Get Quality Timeseries
Changed onReturn 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.
Raises: HTTPException: 400 when the resolved window is empty; 503 when the bucketed read fails, with the cause logged server-side rather than returned to the caller.
Request
- Base URLhttps://api.pioneer.ai (the document declares no server; this is the origin it was published from)
- Auth
- API key in header X-API-Key
- or HTTP bearer
- TypeScriptA function with typed inputs. Its response is checked against the schema.
Query parameters
Training-job UUID (task model) or base catalog id (e.g. 'meta-llama/Llama-3-8B').
Bucket size used for date_trunc.
Inclusive start of the window (UTC). Defaults to 90 days ago.
Exclusive end of the window (UTC). Defaults to now.
Response
Successful Response
Changes
- info
endpoint added
- info