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Laminar

Open source

Open-source observability platform for AI agents with OpenTelemetry-based tracing, evaluations, dashboards, and plain-English alerts on agent behavior.

laminar.sh
Laminar homepage screenshot
GitHub stars
3.3k
Last commit
today
Repository age
2 years
Version
v0.2.5
Licence
Apache-2.0
Self-hosted
Yes

About Laminar

Laminar is an open-source observability platform built for AI agents. It records what agents do during each run so that teams can debug failures, track behavior, and measure quality. The project is released under the Apache-2.0 license and the backend is written largely in Rust, with a TypeScript front end.

Tracing is based on OpenTelemetry, and a single line of SDK setup can automatically trace libraries such as the Vercel AI SDK, Browser Use, Stagehand, LangChain, OpenAI, Anthropic, and Gemini. Signals let you describe a behavior, such as an agent getting stuck in a loop, in plain English and be notified in Slack when it occurs. Evals run through an SDK and CLI locally or in CI, with a UI for comparing results, and SQL queries and dashboards cover traces, metrics, and events.

Coding agents can reach the data through MCP and CLI access to investigate issues themselves. Laminar can be self-hosted locally with Docker Compose, or used as the managed platform at laminar.sh. It suits teams building production agents who need tracing, evaluation datasets, and annotation in one place.

Key features

  • OpenTelemetry-native tracing SDK
  • Plain-English signals with Slack alerts
  • Evals via SDK and CLI with comparison UI
  • SQL queries over traces, spans, and metrics
  • Custom dashboards for traces and events
  • MCP and CLI access for coding agents
  • Datasets and data annotation tools

Good fit for

  • →Debugging failing AI agent runs
  • →Running agent evaluations in CI
Built with
TypeScript
Rust
Tags
observability
ai-agents
llm-tracing
evals
opentelemetry
llmops
self-hosted
monitoring

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