PHP code example of ferry-ai / php-inference

    
        
<?php
require_once('vendor/autoload.php');

/* Start to develop here. Best regards https://php-download.com/ */

    

ferry-ai / php-inference example snippets

use FerryAI\AI;

AI::config([
    'backend' => 'onnx',
    'backends' => ['embedding' => ['model_path' => '/models/all-MiniLM-L6-v2-onnx']],
]);

// embed → 384d vector, then store and search
$vec = AI::embed('Hello world');
$store = AI::vector('docs');
$store->add('doc1', $vec->vector, ['title' => 'Getting Started']);
$hits = $store->search(AI::embed('semantic query')->vector, k: 5);

// similarity between any two texts
echo AI::similarity('cat', 'kitten');   // 0.79

// compose a processing pipeline
$results = AI::pipeline()
    ->pipe(new TransformStage(strtoupper(...)))
    ->pipe(new FilterStage(fn($x) => strlen($x) > 3))
    ->run(['hi', 'hello', 'hey']);

AI::config(['backend' => 'llama', 'backends' => ['llama' => ['model_path' => '/models/qwen.gguf']]]);

echo AI::chat('Explain PHP FFI in one sentence.');        // full reply
foreach (AI::stream('Write a haiku about ferries.') as $token) { echo $token; }

// structured output via JSON Schema → GBNF grammar
$json = AI::chat('List 3 famous bridges with year and city.', [
    'grammar' => [
        'type' => 'object',
        'properties' => ['bridges' => [
            'type' => 'array',
            'items' => ['type' => 'object', 'properties' => [
                'name' => ['type' => 'string'],
                'year' => ['type' => 'integer'],
                'city' => ['type' => 'string'],
            ]],
        ]],
    ],
]);

// HTTP streaming response (PSR-7 SSE/NDJSON) for web apps
return AI::streamResponse([['role' => 'user', 'content' => $prompt]]);

AI::config([
    'backend'  => 'llama',
    'device'   => 'cuda',   // or 'cpu'
    'backends' => ['llama' => ['model_path' => '/models/model.gguf', 'n_gpu_layers' => 35]],
]);

echo AI::chat('Summarize FFI in PHP.');

AI::config(['vector' => [
    'driver' => 'pgsql',                                     // or omit for SQLite
    'dsn' => 'pgsql:host=127.0.0.1;port=5432',
    'user' => 'postgres', 'password' => 'postgres',
]]);

$store = AI::vector('docs');
$store->add('doc1', $vec->vector, ['lang' => 'en']);
$hits = $store->search($query, k: 5, filter: ['lang' => ['eq' => 'en']]);

AI::config(['observability' => ['metrics' => true, 'profiling' => true, 'logging' => true]]);

AI::embed('hello');                 // automatically timed, counted and logged
print_r(FerryAI\Metrics::report()); // counters + timing histograms per operation
print_r(FerryAI\Profiler::report());// per-operation count / avg / min / max ms

bash
composer 

bash
set FERRY_AI_MODEL_DIR=C:\models\all-MiniLM-L6-v2-onnx
php examples/01-hello-embedding.php