On the final day, we’ll wrap up the AI-powered sales forecasting system by:
- Securing access with authentication
- Polishing the dashboard UI
- Adding final routes and links
- Preparing for production deployment
🔐 Step 1: Protect forecast routes with auth middleware
In routes/web.php, group all forecast routes:
Route::middleware('auth')->group(function () {
Route::get('/sales', [SalesController::class, 'index'])->name('sales.index');
Route::post('/forecast/insights', [SalesController::class, 'generateInsights'])->name('forecast.insights');
Route::get('/forecast/image', [SalesController::class, 'forecastImage'])->name('forecast.image');
Route::get('/forecast/export/csv', fn() => Excel::download(new ForecastExport, 'forecast_report.csv'))->name('forecast.export.csv');
Route::get('/forecast/export/pdf', function () {
$data = \App\Models\ForecastResult::orderBy('forecast_date')->get();
$pdf = \PDF::loadView('forecast.pdf', compact('data'));
return $pdf->download('forecast_report.pdf');
})->name('forecast.export.pdf');
});
Enable login system (if not already):
composer require laravel/ui
php artisan ui bootstrap --auth
npm install && npm run dev
php artisan migrate
🧼 Step 2: Clean up the dashboard layout
Update sales/index.blade.php with headings, spacing, and layout structure:
<x-app-layout>
<x-slot name="header">
<h2 class="text-xl font-semibold">Sales Forecast Dashboard</h2>
</x-slot>
<div class="my-6">
<canvas id="forecastChart" height="120"></canvas>
</div>
<div class="mt-6">
<form method="POST" action="{{ route('forecast.insights') }}">
@csrf
<button class="bg-orange-500 text-white px-4 py-2 rounded">Generate AI Insight</button>
</form>
</div>
@if(session('forecast_insight'))
<div class="bg-orange-100 text-orange-900 p-3 rounded mt-4 whitespace-pre-wrap">
{!! nl2br(e(session('forecast_insight'))) !!}
</div>
@endif
<div class="flex gap-4 mt-6">
<a href="{{ route('forecast.export.csv') }}" class="bg-green-500 text-white px-4 py-2 rounded">Export CSV</a>
<a href="{{ route('forecast.export.pdf') }}" class="bg-red-500 text-white px-4 py-2 rounded">Download PDF</a>
</div>
</x-app-layout>
🚀 Step 3: Prepare for deployment
Set the following in .env.production:
APP_ENV=production
APP_DEBUG=false
LOG_CHANNEL=stack
QUEUE_CONNECTION=database
Then:
php artisan config:cache
php artisan route:cache
php artisan view:cache
php artisan storage:link
Deploy to Laravel Forge, DigitalOcean, or any host with PHP 8+ and Python support.
✅ Final Features Recap
- Sales chart with real-time and forecasted data
- CSV + PDF export
- GPT-generated insights
- Anomaly detection
- Role-based access
- Artisan-powered Python integration
🎉 Your AI-powered Laravel Sales Forecasting System is now complete and production-ready.
You’ve built a full-stack tool combining real data, AI prediction, and business-ready reporting — all in 10 days.
