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Deep Memory

by @halfmoon82

One-click clone of a production-grade semantic memory system: HOT/WARM/COLD tiered storage + Qdrant vector DB + Neo4j graph DB + qwen3-embedding. Enables cro...

Versionv1.0.0
Installs3
πŸ’‘ Examples

Setup (first time)

python3 ~/.openclaw/workspace/skills/deep-memory/scripts/setup.py

Write a memory

from deep_memory import MemorySystem
mem = MemorySystem()
mem.store("user_sir", "Sir prefers direct communication, no pleasantries", tags=["preference", "communication"])

Search memories

results = mem.search("how does Sir like to communicate?", top_k=5)
for r in results:
    print(r['content'], r['score'])

Joint query (vector + graph)

results = mem.joint_query("investment strategy", entity="Sir", top_k=3)

βš™οΈ Configuration

  • Docker Desktop (running)
  • Ollama installed (brew install ollama on macOS)
  • View on ClawHub
    TERMINAL
    clawhub install deep-memory

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