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[Database & ORM](/categories/database) 4. / 5. pgvector/pgvector ActiveLibrary[Database & ORM](/categories/database) pgvector/pgvector ================= pgvector support for PHP v0.2.2(1y ago)194457.8k↑25.6%149MITPHPPHP >= 8.1CI passing Since Aug 5Pushed 1mo ago6 watchersCompare [ Source](https://github.com/pgvector/pgvector-php)[ Packagist](https://packagist.org/packages/pgvector/pgvector)[ RSS](/packages/pgvector-pgvector/feed)WikiDiscussions master Synced 1mo ago READMEChangelogDependencies (6)Versions (11)Used By (9) pgvector-php ============ [](#pgvector-php) [pgvector](https://github.com/pgvector/pgvector) support for PHP Supports [Laravel](https://github.com/laravel/laravel), [Symfony](https://github.com/symfony/symfony), [Doctrine](https://github.com/doctrine/orm), and [PgSql](https://www.php.net/manual/en/book.pgsql.php) [![Build Status](https://github.com/pgvector/pgvector-php/actions/workflows/build.yml/badge.svg)](https://github.com/pgvector/pgvector-php/actions) Getting Started --------------- [](#getting-started) Follow the instructions for your database library: - [Laravel](#laravel) - [Symfony](#symfony) - [Doctrine](#doctrine) - [PgSql](#pgsql) Or check out some examples: - [Embeddings](examples/openai/example.php) with OpenAI - [Binary embeddings](examples/cohere/example.php) with Cohere - [Hybrid search](examples/hybrid/example.php) with Ollama (Reciprocal Rank Fusion) - [Sparse search](examples/sparse/example.php) with Text Embeddings Inference - [Morgan fingerprints](examples/rdkit/example.php) with RDKit - [Recommendations](examples/disco/example.php) with Disco - [Horizontal scaling](examples/citus/example.php) with Citus - [Bulk loading](examples/loading/example.php) with `COPY` ### Laravel [](#laravel) Note: The [Laravel AI SDK](https://laravel.com/docs/13.x/ai-sdk#querying-embeddings) also supports the `vector` type Install the package ``` composer require pgvector/pgvector ``` Enable the extension ``` php artisan vendor:publish --tag="pgvector-migrations" php artisan migrate ``` You can now use the `vector`, `halfvec`, `bit`, and `sparsevec` types in future migrations ``` Schema::create('items', function (Blueprint $table) { $table->vector('embedding', 3); }); ``` Update your model ``` use Pgvector\Laravel\Vector; class Item extends Model { use HasNeighbors; protected $casts = ['embedding' => Vector::class]; } ``` Insert a vector ``` $item = new Item(); $item->embedding = [1, 2, 3]; $item->save(); ``` Get the nearest neighbors to a record ``` use Pgvector\Laravel\Distance; $neighbors = $item->nearestNeighbors('embedding', Distance::L2)->take(5)->get(); ``` Also supports `InnerProduct`, `Cosine`, `L1`, `Hamming`, and `Jaccard` distance Get the nearest neighbors to a vector ``` $neighbors = Item::query()->nearestNeighbors('embedding', [1, 2, 3], Distance::L2)->take(5)->get(); ``` Get the distances ``` $neighbors->pluck('neighbor_distance'); ``` Add an approximate index in a migration ``` public function up() { DB::statement('CREATE INDEX my_index ON items USING hnsw (embedding vector_l2_ops)'); // or DB::statement('CREATE INDEX my_index ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100)'); } public function down() { DB::statement('DROP INDEX my_index'); } ``` Use `vector_ip_ops` for inner product and `vector_cosine_ops` for cosine distance ### Symfony [](#symfony) Install the package ``` composer require pgvector/pgvector ``` Register the types and distance functions in `config/packages/doctrine.yaml` ``` doctrine: dbal: types: vector: Pgvector\Doctrine\VectorType halfvec: Pgvector\Doctrine\HalfVectorType bit: Pgvector\Doctrine\BitType sparsevec: Pgvector\Doctrine\SparseVectorType orm: dql: numeric_functions: l2_distance: Pgvector\Doctrine\L2Distance max_inner_product: Pgvector\Doctrine\MaxInnerProduct cosine_distance: Pgvector\Doctrine\CosineDistance l1_distance: Pgvector\Doctrine\L1Distance hamming_distance: Pgvector\Doctrine\HammingDistance jaccard_distance: Pgvector\Doctrine\JaccardDistance ``` Create a migration to enable the extension ``` php bin/console doctrine:migrations:generate ``` And update it ``` public function up(Schema $schema): void { $this->addSql('CREATE EXTENSION vector'); } public function down(Schema $schema): void { $this->addSql('DROP EXTENSION vector'); } ``` Migrate ``` php bin/console doctrine:migrations:migrate ``` Update your entity ``` use Pgvector\Vector; #[ORM\Entity(repositoryClass: ItemRepository::class)] class Item { #[ORM\Column(type: 'vector', length: 3)] private ?Vector $embedding = null; public function getEmbedding(): ?Vector { return $this->embedding; } public function setEmbedding(Vector $embedding): static { $this->embedding = $embedding; return $this; } } ``` Migrate ``` php bin/console make:migration php bin/console doctrine:migrations:migrate ``` Insert a vector ``` $item = new Item(); $item->setEmbedding(new Vector([1, 2, 3])); $entityManager->persist($item); $entityManager->flush(); ``` Get the nearest neighbors to a vector ``` $neighbors = $entityManager->createQuery('SELECT i FROM App\Entity\Item i ORDER BY l2_distance(i.embedding, ?1)') ->setParameter(1, new Vector([1, 2, 3])) ->setMaxResults(5) ->getResult(); ``` Also supports `max_inner_product`, `cosine_distance`, `l1_distance`, `hamming_distance`, and `jaccard_distance` ### Doctrine [](#doctrine) Install the package ``` composer require pgvector/pgvector ``` Register the types and distance functions ``` use Pgvector\Doctrine\PgvectorSetup; PgvectorSetup::registerTypes($entityManager); ``` Enable the extension ``` $entityManager->getConnection()->executeStatement('CREATE EXTENSION IF NOT EXISTS vector'); ``` Update your entity ``` use Pgvector\Vector; #[ORM\Entity] class Item { #[ORM\Column(type: 'vector', length: 3)] private Vector $embedding; public function setEmbedding(Vector $embedding): void { $this->embedding = $embedding; } } ``` Insert a vector ``` $item = new Item(); $item->setEmbedding(new Vector([1, 2, 3])); $entityManager->persist($item); $entityManager->flush(); ``` Get the nearest neighbors to a vector ``` $neighbors = $entityManager->createQuery('SELECT i FROM Item i ORDER BY l2_distance(i.embedding, ?1)') ->setParameter(1, new Vector([1, 2, 3])) ->setMaxResults(5) ->getResult(); ``` Also supports `max_inner_product`, `cosine_distance`, `l1_distance`, `hamming_distance`, and `jaccard_distance` ### PgSql [](#pgsql) Enable the extension ``` pg_query($db, 'CREATE EXTENSION IF NOT EXISTS vector'); ``` Create a table ``` pg_query($db, 'CREATE TABLE items (embedding vector(3))'); ``` Insert a vector ``` use Pgvector\Vector; $embedding = new Vector([1, 2, 3]); pg_query_params($db, 'INSERT INTO items (embedding) VALUES ($1)', [$embedding]); ``` Get the nearest neighbors to a vector ``` $embedding = new Vector([1, 2, 3]); $result = pg_query_params($db, 'SELECT * FROM items ORDER BY embedding $1 LIMIT 5', [$embedding]); ``` Add an approximate index ``` pg_query($db, 'CREATE INDEX ON items USING hnsw (embedding vector_l2_ops)'); // or pg_query($db, 'CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100)'); ``` See a [full example](examples/pgsql/example.php) Reference --------- [](#reference) ### Vectors [](#vectors) Create a vector from an array ``` $vec = new Vector([1, 2, 3]); ``` Get an array ``` $arr = $vec->toArray(); ``` ### Half Vectors [](#half-vectors) Create a half vector from an array ``` $vec = new HalfVector([1, 2, 3]); ``` Get an array ``` $arr = $vec->toArray(); ``` ### Sparse Vectors [](#sparse-vectors) Create a sparse vector from an indexed array ``` $vec = new SparseVector([1, 0, 2, 0, 3, 0]); ``` Or an associative array of non-zero elements ``` $elements = [0 => 1, 2 => 2, 4 => 3]; $vec = new SparseVector($elements, 6); ``` Note: Indices start at 0 Get the number of dimensions ``` $dim = $vec->dimensions(); ``` Get the indices of non-zero elements ``` $indices = $vec->indices(); ``` Get the values of non-zero elements ``` $values = $vec->values(); ``` Get an array ``` $arr = $vec->toArray(); ``` History ------- [](#history) View the [changelog](https://github.com/pgvector/pgvector-php/blob/master/CHANGELOG.md) Contributing ------------ [](#contributing) Everyone is encouraged to help improve this project. Here are a few ways you can help: - [Report bugs](https://github.com/pgvector/pgvector-php/issues) - Fix bugs and [submit pull requests](https://github.com/pgvector/pgvector-php/pulls) - Write, clarify, or fix documentation - Suggest or add new features To get started with development: ``` git clone https://github.com/pgvector/pgvector-php.git cd pgvector-php composer install createdb pgvector_php_test composer test ``` To run an example: ``` cd examples/loading composer install createdb pgvector_example php example.php ``` ### Health Score 53 — FairBetter than 97% of packages Maintenance69 Regular maintenance activity Popularity55 Moderate usage in the ecosystem Community24 Small or concentrated contributor base Maturity52 Maturing project, gaining track record Bus Factor1 Top contributor holds 99.5% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Every ~132 days Recently: every ~125 days Total 8 Last Release 457d ago PHP version history (2 changes)v0.1.0PHP >= 7.4 v0.2.0PHP >= 8.1 ### Community Maintainers ![](https://avatars.githubusercontent.com/u/220358?v=4)[Andrew Kane](/maintainers/ankane)[@ankane](https://github.com/ankane) --- Top Contributors [![ankane](https://avatars.githubusercontent.com/u/220358?v=4)](https://github.com/ankane "ankane (193 commits)")[![C0chett0](https://avatars.githubusercontent.com/u/1436541?v=4)](https://github.com/C0chett0 "C0chett0 (1 commits)") ### Code Quality TestsPHPUnit ### Embed Badge ![Health badge](/badges/pgvector-pgvector/health.svg) ``` [![Health](https://phpackages.com/badges/pgvector-pgvector/health.svg)](https://phpackages.com/packages/pgvector-pgvector) ``` ### Alternatives [doctrine/orm Object-Relational-Mapper for PHP 10.2k285.3M6.2k](/packages/doctrine-orm)[jdorn/sql-formatter a PHP SQL highlighting library 3.9k115.1M102](/packages/jdorn-sql-formatter)[illuminate/database The Illuminate Database package. 2.8k52.4M9.4k](/packages/illuminate-database)[ramsey/uuid-doctrine Use ramsey/uuid as a Doctrine field type. 90440.3M211](/packages/ramsey-uuid-doctrine)[reliese/laravel Reliese Components for Laravel Framework code generation. 1.7k3.4M16](/packages/reliese-laravel)[wildside/userstamps Laravel Userstamps provides an Eloquent trait which automatically maintains `created\_by` and `updated\_by` columns on your model, populated by the currently authenticated user in your application. 7511.7M13](/packages/wildside-userstamps) PHPackages © 2026 [Directory](/)[Categories](/categories)[Trending](/trending)[Changelog](/changelog)[Analyze](/analyze)