Get Quality Timeseries

Return bucketed LLM-as-Judge quality metrics for a model.

Each bucket reports the average llmaj_score, the fraction of judged inferences with llmaj_verdict = 'pass', and the count of scored inferences. model_id is resolved against training_jobs to determine whether to filter inferences by project_id, training_job_id, or model_id (raw base traffic).

Args: model_id: Training-job UUID or base catalog id. interval: date_trunc bucket size. since: Inclusive start of the window. until: Exclusive end of the window. auth: Authentication result carrying the user id used to scope every aggregate.

Returns: QualityTimeSeriesResponse with descending buckets. An empty series is returned when no inference rows match.

model_idstring required

Training-job UUID (task model) or base catalog id (e.g. 'meta-llama/Llama-3-8B').

interval'day' | 'week'

Bucket size used for date_trunc.

sincestring date-time nullable

Inclusive start of the window (UTC). Defaults to 90 days ago.

untilstring date-time nullable

Exclusive end of the window (UTC). Defaults to now.

Response

Successful Response

model_idstring required

Echo of the requested model id.

interval'day' | 'week' required

date_trunc bucket size used for the aggregation.

sincestring date-time required

Inclusive start of the window (UTC).

untilstring date-time required

Exclusive end of the window (UTC).

v2

Get Quality Timeseries

Query parameters

Response