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* feat(memory): add memory consolidation to synthesize fragmented facts When a fact category accumulates many individual entries, the LLM reviews them during the normal memory-update call (same invocation, no extra API cost) and decides whether groups of related facts can be synthesized into a single richer fact. This completes the memory lifecycle: extraction → guaranteed injection → staleness review → consolidation. - Select fragmented categories by min-facts threshold, surface the most fragmented groups first; prompt-layer caps aligned with apply-layer guardrails so the LLM never sees groups it cannot act on - Cap consolidated confidence at source maximum to prevent inflation; reject results below fact_confidence_threshold - Double-consume protection prevents a fact from being merged into multiple consolidation targets - Feature-gated at both prompt and apply time with per-cycle safety caps - Add 26 tests covering candidate selection, normalization, apply guardrails, and prompt integration * fix(memory): address consolidation correctness issues from PR review Six fixes based on maintainer review of #3996: 1. Deduplicate sourceIds in normalization — ["f1","f1"] previously bypassed the ≥2-distinct-sources check; dict.fromkeys collapses it to ["f1"] which is correctly rejected. 2. Run consolidation after max_facts trim — previously, sources were deleted then the merged fact could be evicted by the trim, leaving no record of either. Moving consolidation last ensures source facts exist in the post-trim index before removal. 3. Fix count= attribute in consolidation prompt — advertised the full category size but listed only max_sources IDs; now uses min(len(group), max_sources) to match what the LLM can act on. 4. Exempt staleness_protected_categories from consolidation candidates — mirrors the existing staleness-review contract so correction facts are never surfaced for merging. 5. Strip and default category in consolidation normalization — " " or " preference " are now normalised, matching _normalize_memory_update_fact. 6. Propagate sourceError from source facts into consolidated fact — correction context is no longer silently lost on merge. * fix(memory): add apply-time guardrails and tests for consolidation P1: mirror the staleness-pass defense-in-depth pattern — build allowed_source_ids from _select_consolidation_candidates at apply time so a protected-category or below-threshold fact proposed by the LLM is rejected regardless of model behavior. P2a: test that LLM-returned confidence is capped at max source confidence and that a capped result below fact_confidence_threshold is rejected. P2b: test that factsToConsolidate with consolidation_enabled=False is a no-op at apply time (35 tests, all pass). * fix(memory): address three correctness issues from second review round 1. Default consolidation_enabled=False — consolidation is lossy (source content is permanently replaced, only consolidatedFrom IDs preserved); new lossy features default to off. config.example.yaml updated to match. 2. Unify confidence coercion between prompt and apply — _build_consolidation_section now calls _coerce_source_confidence(fact) instead of an inline 0.0-default coercion, so a null-confidence fact renders with 0.50 in the LLM prompt and is capped at 0.50 at apply time (same value, same function). 3. Preserve staleness clock on merge — consolidated fact now carries the newest source's createdAt (not now) so aged information does not gain a fresh staleness-review window just by being consolidated; consolidatedAt is added as an explicit audit field. Three regression tests added (default=false, null-confidence consistency, createdAt policy); all guardrail tests now set consolidation_enabled=True explicitly so they test the guardrail, not the feature flag. 38 tests pass. * fix(memory): harden createdAt comparison and confidence handling 1. createdAt max via _parse_fact_datetime — replaces string max() which crashes on non-string createdAt (numeric unix timestamps) and sorts Z/+00:00 mixed formats incorrectly. Mirrors how staleness computes age. 2. Remove dead min(..., 1.0) — _coerce_source_confidence already clamps each source confidence to [0, 1], so max(source_confidences) ≤ 1.0 by contract; the outer min could never bind. 3. Clamp raw_llm_conf to [0, 1] before applying the source cap — out-of- range values like 1.5 are safe today (pinned by the cap) but defensively clamped first so the invariant holds even if the cap is ever loosened. 4. Doc: expand the apply-time guardrails comment to call out the protected- category exclusion via allowed_source_ids — this is the central safety property ("explicit user feedback is never silently merged away"). 5. Test: add test_confidence_fallback_to_max_source_when_llm_omits_field covering the else-branch (LLM omits confidence → uses max_source_conf). 6. Fix lint: reorder imports in test file (stdlib before third-party). 39 tests, all pass. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>