How to Integrate GPT-4 into Your Laravel SaaS Application

Integrating GPT-4 into your Laravel SaaS application can greatly enhance its capabilities by offering features like smart chatbots, content generation, summarization, and more. In this beginner-friendly guide, we’ll walk through the entire process of integrating OpenAI's GPT-4 into a Laravel 10+ application using the official PHP SDK.

🚪 Prerequisites

Make sure you have the following before starting:

Laravel 10 or higher
PHP 8.2+
Composer installed
An OpenAI API key (get it here)

⚙️ Step 1: Install the OpenAI Laravel Package

Open your terminal in the Laravel project directory and run:

composer require openai-php/laravel

Next, publish the config file:

php artisan openai:install

This will add a new config file: config/openai.php and update your .env file.

🔐 Step 2: Add Your OpenAI API Key

Open your .env file and add:

OPENAI_API_KEY=your-api-key-here
OPENAI_ORGANIZATION=your-org-id # Optional

Make sure config/openai.php references these values.

🧠 Step 3: Create a Service to Interact with OpenAI

Run the command to make a new service class:

php artisan make:service OpenAIService

In app/Services/OpenAIService.php, add the following:

<?php

namespace App\Services;

use OpenAI\Laravel\Facades\OpenAI;

class OpenAIService
{
    public function generateChatResponse(string $prompt): string
    {
        $response = OpenAI::chat()->create([
            'model' => 'gpt-4',
            'messages' => [
                ['role' => 'user', 'content' => $prompt],
            ],
        ]);

        return $response->choices[0]->message->content;
    }
}

📝 Step 4: Create a Controller to Handle Requests

Run:

php artisan make:controller OpenAIController

Then edit app/Http/Controllers/OpenAIController.php:

<?php

namespace App\Http\Controllers;

use Illuminate\Http\Request;
use App\Services\OpenAIService;

class OpenAIController extends Controller
{
    protected $openAIService;

    public function __construct(OpenAIService $openAIService)
    {
        $this->openAIService = $openAIService;
    }

    public function generateResponse(Request $request)
    {
        $request->validate([
            'prompt' => 'required|string',
        ]);

        try {
            $response = $this->openAIService->generateChatResponse($request->input('prompt'));
            return response()->json(['response' => $response]);
        } catch (\Exception $e) {
            return response()->json(['error' => 'Something went wrong.'], 500);
        }
    }
}

🚧 Step 5: Add Routes

Open routes/web.php or routes/api.php and add:

use App\Http\Controllers\OpenAIController;

Route::post('/generate-response', [OpenAIController::class, 'generateResponse']);
Route::get('/gpt', function () {
    return view('gpt');
});

🎨 Step 6: Build the Frontend

Create a Blade view: resources/views/gpt.blade.php:

<!DOCTYPE html>
<html>
<head>
    <title>GPT-4 Integration</title>
</head>
<body>
    <h1>Ask GPT-4</h1>
    <form id="gpt-form">
        @csrf
        <textarea name="prompt" id="prompt" rows="4" cols="50" placeholder="Enter your prompt here..."></textarea><br>
        <button type="submit">Submit</button>
    </form>
    <div id="response"></div>

    <script>
        document.getElementById('gpt-form').addEventListener('submit', function(e) {
            e.preventDefault();
            fetch('/generate-response', {
                method: 'POST',
                headers: {
                    'Content-Type': 'application/json',
                    'X-CSRF-TOKEN': '{{ csrf_token() }}'
                },
                body: JSON.stringify({
                    prompt: document.getElementById('prompt').value
                })
            })
            .then(response => response.json())
            .then(data => {
                document.getElementById('response').innerText = data.response || data.error;
            });
        });
    </script>
</body>
</html>

🚀 Step 7: Test Everything

Run your server:

php artisan serve

Visit http://localhost:8000/gpt, enter a prompt, and see the response from GPT-4!

🛡️ Step 8: Add Rate Limiting & Error Handling

To protect your app:

Rate Limiting

Use Laravel’s built-in throttle middleware:

Route::middleware('throttle:60,1')->post('/generate-response', [OpenAIController::class, 'generateResponse']);

Error Handling

Already handled in the controller using try-catch. You can log errors for further inspection if needed.

📊 Step 9: Write a Test

Generate a test file:

php artisan make:test OpenAIIntegrationTest

In tests/Feature/OpenAIIntegrationTest.php:

<?php

namespace Tests\Feature;

use Tests\TestCase;

class OpenAIIntegrationTest extends TestCase
{
    /** @test */
    public function it_returns_a_response_from_gpt()
    {
        $response = $this->postJson('/generate-response', [
            'prompt' => 'Hello, GPT-4!'
        ]);

        $response->assertStatus(200)
                 ->assertJsonStructure(['response']);
    }
}

Run your test:

php artisan test

🔄 Bonus: Use LaravelGPT for Advanced Use Cases

Consider using LaravelGPT if you need:

Function calling
Custom workflows
Multi-turn conversations

✅ Conclusion

You’ve now successfully integrated GPT-4 into your Laravel SaaS application! With GPT-4, your app can offer intelligent, conversational capabilities and enhance user experience like never before.

Keep experimenting, monitor your usage, and build amazing things!

🚪 Prerequisites

⚙️ Step 1: Install the OpenAI Laravel Package

🔐 Step 2: Add Your OpenAI API Key

🧠 Step 3: Create a Service to Interact with OpenAI

📝 Step 4: Create a Controller to Handle Requests

🚧 Step 5: Add Routes

🎨 Step 6: Build the Frontend

🚀 Step 7: Test Everything

🛡️ Step 8: Add Rate Limiting & Error Handling

Rate Limiting

Error Handling

📊 Step 9: Write a Test

🔄 Bonus: Use LaravelGPT for Advanced Use Cases

✅ Conclusion

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How to Integrate GPT-4 into Your Laravel SaaS Application

🚪 Prerequisites

⚙️ Step 1: Install the OpenAI Laravel Package

🔐 Step 2: Add Your OpenAI API Key

🧠 Step 3: Create a Service to Interact with OpenAI

📝 Step 4: Create a Controller to Handle Requests

🚧 Step 5: Add Routes

🎨 Step 6: Build the Frontend

🚀 Step 7: Test Everything

🛡️ Step 8: Add Rate Limiting & Error Handling

Rate Limiting

Error Handling

📊 Step 9: Write a Test

🔄 Bonus: Use LaravelGPT for Advanced Use Cases

✅ Conclusion

Laravel Mastery Coaching Class Program

Daily Sessions

Real Projects

Best Practices

Career Support

Enrollment Closes In

Join the Program

Application Submitted!

What happens next?

Tags

Comments

Related Posts

Laravel Mastery
Coaching Class Program