@memberjunction/ai-recommendations

The MemberJunction Recommendations Engine provides a flexible and extensible framework for integrating with AI-powered recommendation systems. It handles the orchestration of recommendation requests, provider management, and the storage of recommendation results within the MemberJunction ecosystem.

Features

• Extensible Provider Framework: Support for multiple recommendation providers through a unified API
• Built-in Tracking: Automatic tracking of recommendation runs and results
• Entity Integration: Seamless integration with MemberJunction entities and records
• List Support: Generate recommendations for records in a list
• Error Handling: Comprehensive error tracking and reporting
• Batch Processing: Process multiple recommendation requests efficiently
• Metadata Management: Automatic management of recommendation metadata

Installation

npm install @memberjunction/ai-recommendations
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Core Components

RecommendationEngineBase

The main engine class that coordinates recommendation requests:

import { RecommendationEngineBase, RecommendationRequest } from '@memberjunction/ai-recommendations';

// Initialize and load the engine
await RecommendationEngineBase.Instance.Config();

// Create a recommendation request
const request = new RecommendationRequest();

// Configure the request
request.EntityAndRecordsInfo = {
  EntityName: 'Customers',
  RecordIDs: ['CUST001', 'CUST002']
};

// Execute the recommendation
const result = await RecommendationEngineBase.Instance.Recommend(request);
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RecommendationProviderBase

Abstract base class for implementing recommendation providers:

import { RecommendationProviderBase, RecommendationRequest, RecommendationResult } from '@memberjunction/ai-recommendations';
import { UserInfo } from '@memberjunction/core';
import { RecommendationItemEntity } from '@memberjunction/core-entities';

export class MyRecommendationProvider extends RecommendationProviderBase {
  constructor(contextUser: UserInfo) {
    super(contextUser);
  }

  public async Recommend(request: RecommendationRequest): Promise<RecommendationResult> {
    const result = new RecommendationResult(request);
    
    try {
      // Process each recommendation
      for (const recommendation of request.Recommendations) {
        // Generate items for this recommendation
        const items: RecommendationItemEntity[] = [];
        
        // Your recommendation logic here
        // ...
        
        // Save the recommendation and its items
        await this.SaveRecommendation(recommendation, request.RunID, items);
      }
    } catch (error) {
      result.AppendError(error.message);
    }
    
    return result;
  }
}
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Usage Examples

Generate Recommendations for Specific Records

import { RecommendationEngineBase, RecommendationRequest } from '@memberjunction/ai-recommendations';

async function getCustomerRecommendations(customerIds: string[]) {
  // Ensure the engine is configured
  await RecommendationEngineBase.Instance.Config();
  
  // Create a request for specific customer records
  const request = new RecommendationRequest();
  request.EntityAndRecordsInfo = {
    EntityName: 'Customers',
    RecordIDs: customerIds
  };
  
  // Optionally specify a provider
  // request.Provider = RecommendationEngineBase.Instance.RecommendationProviders.find(p => p.Name === 'MyProvider');
  
  // Execute the recommendation
  const result = await RecommendationEngineBase.Instance.Recommend(request);
  
  if (result.Success) {
    console.log('Recommendations generated successfully!');
    return result.RecommendationItems;
  } else {
    console.error('Error generating recommendations:', result.ErrorMessage);
    return null;
  }
}
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Generate Recommendations from a List

import { RecommendationEngineBase, RecommendationRequest } from '@memberjunction/ai-recommendations';

async function getRecommendationsFromList(listId: string) {
  await RecommendationEngineBase.Instance.Config();
  
  // Create a request for records in a list
  const request = new RecommendationRequest();
  request.ListID = listId;
  request.CreateErrorList = true; // Create a list to track errors
  
  // Execute the recommendation
  const result = await RecommendationEngineBase.Instance.Recommend(request);
  
  if (result.Success) {
    console.log('Recommendations generated successfully!');
    console.log('Error list ID (if needed):', result.Request.ErrorListID);
    return result.RecommendationItems;
  } else {
    console.error('Error generating recommendations:', result.ErrorMessage);
    return null;
  }
}
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Using Advanced Options

import { RecommendationEngineBase, RecommendationRequest } from '@memberjunction/ai-recommendations';

// Define a custom options interface for your provider
interface MyProviderOptions {
  similarityThreshold: number;
  maxRecommendations: number;
  includeRatings: boolean;
}

async function getCustomizedRecommendations(customerId: string) {
  await RecommendationEngineBase.Instance.Config();
  
  // Create a request with custom options
  const request = new RecommendationRequest<MyProviderOptions>();
  request.EntityAndRecordsInfo = {
    EntityName: 'Customers',
    RecordIDs: [customerId]
  };
  
  // Add provider-specific options
  request.Options = {
    similarityThreshold: 0.75,
    maxRecommendations: 5,
    includeRatings: true
  };
  
  // Execute the recommendation
  return await RecommendationEngineBase.Instance.Recommend(request);
}
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Recommendation Flow

The recommendation process follows these steps:

1. Request Creation: A RecommendationRequest is created with entity records or a list
2. Run Tracking: A RecommendationRun entity is created to track the process
3. Provider Selection: The appropriate recommendation provider is selected
4. Recommendation Generation: The provider generates recommendations for each requested record
5. Result Storage: Recommendations and items are saved to the database
6. Status Update: The run status is updated (completed or error)
7. Result Return: The RecommendationResult is returned to the caller

Data Model

The recommendation engine works with these key entities:

• RecommendationProviderEntity: Configuration for recommendation providers
• RecommendationRunEntity: Tracks each recommendation execution
• RecommendationEntity: Represents a recommendation for a source record
• RecommendationItemEntity: Individual recommendation items (products, content, etc.)

Provider Implementation

To create a custom recommendation provider:

1. Create a class that extends RecommendationProviderBase
2. Implement the Recommend method to generate recommendations
3. Register your provider implementation:

// Register your provider with MemberJunction's class factory
import { MJGlobal } from '@memberjunction/global';
import { RecommendationProviderBase } from '@memberjunction/ai-recommendations';

MJGlobal.Instance.ClassFactory.RegisterClass(
  RecommendationProviderBase,
  'MyRecommendationProvider',
  MyRecommendationProvider
);
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Integration with MemberJunction

This package integrates with the MemberJunction ecosystem:

• Uses MemberJunction entities for data storage and retrieval
• Works with MemberJunction lists for batch processing
• Leverages MemberJunction's metadata system

Dependencies

• @memberjunction/global: MemberJunction global utilities
• @memberjunction/core: MemberJunction core library
• @memberjunction/core-entities: MemberJunction entity definitions
• @memberjunction/ai: MemberJunction AI abstractions

License

ISC