Evaluation & observability
langfuse/langfuse
Langfuse is an open-source platform for tracing LLM applications, managing prompts and running evaluations. It creates an operational record of model calls, costs, latency and outcomes across complex applications.
THE PRACTICAL EXPLANATION
Langfuse is an open-source platform for tracing LLM applications, managing prompts and running evaluations. It creates an operational record of model calls, costs, latency and outcomes across complex applications.
WHERE TO USE IT
Use it when a team needs shared visibility into prompts and agent traces, controlled prompt releases and evidence about production performance.
WHO MAY USE IT
AI product and engineering teams operating model-powered services across development and production environments.
HOW TO USE IT
Instrument one application path and redact sensitive fields before broad capture. Add prompt versions and meaningful user or evaluator feedback, then use traces to find recurring failure patterns. Set retention and role-based access deliberately.
GETTING THE BEST RESULTS
WHY IT MAY BE USEFUL
Open-source tracing, prompt management and evaluation for LLM applications.
Best considered for: Teams that need an observable history of prompts, costs and outcomes.
READ BEFORE YOU ADOPT IT
Telemetry may contain sensitive inputs; configure retention and access carefully.
Confirm the current licence, maintenance status, dependency risk, data path, model access, tool permissions and human approval points at the source. A public repository is inspectable raw material—not proof that a system is secure, supported or suitable for your production environment.