Graph Memory

September 4, 2026 · View on GitHub

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 · Architecture

The problem it solves

Long agent history becomes graph navigation plus a compact recent-turn context

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.

Measured first

DSH 20-turn first-request context comparison

Real 20-turn GLM-5.2 run	Native DSH	DSH + Graph Memory	Change
T20 first request	56,998 tokens	16,769 tokens	−70.58%
T20 model-visible messages	171	24	−85.96%
T01–T20 first-request context	532,451 tokens	257,656 tokens	−51.61%
All measured tokens¹	2,487,776	2,401,512	−3.47%

_{¹ Includes nondeterministic main-agent tool loops, 20 graph extractions, and 125 embedding requests. Context ownership is the direct adapter metric; the full bill is shown to avoid overstating savings.}

20/20 scenario turns passed · 19/20 structured extractions succeeded · 42 nodes · 55 edges · 42 vectors · cross-session final facts recalled without gm_search.

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

Memory survives the context window

Graph Memory active in DSH Cross-session recall in a fresh DSH session

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 · current beta installs directly from GitHub:

npx @deepseek-ai/dsh plugin --profile web add github:adoresever/graph-memory
npx @deepseek-ai/dsh --profile web --dump-config
npx @deepseek-ai/dsh web

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

Capability	Implementation
Context takeover	Configurable newest-N completed turns; one archive marker replaces the older model surface
Lightweight extraction	Only the user question and final answer; strict structured tool contract; no reasoning/tool transcript ingestion
Query-first recall	Vector Top-K with FTS5 fallback; exact source Q/A travels with graph hits
Durable memory	Local SQLite, stable provenance, cross-session and cross-project recall
Failure behavior	Invalid extraction is quarantined; foreground conversation continues; bad data is not repaired or persisted
Host support	Native DSH/Cordis adapter; maintained OpenClaw Context Engine adapter

Optional embeddings

Graph Memory supports OpenAI-compatible embedding endpoints. Without embeddings it falls back to FTS5 and does not block conversation.

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

DSH tools and extraction route

Tool	Purpose
`gm_status`	Store, extraction, recall, vector, and retention state
`gm_search`	Explicit graph-memory search
`gm_record`	Deterministically persist a `TASK`, `SKILL`, or `EVENT`
`gm_stats`	Graph and retention receipts
`gm_maintain`	One bounded maintenance tick
`gm_retry_extraction`	Explicitly retry quarantined extraction

Automatic recall needs no tool call. Extraction may use a dedicated model via GRAPH_MEMORY_LLM_PROVIDER and GRAPH_MEMORY_LLM_MODEL; optional reasoning and output controls are GRAPH_MEMORY_LLM_REASONING_EFFORT and GRAPH_MEMORY_LLM_MAX_TOKENS.

OpenClaw compatibility

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

Activate the Context Engine slot in ~/.openclaw/openclaw.json:

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

Earlier OpenClaw seven-turn token comparison

Graph Memory Pro

The repository also contains an experimental read-only DSH Pro Lite Host + Client plugin backed by Community SQLite. The 2D/3D graph workbench, split view, and controlled drag-to-context remain planned. See dsh-pro/README_CN.md.

Verification and limits

Current beta 1.6.0-beta.13 passes 124/124 automated tests, both TypeScript builds, npm package verification, and a clean-profile install/boot on official DSH 0.1.3-alpha.1 (d347e70390).

Structured extraction still depends on model contract compliance: the measured run succeeded 19/20 times; failures stay quarantined and never block 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.

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