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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