dawn-memory-arch

Dawn Memory Architecture v7.1

One-liner

Three-layer storage + four mechanisms + P0-P3 truth hierarchy — central index as entry, layered files for details, vector DB for semantic search, four rules for quality, P0-P3 hierarchy for data accuracy.

Core Design Principles

1. Text > Brain — Write it down, don't bet on context memory
2. Simple > Verbose — One sentence over two
3. Data > Pride — Admit when wrong, API is the only truth
4. WAL > Impulse — Write first, reply later
5. Look up, don't memorize — If it can be inferred from code/API/real-time data, don't write it into memory

Directory Structure

workspace/
├── MEMORY.md               # Central index (hard limit: 200 lines / 25KB)
├── memory/
│   ├── core/               # Structured facts (JSON files)
│   │   ├── identity.json
│   │   ├── lessons.json
│   │   ├── preferences.json
│   │   ├── profile.json
│   │   └── strategies.json
│   ├── sessions/           # Session logs (history, not used in decisions)
│   ├── daily/              # Daily logs
│   ├── learnings/          # Learning notes + error logs
│   └── archive/            # Packaged archives
├── scripts/
│   ├── memory/             # Maintenance scripts
│   └── analysis/           # Analysis scripts
└── state.db               # SQLite single source of truth (6 tables)

Three-layer Storage

Layer 1: MEMORY.md (Central Index)

• Navigation entry for all memories
• Hard limit: 200 lines / 25KB
• Must read on every startup
• Contains: core info, status summary, system capabilities, key conclusions, promoted memories

Layer 2: memory/core/ (Structured Facts)

• One JSON file per topic, version managed
• 5 files: identity.json, lessons.json, preferences.json, profile.json, strategies.json

Layer 3: Local Vector DB (Semantic Search)

• LanceDB + all-MiniLM-L6-v2 (384 dimensions)
• Zero external API dependency, fully offline
• Local port @ localhost:19999
• Cross-session semantic search

Four Mechanisms

1. Engramory Curation Discipline

• Deduplicate before write — If similar content exists, update instead of add
• Update over insert — Prefer updating existing entries
• Delete on error — Don't mark as deprecated, just delete
• Hard limit — MEMORY.md max 200 lines

2. WAL Protocol (Write-Ahead Logging)

Trigger on detecting corrections, decisions, preference changes, or value changes. Write to session-state.json before replying. Ensures no data loss on crash.

3. Working Buffer (Context Fuse)

When context usage > 60%, auto-trigger: write summary to working-buffer.md, record key decisions and context snapshots.

4. Short-to-Long Term Auto Promotion

High-value memories (score > 0.8, appears 3+ times, affects trading decisions, user explicitly asked to remember) auto-promote from daily logs to MEMORY.md.

Truth Source Hierarchy (P0-P3)

Core rule: Real-time decisions only use P0 (API real positions + hardcoded rules). Historical memory only for post-mortem.

Maintenance Scripts

Version History

Deployment Checklist (10 Steps)

1. Create memory/ directory and subdirectories
2. Create MEMORY.md (core info + system capabilities + file structure)
3. Create session-state.json (WAL protocol cache)
4. Create HEARTBEAT.md (periodic task checklist)
5. Deploy local vector DB (LanceDB + all-MiniLM-L6-v2)
6. Register Engramory curation discipline in boot manual
7. Write memory principles in soul file
8. Configure WAL protocol triggers
9. Configure Working Buffer threshold (60% context trigger)
10. Configure learnings/ directory and auto-promotion rules

Author: Dawn (chen6896qqwee) License: MIT