feat: bring in Llama 3.3 support with Azure

.env

@@ -21,6 +21,10 @@ AZURE_OPENAI_DEPLOYMENT=
 AZURE_OPENAI_VERSION=
 AZURE_OPENAI_KEY=
 
+# For using Llama on Azure
+AZURE_LLAMA_BASEURL=
+AZURE_LLAMA_KEY=
+
 # For using OpenRouter
 OPENROUTER_KEY=
 

README.md

@@ -62,9 +62,8 @@ $embeddings = new Embeddings();
 * Language Models
   * [OpenAI's GPT](https://platform.openai.com/docs/models/overview) with [OpenAI](https://platform.openai.com/docs/overview) and [Azure](https://learn.microsoft.com/azure/ai-services/openai/concepts/models) as Platform
   * [Anthropic's Claude](https://www.anthropic.com/claude) with [Anthropic](https://www.anthropic.com/) as Platform
-  * [Meta's Llama](https://www.llama.com/) with [Ollama](https://ollama.com/) and [Replicate](https://replicate.com/) as Platform
-  * [Google's Gemini](https://gemini.google.com/) with [Google](https://ai.google.dev/) as Platform
-  * [Google's Gemini](https://gemini.google.com/) with [OpenRouter](https://www.openrouter.com/) as Platform
+  * [Meta's Llama](https://www.llama.com/) with [Azure](https://learn.microsoft.com/azure/machine-learning/how-to-deploy-models-llama), [Ollama](https://ollama.com/) and [Replicate](https://replicate.com/) as Platform
+  * [Google's Gemini](https://gemini.google.com/) with [Google](https://ai.google.dev/) and [OpenRouter](https://www.openrouter.com/) as Platform
   * [DeepSeek's R1](https://www.deepseek.com/) with [OpenRouter](https://www.openrouter.com/) as Platform
 * Embeddings Models
   * [OpenAI's Text Embeddings](https://platform.openai.com/docs/guides/embeddings/embedding-models) with [OpenAI](https://platform.openai.com/docs/overview) and [Azure](https://learn.microsoft.com/azure/ai-services/openai/concepts/models) as Platform

examples/chat-llama-azure.php

@@ -0,0 +1,31 @@
+<?php
+
+use PhpLlm\LlmChain\Bridge\Azure\Meta\PlatformFactory;
+use PhpLlm\LlmChain\Bridge\Meta\Llama;
+use PhpLlm\LlmChain\Chain;
+use PhpLlm\LlmChain\Model\Message\Message;
+use PhpLlm\LlmChain\Model\Message\MessageBag;
+use Symfony\Component\Dotenv\Dotenv;
+
+require_once dirname(__DIR__).'/vendor/autoload.php';
+(new Dotenv())->loadEnv(dirname(__DIR__).'/.env');
+
+if (empty($_ENV['AZURE_LLAMA_BASEURL']) || empty($_ENV['AZURE_LLAMA_KEY'])) {
+    echo 'Please set the AZURE_LLAMA_BASEURL and AZURE_LLAMA_KEY environment variable.'.PHP_EOL;
+    exit(1);
+}
+
+$platform = PlatformFactory::create($_ENV['AZURE_LLAMA_BASEURL'], $_ENV['AZURE_LLAMA_KEY']);
+$llm = new Llama(Llama::LLAMA_3_3_70B_INSTRUCT);
+
+$chain = new Chain($platform, $llm);
+$messages = new MessageBag(Message::ofUser('I am going to Paris, what should I see?'));
+$response = $chain->call($messages, [
+    'max_tokens' => 2048,
+    'temperature' => 0.8,
+    'top_p' => 0.1,
+    'presence_penalty' => 0,
+    'frequency_penalty' => 0,
+]);
+
+echo $response->getContent().PHP_EOL;

src/Bridge/Azure/Meta/LlamaHandler.php

@@ -0,0 +1,60 @@
+<?php
+
+declare(strict_types=1);
+
+namespace PhpLlm\LlmChain\Bridge\Azure\Meta;
+
+use PhpLlm\LlmChain\Bridge\Meta\Llama;
+use PhpLlm\LlmChain\Exception\RuntimeException;
+use PhpLlm\LlmChain\Model\Message\MessageBagInterface;
+use PhpLlm\LlmChain\Model\Model;
+use PhpLlm\LlmChain\Model\Response\ResponseInterface as LlmResponse;
+use PhpLlm\LlmChain\Model\Response\TextResponse;
+use PhpLlm\LlmChain\Platform\ModelClient;
+use PhpLlm\LlmChain\Platform\ResponseConverter;
+use Symfony\Contracts\HttpClient\HttpClientInterface;
+use Symfony\Contracts\HttpClient\ResponseInterface;
+use Webmozart\Assert\Assert;
+
+final readonly class LlamaHandler implements ModelClient, ResponseConverter
+{
+    public function __construct(
+        private HttpClientInterface $httpClient,
+        private string $baseUrl,
+        #[\SensitiveParameter] private string $apiKey,
+    ) {
+    }
+
+    public function supports(Model $model, object|array|string $input): bool
+    {
+        return $model instanceof Llama && $input instanceof MessageBagInterface;
+    }
+
+    public function request(Model $model, object|array|string $input, array $options = []): ResponseInterface
+    {
+        Assert::isInstanceOf($input, MessageBagInterface::class);
+        $url = sprintf('https://%s/chat/completions', $this->baseUrl);
+
+        return $this->httpClient->request('POST', $url, [
+            'headers' => [
+                'Content-Type' => 'application/json',
+                'Authorization' => $this->apiKey,
+            ],
+            'json' => array_merge($options, [
+                'model' => $model->getVersion(),
+                'messages' => $input,
+            ]),
+        ]);
+    }
+
+    public function convert(ResponseInterface $response, array $options = []): LlmResponse
+    {
+        $data = $response->toArray();
+
+        if (!isset($data['choices'][0]['message']['content'])) {
+            throw new RuntimeException('Response does not contain output');
+        }
+
+        return new TextResponse($data['choices'][0]['message']['content']);
+    }
+}

src/Bridge/Azure/Meta/PlatformFactory.php

@@ -0,0 +1,23 @@
+<?php
+
+declare(strict_types=1);
+
+namespace PhpLlm\LlmChain\Bridge\Azure\Meta;
+
+use PhpLlm\LlmChain\Platform;
+use Symfony\Component\HttpClient\HttpClient;
+use Symfony\Contracts\HttpClient\HttpClientInterface;
+
+final readonly class PlatformFactory
+{
+    public static function create(
+        string $baseUrl,
+        #[\SensitiveParameter]
+        string $apiKey,
+        ?HttpClientInterface $httpClient = null,
+    ): Platform {
+        $modelClient = new LlamaHandler($httpClient ?? HttpClient::create(), $baseUrl, $apiKey);
+
+        return new Platform([$modelClient], [$modelClient]);
+    }
+}

src/Bridge/Meta/Llama.php

@@ -8,6 +8,7 @@
 
 final readonly class Llama implements LanguageModel
 {
+    public const LLAMA_3_3_70B_INSTRUCT = 'llama-3.3-70B-Instruct';
     public const LLAMA_3_2_90B_VISION_INSTRUCT = 'llama-3.2-90b-vision-instruct';
     public const LLAMA_3_2_11B_VISION_INSTRUCT = 'llama-3.2-11b-vision-instruct';
     public const LLAMA_3_2_3B = 'llama-3.2-3b';