Principle:Openai Evals Batch Eval Execution
| Knowledge Sources | |
|---|---|
| Domains | Evaluation, Orchestration |
| Last Updated | 2026-02-14 10:00 GMT |
Overview
A batch orchestration pattern that sequentially executes multiple evaluations from an eval set with progress tracking and resume support.
Description
Batch Eval Execution runs a series of evaluations by resolving an eval set to its constituent eval names, then spawning oaieval as a subprocess for each eval in sequence. It supports resuming interrupted runs via a progress file, pass-through of additional CLI arguments, and configurable error handling (stop on first failure vs continue). Each subprocess invocation is a complete oaieval execution with its own log file.
Usage
Use batch execution when running a comprehensive evaluation suite across multiple tasks. This is the primary use case for the oaievalset CLI.
Theoretical Basis
The batch execution follows a sequential subprocess pattern:
- Resolve eval set name to list of eval names
- Build command list: oaieval <model> <eval_name> [pass-through args] for each eval
- Load progress file to determine which evals have already completed
- Filter out completed evals
- Execute remaining evals sequentially via subprocess.run
- Save progress after each successful completion