​
Overview

In case you want to take control over the prompts sent by Instructor to LLM for different modes, you can use the prompt parameter in the request() or respond() methods.

It will override the default Instructor prompts, allowing you to fully customize how LLM is instructed to process the input.

​
Example

<?php

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

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



use Cognesy\Instructor\Enums\Mode;

use Cognesy\Instructor\Events\HttpClient\RequestSentToLLM;

use Cognesy\Instructor\Instructor;



class User {

    public int $age;

    public string $name;

}



$instructor = (new Instructor)

    ->onEvent(RequestSentToLLM::class, fn(RequestSentToLLM $event)=>dump($event->request->toMessages()));



print("\n# Request for Mode::Tools:\n\n");

$user = $instructor

    ->respond(

        messages: "Our user Jason is 25 years old.",

        responseModel: User::class,

        prompt: "\nYour task is to extract correct and accurate data from the messages using provided tools.\n",

        mode: Mode::Tools

    );

echo "\nRESPONSE:\n";

dump($user);



print("\n# Request for Mode::Json:\n\n");

$user = $instructor

    ->respond(

        messages: "Our user Jason is 25 years old.",

        responseModel: User::class,

        prompt: "\nYour task is to respond correctly with JSON object. Response must follow JSONSchema:\n<|json_schema|>\n",

        mode: Mode::Json

    );

echo "\nRESPONSE:\n";

dump($user);



print("\n# Request for Mode::MdJson:\n\n");

$user = $instructor

    ->respond(

        messages: "Our user Jason is 25 years old.",

        responseModel: User::class,

        prompt: "\nYour task is to respond correctly with strict JSON object containing extracted data within a ```json {} ``` codeblock. Object must validate against this JSONSchema:\n<|json_schema|>\n",

        mode: Mode::MdJson

    );

echo "\nRESPONSE:\n";

dump($user);



?>
Customize parameters of OpenAI clientUsing structured data as an input