langsmith-tracing

# langsmith-tracing Configure LangSmith observability and tracing for LLM applications built with LangChain and LangGraph frameworks. ## Overview LangSmith is the managed observability suite by LangChain that provides: - Dashboards and alerting for LLM applications - Human-in-the-loop evaluation capabilities - Deep LangChain/LangGraph integration - Run Tree model for nested traces - MCP connectivity to Claude, VSCode ## Capabilities ### Core Tracing Setup - Initialize LangSmith client and API configuration - Configure project/workspace settings - Set up trace collection and sampling - Enable debug logging for agent execution ### Integration Patterns - LangChain chain tracing with automatic instrumentation - LangGraph workflow state tracking - Custom span creation for non-LangChain code - Parent-child trace relationships ### Debugging Features - Fetch execution traces for analysis - Query run history and metadata - Export traces for offline analysis - Compare runs across different versions ## Usage ### Environment Setup ```bash # Set required environment variables export LANGCHAIN_TRACING_V2=true export LANGCHAIN_API_KEY=<your-api-key> export LANGCHAIN_PROJECT=<project-name> ``` ### Python Integration ```python from langsmith import Client, traceable from langchain.callbacks.tracers import LangChainTracer # Initialize client client = Client() # Use @traceable decorator for custom functions @traceable(name="custom_operation") def my_function(input_data): # You...