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[framework, tasks] feat: retain runner scoring diagnostics in trajectories - #237
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Summary
Preserve runner scoring evidence in trajectory output so task failures can be diagnosed independently of the final training reward.
Changes
extra_fields.runner_reward_info.Validation
PYTHONPATH=.:verl uv run --no-project --python /usr/bin/python python -m pytest -q tests/uni_agent/tasks/test_swe_agent_error_on_cpu.py tests/uni_agent/tasks/test_swe_reward_on_cpu.py tests/uni_agent/framework/test_generate_sequences_on_cpu.py: 75 passed. Tests used the runtime interpreter with Uni-Agent and the pinned public verl gitlink explicitly selected.pre-commit run --all-files --show-diff-on-failure: passed.Internal validation and observed benefit
A historical internal GPU smoke evaluated four tasks across four model-version evaluations, producing 16 completed sessions. Persisted results contained runner reward, evaluator exit code and parsed test-status evidence for 16/16 sessions, and runner rewards matched the corresponding evaluation results in 16/16 cases. This made the task-side scoring evidence inspectable alongside the final result.
This is diagnostic coverage from an integrated implementation of the feature, not a before/after reward-quality comparison or an end-to-end validation of this split PR's exact head. No accuracy or throughput gain is claimed. The isolated PR regression tests are listed above.
Compatibility
The diagnostic fields are additive. Reward-worker scores, training masks, and SWE-bench resolution criteria retain their existing behavior. No migration is needed. This is a standalone observability improvement without a linked issue.
Checklist
pre-commit run --all-files --show-diff-on-failurepasses.