Local Waifu 0.1.13

Added

• She knows the difference between what you said and what she
  guessed. Memories now split into two kinds: deductive (direct
  quotes from things you explicitly told her) and inductive
  (patterns she noticed over multiple turns but were never said).
  The digest in her system prompt labels inductive entries as
  (impression) so she hedges them ("I get the sense that…")
  instead of asserting them as fact ("you told me…"). Inspired by
  Honcho's deductive/inductive observation split.
• Memory provenance. Every memory she creates now records which
  chat message produced it (source_message_ids column). Future
  work can wire citations into her replies — "Last Tuesday you
  mentioned X" — instead of asserting context in a vacuum.
• Smarter knowledge extraction. Instead of running the KG
  extraction LLM every 5 turns regardless of what you said, she
  now checks if your latest message is semantically novel vs what
  she already remembers. If you're repeating a topic she's heard,
  she skips the extraction call (saves Ollama). If you bring up
  something new, she extracts immediately. Force-fallback every 20
  turns so slow patterns still get logged. Net result: fewer
  background LLM calls + faster reactions when the topic IS new.

Inspired by

• plastic-labs/honcho —
  their peer-representation work + deductive/inductive split + dream
  cycle. AGPL-3.0; we ported only patterns, no code. Honcho remains
  the right pick if you want managed cross-session user modeling.