@memberjunction/ai-recommendations-rex

MemberJunction recommendation provider for the rasa.io Rex recommendation engine. Retrieves content recommendations from Rex and saves them into MJ Recommendation/Recommendation Item entities.

Overview

This package implements RecommendationProviderBase for the rasa.io Rex engine. It authenticates with the Rex API, looks up vector IDs from MJ Entity Record Documents, requests content-based recommendations via Rex’s /suggest endpoint, and persists the results as RecommendationItem entities in the MemberJunction database.

graph TD
    PROVIDER["RexRecommendationsProvider"] --> TOKEN["Get Rex Access Token\n(/tokens)"]
    PROVIDER --> DOCS["Load Entity Record Documents\n(Vector IDs)"]
    PROVIDER --> SUGGEST["Get Recommendations\n(/suggest)"]
    PROVIDER --> SAVE["Save Recommendation Items\n(MJ Entities)"]

    TOKEN --> REXAPI["Rex API"]
    SUGGEST --> REXAPI
    DOCS --> RUNVIEW["RunView\n(Entity Record Documents)"]
    SAVE --> MJDB["MJ Database"]

    style PROVIDER fill:#7c5295,stroke:#563a6b,color:#fff
    style TOKEN fill:#2d6a9f,stroke:#1a4971,color:#fff
    style DOCS fill:#2d6a9f,stroke:#1a4971,color:#fff
    style SUGGEST fill:#2d6a9f,stroke:#1a4971,color:#fff
    style SAVE fill:#2d6a9f,stroke:#1a4971,color:#fff
    style REXAPI fill:#b8762f,stroke:#8a5722,color:#fff
    style RUNVIEW fill:#2d8659,stroke:#1a5c3a,color:#fff
    style MJDB fill:#2d8659,stroke:#1a5c3a,color:#fff

Features

Rex API integration: Authenticates and retrieves recommendations from the rasa.io Rex engine
Batch processing: Processes recommendations in configurable batch sizes (default 200)
Vector ID resolution: Looks up Pinecone vector IDs from MJ Entity Record Documents
Type mapping: Configurable mapping from Rex content types to MJ entity names
Score clamping: Normalizes recommendation scores to a 0-1 probability range
Error tracking: Optionally logs errors to a MJ List for review
Auto-registration: Registers with MJ class factory as "rasa.io Rex"

Installation

npm install @memberjunction/ai-recommendations-rex

Configuration

Set the following environment variables:

Variable	Required	Description
`REX_API_HOST`	Yes	Rex API base URL for authentication
`REX_RECOMMEND_HOST`	Yes	Rex recommendation service URL
`REX_USERNAME`	Yes	Rex API username
`REX_PASSWORD`	Yes	Rex API password
`REX_API_KEY`	Yes	Rex API key
`REX_BATCH_SIZE`	No	Batch size for processing (default: 200)

Usage

import { RexRecommendationsProvider } from '@memberjunction/ai-recommendations-rex';
import { RecommendationRequest } from '@memberjunction/ai-recommendations';

// The provider is auto-registered as "rasa.io Rex" via @RegisterClass.
// It can also be instantiated directly:
const provider = new RexRecommendationsProvider();

const request: RecommendationRequest = {
  Recommendations: recommendationEntities,  // Array of RecommendationEntity
  RunID: 'run-id',
  CurrentUser: contextUser,
  Options: {
    EntityDocumentID: 'entity-doc-id',  // Required
    type: 'course',                     // Rex content type
    filters: [{ type: 'course', max_results: 10 }],
    TypeMap: {                          // Optional: custom type-to-entity mapping
      'course': 'Contents',
      'person': 'Contributors'
    }
  }
};

const result = await provider.Recommend(request);

if (result.Success) {
  console.log('Recommendations generated successfully');
} else {
  console.error('Errors:', result.Errors);
}

Key Dependencies

Dependency	Purpose
`@memberjunction/ai-recommendations`	`RecommendationProviderBase` abstract class
`@memberjunction/core`	`Metadata`, `RunView`, `LogError`, `LogStatus`
`@memberjunction/core-entities`	Entity types (`RecommendationEntity`, `RecommendationItemEntity`, etc.)
`@memberjunction/global`	`@RegisterClass` decorator
`axios`	HTTP client for Rex API calls

@memberjunction/ai-recommendations - Base recommendation provider abstraction
@memberjunction/ai-vectors-pinecone - Pinecone vector database provider (source of vector IDs)

License

ISC