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
- •Tracing: Track LLM calls, chains, and agents
- •Prompts: Version and manage prompts
- •Analytics: Usage, latency, cost metrics
- •Datasets: Evaluation and testing data
- •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)