AWS S3 Vectors Bridge

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use AsyncAws\S3Vectors\S3VectorsClient;
use Symfony\AI\Store\Bridge\S3Vectors\Store;

$client = new S3VectorsClient([
    'region' => 'us-east-1',
]);

$store = new Store(
    client: $client,
    vectorBucketName: 'my-vector-bucket',
    indexName: 'my-index',
    filter: [], // Optional: default filter for queries
    topK: 3, // Optional: default number of results
    dimensions: 1536, // Optional: dimensions of the index, default: 1536
    metric: \AsyncAws\S3Vectors\Enum\DistanceMetric::COSINE, // Optional
    dataType: \AsyncAws\S3Vectors\Enum\DataType::FLOAT_32, // Optional
    kmsKeyId: 'your-kms-key-id', // Optional: encrypts the bucket and the index
    tags: ['env' => 'production'], // Optional
);

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use Symfony\AI\Platform\Vector\Vector;
use Symfony\AI\Store\Document\Metadata;
use Symfony\AI\Store\Document\VectorDocument;
use Symfony\Component\Uid\Uuid;

$document = new VectorDocument(
    id: Uuid::v4()->toRfc4122(),
    vector: new Vector([0.1, 0.2, 0.3, ...]),
    metadata: new Metadata(['title' => 'My Document'])
);
$store->add($document);

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use Symfony\AI\Platform\Vector\Vector;
use Symfony\AI\Store\Query\VectorQuery;

$results = $store->query(
    query: new VectorQuery(new Vector([0.1, 0.2, 0.3, ...])),
    options: [
        'topK' => 5,
        'filter' => ['category' => 'documentation'],
    ]
);

foreach ($results as $result) {
    echo $result->getMetadata()['title'] . ' (score: ' . $result->getScore() . ')' . PHP_EOL;
}