feat: add Gemini Embeddings

examples/google/embeddings.php

@@ -0,0 +1,36 @@
+<?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\Platform\Bridge\Google\Embeddings;
+use Symfony\AI\Platform\Bridge\Google\PlatformFactory;
+use Symfony\AI\Platform\Response\VectorResponse;
+use Symfony\Component\Dotenv\Dotenv;
+
+require_once dirname(__DIR__).'/vendor/autoload.php';
+(new Dotenv())->loadEnv(dirname(__DIR__).'/.env');
+
+if (empty($_ENV['GOOGLE_API_KEY'])) {
+    echo 'Please set the GOOGLE_API_KEY environment variable.'.\PHP_EOL;
+    exit(1);
+}
+
+$platform = PlatformFactory::create($_ENV['GOOGLE_API_KEY']);
+$embeddings = new Embeddings();
+
+$response = $platform->request($embeddings, <<<TEXT
+    Once upon a time, there was a country called Japan. It was a beautiful country with a lot of mountains and rivers.
+    The people of Japan were very kind and hardworking. They loved their country very much and took care of it. The
+    country was very peaceful and prosperous. The people lived happily ever after.
+    TEXT);
+
+assert($response instanceof VectorResponse);
+
+echo 'Dimensions: '.$response->getContent()[0]->getDimensions().\PHP_EOL;

examples/store/mariadb-similarity-search-gemini.php

@@ -0,0 +1,85 @@
+<?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 Doctrine\DBAL\DriverManager;
+use Doctrine\DBAL\Tools\DsnParser;
+use PhpLlm\LlmChain\Chain\Chain;
+use PhpLlm\LlmChain\Chain\Toolbox\ChainProcessor;
+use PhpLlm\LlmChain\Chain\Toolbox\Tool\SimilaritySearch;
+use PhpLlm\LlmChain\Chain\Toolbox\Toolbox;
+use PhpLlm\LlmChain\Platform\Bridge\Google\Embeddings;
+use PhpLlm\LlmChain\Platform\Bridge\Google\Embeddings\TaskType;
+use PhpLlm\LlmChain\Platform\Bridge\Google\Gemini;
+use PhpLlm\LlmChain\Platform\Bridge\Google\PlatformFactory;
+use PhpLlm\LlmChain\Platform\Message\Message;
+use PhpLlm\LlmChain\Platform\Message\MessageBag;
+use PhpLlm\LlmChain\Store\Bridge\MariaDB\Store;
+use PhpLlm\LlmChain\Store\Document\Metadata;
+use PhpLlm\LlmChain\Store\Document\TextDocument;
+use PhpLlm\LlmChain\Store\Indexer;
+use Symfony\Component\Dotenv\Dotenv;
+use Symfony\Component\Uid\Uuid;
+
+require_once dirname(__DIR__, 2).'/vendor/autoload.php';
+(new Dotenv())->loadEnv(dirname(__DIR__, 2).'/.env');
+
+if (empty($_ENV['GOOGLE_API_KEY']) || empty($_ENV['MARIADB_URI'])) {
+    echo 'Please set GOOGLE_API_KEY and MARIADB_URI environment variables.'.\PHP_EOL;
+    exit(1);
+}
+
+// initialize the store
+$store = Store::fromDbal(
+    connection: DriverManager::getConnection((new DsnParser())->parse($_ENV['MARIADB_URI'])),
+    tableName: 'my_table',
+    indexName: 'my_index',
+    vectorFieldName: 'embedding',
+);
+
+// our data
+$movies = [
+    ['title' => 'Inception', 'description' => 'A skilled thief is given a chance at redemption if he can successfully perform inception, the act of planting an idea in someone\'s subconscious.', 'director' => 'Christopher Nolan'],
+    ['title' => 'The Matrix', 'description' => 'A hacker discovers the world he lives in is a simulated reality and joins a rebellion to overthrow its controllers.', 'director' => 'The Wachowskis'],
+    ['title' => 'The Godfather', 'description' => 'The aging patriarch of an organized crime dynasty transfers control of his empire to his reluctant son.', 'director' => 'Francis Ford Coppola'],
+];
+
+// create embeddings and documents
+foreach ($movies as $i => $movie) {
+    $documents[] = new TextDocument(
+        id: Uuid::v4(),
+        content: 'Title: '.$movie['title'].\PHP_EOL.'Director: '.$movie['director'].\PHP_EOL.'Description: '.$movie['description'],
+        metadata: new Metadata($movie),
+    );
+}
+
+// initialize the table
+$store->initialize(['dimensions' => 768]);
+
+// create embeddings for documents
+$platform = PlatformFactory::create($_ENV['GOOGLE_API_KEY']);
+$embeddings = new Embeddings(options: ['dimensions' => 768, 'task_type' => TaskType::SemanticSimilarity]);
+$indexer = new Indexer($platform, $embeddings, $store);
+$indexer->index($documents);
+
+$model = new Gemini(Gemini::GEMINI_2_FLASH_LITE);
+
+$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$toolbox = Toolbox::create($similaritySearch);
+$processor = new ChainProcessor($toolbox);
+$chain = new Chain($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 = $chain->call($messages);
+
+echo $response->getContent().\PHP_EOL;

src/platform/doc/index.rst

@@ -78,6 +78,7 @@ usually defined by the specific models and their documentation.
     * `Amazon's Nova`_ with `AWS Bedrock`_ as Platform
     * `Mistral's Mistral`_ with `Mistral`_ as Platform
 * **Embeddings Models**
+    * `Google's Text Embeddings`_ with `Google`_
     * `OpenAI's Text Embeddings`_ with `OpenAI`_ and `Azure`_ as Platform
     * `Voyage's Embeddings`_ with `Voyage`_ as Platform
     * `Mistral Embed`_ with `Mistral`_ as Platform
@@ -274,6 +275,7 @@ which can be useful to speed up the processing::
 .. _`Amazon's Nova`: https://nova.amazon.com
 .. _`Mistral's Mistral`: https://www.mistral.ai/
 .. _`Mistral`: https://www.mistral.ai/
+.. _`Google's Text Embeddings`: https://ai.google.dev/gemini-api/docs/embeddings
 .. _`OpenAI's Text Embeddings`: https://platform.openai.com/docs/guides/embeddings/embedding-models
 .. _`Voyage's Embeddings`: https://docs.voyageai.com/docs/embeddings
 .. _`Voyage`: https://www.voyageai.com/

src/platform/src/Bridge/Google/Embeddings.php

@@ -0,0 +1,37 @@
+<?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\Platform\Bridge\Google;
+
+use Symfony\AI\Platform\Bridge\Google\Embeddings\TaskType;
+use Symfony\AI\Platform\Capability;
+use Symfony\AI\Platform\Model;
+
+/**
+ * @author Valtteri R <[email protected]>
+ */
+class Embeddings extends Model
+{
+    /** Supported dimensions: 3072, 1536, or 768 */
+    public const GEMINI_EMBEDDING_EXP_03_07 = 'gemini-embedding-exp-03-07';
+    /** Fixed 768 dimensions */
+    public const TEXT_EMBEDDING_004 = 'text-embedding-004';
+    /** Fixed 768 dimensions */
+    public const EMBEDDING_001 = 'embedding-001';
+
+    /**
+     * @param array{dimensions?: int, task_type?: TaskType|string} $options
+     */
+    public function __construct(string $name = self::GEMINI_EMBEDDING_EXP_03_07, array $options = [])
+    {
+        parent::__construct($name, [Capability::INPUT_MULTIPLE], $options);
+    }
+}

src/platform/src/Bridge/Google/Embeddings/ModelClient.php

@@ -0,0 +1,80 @@
+<?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\Platform\Bridge\Google\Embeddings;
+
+use Symfony\AI\Platform\Bridge\Google\Embeddings;
+use Symfony\AI\Platform\Exception\RuntimeException;
+use Symfony\AI\Platform\Model;
+use Symfony\AI\Platform\ModelClientInterface;
+use Symfony\AI\Platform\Response\VectorResponse;
+use Symfony\AI\Platform\ResponseConverterInterface;
+use Symfony\AI\Platform\Vector\Vector;
+use Symfony\Contracts\HttpClient\HttpClientInterface;
+use Symfony\Contracts\HttpClient\ResponseInterface;
+
+/**
+ * @author Valtteri R <[email protected]>
+ */
+final readonly class ModelClient implements ModelClientInterface, ResponseConverterInterface
+{
+    public function __construct(
+        private HttpClientInterface $httpClient,
+        #[\SensitiveParameter]
+        private string $apiKey,
+    ) {
+    }
+
+    public function supports(Model $model): bool
+    {
+        return $model instanceof Embeddings;
+    }
+
+    public function request(Model $model, array|string $payload, array $options = []): ResponseInterface
+    {
+        $url = \sprintf('https://generativelanguage.googleapis.com/v1beta/models/%s:%s', $model->getName(), 'batchEmbedContents');
+        $modelOptions = $model->getOptions();
+
+        return $this->httpClient->request('POST', $url, [
+            'headers' => [
+                'x-goog-api-key' => $this->apiKey,
+            ],
+            'json' => [
+                'requests' => array_map(
+                    static fn (string $text) => array_filter([
+                        'model' => 'models/'.$model->getName(),
+                        'content' => ['parts' => [['text' => $text]]],
+                        'outputDimensionality' => $modelOptions['dimensions'] ?? null,
+                        'taskType' => $modelOptions['task_type'] ?? null,
+                        'title' => $options['title'] ?? null,
+                    ]),
+                    \is_array($payload) ? $payload : [$payload],
+                ),
+            ],
+        ]);
+    }
+
+    public function convert(ResponseInterface $response, array $options = []): VectorResponse
+    {
+        $data = $response->toArray();
+
+        if (!isset($data['embeddings'])) {
+            throw new RuntimeException('Response does not contain data');
+        }
+
+        return new VectorResponse(
+            ...array_map(
+                static fn (array $item): Vector => new Vector($item['values']),
+                $data['embeddings'],
+            ),
+        );
+    }
+}

src/platform/src/Bridge/Google/Embeddings/TaskType.php

@@ -0,0 +1,34 @@
+<?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\Platform\Bridge\Google\Embeddings;
+
+enum TaskType: string
+{
+    /** Unset value, which will default to one of the other enum values. */
+    public const TaskTypeUnspecified = 'TASK_TYPE_UNSPECIFIED';
+    /** Specifies the given text is a query in a search/retrieval setting. */
+    public const RetrievalQuery = 'RETRIEVAL_QUERY';
+    /** Specifies the given text is a document from the corpus being searched. */
+    public const RetrievalDocument = 'RETRIEVAL_DOCUMENT';
+    /** Specifies the given text will be used for STS. */
+    public const SemanticSimilarity = 'SEMANTIC_SIMILARITY';
+    /** Specifies that the given text will be classified. */
+    public const Classification = 'CLASSIFICATION';
+    /** Specifies that the embeddings will be used for clustering. */
+    public const Clustering = 'CLUSTERING';
+    /** Specifies that the given text will be used for question answering. */
+    public const QuestionAnswering = 'QUESTION_ANSWERING';
+    /** Specifies that the given text will be used for fact verification. */
+    public const FactVerification = 'FACT_VERIFICATION';
+    /** Specifies that the given text will be used for code retrieval. */
+    public const CodeRetrievalQuery = 'CODE_RETRIEVAL_QUERY';
+}

src/platform/src/Bridge/Google/PlatformFactory.php

@@ -16,6 +16,7 @@
 use Symfony\AI\Platform\Bridge\Google\Contract\ToolCallMessageNormalizer;
 use Symfony\AI\Platform\Bridge\Google\Contract\ToolNormalizer;
 use Symfony\AI\Platform\Bridge\Google\Contract\UserMessageNormalizer;
+use Symfony\AI\Platform\Bridge\Google\Embeddings\ModelClient;
 use Symfony\AI\Platform\Contract;
 use Symfony\AI\Platform\Platform;
 use Symfony\Component\HttpClient\EventSourceHttpClient;
@@ -33,8 +34,9 @@ public static function create(
     ): Platform {
         $httpClient = $httpClient instanceof EventSourceHttpClient ? $httpClient : new EventSourceHttpClient($httpClient);
         $responseHandler = new ModelHandler($httpClient, $apiKey);
+        $embeddings = new ModelClient($httpClient, $apiKey);
 
-        return new Platform([$responseHandler], [$responseHandler], Contract::create(
+        return new Platform([$responseHandler, $embeddings], [$responseHandler, $embeddings], Contract::create(
             new AssistantMessageNormalizer(),
             new MessageBagNormalizer(),
             new ToolNormalizer(),

src/platform/src/ModelClientInterface.php

@@ -21,8 +21,8 @@ interface ModelClientInterface
     public function supports(Model $model): bool;
 
     /**
-     * @param array<string, mixed> $payload
-     * @param array<string, mixed> $options
+     * @param array<string|int, mixed> $payload
+     * @param array<string, mixed>     $options
      */
     public function request(Model $model, array|string $payload, array $options = []): ResponseInterface;
 }