Laminar Evaluations API
The lower-level LaminarClient.evals surface for wiring evaluations into an existing pipeline: create an evaluation, pre-register each datapoint so a row is visible in the UI before the executor runs, then update that datapoint with a trace id, executor output, and scores. Because update can be called any time after create, the executor and the scorer can run in different processes, which supports async LLM-judge scoring and pure backfills of scored rows.