WIP: AWS Bedrock Support, Google Gemini Function calling, and file support, and more.

.env

@@ -56,3 +56,10 @@ RUN_EXPENSIVE_EXAMPLES=false
 
 # For using Gemini
 GOOGLE_API_KEY=
+
+# For using Aws BedRock
+
+AWS_ACCESS_KEY=
+AWS_ACCESS_SECRET=
+AWS_REGION=
+AWS_INFERENCE_PROFILE_REGION=

composer.json

@@ -56,15 +56,17 @@
         "symfony/event-dispatcher": "^6.4 || ^7.1",
         "symfony/finder": "^6.4 || ^7.1",
         "symfony/process": "^6.4 || ^7.1",
-        "symfony/var-dumper": "^6.4 || ^7.1"
+        "symfony/var-dumper": "^6.4 || ^7.1",
+        "aws/aws-sdk-php": "^3"
     },
     "suggest": {
         "codewithkyrian/chromadb-php": "For using the ChromaDB as retrieval vector store.",
         "codewithkyrian/transformers": "For using the TransformersPHP with FFI to run models in PHP.",
         "mongodb/mongodb": "For using MongoDB Atlas as retrieval vector store.",
         "probots-io/pinecone-php": "For using the Pinecone as retrieval vector store.",
         "symfony/css-selector": "For using the YouTube transcription tool.",
-        "symfony/dom-crawler": "For using the YouTube transcription tool."
+        "symfony/dom-crawler": "For using the YouTube transcription tool.",
+        "aws/aws-sdk-php": "For using AWS Bedrock"
     },
     "config": {
         "allow-plugins": {

examples/awsbedrock/embeddings.php

@@ -0,0 +1,34 @@
+<?php
+
+use PhpLlm\LlmChain\Bridge\AwsBedrock\Embeddings;
+use PhpLlm\LlmChain\Bridge\AwsBedrock\PlatformFactory;
+use PhpLlm\LlmChain\Document\Vector;
+use Symfony\Component\Dotenv\Dotenv;
+
+require_once dirname(__DIR__, 2).'/vendor/autoload.php';
+(new Dotenv())->loadEnv(dirname(__DIR__, 2).'/.env');
+
+if (empty($_ENV['AWS_ACCESS_KEY']) || empty($_ENV['AWS_ACCESS_SECRET']) || empty($_ENV['AWS_REGION'])) {
+    echo 'Please set the AWS_ACCESS_KEY, AWS_ACCESS_SECRET, AWS_REGION environment variables.'.PHP_EOL;
+    exit(1);
+}
+
+$platform = PlatformFactory::create(
+    [
+        'key' => $_ENV['AWS_ACCESS_KEY'],
+        'secret' => $_ENV['AWS_ACCESS_SECRET'],
+    ],
+    $_ENV['AWS_REGION'],
+);
+
+$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($response->getContent()[0] instanceof Vector);
+
+echo 'Dimensions: '.$response->getContent()[0]->getDimensions().PHP_EOL;

examples/google/toolcall.php

@@ -0,0 +1,33 @@
+<?php
+
+use PhpLlm\LlmChain\Bridge\Google\Gemini;
+use PhpLlm\LlmChain\Bridge\Google\PlatformFactory;
+use PhpLlm\LlmChain\Chain;
+use PhpLlm\LlmChain\Chain\Toolbox\ChainProcessor;
+use PhpLlm\LlmChain\Chain\Toolbox\Tool\YouTubeTranscriber;
+use PhpLlm\LlmChain\Chain\Toolbox\Toolbox;
+use PhpLlm\LlmChain\Model\Message\Message;
+use PhpLlm\LlmChain\Model\Message\MessageBag;
+use Symfony\Component\Dotenv\Dotenv;
+use Symfony\Component\HttpClient\HttpClient;
+
+require_once dirname(__DIR__, 2).'/vendor/autoload.php';
+(new Dotenv())->loadEnv(dirname(__DIR__, 2).'/.env');
+
+if (empty($_ENV['GOOGLE_API_KEY'])) {
+    echo 'Please set the GOOGLE_API_KEY environment variable.'.PHP_EOL;
+    exit(1);
+}
+
+$platform = PlatformFactory::create($_ENV['GOOGLE_API_KEY']);
+$llm = new Gemini(Gemini::GEMINI_2_FLASH);
+
+$transcriber = new YouTubeTranscriber(HttpClient::create());
+$toolbox = Toolbox::create($transcriber);
+$processor = new ChainProcessor($toolbox);
+$chain = new Chain($platform, $llm, [$processor], [$processor]);
+
+$messages = new MessageBag(Message::ofUser('Please summarize this video for me https://www.youtube.com/watch?v=6uXW-ulpj0s with the video ID as 6uXW-ulpj0s'));
+$response = $chain->call($messages);
+
+echo $response->getContent().PHP_EOL;

src/Bridge/AwsBedrock/AmazonNova.php

@@ -0,0 +1,64 @@
+<?php
+
+declare(strict_types=1);
+
+namespace PhpLlm\LlmChain\Bridge\AwsBedrock;
+
+final readonly class AmazonNova implements BedrockLanguageModel
+{
+    public const NOVA_MICRO_V1 = 'amazon.nova-micro-v1:0';
+
+    public const NOVA_LITE_V1 = 'amazon.nova-lite-v1:0';
+
+    public const NOVA_PRO_V1 = 'amazon.nova-pro-v1:0';
+
+    /**
+     * @param array<string, mixed> $options
+     * @param string|null          $inferenceProfileRegion if you need to use an inference profile just add the region here
+     */
+    public function __construct(
+        private string $name = self::NOVA_LITE_V1,
+        private array $options = [],
+        private ?string $inferenceProfileRegion = null,
+    ) {
+    }
+
+    public function getName(): string
+    {
+        if ($this->inferenceProfileRegion) {
+            return $this->inferenceProfileRegion.'.'.$this->name;
+        }
+
+        return $this->name;
+    }
+
+    public function getOptions(): array
+    {
+        return $this->options;
+    }
+
+    public function supportsAudioInput(): bool
+    {
+        return false; // Only videos (!?)
+    }
+
+    public function supportsImageInput(): bool
+    {
+        return true;
+    }
+
+    public function supportsStreaming(): bool
+    {
+        return false; // It does, but it's not implemented yet.
+    }
+
+    public function supportsToolCalling(): bool
+    {
+        return true;
+    }
+
+    public function supportsStructuredOutput(): bool
+    {
+        return false;
+    }
+}

src/Bridge/AwsBedrock/BedrockLanguageModel.php

@@ -0,0 +1,9 @@
+<?php
+
+namespace PhpLlm\LlmChain\Bridge\AwsBedrock;
+
+use PhpLlm\LlmChain\Model\LanguageModel;
+
+interface BedrockLanguageModel extends LanguageModel
+{
+}

src/Bridge/AwsBedrock/BedrockRequestSigner.php

@@ -0,0 +1,48 @@
+<?php
+
+namespace PhpLlm\LlmChain\Bridge\AwsBedrock;
+
+use Aws\Credentials\Credentials;
+use Aws\Signature\SignatureV4;
+use GuzzleHttp\Psr7\Request;
+use GuzzleHttp\Psr7\Uri;
+
+final class BedrockRequestSigner
+{
+    public function __construct(#[\SensitiveParameter] private Credentials $credentials, private string $region)
+    {
+    }
+
+    public function signRequest(string $method, string $endpoint, array $jsonBody, array $extraHeaders = [])
+    {
+        $signature = new SignatureV4('bedrock', $this->region);
+
+        $uri = new Uri($endpoint);
+
+        $finalHeaders = array_merge([
+            'Host' => $uri->getHost(),
+            'Content-Type' => 'application/json',
+        ], $extraHeaders);
+
+        $request = new Request(
+            $method,
+            $uri,
+            $finalHeaders,
+            $encodedBody = json_encode($jsonBody)
+        );
+
+        $signedRequest = $signature->signRequest($request, $this->credentials);
+
+        $signedHeaders = [];
+        foreach ($signedRequest->getHeaders() as $name => $values) {
+            $signedHeaders[$name] = $signedRequest->getHeaderLine($name);
+        }
+
+        unset($request, $finalHeaders, $uri, $signature);
+
+        return [
+            'headers' => $signedHeaders,
+            'body' => $encodedBody,
+        ];
+    }
+}

src/Bridge/AwsBedrock/Embeddings.php

@@ -0,0 +1,37 @@
+<?php
+
+namespace PhpLlm\LlmChain\Bridge\AwsBedrock;
+
+use PhpLlm\LlmChain\Model\EmbeddingsModel;
+
+final readonly class Embeddings implements EmbeddingsModel
+{
+    public const TITAN_EMBED_TEXT_V2 = 'amazon.titan-embed-text-v2:0';
+    public const TITAN_MULTIMODAL_G1 = 'amazon.titan-embed-image-v1';
+
+    public function __construct(
+        private string $name = self::TITAN_EMBED_TEXT_V2,
+        private array $options = [],
+        private ?string $inferenceProfileRegion = null,
+    ) {
+    }
+
+    public function supportsMultipleInputs(): bool
+    {
+        return false;
+    }
+
+    public function getName(): string
+    {
+        if ($this->inferenceProfileRegion) {
+            return $this->inferenceProfileRegion.'.'.$this->name;
+        }
+
+        return $this->name;
+    }
+
+    public function getOptions(): array
+    {
+        return $this->options;
+    }
+}

src/Bridge/AwsBedrock/Embeddings/ModelClient.php

@@ -0,0 +1,51 @@
+<?php
+
+declare(strict_types=1);
+
+namespace PhpLlm\LlmChain\Bridge\AwsBedrock\Embeddings;
+
+use PhpLlm\LlmChain\Bridge\AwsBedrock\BedrockRequestSigner;
+use PhpLlm\LlmChain\Bridge\AwsBedrock\Embeddings;
+use PhpLlm\LlmChain\Model\Model;
+use PhpLlm\LlmChain\Platform\ModelClient as PlatformResponseFactory;
+use Symfony\Contracts\HttpClient\HttpClientInterface;
+use Symfony\Contracts\HttpClient\ResponseInterface;
+use Webmozart\Assert\Assert;
+
+final readonly class ModelClient implements PlatformResponseFactory
+{
+    public function __construct(
+        private HttpClientInterface $httpClient,
+        #[\SensitiveParameter] private BedrockRequestSigner $requestSigner,
+        private string $region,
+    ) {
+        Assert::stringNotEmpty($region, 'The region must not be empty.');
+    }
+
+    public function supports(Model $model, array|string|object $input): bool
+    {
+        return $model instanceof Embeddings;
+    }
+
+    public function request(Model $model, object|array|string $input, array $options = []): ResponseInterface
+    {
+        $signedParameters = $this->requestSigner->signRequest(
+            method: 'POST',
+            endpoint: $bedrockEndpoint = sprintf(
+                'https://bedrock-runtime.%s.amazonaws.com/model/%s/invoke',
+                $this->region,
+                $model->getName(),
+            ),
+            jsonBody: is_string($input) ? array_merge(
+                $model->getOptions(), [
+                    'inputText' => $input,
+                ]
+            ) : (
+                is_array($input) ?
+                    array_merge($model->getOptions(), $options, $input) : $input
+            )
+        );
+
+        return $this->httpClient->request('POST', $bedrockEndpoint, $signedParameters);
+    }
+}

src/Bridge/AwsBedrock/Embeddings/ResponseConverter.php

@@ -0,0 +1,34 @@
+<?php
+
+declare(strict_types=1);
+
+namespace PhpLlm\LlmChain\Bridge\AwsBedrock\Embeddings;
+
+use PhpLlm\LlmChain\Bridge\AwsBedrock\Embeddings;
+use PhpLlm\LlmChain\Document\Vector;
+use PhpLlm\LlmChain\Exception\RuntimeException;
+use PhpLlm\LlmChain\Model\Model;
+use PhpLlm\LlmChain\Model\Response\VectorResponse;
+use PhpLlm\LlmChain\Platform\ResponseConverter as PlatformResponseConverter;
+use Symfony\Contracts\HttpClient\ResponseInterface;
+
+final class ResponseConverter implements PlatformResponseConverter
+{
+    public function supports(Model $model, array|string|object $input): bool
+    {
+        return $model instanceof Embeddings;
+    }
+
+    public function convert(ResponseInterface $response, array $options = []): VectorResponse
+    {
+        $data = $response->toArray();
+
+        if (!isset($data['embedding'])) {
+            throw new RuntimeException('Response does not contain data');
+        }
+
+        return new VectorResponse(
+            new Vector($data['embedding'])
+        );
+    }
+}