langsmith

name	langsmith
description	Trace, evaluate, and deploy AI agents and LLM applications with LangSmith. Use when adding observability, running evaluations, engineering prompts, or deploying agents to production.
license	MIT
compatibility	Framework-agnostic. Works with LangChain, LangGraph, Deep Agents, OpenAI Agents SDK, CrewAI, Pydantic AI, and more.
metadata	{"author":"langchain-ai","version":"1.0"}

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.

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, LangGraph, or Deep Agents instead
• LangSmith is the platform layer that complements these frameworks

Quick setup

Set two environment variables to enable tracing from any supported framework:

export LANGSMITH_TRACING=true
export LANGSMITH_API_KEY="your-api-key"  # from smith.langchain.com/settings

Install the SDK

# Python
pip install langsmith

# JavaScript/TypeScript
npm install langsmith

Verify tracing

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—Get started with LangSmith
• Observability quickstart—Add tracing in minutes
• Evaluation quickstart—Run your first evaluation
• Prompt engineering quickstart—Iterate on prompts
• Deployment quickstart—Deploy an agent
• Integrations—Connect your framework or provider
• Create account & API key—Account setup

API reference

For SDK class and method details, use the LangChain API Reference 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