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Give Lyra a model of *herself* (vs the profile/narrative which model Brian): - persona: a real origin/identity — she's an AI and knows it (Bender/C-3PO style), with the Cortex/NeoMem lineage as her actual past, so "how were you made" stops falling through to generic-assistant deflection. - memory: self_state table (JSON blob) + get/set_self_state. - lyra/self_state.py: evolving first-person inner state (mood, valence, energy, confidence, curiosity, self_narrative, relationship, reflections). render_for_ context injects it; reflect() updates it from recent activity. `lyra-reflect`. - chat.build_messages injects her interiority right after the persona — she speaks from a continuous self, not a reset. The state -> behavior -> reflection -> updated state loop is the substrate for the emergence experiment. Verified: reflection shifted mood curious->reflective and produced genuine first-person self-observations. 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.