LangSmith
LangChain's observability and evaluation platform — trace, debug, and evaluate LLM applications with deep LangChain ecosystem integration.
Why LangSmith?
Your app is built on LangChain or LangGraph — integration is seamless
You need prompt management and dataset-driven evaluations
Team wants a managed cloud with minimal setup
Signal Breakdown
What drives the Trust Score
Download Trend
Last 12 months
Tradeoffs & Caveats
Know before you commitYou want a fully open-source or self-hostable solution — use Langfuse
Not using LangChain — the value proposition is weaker
Pricing
Free tier & paid plans
Free tier: 5k traces/mo
Plus: $39/mo, Team plans available
Alternative Tools
Other options worth considering
Open-source LLM observability platform for tracing, evaluating, and debugging AI applications — self-host or use the cloud.
Lightweight LLM observability via a proxy URL swap — get cost tracking, request logging, and caching with a one-line integration.
Often Used Together
Complementary tools that pair well with LangSmith
Learning Resources
Docs, videos, tutorials, and courses
Get Started
Repository and installation options
View on GitHub
github.com/langchain-ai/langsmith-sdk
npm install langsmithpip install langsmithQuick Start
Copy and adapt to get going fast
import { Client } from 'langsmith';
const client = new Client({ apiKey: process.env.LANGSMITH_API_KEY });
// Auto-traces when LANGCHAIN_TRACING_V2=true is set
// Or manually:
const run = await client.createRun({
name: 'my-llm-call',
run_type: 'llm',
inputs: { prompt: 'Hello' },
});Community Notes
Real experiences from developers who've used this tool