@wwskills/dsh-long-memory

August 28, 2026 · View on GitHub

Long-term cross-session memory + self-evolving learning plugin for DeepSeek Harness.

SQLite-backed, FTS5 + optional embedding recall, append-only audit log, L7 auto-extraction, lesson capture from user corrections, rule lifecycle with context injection. Single-bundle dual-face packaging (Node service + browser UI).

Features

Memory & Recall

8 mem_* tools — search, record, status, stats, forget, confirm, scope list, scope set
FTS5 full-text search with CJK support (works out of the box, zero config)
Optional embedding — Ollama (local, zero cost) or any OpenAI-compatible API
Hybrid recall — BM25 + vector + RRF fusion when embedding is enabled
L7 auto-extraction — automatically extracts memories from conversations on turn/end using your DSH LLM provider (zero extra config)
Keyword fallback — if LLM is unavailable, regex-based keyword extraction kicks in
File tracks — MEMORY.md session markers + memory/YYYY-MM-DD.md daily notes
Audit log — append-only, tracks every memory operation

Self-Evolving Learning (merged from agent-evolve)

Signal word detection — real-time capture when user says "不对" / "wrong" / "should be" etc. (8 CN + 7 EN, configurable)
Tool error capture — tools/result event listener auto-records tool failures as corrections
Agent error capture — agent/error event listener auto-records harness-level errors
Lesson extraction — LLM-powered structured lesson extraction from correction-triggering messages
Rule lifecycle — proposed → approved → rejected → archived → promoted_to_agents
Rule injection — approved rules auto-injected into agent context via agent/pre-step (≤800 token budget, hit_count tracking)
Rule conflict detection — Jaccard overlap >60% warns on approve
AGENTS.md promotion — high-hit-count rules can be promoted to AGENTS.md format
Daily decay — stale rules (90 days unhit) auto-archived

Browser UI

4 Tab management panel — 教训 (Corrections) / 规则 (Rules) / 记忆 (Memories) / 画像 (Persona)
Overview strip — pending corrections, proposed rules, active memories at a glance
Config panel — embedding, LLM model, signal words, extraction settings
30s auto-refresh — stats and badges stay current

Install

dsh plugin --profile web add @wwskills/dsh-long-memory

Configuration

Defaults are sensible. Override via your profile's patch layer as needed.

Embedding

Provider	Use case	Cost
`none`	FTS5 keyword only (default)	Zero
`ollama`	Local Ollama service	Zero (local)
`openai-compatible`	Any OpenAI-style API	Per-call

- id: long-memory
  config:
    embedding:
      provider: 'ollama'          # 'none' | 'ollama' | 'openai-compatible'
      model: 'bge-m3'
      dimension: 1024
      ollama:
        base_url: 'http://127.0.0.1:11434'

L7 Auto-extraction

L7 reads your DSH LLM provider config automatically — no extra API key needed.

- id: long-memory
  config:
    l7:
      enabled: true               # enable auto memory extraction
      auto_extract: true          # LLM-based + keyword fallback
      extractor_model: ''         # empty = use cheapest model from your DSH config
      extractor_temp: 0.2
      interval_ms: 21600000       # 6h minimum between extractions

Signal Words (Self-Evolving)

Signal words trigger real-time correction capture when users say things like "不对" or "wrong":

- id: long-memory
  config:
    # Default signal words (8 CN + 7 EN) are built-in.
    # Override via WebUI Settings → Plugins → Long Memory.
    # Or set in patch:
    # signal_words:
    #   - '不对'
    #   - 'wrong'
    #   - ...

Storage

    storage:
      path: '${DSH_HOME}/long-memory/long-memory.db'
      markdown_dir: '${DSH_HOME}/long-memory/markdown'

Tools

Tool	Purpose
`mem_search`	FTS5 + hybrid search across memories
`mem_record`	Persist a memory; auto-detects scope
`mem_status`	Storage + recall state
`mem_stats`	Aggregate statistics
`mem_forget`	Archive or delete; writes audit log
`mem_confirm`	Approve/reject queued sensitive memory
`mem_scope_list`	List all scopes
`mem_scope_set_active`	Set active scope filter

Web API

Method	Path	Purpose
GET	`/plugins/dsh-long-memory/api/memories`	List memories (scope/type/q filter)
DELETE	`/plugins/dsh-long-memory/api/memories`	Delete a memory
GET	`/plugins/dsh-long-memory/api/confirm-queue`	Pending sensitive memories
POST	`/plugins/dsh-long-memory/api/confirm-queue`	Approve/reject
GET/POST	`/plugins/dsh-long-memory/api/embedding-config`	Embedding settings
GET	`/plugins/dsh-long-memory/api/corrections`	List corrections (status/trigger filter)
POST	`/plugins/dsh-long-memory/api/corrections/:id/extract`	Promote correction to rule
POST	`/plugins/dsh-long-memory/api/corrections/:id/ignore`	Ignore correction
GET	`/plugins/dsh-long-memory/api/rules`	List rules (status filter)
POST	`/plugins/dsh-long-memory/api/rules/:id/approve`	Approve rule
POST	`/plugins/dsh-long-memory/api/rules/:id/reject`	Reject rule
POST	`/plugins/dsh-long-memory/api/rules/:id/promote`	Promote to AGENTS.md
GET	`/plugins/dsh-long-memory/api/rules/:id/source`	View source corrections
PUT	`/plugins/dsh-long-memory/api/rules/:id`	Edit rule
GET	`/plugins/dsh-long-memory/api/stats`	Monthly stats

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    long-memory plugin                       │
├──────────────┬──────────────┬──────────────────────────────┤
│  Memory &    │  Self-Evolving│  Browser UI                  │
│  Recall      │  Learning     │  (4 Tab Panel)               │
│              │               │                              │
│ • memories   │ • corrections │ • 教训 Tab (list/extract)   │
│ • FTS5       │ • rules       │ • 规则 Tab (approve/edit)   │
│ • embedding  │ • signal words│ • 记忆 Tab (search/filter)  │
│ • L7 extract │ • tool errors │ • 画像 Tab (persona)        │
│ • scope      │ • rule inject │ • Config panel              │
│ • KG         │ • decay       │ • 30s auto-refresh          │
│ • 8 tools    │ • conflicts   │                              │
│ • audit log  │ • AGENTS.md   │                              │
└──────────────┴──────────────┴──────────────────────────────┘

Requirements

Node ≥ 22.5 (uses built-in node:sqlite)
DeepSeek Harness 0.1.0-rc.2+

Migrations

#	File	Description
0001	`0001_initial.sql`	Core tables: memories, embeddings, audit_log, confirm_queue, schema_meta
0002	`0002_l7_buffer.sql`	L7 message buffer table
0003	`0003_embedding_cache_key.sql`	Composite PK for embeddings
0004	`0004_corrections_rules.sql`	Corrections + rules + usage_stats (self-evolving)

License

MIT — see LICENSE.