2.6 KiB
2.6 KiB
Lyra Core — Project Summary
v0.4 (2025-10-03)
🧠 High-Level Architecture
-
Lyra Core (v0.3.1) — Orchestration layer.
- Accepts chat requests (
/v1/chat/completions). - Routes through Cortex for subconscious annotation.
- Stores everything in Mem0 (no discard).
- Fetches persona + relevant memories.
- Injects context back into LLM.
- Accepts chat requests (
-
Cortex (v0.3.0) — Subconscious annotator.
- Runs locally via
llama.cpp(Phi-3.5-mini Q4_K_M). - Strict JSON schema:
{ "sentiment": "positive" | "neutral" | "negative", "novelty": 0.0–1.0, "tags": ["keyword", "keyword"], "notes": "short string" } - Normalizes keys (lowercase).
- Strips Markdown fences before parsing.
- Configurable via
.env(CORTEX_ENABLED=true|false). - Currently generates annotations, but not yet persisted into Mem0 payloads (stored as empty
{cortex:{}}).
- Runs locally via
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Mem0 (v0.4.0) — Persistent memory layer.
- Handles embeddings, graph storage, and retrieval.
- Dual embedder support:
- OpenAI Cloud (
text-embedding-3-small, 1536-dim). - HuggingFace TEI (gte-Qwen2-1.5B-instruct, 1536-dim, hosted on 3090).
- OpenAI Cloud (
- Environment toggle for provider (
.env.openaivs.env.3090). - Memory persistence in Postgres (
payloadJSON). - CSV export pipeline confirmed (id, user_id, data, created_at).
-
Persona Sidecar
- Provides personality, style, and protocol instructions.
- Injected at runtime into Core prompt building.
🚀 Recent Changes
-
Mem0
- Added HuggingFace TEI integration (local 3090 embedder).
- Enabled dual-mode environment switch (OpenAI cloud ↔ local TEI).
- Fixed
.envline ending mismatch (CRLF vs LF). - Added memory dump/export commands for Postgres.
-
Core/Relay
- No major changes since v0.3.1 (still routing input → Cortex → Mem0).
-
Cortex
- Still outputs annotations, but not yet persisted into Mem0 payloads.
📈 Versioning
- Lyra Core → v0.3.1
- Cortex → v0.3.0
- Mem0 → v0.4.0
📋 Next Steps
- Wire Cortex annotations into Mem0 payloads (
cortexobject). - Add “export all memories” script to standard workflow.
- Consider async embedding for faster
mem.add. - Build visual diagram of data flow (Core ↔ Cortex ↔ Mem0 ↔ Persona).
- Explore larger LLMs for Cortex (Qwen2-7B, etc.) for richer subconscious annotation.