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Hybrid Memory

结合OpenClaw内置向量记忆与Graphiti时序知识图谱的混合记忆策略。适用于回忆过往上下文、回答时序问题(如“X何时发生?”)或搜索记忆文件。提供了何时使用memory_search与Graphiti的决策框架。

person作者: clawdbrunnerhubclawhub

Hybrid Memory System

Two memory systems, each with different strengths. Use both.

When to Use Which

| Question Type | Tool | Example | |--------------|------|---------| | Document content | memory_search | "What's in GOALS.md?" | | Curated notes | memory_search | "What are our project guidelines?" | | Temporal facts | Graphiti | "When did we set up Slack?" | | Conversations | Graphiti | "What did the user say last Tuesday?" | | Entity tracking | Graphiti | "What projects involve Alice?" |

Quick Reference

memory_search (Built-in)

Semantic search over markdown files (MEMORY.md, memory/**/*.md).

memory_search query="your question"

Then use memory_get to read specific lines if needed.

Graphiti (Temporal)

Search for facts with time awareness:

graphiti-search.sh "your question" GROUP_ID 10

Log important facts:

graphiti-log.sh GROUP_ID user "Name" "Fact to remember"

Common group IDs:

  • main-agent — Primary agent
  • user-personal — User's personal context

Recall Pattern

When answering questions about past context:

  1. Temporal questions → Check Graphiti first
  2. Document questions → Use memory_search
  3. Uncertain → Try both, combine results
  4. Low confidence → Say you checked but aren't sure

AGENTS.md Template

Add to your AGENTS.md:

### Memory Recall (Hybrid)

**Temporal questions** ("when?", "what changed?", "last Tuesday"):
```bash
graphiti-search.sh "query" main-agent 10

Document questions ("what's in X?", "find notes about Y"):

memory_search query="your query"

When answering past context: check Graphiti for temporal, memory_search for docs.


## Setup

Full setup guide: https://github.com/clawdbrunner/openclaw-graphiti-memory

**Part 1: OpenClaw Memory** — Configure embedding provider (Gemini recommended)
**Part 2: Graphiti** — Deploy Docker stack, install sync daemons