Optimasi Performa AI Agent

Terakhir diperbarui: 28 Jul 2026

Response Caching

<?php

namespace App;

class ResponseCache
{
    private string $cacheDir;
    private int $ttl;

    public function __construct(string $cacheDir = './cache', int $ttlSeconds = 3600)
    {
        $this->cacheDir = $cacheDir;
        $this->ttl      = $ttlSeconds;
        if (!is_dir($cacheDir)) {
            mkdir($cacheDir, 0755, true);
        }
    }

    private function getCacheKey(string $task, array $tools): string
    {
        return md5($task . json_encode($tools));
    }

    public function get(string $task, array $tools = []): ?string
    {
        $key  = $this->getCacheKey($task, $tools);
        $file = $this->cacheDir . DIRECTORY_SEPARATOR . $key . '.cache';

        if (!file_exists($file)) {
            return null;
        }

        $data = unserialize(file_get_contents($file));
        if (!$data || $data['expires_at'] < time()) {
            unlink($file);
            return null;
        }

        return $data['value'];
    }

    public function set(string $task, string $value, array $tools = []): void
    {
        $key  = $this->getCacheKey($task, $tools);
        $file = $this->cacheDir . DIRECTORY_SEPARATOR . $key . '.cache';
        file_put_contents($file, serialize([
            'value'      => $value,
            'expires_at' => time() + $this->ttl,
        ]));
    }
}

// Penggunaan di Agent:
$cache  = new ResponseCache(ttlSeconds: 1800);
$cached = $cache->get($task);
if ($cached) {
    return $cached . ' [dari cache]';
}
$result = $agent->run($task);
$cache->set($task, $result);
return $result;

Streaming Response (Server-Sent Events)

<?php
// stream.php
header('Content-Type: text/event-stream');
header('Cache-Control: no-cache');
header('X-Accel-Buffering: no'); // Penting untuk Nginx

// Payload dengan stream: true
$payload = json_encode([
    'model'    => 'gpt-4o-mini',
    'messages' => $messages,
    'stream'   => true,
]);

$ch = curl_init('https://api.openai.com/v1/chat/completions');
curl_setopt_array($ch, [
    CURLOPT_RETURNTRANSFER => false,
    CURLOPT_POST           => true,
    CURLOPT_POSTFIELDS     => $payload,
    CURLOPT_HTTPHEADER     => [
        'Authorization: Bearer ' . $apiKey,
        'Content-Type: application/json',
    ],
    CURLOPT_WRITEFUNCTION  => function($ch, $chunk) {
        // Setiap chunk adalah baris "data: {...}"
        $lines = explode("\n", $chunk);
        foreach ($lines as $line) {
            if (str_starts_with($line, 'data: ') && $line !== 'data: [DONE]') {
                $data  = json_decode(substr($line, 6), true);
                $delta = $data['choices'][0]['delta']['content'] ?? '';
                if ($delta) {
                    echo "data: " . json_encode(['text' => $delta]) . "\n\n";
                    ob_flush();
                    flush();
                }
            }
        }
        return strlen($chunk);
    },
]);

curl_exec($ch);
curl_close($ch);
echo "data: [DONE]\n\n";

Async Queue dengan Redis

sudo apt install redis-server -y
composer require predis/predis

// Kirim task ke queue (non-blocking)
$redis = new Predis\Client();
$jobId = uniqid('job-', true);
$redis->rpush('agent:queue', json_encode([
    'id'         => $jobId,
    'task'       => $task,
    'user_id'    => $userId,
    'created_at' => date('Y-m-d H:i:s'),
]));

// Worker (jalankan via Supervisor)
while (true) {
    $job = $redis->blpop('agent:queue', 5); // Block 5 detik
    if (!$job) { continue; }

    $data   = json_decode($job[1], true);
    $result = $agent->run($data['task']);

    // Simpan hasil ke Redis dengan TTL 1 jam
    $redis->setex("agent:result:{$data['id']}", 3600, $result);
}