return [
    'model' => env('OLLAMA_MODEL', 'llama3.1'),
    'url' => env('OLLAMA_URL', 'http://127.0.0.1:11434'),
    'default_prompt' => env('OLLAMA_DEFAULT_PROMPT', 'Hello, how can I assist you today?'),
    'connection' => [
        'timeout' => env('OLLAMA_CONNECTION_TIMEOUT', 300),
    ],
];

use Cloudstudio\Ollama\Facades\Ollama;

$response = Ollama::agent('You are a helpful assistant.')
    ->prompt('Explain quantum computing in simple terms')
    ->model('llama3.1')
    ->ask();

echo $response['response'];

$response = Ollama::agent('You are a creative writing assistant.')
    ->prompt('Write a short story about a robot learning to paint')
    ->model('llama3.1')
    ->options([
        'temperature' => 0.8,  // More creative
        'top_p' => 0.9,
        'max_tokens' => 500
    ])
    ->ask();

$response = Ollama::agent('You are an expert PHP developer.')
    ->prompt('Create a Laravel middleware that logs API requests with rate limiting')
    ->model('codellama')
    ->options(['temperature' => 0.2]) // Less creative for code
    ->ask();

$response = Ollama::model('llava:13b')
    ->prompt('Describe what you see in this image in detail')
    ->image(public_path('images/product-photo.jpg'))
    ->ask();

echo $response['response'];
// "This image shows a modern smartphone with a sleek black design..."

$response = Ollama::model('llava:13b')
    ->prompt('Extract product information from this image including brand, model, features, and estimated price range')
    ->image(storage_path('app/uploads/product.jpg'))
    ->ask();

$response = Ollama::model('llava:13b')
    ->prompt('Compare these images and identify the differences')
    ->images([
        public_path('images/before.jpg'),
        public_path('images/after.jpg')
    ])
    ->ask();

$response = Ollama::model('llava:13b')
    ->prompt('Extract all text from this document and summarize the key points')
    ->image(storage_path('app/documents/invoice.pdf'))
    ->ask();

$messages = [
    ['role' => 'system', 'content' => 'You are a helpful customer support agent for an e-commerce website.'],
    ['role' => 'user', 'content' => 'I ordered a laptop 3 days ago but haven\'t received tracking information'],
    ['role' => 'assistant', 'content' => 'I understand your concern. Let me help you track your laptop order. Could you please provide your order number?'],
    ['role' => 'user', 'content' => 'My order number is ORD-12345']
];

$response = Ollama::model('llama3.1')
    ->chat($messages);

$messages = [
    ['role' => 'system', 'content' => 'You are a patient math tutor helping a student learn calculus.'],
    ['role' => 'user', 'content' => 'I don\'t understand how to find the derivative of x^2 + 3x + 2'],
    ['role' => 'assistant', 'content' => 'I\'d be happy to help! Let\'s break this down step by step...'],
    ['role' => 'user', 'content' => 'Can you show me the power rule?']
];

$response = Ollama::model('llama3.1')
    ->options(['temperature' => 0.3]) // Lower temperature for educational content
    ->chat($messages);

$messages = [
    ['role' => 'system', 'content' => 'You are a senior software engineer providing code reviews.'],
    ['role' => 'user', 'content' => 'Please review this PHP function for potential improvements:'],
    ['role' => 'user', 'content' => '```php
function calculateTotal($items) {
    $total = 0;
    foreach($items as $item) {
        $total += $item["price"] * $item["quantity"];
    }
    return $total;
}
```']
];

$response = Ollama::model('codellama')
    ->chat($messages);

$messages = [
    ['role' => 'user', 'content' => 'What\'s the current weather in Tokyo and London?']
];

$response = Ollama::model('llama3.1')
    ->tools([
        [
            "type" => "function",
            "function" => [
                "name" => "get_current_weather",
                "description" => "Get the current weather for a specific location",
                "parameters" => [
                    "type" => "object",
                    "properties" => [
                        "location" => [
                            "type" => "string",
                            "description" => "The city and country, e.g. Tokyo, Japan",
                        ],
                        "unit" => [
                            "type" => "string",
                            "description" => "Temperature unit",
                            "enum" => ["celsius", "fahrenheit"],
                        ],
                    ],
                    "required" => ["location"],
                ],
            ],
        ]
    ])
    ->chat($messages);

$tools = [
    [
        "type" => "function",
        "function" => [
            "name" => "execute_sql_query",
            "description" => "Execute a read-only SQL query on the database",
            "parameters" => [
                "type" => "object",
                "properties" => [
                    "query" => [
                        "type" => "string",
                        "description" => "The SQL SELECT query to execute",
                    ],
                    "table" => [
                        "type" => "string",
                        "description" => "The primary table being queried",
                    ]
                ],
                "required" => ["query", "table"],
            ],
        ],
    ]
];

$messages = [
    ['role' => 'user', 'content' => 'Show me the top 5 customers by total orders']
];

$response = Ollama::model('llama3.1')
    ->tools($tools)
    ->chat($messages);

use Illuminate\Console\BufferedConsoleOutput;

$response = Ollama::agent('You are a creative storyteller.')
    ->prompt('Write an engaging short story about time travel')
    ->model('llama3.1')
    ->options(['temperature' => 0.8])
    ->stream(true)
    ->ask();

$output = new BufferedConsoleOutput();
$responses = Ollama::processStream($response->getBody(), function($data) use ($output) {
    echo $data['response']; // Output in real-time
    flush();
});

$complete = implode('', array_column($responses, 'response'));

// In your controller
public function streamChat(Request $request)
{
    $response = Ollama::agent('You are a helpful assistant.')
        ->prompt($request->input('message'))
        ->model('llama3.1')
        ->stream(true)
        ->ask();

    return response()->stream(function() use ($response) {
        Ollama::processStream($response->getBody(), function($data) {
            echo "data: " . json_encode($data) . "\n\n";
            flush();
        });
    }, 200, [
        'Content-Type' => 'text/plain',
        'Cache-Control' => 'no-cache',
        'X-Accel-Buffering' => 'no'
    ]);
}

// Generate embeddings for documents
$documents = [
    'Laravel is a PHP web framework',
    'Python is a programming language',
    'React is a JavaScript library'
];

$embeddings = [];
foreach ($documents as $doc) {
    $embeddings[] = Ollama::model('nomic-embed-text')
        ->embeddings($doc);
}

// Search for similar content
$query = 'Web development framework';
$queryEmbedding = Ollama::model('nomic-embed-text')
    ->embeddings($query);

// Calculate cosine similarity (implement your similarity function)
$similarities = calculateCosineSimilarity($queryEmbedding, $embeddings);

// Generate product embeddings
$productDescription = 'Wireless noise-canceling headphones with 30-hour battery life';
$productEmbedding = Ollama::model('nomic-embed-text')
    ->embeddings($productDescription);

// Store embedding in database for later similarity searches
DB::table('products')->where('id', $productId)->update([
    'embedding' => json_encode($productEmbedding['embedding'])
]);

$models = Ollama::models();
foreach ($models['models'] as $model) {
    echo "Model: " . $model['name'] . " (Size: " . $model['size'] . ")\n";
}

$info = Ollama::model('llama3.1')->show();
echo "Model: " . $info['details']['family'] . "\n";
echo "Parameters: " . $info['details']['parameter_size'] . "\n";

// Copy a model
Ollama::model('llama3.1')->copy('my-custom-llama');

// Pull a new model
Ollama::model('codellama:7b')->pull();

// Delete a model
Ollama::model('old-model')->delete();

class ContentModerationService
{
    public function moderateContent(string $content): array
    {
        $response = Ollama::agent(
            'You are a content moderator. Analyze content for inappropriate material, spam, or policy violations. Respond with JSON containing "safe" (boolean), "categories" (array), and "confidence" (0-1).'
        )
        ->prompt("Analyze this content: {$content}")
        ->model('llama3.1')
        ->format('json')
        ->options(['temperature' => 0.1])
        ->ask();

        return json_decode($response['response'], true);
    }
}

class CodeDocumentationService
{
    public function generateDocumentation(string $code): string
    {
        return Ollama::agent(
            'You are a technical writer. Generate comprehensive PHPDoc comments for the given code.'
        )
        ->prompt("Generate documentation for this code:\n\n{$code}")
        ->model('codellama')
        ->options(['temperature' => 0.2])
        ->ask()['response'];
    }
}

class TranslationService
{
    public function translate(string $text, string $fromLang, string $toLang): string
    {
        return Ollama::agent(
            "You are a professional translator. Translate the given text accurately while preserving tone and context."
        )
        ->prompt("Translate from {$fromLang} to {$toLang}: {$text}")
        ->model('llama3.1')
        ->options(['temperature' => 0.3])
        ->ask()['response'];
    }
}

class DataAnalysisService
{
    public function analyzeCSV(string $csvPath): array
    {
        $csvContent = file_get_contents($csvPath);
        
        $response = Ollama::agent(
            'You are a data analyst. Analyze the CSV data and provide insights, trends, and recommendations in JSON format.'
        )
        ->prompt("Analyze this CSV data:\n\n{$csvContent}")
        ->model('llama3.1')
        ->format('json')
        ->ask();

        return json_decode($response['response'], true);
    }
}

// Good: Specific and detailed
$response = Ollama::agent('You are a senior Laravel developer with 10 years of experience.')
    ->prompt('Create a secure user authentication system using Laravel Sanctum with rate limiting and email verification')
    ->ask();

// Better: Include context and constraints
$response = Ollama::agent('You are a senior Laravel developer. Follow PSR-12 coding standards and include comprehensive error handling.')
    ->prompt('Create a user authentication system with these requirements: Laravel Sanctum, rate limiting (5 attempts per minute), email verification, and password reset functionality. Include middleware and proper validation.')
    ->ask();

try {
    $response = Ollama::model('llama3.1')
        ->prompt('Your prompt here')
        ->ask();
} catch (\Exception $e) {
    Log::error('Ollama request failed: ' . $e->getMessage());
    // Handle gracefully
}

// Use keepAlive for multiple requests
$ollama = Ollama::model('llama3.1')->keepAlive('10m');

// Process multiple prompts
foreach ($prompts as $prompt) {
    $response = $ollama->prompt($prompt)->ask();
    // Process response
}

it('can generate content with Ollama', function () {
    $response = Ollama::agent('You are a test assistant.')
        ->prompt('Say hello')
        ->model('llama3.1')
        ->ask();
    
    expect($response)->toHaveKey('response');
    expect($response['response'])->toBeString();
});