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Implements SimilarityDriver — registers as the pgsql driver, similarity search runs entirely in PostgreSQL using pgvector's <=> cosine distance operator
No custom VectorStore needed — pgvector's text format ([1.0, 2.0, ...]) is valid JSON, so the core JSON storage works transparently
The PgsqlEmbeddingServiceProvider is auto-discovered and registers the pgsql driver automatically.
Setup
1. Configure x-laravel/embedding
Publish the config if you haven't already:
Set the similarity driver and database connection in config/embedding.php:
2. Create the embeddings table
This driver ships its own PostgreSQL-native migration that replaces the default one from x-laravel/embedding. It enables the pgvector extension and creates a vector(1536) column.
Run the migration:
If you need to customise the DDL, publish the migration first:
Note:CREATE EXTENSION IF NOT EXISTS vector requires CREATE privilege on the database. On managed platforms (RDS, Supabase, Cloud SQL), enable the extension separately with elevated privileges before running the migration.
3. Model
Follow the standard x-laravel/embedding setup. No PostgreSQL-specific changes are needed on your models.
Usage
The driver is transparent — use the standard x-laravel/embedding API:
All methods set a similarity_score float attribute on each returned model.
Testing
License
This package is open-sourced software licensed under the MIT license.
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