hybrid-memory

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Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.

AI & Automation 69 stars 7 forks Updated 3 months ago MIT

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# Hybrid Memory System We use two memory systems integrated into a single view: 1. **QMD (Vector Store):** For retrieving documents, specs, and full content. 2. **Graphiti (Knowledge Graph):** For retrieving facts, timelines, and relationships. ## Primary Tool For 95% of memory queries, use the hybrid search script. It queries both systems in parallel. ```bash ~/clawd/scripts/memory-hybrid-search.sh "your query" ``` Optional flags: - `[group_id]` — Specify agent group (default: `clawdbot-main`) - `--json` — Output JSON for programmatic use ## Specific Tools (Advanced) Only use these if the hybrid script fails or you need granular control. ### Graphiti Only (Temporal/Facts) Search for specific temporal facts: ```bash ~/clawd/scripts/graphiti-search.sh "your question" clawdbot-main 10 ``` Log new facts (IMPORTANT): ```bash ~/clawd/scripts/graphiti-log.sh clawdbot-main user "Name" "Fact to remember" ``` ### QMD Only (Deep Document Search) If you need more results or specific file filtering: ```bash qmd search "query" -n 10 ``` ## Recall Pattern 1. **User asks question** ("What was the plan for the project?") 2. **Run Hybrid Search** (`~/clawd/scripts/memory-hybrid-search.sh "plan for the project"`) 3. **Synthesize Answer** from both the temporal facts and document snippets found. 4. **If needed:** Use `read` to get the full content of a file found in the QMD results. ## When to Use Which | Question Type | Use | |---------------|-----| | "What's in GOALS.md?" ...

Details

Author
clawdbrunner
Repository
clawdbrunner/openclaw-graphiti-memory
Created
3 months ago
Last Updated
3 months ago
Language
Shell
License
MIT

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