Langfuse
Definition
Langfuse records workflows of language model applications and supports their technical evaluation.
Langfuse is an open-source platform for observability of language model applications. It captures traces with inputs, outputs, runtimes, token usage, and tool calls.
Simply explained
Like a logbook for model calls. It makes workflows traceable but does not automatically assess whether an answer was factually correct.
Why it matters in practice
Before logging, purpose, allowed data fields, retention, and access rights should be defined.
Example from business
Possible example: A team investigates in Langfuse at which step an internal assistant takes particularly long.
Limits and pitfalls
- Technical traces are not a complete quality proof. Personal or confidential content must not be logged without review.
Origin & history
The Langfuse documentation describes traces for inputs, outputs, tokens, runtimes, calls, and tool calls.
Use in mid-sized companies
- Possible application areas include error analysis and cost monitoring for internal language model applications with data-minimal logging.
Frequently asked questions
Does Langfuse automatically evaluate answers as correct?
No, the platform provides observational data for further evaluation.
Must all inputs be stored?
No, scope and protection of log data must be defined separately.
Sources
- Observability · Langfuse (o. J.): Observability
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