Events

Polyglot uses an event system to provide observability into the internal execution pipeline. Events are dispatched at each stage of the lifecycle, making it straightforward to implement logging, metrics, debugging, and monitoring without modifying the core library.

Listening to Events

Both inference and embeddings runtimes expose two ways to listen to events:

Targeted Listeners

Use onEvent() to listen for a specific event class:

use Cognesy\Polyglot\Inference\Config\LLMConfig;
use Cognesy\Polyglot\Inference\Events\InferenceResponseCreated;
use Cognesy\Polyglot\Inference\InferenceRuntime;

$runtime = InferenceRuntime::fromConfig(
    new LLMConfig(
        driver: 'openai',
        apiUrl: 'https://api.openai.com/v1',
        apiKey: getenv('OPENAI_API_KEY'),
        endpoint: '/chat/completions',
        model: 'gpt-4.1-nano',
    ),
)->onEvent(InferenceResponseCreated::class, function ($event): void {
    // Log or inspect the response
});
// @doctest id="1154"

You can register multiple listeners for the same event class. An optional priority parameter controls the order (higher values run first):

$runtime->onEvent(InferenceStarted::class, $highPriorityListener, priority: 10);
$runtime->onEvent(InferenceStarted::class, $lowPriorityListener, priority: 0);
// @doctest id="f5aa"

Wiretap

Use wiretap() to receive all events regardless of type. This is useful for debugging and general-purpose logging:

$runtime->wiretap(function ($event): void {
    echo get_class($event) . "\n";
});
// @doctest id="9991"

Inference Events

The inference lifecycle dispatches events in this order:

Execution-Level Events

Event	When Dispatched	Key Data
`InferenceStarted`	Beginning of execution	`data['executionId']`, `data['requestId']`, `data['isStreamed']`, `data['model']`, `data['messageCount']`
`InferenceCompleted`	End of execution (success or failure)	`data['executionId']`, `data['isSuccess']`, `data['finishReason']`, `data['attemptCount']`, `data['durationMs']`, token-count fields

These events bracket the entire inference operation, including any retry attempts. InferenceCompleted is dispatched exactly once per execution, whether it succeeded or failed.

Attempt-Level Events

Each retry attempt dispatches its own events:

Event	When Dispatched	Key Data
`InferenceAttemptStarted`	Beginning of an attempt	execution ID, attempt ID, attempt number, model
`InferenceAttemptSucceeded`	Attempt completed successfully	`data['executionId']`, `data['attemptId']`, `data['attemptNumber']`, `data['finishReason']`, `data['durationMs']`, token-count fields
`InferenceAttemptFailed`	Attempt failed	`data['executionId']`, `data['attemptId']`, `data['attemptNumber']`, `data['errorMessage']`, `data['errorType']`, `data['willRetry']`, `data['httpStatusCode']`, partial token-count fields, `data['durationMs']`
`InferenceUsageReported`	After a successful attempt	`data['executionId']`, `data['model']`, `data['isFinal']`, token-count fields

When retries are configured, you may see multiple InferenceAttemptStarted/InferenceAttemptFailed pairs before a final InferenceAttemptSucceeded event. The attemptNumber field tracks which attempt is running.

Response Events

Event	When Dispatched	Key Data
`InferenceRequested`	Before sending the HTTP request	request data
`InferenceResponseCreated`	After receiving and parsing the response	`data['executionId']`, `data['requestId']`, `data['responseId']`, `data['finishReason']`, content-length fields, tool-call summary, `data['usage']`
`InferenceFailed`	On unrecoverable failure	error details

Streaming Events

Event	When Dispatched	Key Data
`StreamFirstChunkReceived`	First visible delta arrives	execution ID, timeToFirstChunkMs, receivedAt, model, initial content
`PartialInferenceDeltaCreated`	Each visible delta	`data['executionId']`, `data['contentDelta']`
`StreamEventReceived`	Raw SSE event received	raw event data
`StreamEventParsed`	SSE event parsed into a delta	parsed event data

The StreamFirstChunkReceived event is particularly useful for measuring time-to-first-chunk (TTFC), as it includes the requestStartedAt timestamp.

Driver Events

Event	When Dispatched	Key Data
`InferenceDriverBuilt`	After the driver is created by the factory	driver class, redacted config, HTTP client class

Sensitive configuration values (API keys, tokens, secrets) are automatically redacted in the InferenceDriverBuilt event payload.

Embeddings Events

The embeddings lifecycle dispatches a smaller set of events:

Event	When Dispatched	Key Data
`EmbeddingsDriverBuilt`	After the embeddings driver is created	driver class, config, HTTP client class
`EmbeddingsRequested`	Before sending the embeddings request	request data
`EmbeddingsResponseReceived`	After receiving the response	`data['model']`, `data['inputCount']`, `data['vectorCount']`, `data['dimensions']`, `data['usage']`
`EmbeddingsFailed`	On failure	error details

Practical Examples

Logging Token Usage

use Cognesy\Polyglot\Inference\Events\InferenceUsageReported;

$runtime->onEvent(InferenceUsageReported::class, function ($event): void {
    logger()->info('Token usage', [
        'model' => $event->data['model'] ?? null,
        'inputTokens' => $event->data['inputTokens'] ?? 0,
        'outputTokens' => $event->data['outputTokens'] ?? 0,
        'totalTokens' => $event->data['totalTokens'] ?? 0,
    ]);
});
// @doctest id="6c65"

Measuring Time-to-First-Chunk

use Cognesy\Polyglot\Inference\Events\StreamFirstChunkReceived;

$runtime->onEvent(StreamFirstChunkReceived::class, function (StreamFirstChunkReceived $event): void {
    logger()->info("TTFC: {$event->timeToFirstChunkMs}ms for model {$event->model}");
});
// @doctest id="35d4"

Tracking Retry Attempts

use Cognesy\Polyglot\Inference\Events\InferenceAttemptFailed;

$runtime->onEvent(InferenceAttemptFailed::class, function (InferenceAttemptFailed $event): void {
    logger()->warning('Attempt failed', [
        'attemptNumber' => $event->data['attemptNumber'] ?? null,
        'errorMessage' => $event->data['errorMessage'] ?? null,
        'errorType' => $event->data['errorType'] ?? null,
        'willRetry' => $event->data['willRetry'] ?? false,
        'httpStatus' => $event->data['httpStatusCode'] ?? null,
    ]);
});
// @doctest id="3f51"

Monitoring Execution Outcomes

use Cognesy\Polyglot\Inference\Events\InferenceCompleted;

$runtime->onEvent(InferenceCompleted::class, function (InferenceCompleted $event): void {
    logger()->info('Inference completed', [
        'success' => $event->data['isSuccess'] ?? false,
        'finishReason' => $event->data['finishReason'] ?? null,
        'attempts' => $event->data['attemptCount'] ?? 0,
        'totalTokens' => $event->data['totalTokens'] ?? 0,
        'durationMs' => $event->data['durationMs'] ?? 0,
    ]);
});
// @doctest id="4466"

Event Dispatcher

Events are dispatched through an EventDispatcher that implements CanHandleEvents (which extends Psr\EventDispatcher\EventDispatcherInterface). When a runtime is created without an explicit event dispatcher, it creates a default one named 'polyglot.inference.runtime' or 'polyglot.embeddings.runtime'. You can inject a shared event dispatcher to correlate events across multiple runtimes or integrate with your application’s existing event system:

use Cognesy\Events\Dispatchers\EventDispatcher;

$events = new EventDispatcher(name: 'my-app');
$runtime = InferenceRuntime::fromConfig($config, events: $events);
// @doctest id="367d"

The same event dispatcher instance can be shared between inference and embeddings runtimes, allowing a single wiretap listener to observe all Polyglot activity.

Packages

Instructor

Polyglot

Agents

Agent-ctrl

Telemetry

Sandbox

HTTP Client

Laravel

Symfony

Xprompt

Listening to Events

Targeted Listeners

Wiretap

Inference Events

Execution-Level Events

Attempt-Level Events

Response Events

Streaming Events

Driver Events

Embeddings Events

Practical Examples

Logging Token Usage

Measuring Time-to-First-Chunk

Tracking Retry Attempts

Monitoring Execution Outcomes

Event Dispatcher

​Listening to Events

​Targeted Listeners

​Wiretap

​Inference Events

​Execution-Level Events

​Attempt-Level Events

​Response Events

​Streaming Events

​Driver Events

​Embeddings Events

​Practical Examples

​Logging Token Usage

​Measuring Time-to-First-Chunk

​Tracking Retry Attempts

​Monitoring Execution Outcomes

​Event Dispatcher

Listening to Events

Targeted Listeners

Wiretap

Inference Events

Execution-Level Events

Attempt-Level Events

Response Events

Streaming Events

Driver Events

Embeddings Events

Practical Examples

Logging Token Usage

Measuring Time-to-First-Chunk

Tracking Retry Attempts

Monitoring Execution Outcomes

Event Dispatcher