[Store] Add support for Redis

src/ai-bundle/config/options.php

@@ -15,6 +15,7 @@
 use MongoDB\Client as MongoDbClient;
 use Probots\Pinecone\Client as PineconeClient;
 use Symfony\AI\Platform\PlatformInterface;
+use Symfony\AI\Store\Bridge\Redis\Distance;
 use Symfony\AI\Store\StoreInterface;
 
 return static function (DefinitionConfigurator $configurator): void {
@@ -252,10 +253,30 @@
                             ->end()
                         ->end()
                     ->end()
+                    ->arrayNode('redis')
+                        ->normalizeKeys(false)
+                        ->useAttributeAsKey('name')
+                        ->arrayPrototype()
+                            ->children()
+                                ->variableNode('connection_parameters')
+                                    ->info('see https://github.com/phpredis/phpredis?tab=readme-ov-file#example-1')
+                                    ->isRequired()
+                                    ->cannotBeEmpty()
+                                ->end()
+                                ->scalarNode('index_name')->isRequired()->cannotBeEmpty()->end()
+                                ->scalarNode('key_prefix')->defaultValue('vector:')->end()
+                                ->enumNode('distance')
+                                    ->info('Distance metric to use for vector similarity search')
+                                    ->values(Distance::cases())
+                                    ->defaultValue(Distance::Cosine)
+                                ->end()
+                            ->end()
+                        ->end()
+                    ->end()
                     ->arrayNode('surreal_db')
                         ->normalizeKeys(false)
                         ->useAttributeAsKey('name')
-                            ->arrayPrototype()
+                        ->arrayPrototype()
                             ->children()
                                 ->scalarNode('endpoint')->cannotBeEmpty()->end()
                                 ->scalarNode('username')->cannotBeEmpty()->end()

src/ai-bundle/src/AiBundle.php

@@ -45,6 +45,7 @@
 use Symfony\AI\Store\Bridge\Neo4j\Store as Neo4jStore;
 use Symfony\AI\Store\Bridge\Pinecone\Store as PineconeStore;
 use Symfony\AI\Store\Bridge\Qdrant\Store as QdrantStore;
+use Symfony\AI\Store\Bridge\Redis\Store as RedisStore;
 use Symfony\AI\Store\Bridge\SurrealDb\Store as SurrealDbStore;
 use Symfony\AI\Store\Document\Vectorizer;
 use Symfony\AI\Store\Indexer;
@@ -638,6 +639,28 @@ private function processStoreConfig(string $type, array $stores, ContainerBuilde
             }
         }
 
+        if ('redis' === $type) {
+            foreach ($stores as $name => $store) {
+                $connectionDefinition = new Definition(\Redis::class);
+                $connectionDefinition->setArguments([$store['connection_parameters']]);
+
+                $arguments = [
+                    $connectionDefinition,
+                    $store['index_name'],
+                    $store['key_prefix'],
+                    $store['distance'],
+                ];
+
+                $definition = new Definition(RedisStore::class);
+                $definition
+                    ->addTag('ai.store')
+                    ->setArguments($arguments)
+                ;
+
+                $container->setDefinition('ai.store.'.$type.'.'.$name, $definition);
+            }
+        }
+
         if ('surreal_db' === $type) {
             foreach ($stores as $name => $store) {
                 $arguments = [

src/ai-bundle/tests/DependencyInjection/AiBundleTest.php

@@ -259,6 +259,15 @@ private function getFullConfig(): array
                             'distance' => 'Cosine',
                         ],
                     ],
+                    'redis' => [
+                        'my_redis_store' => [
+                            'connection_parameters' => [
+                                'host' => '1.2.3.4',
+                                'port' => 6379,
+                            ],
+                            'index_name' => 'my_vector_index',
+                        ],
+                    ],
                     'surreal_db' => [
                         'my_surreal_db_store' => [
                             'endpoint' => 'http://127.0.0.1:8000',

src/store/CHANGELOG.md

@@ -45,6 +45,7 @@ CHANGELOG
    - Qdrant
    - SurrealDB
    - Neo4j
+   - Redis
  * Add Retrieval Augmented Generation (RAG) support:
    - Document embedding storage
    - Similarity search for relevant documents

src/store/composer.json

@@ -32,6 +32,7 @@
         "symfony/ai-platform": "@dev",
         "symfony/clock": "^6.4 || ^7.1",
         "symfony/http-client": "^6.4 || ^7.1",
+        "symfony/polyfill-php83": "^1.32",
         "symfony/uid": "^6.4 || ^7.1"
     },
     "require-dev": {

src/store/src/Bridge/Redis/Distance.php

@@ -0,0 +1,31 @@
+<?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\Redis;
+
+use OskarStark\Enum\Trait\Comparable;
+
+/**
+ * @author Grégoire Pineau <[email protected]>
+ */
+enum Distance: string
+{
+    use Comparable;
+
+    case Cosine = 'COSINE';
+    case L2 = 'L2';
+    case Ip = 'IP';
+
+    public function getRedisMetric(): string
+    {
+        return $this->value;
+    }
+}

src/store/src/Bridge/Redis/Store.php

@@ -0,0 +1,173 @@
+<?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\Redis;
+
+use Symfony\AI\Platform\Vector\Vector;
+use Symfony\AI\Platform\Vector\VectorInterface;
+use Symfony\AI\Store\Document\Metadata;
+use Symfony\AI\Store\Document\VectorDocument;
+use Symfony\AI\Store\Exception\RuntimeException;
+use Symfony\AI\Store\InitializableStoreInterface;
+use Symfony\AI\Store\VectorStoreInterface;
+use Symfony\Component\Uid\Uuid;
+
+/**
+ * @author Grégoire Pineau <[email protected]>
+ */
+class Store implements VectorStoreInterface, InitializableStoreInterface
+{
+    public function __construct(
+        private readonly \Redis $redis,
+        private readonly string $indexName,
+        private readonly string $keyPrefix = 'vector:',
+        private readonly Distance $distance = Distance::Cosine,
+    ) {
+    }
+
+    /**
+     * @param array{vector_size?: positive-int, index_method?: string, extra_schema?: list<string>} $options
+     *
+     * - For Mistral: ['vector_size' => 1024]
+     * - For OpenAI: ['vector_size' => 1536]
+     * - For Gemini: ['vector_size' => 3072] (default)
+     * - For other models: adjust vector_size accordingly
+     */
+    public function initialize(array $options = []): void
+    {
+        $vectorSize = $options['vector_size'] ?? 3072;
+        $indexMethod = $options['index_method'] ?? 'FLAT'; // Or 'HNSW' for approximate search
+        $distanceMetric = $this->distance->getRedisMetric();
+        $extraSchema = $options['extra_schema'] ?? [];
+
+        // Create the index with vector field for JSON documents
+        try {
+            $this->redis->rawCommand(
+                'FT.CREATE', $this->indexName, 'ON', 'JSON',
+                'PREFIX', '1', $this->keyPrefix,
+                'SCHEMA',
+                '$.id', 'AS', 'id', 'TEXT',
+                // '$.metadata', 'AS', 'metadata', 'TEXT',
+                '$.embedding', 'AS', 'embedding', 'VECTOR', $indexMethod, '6', 'TYPE', 'FLOAT32', 'DIM', $vectorSize, 'DISTANCE_METRIC', $distanceMetric,
+                ...$extraSchema,
+            );
+        } catch (\RedisException $e) {
+            // Index might already exist, check if it's a "already exists" error
+            if (!str_contains($e->getMessage(), 'Index already exists')) {
+                throw new RuntimeException(\sprintf('Failed to create Redis index: "%s".', $e->getMessage()), 0, $e);
+            }
+        }
+    }
+
+    public function add(VectorDocument ...$documents): void
+    {
+        $pipeline = $this->redis->multi(\Redis::PIPELINE);
+
+        foreach ($documents as $document) {
+            $key = $this->keyPrefix.$document->id->toRfc4122();
+            $data = [
+                'id' => $document->id->toRfc4122(),
+                'metadata' => $document->metadata->getArrayCopy(),
+                'embedding' => $document->vector->getData(),
+            ];
+
+            $pipeline->rawCommand('JSON.SET', $key, '$', json_encode($data, \JSON_THROW_ON_ERROR));
+        }
+
+        $pipeline->exec();
+    }
+
+    /**
+     * @param array<string, mixed> $options
+     *
+     * @return VectorDocument[]
+     */
+    public function query(Vector $vector, array $options = []): array
+    {
+        $limit = $options['limit'] ?? 5;
+        $maxScore = $options['maxScore'] ?? null;
+        $whereFilter = $options['where'] ?? '*';
+
+        $query = "({$whereFilter}) => [KNN {$limit} @embedding \$query_vector AS vector_score]";
+
+        try {
+            $results = $this->redis->rawCommand(
+                'FT.SEARCH',
+                $this->indexName,
+                $query,
+                'PARAMS', 2, 'query_vector', $this->toRedisVector($vector),
+                'RETURN', 4, '$.id', '$.metadata', '$.embedding', 'vector_score',
+                'SORTBY', 'vector_score', 'ASC',
+                'LIMIT', 0, $limit,
+                'DIALECT', 2
+            );
+        } catch (\RedisException $e) {
+            throw new RuntimeException(\sprintf('Failed to execute query: "%s".', $e->getMessage()), 0, $e);
+        }
+
+        if (!\is_array($results) || \count($results) < 2) {
+            return [];
+        }
+
+        $documents = [];
+        $numResults = $results[0];
+
+        // Parse results (skip first element which is the count)
+        for ($i = 1; $i <= $numResults; $i += 2) {
+            // $docKey = $results[$i];
+            $docData = $results[$i + 1];
+
+            // Convert flat array to associative array
+            $data = [];
+            for ($j = 0; $j < \count($docData); $j += 2) {
+                $fieldName = $docData[$j];
+                $fieldValue = $docData[$j + 1] ?? null;
+
+                if (\is_string($fieldValue) && json_validate($fieldValue)) {
+                    $fieldValue = json_decode($fieldValue, true);
+                }
+
+                $data[$fieldName] = $fieldValue;
+            }
+
+            if (!isset($data['$.id'], $data['vector_score'])) {
+                continue;
+            }
+
+            $score = (float) $data['vector_score'];
+
+            // Apply max score filter if specified
+            if (null !== $maxScore && $score > $maxScore) {
+                continue;
+            }
+
+            $documents[] = new VectorDocument(
+                id: Uuid::fromString($data['$.id']),
+                vector: new Vector($data['$.embedding'] ?? []),
+                metadata: new Metadata($data['$.metadata'] ?? []),
+                score: $score,
+            );
+        }
+
+        return $documents;
+    }
+
+    private function toRedisVector(VectorInterface $vector): string
+    {
+        $data = $vector->getData();
+        $bytes = '';
+        foreach ($data as $value) {
+            $bytes .= pack('f', $value);
+        }
+
+        return $bytes;
+    }
+}