langsmith

# LangSmith LangSmith is a framework-agnostic platform for building, debugging, and deploying AI agents and LLM applications. Trace requests, evaluate outputs, test prompts, and manage deployments all in one place at [smith.langchain.com](https://smith.langchain.com). ## When to use Use LangSmith when you need to: - **Trace and debug** LLM calls, agent steps, retrieval, and tool use - **Evaluate** LLM outputs with automated or human-in-the-loop scoring - **Engineer prompts** with a visual playground and version control - **Deploy agents** to production with the LangGraph-based agent server - **Monitor** production systems with dashboards, alerts, and cost tracking ## When NOT to use - To build agent logic or LLM pipelines, use [LangChain](https://docs.langchain.com/oss/langchain/overview), [LangGraph](https://docs.langchain.com/oss/langgraph/overview), or [Deep Agents](https://docs.langchain.com/oss/deepagents/overview) instead - LangSmith is the **platform layer** that complements these frameworks ## Quick setup Set two environment variables to enable tracing from any supported framework: ```bash export LANGSMITH_TRACING=true export LANGSMITH_API_KEY="your-api-key" # from smith.langchain.com/settings ``` ### Install the SDK ```bash # Python pip install langsmith # JavaScript/TypeScript npm install langsmith ``` ### Verify tracing ```python from langsmith import traceable @traceable def my_function(query: str) -> str: # Your LLM logic here—all calls inside are traced automatically return "result" ``` ## Core capabilities | Capability | Description | |-----------|-------------| | Observability | Trace every step of your LLM app with automatic or manual instrumentation | | Evaluation | Run evaluations with code, LLM-as-judge, or composite evaluators | | Prompt engineering | Create, version, and test prompts in a visual playground | | Agent deployment | Deploy LangGraph agents with streaming, human-in-the-loop, and durable execution | | Monitoring | Dashboards, alerts, and cost tracking for production workloads | ## Key documentation - [Overview](https://docs.langchain.com/langsmith/observability)—Get started with LangSmith - [Observability quickstart](https://docs.langchain.com/langsmith/observability-quickstart)—Add tracing in minutes - [Evaluation quickstart](https://docs.langchain.com/langsmith/evaluation-quickstart)—Run your first evaluation - [Prompt engineering quickstart](https://docs.langchain.com/langsmith/prompt-engineering-quickstart)—Iterate on prompts - [Deployment quickstart](https://docs.langchain.com/langsmith/deployment-quickstart)—Deploy an agent - [Integrations](https://docs.langchain.com/langsmith/integrations)—Connect your framework or provider - [Create account & API key](https://docs.langchain.com/langsmith/create-account-api-key)—Account setup ## API reference For SDK class and method details, use the [LangChain API Reference](https://reference.langchain.com) site: - Browse: `https://reference.langchain.com/python/langsmith` - MCP server: `https://reference.langchain.com/mcp` ## Related skills - **langchain**—Build agents with prebuilt architecture and model integrations - **langgraph**—Orchestrate stateful, durable agent workflows - **deep-agents**—Batteries-included agent harness with planning and subagents