README

A Symfony bundle for integrating with Langfuse, providing AI operation tracing, prompt management, and observability for AI applications built with the Lingoda AI SDK.

Features

🔍 Automatic AI Tracing: Traces all AI operations (completions, TTS, STT, translations)
⚡ Async/Sync Flushing: Configurable sync or async trace processing via Symfony Messenger
📝 Prompt Management: Fetch, cache, and manage prompts with intelligent cascade (Cache → API → Storage)
💰 Usage Metrics: Automatic token counting and cost tracking with proper generation support
🗄️ Flexible Storage: Path-based or Flysystem storage for prompt fallbacks
🔧 Console Commands: Connection testing and prompt management tools

Requirements

PHP 8.3 or higher
Symfony 6.4 or 7.0+
Lingoda AI Bundle 1.2+ (the bundle decorates the Lingoda AI SDK)
Dropsolid Langfuse PHP SDK 1.2+

Installation

Install the bundle via Composer:

composer require lingoda/langfuse-bundle

Add the bundle to config/bundles.php:

return [
    // ...
    Lingoda\LangfuseBundle\LingodaLangfuseBundle::class => ['all' => true],
];

Configure the bundle in config/packages/lingoda_langfuse.yaml:

lingoda_langfuse:
    connection:
        public_key: '%env(LANGFUSE_PUBLIC_KEY)%'
        secret_key: '%env(LANGFUSE_SECRET_KEY)%'
        host: '%env(default:LANGFUSE_HOST:https://cloud.langfuse.com)%'
        timeout: 30
        retry:
            max_attempts: 3
            delay: 1000

    tracing:
        enabled: true
        sampling_rate: 1.0
        async_flush:
            enabled: false
            message_bus: 'messenger.bus.default'

    prompts:
        caching:
            enabled: false
            ttl: 3600
            service: 'cache.app'
        fallback:
            enabled: true
            storage:
                path: '%kernel.project_dir%/var/prompts'

Core Features

Automatic AI Operation Tracing

The bundle automatically traces all AI operations by decorating the Lingoda AI SDK's PlatformInterface:

use Lingoda\AiSdk\PlatformInterface;

class ContentService
{
    public function __construct(
        private PlatformInterface $platform
    ) {}

    public function generateContent(string $prompt): string
    {
        // This call is automatically traced to Langfuse with proper generation and usage metrics
        $result = $this->platform->ask($prompt, 'gpt-4');

        return $result->getContent();
    }

    public function generateAudio(string $text): string
    {
        // TTS operations are also traced
        $audio = $this->platform->textToSpeech($text);

        return $audio->getContent();
    }
}

Automatic trace data includes:

Operation type (ai-completion, text-to-speech, etc.)
Model information and provider resolution
Input/output content and metadata
Duration and timing information
Usage metrics (prompt tokens, completion tokens, total tokens)
Proper Langfuse generation structure for cost tracking
Error handling and status tracking

Usage Metrics and Cost Tracking

The bundle automatically extracts and sends usage metrics in the proper format for Langfuse:

Prompt tokens: Input token count
Completion tokens: Output token count
Total tokens: Combined count
Model information: For accurate cost calculation
Proper generation structure: Trace → Generation hierarchy

This enables accurate cost tracking and usage analysis in the Langfuse dashboard.

Async Trace Flushing

For production applications, enable asynchronous trace processing to eliminate latency impact:

1. Configure Messenger Transport

# config/packages/messenger.yaml
framework:
    messenger:
        transports:
            langfuse_traces:
                dsn: '%env(MESSENGER_TRANSPORT_DSN)%/langfuse-traces'
                retry_strategy:
                    max_retries: 3
                    delay: 1000
                    multiplier: 2
        routing:
            'Lingoda\LangfuseBundle\Message\FlushLangfuseTrace': langfuse_traces

2. Enable Async Processing

# config/packages/lingoda_langfuse.yaml
lingoda_langfuse:
    tracing:
        enabled: true
        sampling_rate: 1.0
        async_flush:
            enabled: true
            message_bus: 'messenger.bus.default'  # optional, defaults to messenger.bus.default

3. Run Message Consumers

php bin/console messenger:consume langfuse_traces --time-limit=3600

# or multiple workers for high throughput
php bin/console messenger:consume langfuse_traces --limit=100
php bin/console messenger:consume langfuse_traces --limit=100
...

Benefits:

Zero latency impact on AI operations
Higher throughput for AI-intensive applications
Reliable delivery with retry mechanisms
Scalable processing with multiple workers

Prompt Management

The bundle provides a complete prompt management system with intelligent caching and fallback storage:

use Lingoda\LangfuseBundle\Prompt\PromptRegistryInterface;
use Lingoda\AiSdk\Prompt\Conversation;

class EmailService
{
    public function __construct(
        private PromptRegistryInterface $prompts
    ) {}

    public function generateWelcomeEmail(string $userName): Conversation
    {
        // Intelligent cascade: Cache → API → Storage
        return $this->prompts->get('welcome_email');
    }

    public function generateCustomEmail(string $promptName, array $variables): Conversation
    {
        // Get specific version with variables
        $prompt = $this->prompts->get($promptName, $variables);

        return $prompt;
    }
}

Prompt Flow:

Cache lookup - Fast in-memory retrieval
API call - Fresh fetch from Langfuse if cache miss
Storage fallback - Local storage if API unavailable
Automatic caching - Cache API results for future use

Storage Configuration Options

Path-based Storage (Default):

lingoda_langfuse:
    prompts:
        fallback:
            storage:
                path: '%kernel.project_dir%/var/prompts'

Flysystem Integration (Cloud Storage):

# Configure Flysystem adapter first
flysystem:
    storages:
        prompts.storage:
            adapter: 's3'
            options:
                bucket: 'my-prompts-bucket'
                region: 'us-east-1'

# Reference in Langfuse config
lingoda_langfuse:
    prompts:
        fallback:
            storage:
                service: 'prompts.storage'

Direct TraceClient Usage

For manual tracing beyond automatic AI operations:

use Lingoda\LangfuseBundle\Client\TraceClient;

class AnalyticsService
{
    public function __construct(
        private TraceClient $traceClient
    ) {}

    public function processUserAction(User $user, string $action): void
    {
        $trace = $this->traceClient->trace([
            'name' => 'user-action',
            'userId' => $user->getId(),
            'metadata' => ['action' => $action],
            'input' => ['timestamp' => time()]
        ]);

        // For AI operations, create a generation
        if ($action === 'ai-query') {
            $generation = $trace->createGeneration(
                name: 'ai-completion',
                model: 'gpt-4',
                input: ['query' => 'user question']
            );

            // Set usage details for cost tracking
            $generation->withUsageDetails([
                'prompt_tokens' => 15,
                'completion_tokens' => 8,
                'total_tokens' => 23
            ]);

            $generation->end(['output' => 'AI response']);
        }

        $trace->end([
            'output' => ['status' => 'completed'],
            'statusMessage' => 'Action processed successfully'
        ]);

        // Manually flush if needed (automatic in most cases)
        $this->traceClient->flush();
    }
}

Configuration Reference

lingoda_langfuse:
    # Connection settings
    connection:
        public_key: string              # Required: Langfuse public key
        secret_key: string              # Required: Langfuse secret key
        host: string                    # Default: https://cloud.langfuse.com
        timeout: int                    # Default: 30 (seconds)
        retry:
            max_attempts: int           # Default: 3
            delay: int                  # Default: 1000 (milliseconds)

    # Tracing configuration
    tracing:
        enabled: bool                   # Default: true
        sampling_rate: float            # Default: 1.0 (0.0-1.0)
        async_flush:
            enabled: bool               # Default: false
            message_bus: string         # Default: 'messenger.default_bus'

    # Prompt management
    prompts:
        caching:
            enabled: bool               # Default: false
            ttl: int                    # Default: 3600 (seconds)
            service: string             # Default: 'cache.app'
        fallback:
            enabled: bool               # Default: false (auto-enabled with storage config)
            storage:
                path: string            # File system path
                # OR
                service: string         # Flysystem service ID

Console Commands

Test Connection

Verify your Langfuse API credentials and connection:

php bin/console langfuse:test-connection

Cache Prompts

Cache specific prompts from Langfuse to local fallback storage:

# Cache specific prompts
php bin/console langfuse:cache-prompt --prompt=greeting --prompt=goodbye

# Preview without saving
php bin/console langfuse:cache-prompt --prompt=greeting --dry-run

# Force overwrite existing cached prompts
php bin/console langfuse:cache-prompt --prompt=greeting --force

Options:

--prompt|-p: Specify prompt name(s) to cache (required, can be used multiple times)
--dry-run: Preview what would be cached without saving files
--force: Overwrite existing cached prompts

Performance Optimization

Sync Mode (Default):

Immediate trace delivery
~50-100ms latency per operation
Guaranteed delivery
Good for low-traffic applications

Async Mode:

Zero latency impact on AI operations
Requires message queue infrastructure
Higher throughput potential
Eventual consistency

Sampling Configuration:

lingoda_langfuse:
    tracing:
        sampling_rate: 0.1  # Trace 10% of operations

Development

Running Tests

# Install dependencies
composer install

# Run PHPUnit tests
vendor/bin/phpunit

# Run static analysis
vendor/bin/phpstan analyse

# Check code style
vendor/bin/ecs check

# Fix code style
vendor/bin/ecs check --fix

Architecture

The bundle follows clean architecture principles with focused, single-responsibility services:

Core Components

LangfusePlatformDecorator: Decorates AI SDK to enable automatic tracing
TraceManager: Coordinates trace data preparation and timing
SyncTraceFlusher: Handles synchronous flushing with generation support
AsyncTraceFlusher: Dispatches traces to message queue
FlushLangfuseTraceHandler: Processes async messages (delegates to sync flusher)
PromptRegistry: Manages prompt lifecycle with caching and storage
PromptClient: Handles API communication with Langfuse
TraceClient: Direct trace creation and management

Trace Processing Architecture

AI Operation → Platform Decorator → TraceManager → FlushService → Langfuse
                                          ↓             ↓
                                    TraceFlusherInterface
                                          ↓
                                    SyncTraceFlusher
                                          ↓
                                    Creates Trace → Generation → Usage Details
                                          ↓
                                    Langfuse API

Async Flow:

AI Operation → TraceManager → AsyncTraceFlusher → Message Queue
                                                      ↓
                                           FlushLangfuseTraceHandler
                                                      ↓
                                                SyncTraceFlusher
                                                      ↓
                                                 Langfuse API

Prompt Management Architecture

Request → PromptRegistry → Cache → Langfuse API → Storage
                             ↓         ↓           ↓
                       Fast Return  Fresh Data    Fallback

Architecture Principles

Design Philosophy

Direct Langfuse Integration: Clean, direct API communication without intermediary layers
Simple Trace Structure: AI operations create trace → generation structure
Async/Sync Flexibility: Choose between immediate or queued processing

Logging

The bundle uses a dedicated langfuse Monolog channel for all operations. Configure it in your Monolog configuration:

# config/packages/monolog.yaml
monolog:
    channels:
        - langfuse
    handlers:
        langfuse:
            type: stream
            path: '%kernel.logs_dir%/langfuse.log'
            level: debug
            channels: [langfuse]

Troubleshooting

Common Issues

Connection failures: Verify your API keys and host URL using langfuse:test-connection
Missing prompts: Use langfuse:cache-prompt to cache prompts locally for offline access
Async processing not working: Ensure Symfony Messenger is configured and consumers are running
Token usage not tracked: Verify the AI SDK returns proper usage metrics

Debug Mode

Enable debug logging to troubleshoot issues:

monolog:
    handlers:
        langfuse:
            level: debug  # Set to debug level

License

MIT License. See LICENSE for details.

lingoda / langfuse-bundle

Maintainers

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