serversdown
f3037b7879
Import the parser's {title, messages} JSON into Lyra's memory so past
conversations seed recall (and, later, the era-rollup tier).
- lyra/ingest.py: one conversation -> one session, text messages -> exchanges;
skips non-text (image asset) messages and non user/assistant roles; embeddings
batched; idempotent by filename-derived session id; `lyra-import <dir>` CLI
- memory.add_exchanges_bulk: batched insert of pre-embedded rows
Format has no timestamps yet, so imports are stamped at import time; a future
dated export will let era memory group by real calendar time.
Verified on the 68-file lyra dev set: 7519 exchanges, idempotent re-run, recall
returns relevant history.
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.