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Overview

For single-label classification, we first define an enum for possible labels and a PHP class for the output.

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Example

Let’s start by defining the data structures.

<?php

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

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



use Cognesy\Instructor\Instructor;



// Enumeration for single-label text classification.

enum Label : string {

    case SPAM = "spam";

    case NOT_SPAM = "not_spam";

}



// Class for a single class label prediction.

class SinglePrediction {

    public Label $classLabel;

}

?>

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Classifying Text

The function classify will perform the single-label classification.

<?php

// Perform single-label classification on the input text.

function classify(string $data) : SinglePrediction {

    return (new Instructor())->respond(

        messages: [[

            "role" => "user",

            "content" => "Classify the following text: $data",

        ]],

        responseModel: SinglePrediction::class,

    );

}

?>

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Testing and Evaluation

Let’s run an example to see if it correctly identifies a spam message.

<?php

// Test single-label classification

$prediction = classify("Hello there I'm a Nigerian prince and I want to give you money");



dump($prediction);



assert($prediction->classLabel == Label::SPAM);

?>
Chain of ThoughtMulticlass classification