Graph Memory

Bound the context. Keep the memory.
A native DeepSeek Harness memory plugin that keeps recent conversation turns, archives older history, and recalls exact source-backed knowledge when it matters.

中文 · dsh.so · 20-turn benchmark · Upgrade guide

The problem it solves

Graph Memory owns the model-visible historical surface without deleting DSH's event log. By default it keeps the newest five completed user turns, removes completed reasoning/tool traces from future requests, and recalls relevant older or cross-session source Q/A automatically.

The 1.6 turn-memory navigation upgrade

Writing one completed turn costs exactly one auxiliary LLM call. Community detection and PPR are local. There are no hard-coded node/edge counts, semantic direction gates, or JSON repair that turns invalid output into accepted data. Read the complete design, source map, and porting sequence →

Measured first

_{¹ The latest candidate includes 166 main-agent requests, 20 turn extractions, and 41 embedding requests; the historical baseline made 77 main requests. DSH commits and nondeterministic tool loops differ, so this is not a simultaneous strict A/B. First-request context is the direct takeover metric; the full bill remains visible.}

20/20 scenario turns passed · 20/20 structured extractions succeeded · 0 quarantined · 20 turn summaries · 92 SPO triples · 30 communities · 20 summary vectors. T11, T19, and T20 automatically recalled out-of-window memory with exact source question and final answer.

Read the Markdown benchmark, per-turn data, method, and limits →

Memory survives the context window

The graph is a navigation layer, not a replacement for evidence. TASK, SKILL, and EVENT nodes point back to the original user question and final visible answer; recalled context includes those exact source messages.

Install on DeepSeek Harness

Node.js 22.13+ · no DSH fork · until npm 1.6 is published, install the pinned GitHub release:

npx @deepseek-ai/dsh plugin --profile web add github:adoresever/graph-memory#v1.6.0-beta.16
npx @deepseek-ai/dsh --profile web --dump-config
npx @deepseek-ai/dsh web

The npm registry still serves the old 1.5.8; do not use it to validate DSH. Switch to npx @deepseek-ai/dsh plugin --profile web add graph-memory only after npm view graph-memory version reports 1.6.0-beta.16 or newer.

Confirm that graph-memory/dsh is active under Settings → Plugins. The default database is $DSH_HOME/graph-memory/graph-memory.db, normally ~/.dsh/graph-memory/graph-memory.db.

What ships

export GRAPH_MEMORY_EMBEDDING_API_KEY='replace-with-your-key'
export GRAPH_MEMORY_EMBEDDING_BASE_URL='https://dashscope.aliyuncs.com/compatible-mode/v1'
export GRAPH_MEMORY_EMBEDDING_MODEL='text-embedding-v4'
export GRAPH_MEMORY_EMBEDDING_DIMENSIONS='1024'
dsh web

openclaw plugins install graph-memory
openclaw plugins enable graph-memory
openclaw gateway restart

{
  "plugins": {
    "slots": { "contextEngine": "graph-memory" },
    "entries": { "graph-memory": { "enabled": true } }
  }
}

Verification and limits

Current beta 1.6.0-beta.16 passes 138/138 automated tests, both TypeScript builds, npm package verification, and a real 20-turn run against the latest DSH source.

• Structured extraction still depends on model contract compliance: the latest run succeeded 20/20 times; any future failure stays quarantined and never blocks the foreground conversation.
• Recall is bounded by configurable Top-K. Focused probes succeeded; one broad multi-topic query can require a larger Top-K or separate questions.
• The published run is an engineering workload, not a universal LoCoMo/LongMemEval score.
• The design, source-code map, and porting sequence for the summary + SPO navigation + exact-Q/A upgrade are documented in the Chinese upgrade guide.

Reproduce it from benchmarks/dsh-context-takeover/. Raw conversations, provider responses, local paths, and credentials are excluded.

Development

npm install
npm test
npm run build
npm run verify:package

MIT © 2026 adoresever · Asset and trademark notes