Overview

You can connect to Azure OpenAI instance using a dedicated client provided by Instructor. Please note it requires setting up your own model deployment using Azure OpenAI service console.

Example

<?php

$loader = require 'vendor/autoload.php';

$loader->add('Cognesy\\Instructor\\', __DIR__ . '../../src/');



use Cognesy\Instructor\Enums\Mode;

use Cognesy\Instructor\Instructor;



enum UserType : string {

    case Guest = 'guest';

    case User = 'user';

    case Admin = 'admin';

}



class User {

    public int $age;

    public string $name;

    public string $username;

    public UserType $role;

    /** @var string[] */

    public array $hobbies;

}



// Get Instructor with specified LLM client connection

// See: /config/llm.php to check or change LLM client connection configuration details

$instructor = (new Instructor)->withConnection('azure');



// Call with your model name and preferred execution mode

$user = $instructor->respond(

    messages: "Jason (@jxnlco) is 25 years old and is the admin of this project. He likes playing football and reading books.",

    responseModel: User::class,

    examples: [[

        'input' => 'Ive got email Frank - their developer, who\'s 30. He asked to come back to him frank@hk.ch. Btw, he plays on drums!',

        'output' => ['age' => 30, 'name' => 'Frank', 'username' => 'frank@hk.ch', 'role' => 'developer', 'hobbies' => ['playing drums'],],

    ]],

    model: 'gpt-4o-mini', // set your own value/source

    mode: Mode::Json,

);



print("Completed response model:\n\n");

dump($user);



assert(isset($user->name));

assert(isset($user->role));

assert(isset($user->age));

assert(isset($user->hobbies));

assert(isset($user->username));

assert(is_array($user->hobbies));

assert(count($user->hobbies) > 0);

assert($user->role === UserType::Admin);

assert($user->age === 25);

assert($user->name === 'Jason');

assert(in_array($user->username, ['jxnlco', '@jxnlco']));

?>