langfuse-integration

# LangFuse Integration Skill ## Capabilities - Set up LangFuse tracing for LLM calls - Configure cost tracking and analytics - Implement prompt management - Set up evaluation datasets - Design custom trace metadata - Create dashboards and alerts ## Target Processes - llm-observability-monitoring - cost-optimization-llm ## Implementation Details ### Core Features 1. **Tracing**: Track LLM calls, chains, and agents 2. **Prompts**: Version and manage prompts 3. **Analytics**: Usage, latency, cost metrics 4. **Datasets**: Evaluation and testing data 5. **Scores**: Track output quality ### Integration Methods - LangChain callback handler - Direct SDK integration - OpenAI drop-in replacement - Decorator-based tracing ### Configuration Options - Public/secret keys - Host URL (cloud or self-hosted) - Sampling rate - Metadata configuration - User tracking ### Best Practices - Consistent trace naming - Meaningful metadata - Regular prompt versioning - Set up alerting ### Dependencies - langfuse - langchain (for callback integration)