Documentation Index
Fetch the complete documentation index at: https://docs.instructorphp.com/llms.txt
Use this file to discover all available pages before exploring further.
Overview
This example uses InferenceRuntime directly and shows the Langfuse connection
inline. It is useful when you want visibility into the raw LLM call path
without the additional StructuredOutput layer.
Key concepts:
- explicit
LangfuseConfig / LangfuseHttpTransport / LangfuseExporter setup
InferenceRuntime: direct Polyglot runtime for inference calls
PolyglotTelemetryProjector: maps inference lifecycle events
HttpClientTelemetryProjector: captures transport spans
Telemetry::flush(): pushes the final batch to Langfuse
Example
<?php
require 'examples/boot.php';
use Cognesy\Config\Env;
use Cognesy\Events\Dispatchers\EventDispatcher;
use Cognesy\Http\Telemetry\HttpClientTelemetryProjector;
use Cognesy\Messages\Messages;
use Cognesy\Polyglot\Inference\Inference;
use Cognesy\Polyglot\Inference\InferenceRuntime;
use Cognesy\Polyglot\Inference\LLMProvider;
use Cognesy\Polyglot\Telemetry\PolyglotTelemetryProjector;
use Cognesy\Telemetry\Adapters\Langfuse\LangfuseConfig;
use Cognesy\Telemetry\Adapters\Langfuse\LangfuseExporter;
use Cognesy\Telemetry\Adapters\Langfuse\LangfuseHttpTransport;
use Cognesy\Telemetry\Application\Registry\TraceRegistry;
use Cognesy\Telemetry\Application\Telemetry;
use Cognesy\Telemetry\Application\Projector\CompositeTelemetryProjector;
use Cognesy\Telemetry\Application\Projector\RuntimeEventBridge;
$serviceName = 'examples.b03.telemetry-langfuse';
$baseUrl = (string) Env::get('LANGFUSE_BASE_URL', '');
if ($baseUrl === '') {
throw new RuntimeException('Set LANGFUSE_BASE_URL in .env to run this example.');
}
$publicKey = (string) Env::get('LANGFUSE_PUBLIC_KEY', '');
if ($publicKey === '') {
throw new RuntimeException('Set LANGFUSE_PUBLIC_KEY in .env to run this example.');
}
$secretKey = (string) Env::get('LANGFUSE_SECRET_KEY', '');
if ($secretKey === '') {
throw new RuntimeException('Set LANGFUSE_SECRET_KEY in .env to run this example.');
}
$events = new EventDispatcher($serviceName);
$hub = new Telemetry(
registry: new TraceRegistry(),
exporter: new LangfuseExporter(
transport: new LangfuseHttpTransport(new LangfuseConfig(
baseUrl: $baseUrl,
publicKey: $publicKey,
secretKey: $secretKey,
)),
),
);
(new RuntimeEventBridge(new CompositeTelemetryProjector([
new PolyglotTelemetryProjector($hub),
new HttpClientTelemetryProjector($hub),
])))->attachTo($events);
$runtime = InferenceRuntime::fromProvider(
provider: LLMProvider::using('openai'),
events: $events,
);
$response = Inference::fromRuntime($runtime)
->with(
messages: Messages::fromString('Summarize why observability matters for LLM applications in exactly 3 bullet points.'),
options: ['max_tokens' => 180],
)
->response();
$hub->flush();
echo "Response:\n";
echo $response->content() . "\n\n";
if ($response->usage() !== null) {
echo "Tokens: {$response->usage()->inputTokens} in / {$response->usage()->outputTokens} out\n";
}
echo "Telemetry: flushed to Langfuse\n";
assert($response->content() !== '');
?>