Brian can rate Lyra's outputs as he uses her; each rating is stored as a
(context, content, rating) triple — the shape a future fine-tune / preference
dataset wants, collected passively during real use.
- memory: ratings table + add_rating (upsert: one row per item, re-rating
replaces), list_ratings, rating_counts
- server: POST /rate, GET /ratings/counts, GET /ratings/export (JSONL download)
- chat UI: subtle 👍/👎 on each assistant reply, captures the prompting message
as context
- journal/reflection UI: 👍/👎 on each thought
- tests: counts + upsert-replace behavior
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
