dsh-memory 🧠
Cross-session memory plugin for DeepSeek Harness (dsh).
YAML-backed remember / recall / view / list / forget / pin tools with embedding search, title-first injection, and two-level (session/auto) automatic injection — the agent "naturally carries" memory without having to remember to call a tool.
English | 中文
🎯 Injection Strategy: Precise, Conservative, Cache-Friendly
| Design Principle | Description |
|---|---|
| Inject once, reuse forever | Fixed memories inject on the session's FIRST step only, then ride the history — no per-round re-render |
| Title-first, expand on demand | Injects concise titles (with id); full details expand via view tool — compact prompts |
| Dynamic memories independent from fixed set | auto memories retrieved by topic, never pollute the fixed injection set |
| Preserves prefix cache | After injection, memories enter history; system prompt + history prefix stays identical — LLM KV cache hit rate unaffected |
| Provenance isolation | Injected memories prefixed with Retrieved memories from the memory store (not conversation history) — model never mistakes them for dialogue |
📊 Comparison with Alternatives
| Approach | Per-round injection | Cache impact | Token cost |
|---|---|---|---|
| Full injection every round | ❌ Repeats each round | ❌ Breaks cache | High |
| This plugin | ✅ Once at start | ✅ Zero impact | Low |
✨ Features
| Feature | Description |
|---|---|
| remember / recall / view / list / forget / pin | Write, semantic search, expand-by-id, list (titles), soft-delete, force-inject pinning |
| Title-first injection | Memories inject as summary titles (with id), not full text — compact prompts; details expand via the view tool |
| Two-level injection | injectLevel: session memories are resident (injected once at session start); auto memories arrive via topic retrieval |
| Once-per-session injection | Fixed memories inject on the session's FIRST step, then ride the history (no per-round re-render — token + prefix-cache friendly) |
| Embedding search | HybridSearch (keyword 2-gram + local embedding via ollama, RRF fusion) — catches paraphrases keyword search misses |
| Tuned matching | Generic-word downweighting (文件/测试/文档…), ≥2-token keyword hits, retrieval gate skips test-chatter ("别管/只是测试") |
| Provenance labeling | Injected memories are prefixed "…from the memory store (not conversation history)" so the model never mistakes them for dialogue |
| Data safety | Serialized write queue (no lost updates), corrupt-file quarantine + backup, atomic writes, mtime cache invalidation |
📦 Install
# From source (inside a dsh checkout)
pnpm install
pnpm run build
# Register in your profile patch (e.g. ~/.dsh/profiles/web/cordis.patch.yml)
- insert:
- id: dsh-memory
name: '@towzai/dsh-memory'
config:
file: /path/to/memory.yaml
injectLimit: 8Requires a local ollama instance with an embedding model (default qwen3-embedding:0.6b; override via DSH_MEMORY_EMBED_MODEL).
🔨 Build (from source)
Requires the dsh checkout's dependencies (the plugin's peer deps live there). On Windows you can junction them instead of reinstalling:
# in the plugin repo
cmd /c mklink /J node_modules <path-to-dsh-checkout>\node_modules
npm run build # outputs lib/index.js🛠️ Tools
| Tool | Purpose |
|---|---|
remember | Save a memory (content / title / category / tags / importance / forceInject / injectLevel / source) |
recall | Hybrid search (keyword + embedding) top-N |
view | Expand ONE memory's full content by id (title-first injection's detail entry) |
list | List memories as titles (category/tag/importance filters, full for content) |
forget | Soft-delete (marks retired, keeps history) |
pin | Toggle forceInject — pinned memories always appear at session start |
🗂️ Storage
Single YAML file (default memory.yaml). Each entry:
- id: MEM-20260814-001
title: "Summary title (auto-derived if absent)" # injected as title
content: "..."
category: preference | project | lesson | fact
tags: [tag1, tag2]
importance: high | normal | low
created: 2026-08-14
updated: 2026-08-14
source: user | agent | conversation
retired: false
forceInject: false # full behavioural rules, always resident
injectLevel: session | auto # resident vs on-demand
vector: [...] # 1024-dim embedding, auto-computed on write🔧 Architecture
src/
├── index.ts # plugin entry: tools + session-first injection + pre-step listener
├── storage.ts # Storage interface + YamlStorage (queue, mtime cache, quarantine)
├── search.ts # KeywordSearch / EmbeddingSearch / HybridSearch (RRF) / OllamaEmbedder
├── inject.ts # selectForInjection / renderSection (title-first) / deriveTitle / entryTitle
├── dynamic.ts # DynamicInjector (per-session dedup + retrieval gate + fixed-set exclusion)
└── types.ts # data model (+ reserved fields: vector/scope/weight for future)Architecture: [docs/architecture.md](docs/architecture.md) · Changelog: [CHANGELOG.md](CHANGELOG.md).
🗺️ Planned
Ideas on the horizon (not yet implemented):
| Feature | Description |
|---|---|
Feedback scoring (weight) | Learn from implicit signals (usage, dismissals, agent feedback) and rank memories by usefulness instead of static importance |
Multi-scope isolation (scope) | Keep separate memory namespaces per project/workspace, so one agent's context never bleeds into another's |
| Auto-learning | Distill session insights into new memories automatically (with human confirmation), instead of relying on explicit remember calls |
| More backends | SQLite / JSON storage behind the existing Storage interface |
| Web UI | Browse, edit and manage memories from the dsh WebUI (view only exists as an agent tool today) |
| Test suite | Expand automated coverage for storage, search and injection logic |
⚠️ Notes
- Embedding model change invalidates stored vectors (dimension mismatch is detected and logged)
- The plugin is developed against dsh
v0.1.0-rc.5; peer dependency ranges may need bumping
🔗 References
This plugin is part of the DeepSeek Harness (dsh) plugin ecosystem.
- Official repo: deepseek-ai/deepseek-harness
- Plugin docs: docs/user/develop — plugin lifecycle, config, and publish guide
- Ecosystem topic:
dsh-plugin
📄 License
MIT