A long-standing ML platform that now covers LLM apps too: tracing, evaluation, a prompt registry and a model gateway. Plugs into most frameworks.
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Evals & observabilitylangfuse
langfuse
An open platform that shows every model call: traces, cost, quality scores and prompt versions. Use it in the cloud or self-host it.
Who it is for
For teams who want to understand what their LLM app does in production.
How to start
- Create a project in Langfuse Cloud or self-host:
git clone --depth=1 https://github.com/langfuse/langfuse.git, thendocker compose up. - Install the SDK:
pip install langfuse openaiand setLANGFUSE_SECRET_KEYandLANGFUSE_PUBLIC_KEYin.env. - Make your first model call and open the trace in the UI.
Steps are taken from the README. Check the current version in the repository before running them.
Stars over the last 30 days
+1,152Sep 7 — Oct 5
Author's description
🪢 Open source agent evals & observability: Trace, evaluate, and improve LLM applications with one open platform.
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