Eval Results Query

When true, only include rows present in all requested evaluations.

When true, populate raw_data_row on each result row. Inline rows are returned as their dict value; dataset-referenced rows are returned as the ref string unless resolve_row_refs is also true.

When true (requires include_raw_data_rows=True), resolve dataset-row reference strings to actual row data via a table lookup. When false, dataset-row refs are returned as-is.

When true, include grouped row/trial data in rows and compute total_rows for the requested row-level view.

When true, include aggregated scorer/evaluation summary data in summary.

Optional intersection behavior for the summary section. When null, the value of require_intersection is used.

When true (default), fetch child calls (predict/score) of each predict_and_score call to populate predict_call_id, scorer_call_ids, and more precise latency/token data. When false, these fields are derived from the predict_and_score call itself (predict_call_id and scorer_call_ids will be null/empty).

When true, enrich the predict-and-score child calls with cost so the summary can report predict-only predict_total_cost. Opt-in: other callers skip the cost computation.

How to combine filters across evaluations: 'and' (Match All - row must match in ALL evals) or 'or' (Match Any - row must match in ANY eval). Defaults to 'or' (Match Any).

Optional row-level page size applied after grouping and intersection.

Optional row-level page offset applied after grouping and intersection.