PHP code example of helgesverre / pagent

    
        
<?php
require_once('vendor/autoload.php');

/* Start to develop here. Best regards https://php-download.com/ */

    

helgesverre / pagent example snippets

// Configure an agent
agent('assistant')
    ->provider('anthropic')
    ->system('You are a helpful assistant')
    ->temperature(0.7);

// Use the agent
$response = agent('assistant')->prompt('Hello!');
echo $response->content;

// Or stream responses in real-time
agent('assistant')->streamTo('Tell me a story', function ($chunk) {
    if ($chunk->isText()) {
        echo $chunk->content;
        flush();
    }
});

// Persist conversations across sessions
agent('support')
    ->memory('sqlite', ['path' => 'storage/conversations.db'])
    ->sessionId('user-123')
    ->contextWindow(100000)
    ->prompt('Hello');

$mock = mock([
    'Hello' => 'Hi there!',
    'How are you?' => 'I am doing great!'
]);

$response = $mock->prompt('Hello');
echo $response->content; // "Hi there!"

$claude = anthropic();
$response = $claude->prompt('Hello!', [
    'model' => 'claude-3-sonnet-20240229',
    'max_tokens' => 100
]);

$gpt = openai();
$response = $gpt->prompt('Hello!', [
    'model' => 'gpt-4',
    'temperature' => 0.8
]);

$ollama = ollama();
$response = $ollama->prompt('Hello!', [
    'model' => 'qwen3:8b',
    'temperature' => 0.7
]);

// Define an agent
agent('support')
    ->provider('anthropic')
    ->system('You are a customer support agent')
    ->model('claude-3-haiku-20240307')
    ->temperature(0.3);

// Have a conversation
$agent = agent('support');
$agent->prompt('I need help with my order');
$agent->prompt('Order number is 12345');

// Access conversation history
foreach ($agent->messages as $message) {
    echo "[{$message['role']}]: {$message['content']}\n";
}

agent('assistant')
    ->provider('anthropic')  // String name
    ->system('You are helpful');

// With config options
agent('custom')
    ->provider('ollama', ['base_url' => 'http://custom:11434', 'timeout' => 180])
    ->model('qwen3:8b');

// Using helper functions
agent('assistant')
    ->provider(anthropic(['api_key' => 'custom-key']))
    ->prompt('Hello');

agent('local')
    ->provider(ollama(['timeout' => 300, 'base_url' => 'http://10.0.0.5:11434']))
    ->model('llama3.1');

// Direct instantiation
use Pagent\Providers\OpenAI;

agent('custom')
    ->provider(new OpenAI(['api_key' => getenv('CUSTOM_KEY')]))
    ->prompt('Hello');

// Anthropic-specific models
$response = anthropic()->prompt('Complex analysis task', [
    'model' => 'claude-3-opus-20240229',
    'max_tokens' => 4096
]);

// OpenAI-specific features
$response = openai()->prompt('Generate JSON data', [
    'model' => 'gpt-3.5-turbo-1106',
    'response_format' => ['type' => 'json_object']
]);

use Pagent\Tool\Tool;

// Create a tool from a closure
$weatherTool = Tool::fromClosure(
    'get_weather',
    'Get the current weather for a location',
    fn(string $location, bool $', 'Get current time', fn(string $tz = 'UTC') => date('H:i:s'));

// Execute tools
$result = $agent->executeTool('calculate', [10, 5]); // 15

// Generate provider-specific schemas
$anthropicSchema = $weatherTool->toAnthropicSchema();
$openaiSchema = $weatherTool->toOpenAISchema();

use Pagent\Tools\FileRead;
use Pagent\Tools\FileWrite;
use Pagent\Tools\WebFetch;
use Pagent\Tools\Bash;
use Pagent\Tools\Grep;
use Pagent\Tools\Glob;
use Pagent\Tools\PdfReader;
use Pagent\Tools\DataExtract;
use Pagent\Tools\SearchTool;

// Use class-based tools with agents
$agent = agent('assistant')
    ->provider('anthropic')
    ->tool(new FileRead())
    ->tool(new WebFetch())
    ->prompt('Read the file data.json and fetch https://api.example.com/data');

// Add multiple tools at once
$agent = agent('file-assistant')
    ->provider('anthropic')
    ->tools([
        new FileRead(baseDir: '/project'),
        new FileWrite(baseDir: '/project'),
        new Glob(baseDir: '/project'),
        new Grep(baseDir: '/project'),
    ])
    ->prompt('List all PHP files and show me the config');

// Create custom class-based tools
use Pagent\Tools\Tool;

class DatabaseQuery extends Tool
{
    public function name(): string
    {
        return 'query_database';
    }

    public function description(): string
    {
        return 'Execute a database query and return results';
    }

    public function parameters(): array
    {
        return [
            'type' => 'object',
            'properties' => [
                'query' => ['type' => 'string', 'description' => 'SQL query to execute'],
                'limit' => ['type' => 'integer', 'description' => 'Maximum rows to return'],
            ],
            '

use Pagent\Tools\SearchTool;

// Search through an array of documents (RAG pattern)
$documents = [
    ['id' => 1, 'title' => 'PHP Guide', 'content' => 'Learn PHP programming...'],
    ['id' => 2, 'title' => 'Laravel Tutorial', 'content' => 'Build web apps with Laravel...'],
];

agent('docs-assistant')
    ->tools([searchDocuments($documents)])
    ->prompt('Find information about PHP');

// Search through files in a directory
agent('codebase-helper')
    ->tools([new SearchTool(paths: ['docs/', 'src/'])])
    ->prompt('Find all documentation about API endpoints');

// Use a pre-built search index
agent('knowledge-bot')
    ->tools([searchIndex('knowledge/docs.index')])
    ->prompt('Search the knowledge base for deployment guides');

// Database-backed search
agent('db-search')
    ->tools([
        new SearchTool(
            query: 'SELECT id, title, content FROM articles',
            connection: ['driver' => 'mysql', 'host' => 'localhost', 'database' => 'mydb']
        )
    ])
    ->prompt('Find articles about Laravel');

new SearchTool(
    documents: $docs,           // Array of documents to index
    returnContent: true,        // Return full documents vs just IDs
    fuzzy: true,                // Enable fuzzy search
    fuzziness: 2,               // Levenshtein distance (1-3)
    maxResults: 20,             // Max results to return
    storage: ':memory:',        // Index storage location
    stemmer: PorterStemmer::class  // Custom stemmer class
);

[
    'hits' => 3,
    'execution_time' => '1.5ms',
    'results' => [
        ['id' => 1, 'score' => 4.2, 'document' => [...]],
        ['id' => 2, 'score' => 3.8, 'document' => [...]],
    ]
]

use function Pagent\{agent, telemetry_console};

// Enable console telemetry for debugging
telemetry_console(verbose: true);

agent('assistant')
    ->provider('anthropic')
    ->telemetry(true)  // Enable tracing for this agent
    ->prompt('Hello!');

// Console shows:
// ┌─ Span: agent.prompt
// │  Duration: 1.23s
// │  Attributes:
// │    - gen_ai.system: anthropic
// │    - gen_ai.usage.total_tokens: 125
// └─

use function Pagent\{agent, telemetry_jaeger};

// Export to Jaeger
telemetry_jaeger('http://localhost:14268/api/traces');

// All operations automatically traced
agent('support')
    ->telemetry(true)
    ->tool('search', 'Search knowledge base', $searchFn)
    ->prompt('Help me find documentation');

// View traces at http://localhost:16686

use function Pagent\{agent, pipeline, telemetry_jaeger};

telemetry_jaeger('http://localhost:14268/api/traces');

// Enable telemetry on agents
agent('researcher')->provider('anthropic')->telemetry(true);
agent('writer')->provider('anthropic')->telemetry(true);

// Run workflow - creates hierarchical trace
pipeline('content-creation')
    ->step('research', agent('researcher'))
    ->step('write', agent('writer'))
    ->run('Write article about PHP');

// Trace shows:
// workflow.pipeline
//   ├─ workflow.step (research)
//   │  └─ agent.prompt → llm.request → tool.execute
//   └─ workflow.step (write)
//      └─ agent.prompt → llm.request