deepDDW — Memory & Knowledge Base for DeepSeek Harness, Reachable from Any Device on Your LAN

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deepDDW gives DeepSeek Harness (DSH) the three pieces it's missing — memory, a knowledge base, and document search — and makes all of it reachable from any device on your LAN. No app install. No DSH source changes.

🧠 Memory — cross-session long-term memory, write/search via DSH's official MCP interface
📚 Knowledge base — ingest & search your docs (industry docs, SOPs, research notes) anytime
🌐 LAN-wide multi-device — deploy once; phones, laptops and tablets on the same network all use the same DSH workbench

Try it in 60 seconds:

npm i -g @deepseek-ai/dsh              # 1. install official DSH on the server
git clone https://github.com/ccch713/deepddw.git && cd deepddw
./install.sh --with-dsh                # 2. install deepDDW
./install.sh --port 8600               # 3. start
# 4. from any device on your LAN: open http://<server-ip>:8600/  (phone: scan the QR to auto-pair)

📸 Screenshot: phone / tablet accessing the workbench (coming soon).

Status: v0.3.0 · MIT · CI (pytest + ruff) ✅ · Multi-device on LAN + workspace isolation + backup/restore + TLS (opt-in) + LLM reflections & ranked memory search · Listed in awesome-deepseek-harness · Roadmap below

Why deepDDW?

Most DSH extensions give you memory alone. deepDDW is a complete workstation — memory + knowledge base + document search + LAN-wide multi-device access:

Official DSH limitation	deepDDW solution
🔒 Local-only access	✅ LAN-wide access: deploy once on a server; desktops, laptops, phones and tablets on the same network all connect
🧠 No memory	✅ Long-term memory write/search — conversation experience is accumulated
📚 No knowledge base	✅ Knowledge base search/ingest — industry docs, SOPs, research notes, callable anytime

In one sentence: turn a "personal toy" into a tool a small team can actually use — fully packaged, easy to deploy, low maintenance, ready for small businesses (up to ~20 people) for their daily AI workflow.

deepDDW is built on our DDW AI HUB platform — validated in enterprise deployments and packaged into the DSH ecosystem as open source (MIT).

How It Works (Technical Path)

📱 Phone / 💻 Desktop / 📱 Tablet / 🖥️ Laptop — any device on the LAN
   │                  (browser access, no App install)
   ▼
deepDDW Gateway (one server on the LAN)
   ├─ /dsh/*   proxy → DSH engine (official UI, model config & chat untouched)
   ├─ /api/*   proxy → DSH RPC/API
   └─ /api/v1/*  deepDDW capabilities: Knowledge Base / Memory / Docs / LLM config
        │
        │  DSH official MCP client (streamable-http)
        ▼
deepDDW MCP tools (auto-invoked by the model)
   ├─ mcp__deepddw__ddw_kb_search          knowledge base search
   ├─ mcp__deepddw__ddw_memory_put         write memory
   ├─ mcp__deepddw__ddw_memory_search      search memory
   └─ mcp__deepddw__ddw_docs_portal_search document search

Integration = DSH standard MCP: DSH natively supports MCP clients; deepDDW exposes a standard streamable-http endpoint — zero intrusion, zero changes to DSH source. The UI, settings and model configuration all remain official.

Why Does It Work on Your LAN?

The official DSH listens on localhost only (for security), so phones/tablets cannot connect. deepDDW solves this with gateway proxying:

DSH stays bound to localhost (official security design preserved)
deepDDW gateway listens on the LAN, any device opens http://<server-ip>:8600/ to reach the original DSH workbench
All data stays on your server — never leaves the LAN

Deploy once, the whole family/team can use it — a capability the official DSH does not provide.

Quick Start

# 1. Install DSH (official) on the server
npm i -g @deepseek-ai/dsh

# 2. Install deepDDW (packaged, one command)
git clone https://github.com/ccch713/deepddw.git
cd deepddw && ./install.sh --with-dsh

# 3. Start
./install.sh --port 8600

# 4. Open from any device on the LAN:
#    http://<server-ip>:8600/   → original DSH workbench
#    Phones/tablets: "Add to Home Screen" for an App-like experience

# 5. Add your API Key in DSH Settings → Models
# 6. In chat, ask the model to "search the knowledge base" or "remember ..."
#    → it auto-invokes the mcp__deepddw__* tools

Requirements: one ordinary computer/server (8 GB RAM minimum, 16 GB+ recommended), Python 3.11+, no GPU needed (LLM via cloud API or local Ollama).

Windows (standalone exe)

A Windows build is produced automatically by the windows-build workflow — download deepddw-windows.zip from the latest Actions → Artifacts:

# 1. Unzip anywhere (no Python/Node needed on the target machine)
deepddw-windows/deepddw.exe

# 2. Optional: point data/config at a custom location
set DDW_DATA_DIR=%USERPROFILE%\.deepddw
set DDW_ACCESS_TOKEN=<your-token>

# 3. Start (listens on 0.0.0.0:8500) → open http://<host>:8500/health
deepddw.exe

Upgrades are cheap: replace the whole folder with a newer zip — your data (under %USERPROFILE%\.deepddw) is untouched. See docs/windows-packaging.md for the full evaluation (PyInstaller one-dir + CI auto-build) and the manual build steps.

Multi-Device on LAN (0.2.0)

deepDDW is built for up to 20 devices on your LAN sharing one gateway:

Device identity — each browser persists a device_id (localStorage) and can set a friendly name on the launcher; reconnects keep the same identity.
Online status — devices register/heartbeat to the gateway; /api/v1/status (Token-protected) shows who is online, active WebSockets, request counts, DB size and version. The launcher renders a live status card for admins.
Rate limiting — sliding-window per Token + per IP (default 60 req/min/token, global cap → 503 overload protection); configurable via config/deployment.yaml → security.rate_limit.* or DDW_RATE_LIMIT_* env.
SQLite concurrency — WAL + busy_timeout=5000 + synchronous=NORMAL on every connection, plus a process-wide write lock for cross-table transactions (20 concurrent writers verified, no database is locked).

POST /api/v1/device/register    # register / rename this device (idempotent)
POST /api/v1/device/heartbeat   # keep-alive
GET  /api/v1/status             # status panel (token required)

Also in 0.2.0:

Workspace isolation — devices pick a workspace (default shared); memory/logs and MCP memory tools are scoped per workspace, docs filtered by slug prefix. Legacy clients are unaffected.
Session resume across devices — recent session summaries (up to 5) with a "continue" button: pick up a conversation on your phone where you left off on desktop.
One-click backup / restore — backup via API (downloadable); restore validates the SQLite file (header + integrity check) and keeps a .pre-restore safety copy before replacing the main DB.
Optional TLS — one-command self-signed cert (scripts/gen_self_signed_cert.sh, 1-year), enabled via security.tls.*; HTTP unchanged when off. For external access prefer a Caddy/Nginx reverse proxy (see docs/tls.md).
Version / upgrade check — /api/v1/version reports latest_version / update_available (GitHub releases, 1h cache, offline-degraded); the launcher shows an upgrade banner.

Security & Privacy

Capability	Description
🔐 Local-only data	Knowledge base & memory stay on your server, never leave the LAN
🏠 LAN password-free	Optional (opt-in): LAN requests skip the token — OFF by default (set `DDW_LAN_BYPASS=1` to enable; trusted LANs only)
🌐 External access	Optional Token gate (short-code supported); unauthorized → 401
🛡️ DSH secure binding	DSH stays on localhost; gateway exposes it — official security design preserved

Tech Stack & License

Component	Description	License
DSH engine	Official DeepSeek Harness (source untouched)	MIT
deepDDW gateway	FastAPI + SQLite + MCP dual-protocol	MIT
Memory / Knowledge base	SQLite storage (agentmemory / vectors optional)	MIT
Search	Optional SearXNG	AGPL-3.0 (server-side HTTP, exemption assessed)

deepDDW itself: MIT License — free to use, modify, and commercially deploy; keep the copyright notice.

See NOTICE for full third-party attribution.

Ecosystem & Feedback

Extend with official DSH plugins: deepDDW keeps DSH's native plugin mechanism intact. Install official plugins straight from the npm registry via the DSH official command — the only channel we recommend, to avoid supply-chain poisoning:
```
dsh plugin --profile web add <npm-package>   # official npm registry only
```
See SECURITY.md for our third-party plugin disclaimer and what deepDDW guarantees (memory & knowledge base only; no data theft/exploitation/sale).
Knowledge distillation: use whatever distillation skill / workflow you prefer — the methodology is yours; deepDDW provides the complete pipeline "distilled output → searchable knowledge base → model-usable". More plugins and tools are on the way.
Memory / knowledge migration: knowledge base uses standard SQLite; memory is organized by namespace/key/value — import from other agents or tools.
Feedback: we'd love to hear how you use it; stronger open-source tools are coming in future releases.

Roadmap

Only items actually planned or already delivered are listed here.

Delivered:

deepDDW — enterprise-grade capability, open-sourced for everyone.

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
config		config
core		core
data		data
docs		docs
frontend		frontend
lib		lib
plugins		plugins
scripts		scripts
sdk		sdk
tests		tests
.env.example		.env.example
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
Dockerfile		Dockerfile
LICENSE		LICENSE
NOTICE		NOTICE
README.md		README.md
README.zh-CN.md		README.zh-CN.md
SECURITY.md		SECURITY.md
VERSION		VERSION
conftest.py		conftest.py
deepddw-compose.yml		deepddw-compose.yml
entry_win.py		entry_win.py
install.sh		install.sh
package-lock.json		package-lock.json
package.json		package.json
pytest.ini		pytest.ini
requirements.txt		requirements.txt

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deepDDW — Memory & Knowledge Base for DeepSeek Harness, Reachable from Any Device on Your LAN

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deepDDW — Memory & Knowledge Base for DeepSeek Harness, Reachable from Any Device on Your LAN

Why deepDDW?

How It Works (Technical Path)

Why Does It Work on Your LAN?

Quick Start

Windows (standalone exe)

Multi-Device on LAN (0.2.0)

Security & Privacy

Tech Stack & License

Ecosystem & Feedback

Roadmap

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