Metrics
Langfuse metrics derive actionable insights from observability and evaluation traces.
Metrics can be sliced and diced via the customizable dashboards and the metrics API.
Features
Metrics & Dimensions
Metrics:
- Quality is measured through user feedback, model-based scoring, human-in-the-loop scored samples or custom scores via SDKs/API (see scores). Quality is assessed over time as well as across prompt versions, LLMs and users.
- Cost and Latency are accurately measured and broken down by user, session, geography, feature, model and prompt version.
- Volume based on the ingested traces and tokens used.
Dimensions:
- Trace name: differentiate between different use cases, features, etc. by adding a
namefield to your traces. - User: track usage and cost by user. Just add a
userIdto your traces (docs). - Tags: filter different use cases, features, etc. by adding tags to your traces.
- Release and version numbers: track how changes to the LLM application affected your metrics.
For an exact definition, please refer to the metrics API docs.