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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>
Lyra
A persistent, autonomous AI assistant. From-scratch rewrite of an earlier attempt.
The design thinking that survives the rewrite lives in docs/ — start with docs/ARCH_v0-6-1.md. The previous implementation is preserved on the archive branch.
Status
Pre-MVP. Building toward the smallest useful version: chat with persistent memory across sessions.
Setup
uv sync
cp .env.example .env
# fill in ANTHROPIC_API_KEY and point LOCAL_BASE_URL at your Ollama
Architecture
The long-term target is the cognitive split in docs/ARCH_v0-6-1.md — Inner Self as the seat of consciousness, Executive for hard reasoning, Cortex Chat for drafting, Persona for voice. The MVP implements only the chat + memory baseline. Cognitive layers come back one at a time.