feat(store): qdrant store started

Author: Guikingone

examples/.env

@@ -81,3 +81,7 @@ MEILISEARCH_API_KEY=changeMe
 
 # For using LMStudio
 LMSTUDIO_HOST_URL=http://127.0.0.1:1234
+
+# Qdrant
+QDRANT_HOST='http://127.0.0.1:6333'
+QDRANT_SERVICE_API_KEY=changeMe

examples/compose.yaml

@@ -5,7 +5,7 @@ services:
       MARIADB_ALLOW_EMPTY_ROOT_PASSWORD: 1
       MARIADB_DATABASE: my_database
     ports:
-      - "3309:3306"
+      - '3309:3306'
 
   postgres:
     image: pgvector/pgvector:0.8.0-pg17
@@ -14,11 +14,18 @@ services:
         POSTGRES_USER: postgres
         POSTGRES_PASSWORD: postgres
     ports:
-        - "5432:5432"
+        - '5432:5432'
 
   meilisearch:
       image: getmeili/meilisearch:v1.15
       environment:
-          MEILI_MASTER_KEY: "${MEILISEARCH_MASTER_KEY:-changeMe}"
+          MEILI_MASTER_KEY: '${MEILISEARCH_MASTER_KEY:-changeMe}'
       ports:
-          - "7700:7700"
+          - '7700:7700'
+
+  qdrant:
+      image: qdrant/qdrant
+      environment:
+          QDRANT__SERVICE__API_KEY: '${QDRAT_SERVICE_API_KEY:-changeMe}'
+      ports:
+          - '6333:6333'

examples/store/qdrant-similarity-search.php

@@ -0,0 +1,78 @@
+<?php
+
+/*
+ * This file is part of the Symfony package.
+ *
+ * (c) Fabien Potencier <[email protected]>
+ *
+ * For the full copyright and license information, please view the LICENSE
+ * file that was distributed with this source code.
+ */
+
+use Symfony\AI\Agent\Agent;
+use Symfony\AI\Agent\Toolbox\AgentProcessor;
+use Symfony\AI\Agent\Toolbox\Tool\SimilaritySearch;
+use Symfony\AI\Agent\Toolbox\Toolbox;
+use Symfony\AI\Fixtures\Movies;
+use Symfony\AI\Platform\Bridge\OpenAI\Embeddings;
+use Symfony\AI\Platform\Bridge\OpenAI\GPT;
+use Symfony\AI\Platform\Bridge\OpenAI\PlatformFactory;
+use Symfony\AI\Platform\Message\Message;
+use Symfony\AI\Platform\Message\MessageBag;
+use Symfony\AI\Store\Bridge\Qdrant\Store;
+use Symfony\AI\Store\Document\Metadata;
+use Symfony\AI\Store\Document\TextDocument;
+use Symfony\AI\Store\Document\Vectorizer;
+use Symfony\AI\Store\Indexer;
+use Symfony\Component\Dotenv\Dotenv;
+use Symfony\Component\HttpClient\HttpClient;
+use Symfony\Component\Uid\Uuid;
+
+require_once dirname(__DIR__).'/vendor/autoload.php';
+(new Dotenv())->loadEnv(dirname(__DIR__).'/.env');
+
+if (!isset($_SERVER['OPENAI_API_KEY'], $_SERVER['QDRANT_HOST'], $_SERVER['QDRANT_SERVICE_API_KEY'])) {
+    echo 'Please set OPENAI_API_KEY, QDRANT_HOST and QDRANT_SERVICE_API_KEY environment variables.'.\PHP_EOL;
+    exit(1);
+}
+
+// initialize the store
+$store = new Store(
+    HttpClient::create(),
+    'http://127.0.0.1:6333',
+    $_SERVER['QDRANT_SERVICE_API_KEY'],
+    'movies',
+);
+
+// initialize the collection (needs to be called before the indexer)
+$store->initialize();
+
+// create embeddings and documents
+foreach (Movies::all() as $movie) {
+    $documents[] = new TextDocument(
+        id: Uuid::v4(),
+        content: 'Title: '.$movie['title'].\PHP_EOL.'Director: '.$movie['director'].\PHP_EOL.'Description: '.$movie['description'],
+        metadata: new Metadata($movie),
+    );
+}
+
+// create embeddings for documents
+$platform = PlatformFactory::create($_SERVER['OPENAI_API_KEY']);
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
+$indexer = new Indexer($vectorizer, $store);
+$indexer->index($documents);
+
+$model = new GPT(GPT::GPT_4O_MINI);
+
+$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$toolbox = Toolbox::create($similaritySearch);
+$processor = new AgentProcessor($toolbox);
+$agent = new Agent($platform, $model, [$processor], [$processor]);
+
+$messages = new MessageBag(
+    Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),
+    Message::ofUser('Which movie fits the theme of the mafia?')
+);
+$response = $agent->call($messages);
+
+echo $response->getContent().\PHP_EOL;

src/store/CHANGELOG.md

@@ -42,6 +42,7 @@ CHANGELOG
    - Meilisearch
    - ChromaDB
    - Pinecone
+   - Qdrant
  * Add Retrieval Augmented Generation (RAG) support:
    - Document embedding storage
    - Similarity search for relevant documents
@@ -52,4 +53,4 @@ CHANGELOG
    - Result limiting
    - Distance/similarity scoring
  * Add custom exception hierarchy with `ExceptionInterface`
- * Add support for specific exceptions for invalid arguments and runtime errors
+ * Add support for specific exceptions for invalid arguments and runtime errors

src/store/doc/index.rst

@@ -42,6 +42,7 @@ You can find more advanced usage in combination with an Agent using the store fo
 * `Similarity Search with Pinecone (RAG)`_
 * `Similarity Search with Meilisearch (RAG)`_
 * `Similarity Search with memory storage (RAG)`_
+* `Similarity Search with Qdrant (RAG)`_
 
 Supported Stores
 ----------------
@@ -54,6 +55,7 @@ Supported Stores
 * `Postgres`_ (requires `ext-pdo`)
 * `Meilisearch`_
 * `InMemory`_
+* `Qdrant`_
 
 .. note::
 
@@ -92,6 +94,7 @@ This leads to a store implementing two methods::
 .. _`Similarity Search with Pinecone (RAG)`: https://github.com/symfony/ai/blob/main/examples/store/pinecone-similarity-search.php
 .. _`Similarity Search with Meilisearch (RAG)`: https://github.com/symfony/ai/blob/main/examples/store/meilisearch-similarity-search.php
 .. _`Similarity Search with memory storage (RAG)`: https://github.com/symfony/ai/blob/main/examples/store/memory-similarity-search.php
+.. _`Similarity Search with Qdrant (RAG)`: https://github.com/symfony/ai/blob/main/examples/store/qdrant-similarity-search.php
 .. _`Azure AI Search`: https://azure.microsoft.com/products/ai-services/ai-search
 .. _`Chroma`: https://www.trychroma.com/
 .. _`MariaDB`: https://mariadb.org/projects/mariadb-vector/
@@ -100,4 +103,5 @@ This leads to a store implementing two methods::
 .. _`Postgres`: https://www.postgresql.org/about/news/pgvector-070-released-2852/
 .. _`Meilisearch`: https://www.meilisearch.com/
 .. _`InMemory`: https://www.php.net/manual/en/language.types.array.php
+.. _`Qdrant`: https://qdrant.tech/
 .. _`GitHub`: https://github.com/symfony/ai/issues/16

src/store/src/Bridge/Qdrant/Store.php

@@ -0,0 +1,142 @@
+<?php
+
+/*
+ * This file is part of the Symfony package.
+ *
+ * (c) Fabien Potencier <[email protected]>
+ *
+ * For the full copyright and license information, please view the LICENSE
+ * file that was distributed with this source code.
+ */
+
+namespace Symfony\AI\Store\Bridge\Qdrant;
+
+use Symfony\AI\Platform\Vector\NullVector;
+use Symfony\AI\Platform\Vector\Vector;
+use Symfony\AI\Store\Document\Metadata;
+use Symfony\AI\Store\Document\VectorDocument;
+use Symfony\AI\Store\Exception\InvalidArgumentException;
+use Symfony\AI\Store\InitializableStoreInterface;
+use Symfony\AI\Store\VectorStoreInterface;
+use Symfony\Component\Uid\Uuid;
+use Symfony\Contracts\HttpClient\HttpClientInterface;
+
+/**
+ * @author Guillaume Loulier <[email protected]>
+ */
+final readonly class Store implements InitializableStoreInterface, VectorStoreInterface
+{
+    public function __construct(
+        private HttpClientInterface $httpClient,
+        private string $endpointUrl,
+        #[\SensitiveParameter] private string $apiKey,
+        private string $collectionName,
+        private int $embeddingsDimension = 1536,
+        private string $embeddingsDistance = 'Cosine',
+    ) {
+    }
+
+    public function add(VectorDocument ...$documents): void
+    {
+        $this->request('PUT', \sprintf('collections/%s/points', $this->collectionName), [
+            'points' => array_map($this->convertToIndexableArray(...), $documents),
+        ]);
+    }
+
+    /**
+     * @param array{
+     *     limit?: positive-int,
+     *     offset?: positive-int
+     * } $options
+     */
+    public function query(Vector $vector, array $options = [], ?float $minScore = null): array
+    {
+        $payload = [
+            'vector' => $vector->getData(),
+            'with_payload' => true,
+            'with_vector' => true,
+        ];
+
+        if (\array_key_exists('limit', $options)) {
+            $payload['limit'] = $options['limit'];
+        }
+
+        if (\array_key_exists('offset', $options)) {
+            $payload['offset'] = $options['offset'];
+        }
+
+        $response = $this->request('POST', \sprintf('collections/%s/points/query', $this->collectionName), $payload);
+
+        return array_map($this->convertToVectorDocument(...), $response['result']['points']);
+    }
+
+    public function initialize(array $options = []): void
+    {
+        if ([] !== $options) {
+            throw new InvalidArgumentException('No supported options');
+        }
+
+        $collectionExistResponse = $this->request('GET', \sprintf('collections/%s/exists', $this->collectionName));
+
+        if ($collectionExistResponse['result']['exists']) {
+            return;
+        }
+
+        $this->request('PUT', \sprintf('collections/%s', $this->collectionName), [
+            'vectors' => [
+                'size' => $this->embeddingsDimension,
+                'distance' => $this->embeddingsDistance,
+            ],
+        ]);
+    }
+
+    /**
+     * @param array<string, mixed> $payload
+     *
+     * @return array<string, mixed>
+     */
+    private function request(string $method, string $endpoint, array $payload = []): array
+    {
+        $url = \sprintf('%s/%s', $this->endpointUrl, $endpoint);
+
+        $response = $this->httpClient->request($method, $url, [
+            'headers' => [
+                'api-key' => $this->apiKey,
+            ],
+            'json' => $payload,
+        ]);
+
+        return $response->toArray();
+    }
+
+    /**
+     * @return array<string, mixed>
+     */
+    private function convertToIndexableArray(VectorDocument $document): array
+    {
+        return [
+            'id' => $document->id->toRfc4122(),
+            'vector' => $document->vector->getData(),
+            'payload' => $document->metadata->getArrayCopy(),
+        ];
+    }
+
+    /**
+     * @param array<string, mixed> $data
+     */
+    private function convertToVectorDocument(array $data): VectorDocument
+    {
+        $id = $data['id'] ?? throw new InvalidArgumentException('Missing "id" field in the document data');
+
+        $vector = !\array_key_exists('vector', $data) || null === $data['vector']
+            ? new NullVector()
+            : new Vector($data['vector']);
+
+        return new VectorDocument(
+            id: Uuid::fromString($id),
+            vector: $vector,
+            metadata: new Metadata($data['payload']),
+            score: $data['score'] ?? null
+        );
+    }
+}