* 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.
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Co-authored-by: Kenny Van de Maele <kenny@kvandemaele.be>
Mazen Tamer Salah