LangSmith Observability

LangSmith Observability provides full visibility into your LLM application: from individual traces to production-wide performance metrics.

LangSmith works with many frameworks and providers. Browse available integrations to connect your stack including OpenAI, Anthropic, CrewAI, Vercel AI SDK, Pydantic AI, and more.

Get started

Create an account

Create an API key

Go to your Settings page → API Keys → Create API Key. Copy the key and save it securely.

Choose your integration

LangSmith works with many frameworks and providers. Browse available integrations to connect your stack.

Once your account and API key are ready, set up tracing:

Set up tracing

Add tracing to your app in minutes with environment variables, framework integrations, or the SDK.

Trace a RAG application

Follow a step-by-step tutorial to instrument a retrieval-augmented generation app from start to finish.

Investigate and monitor

View traces

Filter, export, share, and compare traces via the UI or API.

Monitor performance

Build dashboards and set alerts to track quality and catch issues early.

Configure automations

Automate workflows with rules, webhooks, and online evaluations.

Collect feedback

Annotate outputs and gather user feedback using queues or inline annotation.

Find and fix failures with Engine

Automatically detect recurring issues in your traces, diagnose their root cause, and resolve them with LangSmith Engine.

For terminology and core concepts, refer to Observability concepts. For trace pricing, retention, and limits, see Usage and billing.

To set up a LangSmith instance, visit the Platform setup section to choose between cloud, hybrid, or self-hosted. All options include observability, evaluation, prompt engineering, and deployment.