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* fix(memory): only delete memories the model explicitly drops in tidy The AI memory-tidy path computed deletions as the complement of the model's `keep` list (`if mid not in keep_ids: continue`). When the model returned a valid response that simply omitted some existing ids — a common LLM lapse — every omitted memory was silently deleted, even though it was neither a duplicate nor listed in `drop`. Honor the explicit `drop` set instead: delete only ids the model dropped (minus any it saw only truncated), and preserve everything else, still applying cleaned text/category from `keep`. Adds tests/test_consolidate_memory_explicit_drops.py: a memory the model omits from both keep and drop survives; an explicitly dropped one is removed. * refactor(memory): remove now-dead keep_ids from tidy After deletion switched to drop_ids and text/category rewrites to cleaned_by_id, keep_ids was written but never read. Remove the init, the .add(mid) in the keep loop, and the truncated .update() (its truncated-protection is already covered by `drop_ids -= truncated_ids`). Pure deletion, no behavior change; tests stay green. Addresses review feedback on #3455. --------- Co-authored-by: Kenny Van de Maele <kenny@kvandemaele.be>
1.9 KiB
1.9 KiB