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The real upgrade over the ChatGPT prose-recap workflow: structured data capture via tools Lyra drives during a live session, with stats computed from real data. - lyra/poker.py: domain pack (separate from core memory) — poker_sessions, poker_hands, persistent poker_players (villain file) + player_reads; functions for session lifecycle (start/buyin/end with net+hours), tolerant hand logging, villain upsert/reads, and session/running stats ($/hr, by stake/venue/game) - tools.py: 8 poker tools wired into the chat tool loop (start_session, add_buyin, log_hand, add_read, end_session, session_stats, running_stats, get_villain_file) — partial/terse input tolerated - import/: Brian's real .md session-log format (reference for the phase-2 recap) - tests: lifecycle/net math, partial hand logging, villain upsert, running stats, tool dispatch Verified live: a full talk-through session persisted as structured rows (session +240, AKs hand, seat-5 read) — she drove the tools from natural chat. 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.