feat: clean up batch JSONL files after processing (spec 550)#684
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Batch JSONL files (input payloads and raw results) were written to disk
during provider upload/retrieval but never cleaned up, accumulating
across runs.
- Delete input JSONL immediately after successful provider upload
(batch_base.py submit_batch)
- Delete result JSONL immediately after parsing results back into
memory (batch_base.py retrieve_results)
- Delete remaining .jsonl/.json artifacts in target/{action}/batch/
during --fresh cleanup (coordinator.py _clear_for_fresh_run)
The CLI `batch retrieve` command's output file is NOT deleted — that's
the user-requested artifact from the command.
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Summary
.jsonl/.jsonbatch artifacts intarget/{action}/batch/during--freshcleanupbatch retrieveoutput file is NOT deleted — that's the user-requested artifactWhy
Batch JSONL files accumulate across runs. A 50-action workflow running daily produces ~100 files/run. After 30 days: ~3000 orphaned files. No code reads these files after the initial upload/retrieval call completes.
Files changed (2 production, 2 test)
llm/providers/batch_base.py_submit_to_provider_api, delete result JSONL after_read_jsonl_fileworkflow/coordinator.py_clear_for_fresh_runglobs and deletes.jsonl/.jsonintarget/{action}/batch/tests/unit/llm/test_batch_jsonl_cleanup.pytests/unit/workflow/test_fresh_run_cleanup.pyVerification
pytest→ 7488 passed, 2 skipped (+9 new tests)ruff check→ all checks passedruff format --check→ 954 files already formatted