​
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 create() methods.

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

​
Example

<?php
require 'examples/boot.php';

use Cognesy\Http\Events\HttpRequestSent;
use Cognesy\Instructor\StructuredOutput;
use Cognesy\Polyglot\Inference\Enums\OutputMode;

class User {
    public int $age;
    public string $name;
}

$structuredOutput = (new StructuredOutput)
    // let's dump the request data to see how customized prompts look like in requests
    ->onEvent(HttpRequestSent::class, fn(HttpRequestSent $event) => dump($event));

print("\n# Request for OutputMode::Tools:\n\n");
$user = $structuredOutput
    ->with(
        messages: "Our user Jason is 25 years old.",
        responseModel: User::class,
        prompt: "\nYour task is to extract correct and accurate data from the messages using provided tools.\n",
        mode: OutputMode::Tools
    )->get();
echo "\nRESPONSE:\n";
dump($user);

print("\n# Request for OutputMode::Json:\n\n");
$user = $structuredOutput
    ->with(
        messages: "Our user Jason is 25 years old.",
        responseModel: User::class,
        prompt: "\nYour task is to respond correctly with JSON object. Response must follow JSONSchema:\n<|json_schema|>\n",
        mode: OutputMode::Json
    )->get();
echo "\nRESPONSE:\n";
dump($user);

print("\n# Request for OutputMode::MdJson:\n\n");
$user = $structuredOutput
    ->with(
        messages: "Our user Jason is 25 years old.",
        responseModel: User::class,
        prompt: "\nYour task is to respond correctly with strict JSON object containing extracted data within a ```json {} ``` codeblock. Object must validate against this JSONSchema:\n<|json_schema|>\n",
        mode: OutputMode::MdJson
    )->get();
echo "\nRESPONSE:\n";
dump($user);

?>

​
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 create() methods.

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

​
Example

<?php
require 'examples/boot.php';

use Cognesy\Http\Events\HttpRequestSent;
use Cognesy\Instructor\StructuredOutput;
use Cognesy\Polyglot\Inference\Enums\OutputMode;

class User {
    public int $age;
    public string $name;
}

$structuredOutput = (new StructuredOutput)
    // let's dump the request data to see how customized prompts look like in requests
    ->onEvent(HttpRequestSent::class, fn(HttpRequestSent $event) => dump($event));

print("\n# Request for OutputMode::Tools:\n\n");
$user = $structuredOutput
    ->with(
        messages: "Our user Jason is 25 years old.",
        responseModel: User::class,
        prompt: "\nYour task is to extract correct and accurate data from the messages using provided tools.\n",
        mode: OutputMode::Tools
    )->get();
echo "\nRESPONSE:\n";
dump($user);

print("\n# Request for OutputMode::Json:\n\n");
$user = $structuredOutput
    ->with(
        messages: "Our user Jason is 25 years old.",
        responseModel: User::class,
        prompt: "\nYour task is to respond correctly with JSON object. Response must follow JSONSchema:\n<|json_schema|>\n",
        mode: OutputMode::Json
    )->get();
echo "\nRESPONSE:\n";
dump($user);

print("\n# Request for OutputMode::MdJson:\n\n");
$user = $structuredOutput
    ->with(
        messages: "Our user Jason is 25 years old.",
        responseModel: User::class,
        prompt: "\nYour task is to respond correctly with strict JSON object containing extracted data within a ```json {} ``` codeblock. Object must validate against this JSONSchema:\n<|json_schema|>\n",
        mode: OutputMode::MdJson
    )->get();
echo "\nRESPONSE:\n";
dump($user);

?>