Dual Retrieval

Combines M-Flow graph topology and QMD BM25+vector retrieval to merge and rank results for precise multi-hop and semantic search.

Install

openclaw skills install @sora-mury/dual-retrieval

Dual Retrieval Skill - Phase 4

描述

双重检索:M-Flow(图拓扑检索)+ QMD(BM25+向量检索)优势互补。

M-Flow vs QMD 对比

特性M-FlowQMD
检索方式图拓扑 + Bundle SearchBM25 + 向量 + rerank
适合场景精确问答、多跳推理关键词搜索、语义相似
记忆结构四层 Cone Graph多 Collection
优势时间推理、关联推理灵活、已配置

工作流程

text
Query → 
  ├── M-Flow.search() → Episode + Facet + Entity
  └── QMD search → 文件 + 片段
      ↓
结果合并 → 去重 → 排序 → 返回

文件结构

text
dual-retrieval/
├── SKILL.md
├── scripts/
│   ├── __init__.py      # DualRetrievalPipeline
│   └── test_dual.py     # 测试

依赖

  • m-flow-memory skill (MFlowMemory)
  • QMD (qmd tools)