, source notes are revoked in the same operation that removes their vector entries. They stop appearing as rerank candidates without an MJAPI restart.
  • Protection tier is metadata, not a rerank gate. ProtectionTier (Immutable / Protected / Standard / Ephemeral) lives on the note entity and flows through to the reranker as part of each candidate's data. The reranker itself does not filter or weight by tier; downstream consumers (MemoryManagerAgent's decay phase, retrieval policies layered on top of RerankServiceResult) are responsible for any tier-aware logic.

For the consolidation pipeline mechanics and protection-tier semantics, see @memberjunction/ai-agents.

Dependencies

  • @memberjunction/ai -- BaseReranker, RerankParams, RerankResult
  • @memberjunction/ai-prompts -- AIPromptRunner for LLM-based reranking
  • @memberjunction/ai-core-plus -- Extended entity classes
  • @memberjunction/aiengine -- AIEngine, NoteMatchResult
  • @memberjunction/core -- MJ framework core
  • @memberjunction/core-entities -- Generated entity classes
  • @memberjunction/global -- Class factory