x-laravel / embedding-mysql-plugin
MySQL 9 native VECTOR similarity driver for x-laravel/embedding.
Package info
github.com/x-laravel/embedding-mysql-plugin
pkg:composer/x-laravel/embedding-mysql-plugin
Requires
- php: ^8.3
- illuminate/support: ^12.0|^13.0
- x-laravel/embedding: ^1.0
Requires (Dev)
- orchestra/testbench: ^10.0|^11.0
- phpunit/phpunit: ^11.0|^12.0
This package is auto-updated.
Last update: 2026-05-07 23:13:38 UTC
README
MySQL HeatWave native vector driver for x-laravel/embedding.
How It Works
- Implements
SimilarityDriver— registers as themysqldriver, similarity search runs entirely in MySQL usingVEC_DISTANCE_COSINE - Implements
VectorStore— writes embeddings viaINSERT ... ON DUPLICATE KEY UPDATEwithSTRING_TO_VECTOR(), reads via aVECTOR_TO_STRINGglobal scope
Requirements
- PHP ^8.3
- Laravel ^12.0 | ^13.0
x-laravel/embedding ^1.0- MySQL HeatWave —
VEC_DISTANCE_COSINEis not available in MySQL Community Edition; this plugin requires MySQL HeatWave
Installation
composer require x-laravel/embedding-mysql-plugin
The MysqlEmbeddingServiceProvider is auto-discovered and registers the mysql driver automatically.
Setup
1. Configure x-laravel/embedding
Publish the config if you haven't already:
php artisan vendor:publish --tag=embedding-config
Set the similarity driver and database connection in config/embedding.php:
'database' => [ 'connection' => env('EMBEDDINGS_DATABASE_CONNECTION', env('DB_CONNECTION', 'mysql')), 'table' => env('EMBEDDINGS_DB_TABLE', 'embeddings'), ], 'similarity' => [ 'driver' => env('EMBEDDING_SIMILARITY_DRIVER', 'auto'), ],
2. Create the embeddings table
This plugin ships its own MySQL-native migration that replaces the default one from x-laravel/embedding. It creates a VECTOR(1536) column.
Run the migration:
php artisan migrate
If you need to customise the DDL, publish the migration first:
php artisan vendor:publish --tag=embedding-mysql-migrations php artisan migrate
Note:
VEC_DISTANCE_COSINEis only available on MySQL HeatWave, not MySQL Community Edition. For production, add aVECTOR INDEXon thevectorcolumn after publishing the migration.
3. Model
Follow the standard x-laravel/embedding setup. No MySQL-specific changes are needed on your models.
use XLaravel\Embedding\Attributes\EmbedOn; use XLaravel\Embedding\Concerns\Embeddable; use XLaravel\Embedding\Contracts\HasEmbeddings; #[EmbedOn(['title', 'body'])] class Post extends Model implements HasEmbeddings { use Embeddable; public function toEmbeddingText(): string { return $this->title.' '.$this->body; } }
Usage
The driver is transparent — use the standard x-laravel/embedding API:
Post::similarToText('web framework', limit: 10); Post::similarTo($vector, limit: 10, threshold: 0.8); Post::rankByRelevance($posts, 'web framework'); $post->mostSimilar(limit: 5); $post->similarityTo($otherPost);
All methods set a similarity_score float attribute on each returned model.
Testing
Tests require a MySQL HeatWave instance. The docker-compose.yml uses mysql:9.1.0 for CI convenience but VEC_DISTANCE_COSINE tests will fail against Community Edition — run them against a real HeatWave instance.
# Build first (once per PHP version) DOCKER_BUILDKIT=0 docker compose --profile php83 build # Run tests docker compose --profile php83 up docker compose --profile php84 up docker compose --profile php85 up
License
This package is open-sourced software licensed under the MIT license.