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feat: long-term chat history — time-based window + multi-vector FAISS db5
- db_5_process_session: time-based short-term window (10 day min / 21 day max, 40 msg floor / 200 msg ceiling); sliding-window chunker (8 msgs, 2 overlap); per-chunk LLM summary (Tier C); two FAISS docs per chunk (raw + summary) with rich metadata (chunk_id, timestamps, character, turn_range) - classify_memory_reference: Tier C classifier — detects "do you remember"-style queries; extracts time_hint and character_hint for metadata filtering - util_retrieve: db5 excluded by default; searched only on recalls_past=True; chunk_id deduplication; soft metadata boost for time/character hints; force_db5 flag for internal pivot/nudge calls - app_nn: classify_memory_reference wired before RAG retrieval; pivot calls use force_db5=True to bypass the memory-reference gate Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>1775907
