Adding an AI Chatbot to Your Laravel App with the OpenAI API

A Laravel developer demonstrates how to integrate an AI chatbot into a Laravel application using the OpenAI API and the openai-php/laravel package. The tutorial covers setting up the package, creating a ChatService to handle LLM logic, storing conversation history in the session, and implementing rate limiting. The approach avoids external microservices and relies solely on Laravel and an HTTP API.

Every product I've worked on in the last two years has eventually gotten the same request: "Can we add an AI assistant to this?" As a Laravel developer, the good news is that shipping a production-ready chatbot takes an afternoon — no Python microservice, no LangChain, just Laravel and an HTTP API. In this tutorial we'll build a chatbot that: The community-maintained openai-php/laravel https://github.com/openai-php/laravel package is the de-facto standard: composer require openai-php/laravel php artisan openai:install Add your key to .env : OPENAI API KEY=sk-your-key-here 💡 Never commit the key. Use your host's secret manager in production. Keep the LLM logic out of your controller. Create app/Services/ChatService.php : php <?php namespace App\Services; use OpenAI\Laravel\Facades\OpenAI; class ChatService { private const SYSTEM PROMPT = <<<'PROMPT' You are the helpful assistant for Acme Inc's customer portal. Answer only questions about the product. Be concise. If you don't know the answer, say so and suggest contacting support. PROMPT; / @param array<int, array{role: string, content: string} $history / public function reply array $history, string $userMessage : string { $messages = 'role' = 'system', 'content' = self::SYSTEM PROMPT , ...$history, 'role' = 'user', 'content' = $userMessage , ; $response = OpenAI::chat - create 'model' = 'gpt-4o-mini', 'messages' = $messages, 'max tokens' = 500, ; return $response- choices 0 - message- content; } } Session-based history keeps things simple — no migrations needed for v1: php <?php namespace App\Http\Controllers; use App\Services\ChatService; use Illuminate\Http\JsonResponse; use Illuminate\Http\Request; class ChatController extends Controller { public function invoke Request $request, ChatService $chat : JsonResponse { $validated = $request- validate 'message' = 'required', 'string', 'max:2000' , ; $history = $request- session - get 'chat history', ; $answer = $chat- reply $history, $validated 'message' ; // keep the last 10 exchanges to control token costs $history = 'role' = 'user', 'content' = $validated 'message' ; $history = 'role' = 'assistant', 'content' = $answer ; $request- session - put 'chat history', array slice $history, -20 ; return response - json 'answer' = $answer ; } } Route it — with rate limiting , because every request costs you money: php // routes/web.php use App\Http\Controllers\ChatController; Route::post '/chat', ChatController::class - middleware 'auth', 'throttle:20,1' ; // 20 req/min per user Drop this into any Blade view — no framework required: <div id="chat" <div id="messages" </div <form id="chat-form" <input id="chat-input" type="text" placeholder="Ask me anything…" required / <button type="submit" Send</button </form </div <script document.getElementById 'chat-form' .addEventListener 'submit', async e = { e.preventDefault ; const input = document.getElementById 'chat-input' ; const messages = document.getElementById 'messages' ; messages.insertAdjacentHTML 'beforeend', <p <b You:</b ${input.value}</p ; const res = await fetch '/chat', { method: 'POST', headers: { 'Content-Type': 'application/json', 'X-CSRF-TOKEN': document.querySelector 'meta name="csrf-token" ' .content, }, body: JSON.stringify { message: input.value } , } ; const { answer } = await res.json ; messages.insertAdjacentHTML 'beforeend', <p <b Bot:</b ${answer}</p ; input.value = ''; } ; </script Before you ship this to real users: chat logs table pays for itself the first time you debug a weird answer. max tokens OpenAI::chat - createStreamed + Server-Sent Events makes the bot feel 10x faster. I'm Aditya Kumar adityakdevin — Tech Lead & full-stack developer building AI-powered web products with Laravel, Vue, and LLM APIs. Find me at adityadev.in.