功能: 通用多Agent记忆系统,支持自动捕获、RRF检索、知识图谱、矛盾检测、Token追踪
适用场景:
核心特性:
# 使用ClawHub安装
clawhub install multi-agent-memory
# 或手动安装
npx clawhub@latest install multi-agent-memory
# 运行配置向导
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/setup.py
# 运行集成测试
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/memory-system.py
# 查看可视化面板
open ~/.openclaw/workspace/skills/multi-agent-memory/public/dashboard.html
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/hook-capture.py
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/rrf-search.py
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/graph-builder.py
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/conflict-detector.py
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/token-tracker.py
# 注册Agent
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/agent-manager.py register agent-001
# 注销Agent
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/agent-manager.py unregister agent-001
# 列出Agent
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/agent-manager.py list
# 健康检查
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/agent-manager.py health
# 自动扩展
python3 ~/.openclaw/workspace/skills/multi-agent-memory/scripts/agent-manager.py scale
---
## 配置说明
### 默认配置
memory:
vector_model: "nomic-embed-text-v1.5"
vector_dim: 768
search_mode: "rrf" # rrf / vector / bm25
hooks:
enabled: true
count: 8
rrf:
k: 60
weights:
bm25: 0.2
vector: 0.5
graph: 0.3
### 环境变量
MEMORY_WORKSPACE=/path/to/workspace
MEMORY_VECTOR_MODEL=nomic-embed-text-v1.5
MEMORY_LLM_API_KEY=your-api-key
---
## 示例项目
### 单Agent示例
cd examples/single-agent
python3 run.py
### 多Agent示例
cd examples/multi-agent
python3 run.py
---
## 测试
python3 -m pytest tests/
python3 -m pytest tests/test-hooks.py
---
## 文档
- [快速开始](docs/quick-start.md)
- [配置指南](docs/configuration.md)
- [API参考](docs/api-reference.md)
- [示例项目](docs/examples.md)
- [常见问题](docs/faq.md)
---
## 贡献
欢迎贡献!请参阅 [CONTRIBUTING.md](CONTRIBUTING.md) 了解指南。
---
## 许可证
MIT License
---
## 支持
- GitHub Issues: https://github.com/light-office/multi-agent-memory/issues
- Discord: https://discord.gg/light-office
- 邮件: professor@light-office.local
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