AI Vector Dupe Documentation

**AI Vector Dupe ** is a package designed to identify duplicate records in a database by generating vector representations and finding similar vectors. Users can then take actions, such as merging or deleting the detected duplicates.

Prerequisites

Before using the package, ensure the following requirements are met:

1. SQL Server with MemberJunction Framework
   MemberJunction Documentation

2. Embedding Model API Key
   Supported embedding models include OpenAI, Mistral, and others supported by MemberJunction.

3. Vector Database API Key
   Currently, only Pinecone is supported for vector storage.

How to Run the Package

Follow these steps to use the AI Vector Dupe package:

1. Load Required Packages
   Ensure this package, along with your embedding and vector database packages, is loaded into your application. Verify they are not tree-shaken out.

2. Prepare Records
   Create a list of records to search for duplicates. Note: Currently, this package supports finding duplicates within the same entity. Support for cross-entity duplicate checks is planned for future updates.

3. Call thegetDuplicateRecords Function
   Create an instance of the DuplicateRecordDetector class and call the getDuplicateRecords function with the following parameters:

   Parameter	Type	Description
   listID	string	The ID of the list containing the records to analyze.
   entityID	string	The ID of the entity the records belong to.
   probabilityScore	number (optional)	The minimum similarity score to consider a record as a potential duplicate.

   Return: A Promise that resolves after processing. For large datasets, it is recommended not toawait the result.

Workflow: getDuplicateRecords Function

The getDuplicateRecords function performs the following steps:

1. Fetch Records
   Fetches the list by listID and retrieves all records contained within it.

2. Generate or Fetch Vectors

   • If configured, generates new vectors for all records associated with the specified entityID and upserts them into the vector database.
   • If not configured to upsert new vectors, it queries the vector database to fetch existing vectors for the records.

3. Search for Similar Vectors
   For each vector, queries the vector database to find n similar vectors (where n is user-specified).

4. Fetch Related Records
   Fetches database records corresponding to the similar vectors retrieved.

5. Merge Duplicates (Optional)
   If configured, merges records marked as duplicates into the source record based on a similarity probability threshold.

   • Example: If the similarity score exceeds 0.95, the record is merged.

6. Track Results
   Records are created in the database to log:

   • The duplicate record search run.
   • Which records were analyzed.
   • Which records were marked as potential duplicates.

Example Usage

Here is an example of how to use the package:

const { DuplicateRecordDetector } = require('ai-vector-dupe');

// Create an instance of the DuplicateRecordDetector
const detector = new DuplicateRecordDetector();

// Call getDuplicateRecords
detector.getDuplicateRecords({
  listID: 'example-list-id',
  entityID: 'example-entity-id',
  probabilityScore: 0.9
});