hyperf/qdrant-client
最新稳定版本:v0.0.3
Composer 安装命令:
composer require hyperf/qdrant-client
包简介
README 文档
README
Install
composer require hyperf/qdrant-client
Usage
An example to create a collection:
use App\VectorStore\Qdrant\Config; use Hyperf\Qdrant\Api\Collections; use Hyperf\Qdrant\Api\Points; use Hyperf\Qdrant\Connection\HttpClient; use Hyperf\Qdrant\Struct\Collections\Enums\Distance; use Hyperf\Qdrant\Struct\Collections\VectorParams; use Hyperf\Qdrant\Struct\Points\ExtendedPointId; use Hyperf\Qdrant\Struct\Points\Point\PointStruct; use Hyperf\Qdrant\Struct\Points\SearchCondition\FieldCondition; use Hyperf\Qdrant\Struct\Points\SearchCondition\Filter; use Hyperf\Qdrant\Struct\Points\SearchCondition\Match\MatchValue; use Hyperf\Qdrant\Struct\Points\VectorStruct; $client = new HttpClient(new Config(...)); $collections = new Collections($client); $collections->createCollection('test_collection', new VectorParams(1536, Distance::COSINE)); # insert vector data $points = new Points($client); $points->setWait(true); $points->upsertPoints('test_collection', [ new PointStruct( new ExtendedPointId($key + 10000), new VectorStruct($data['embeddings'][0]), [ # payload 'name' => $data['name'], 'description' => $data['description'], 'image' => $data['image'], ], ), ]); # similarity search $result = $points->searchPoints( 'test_collection', new VectorStruct($data['embeddings'][0]), 3, withPayload: new WithPayload(true), ); print_r($result); # payload filter $result = $points->searchPoints( 'test_collection', new VectorStruct($data['embeddings'][0]), 3, new Filter( must: [ new FieldCondition('name', new MatchValue('qdrant')), ] ), withPayload: new WithPayload(true), ); print_r($result);
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其他信息
- 授权协议: MIT
- 更新时间: 2023-07-24