DD-OS (Digital Dimension Operating System) is a self-evolving AI operating system that runs entirely on your local machine. Unlike traditional AI assistants that treat every conversation as a blank slate, DD-OS builds persistent expertise -- each workflow node (Nexus) develops its own memory, scoring history, and operational genes through use.
Built on a ReAct execution engine with Reflexion self-correction, Critic verification, and confidence-based knowledge promotion, DD-OS turns your AI from a stateless chatbot into a trainable specialist that gets smarter over time.
DD-OS replaces the traditional chatbox with an explorable digital world. Three visual themes available:
| Minimalist Floating particles, breathing glow  |
Cosmos Deep space planets, orbital rings  |
Cityscape Isometric pixel city tiles  |
| World View (with Nexuses) Each node is a trainable AI expert  |
| AI Chat Panel ReAct execution with tool calls  |
Skill Tree 92 skills with particle visualization  |
| Settings OpenAI-compatible API config  |
Most AI agent frameworks give you a loop: plan, act, observe, repeat. DD-OS goes further with self-evolution primitives that no other open-source framework provides:
| Capability | DD-OS | Typical AI Agents |
|---|---|---|
| Per-domain memory | L1 Hot/Cold split per Nexus + L0 global knowledge | Flat session history |
| Knowledge promotion | Multi-signal confidence scoring, auto-promote to global | None |
| Self-correction | Reflexion (structured retry) + Critic (result verification) | Simple retry |
| Experience harvesting | Gene Pool with confidence decay | None |
| File awareness | O(1) File Registry, zero redundant exploration | Re-explore every time |
| Execution scoring | 0-100 per Nexus, streak bonuses, tool dimension tracking | None |
| Dangerous op control | 3-level risk classification + user approval flow | Basic confirmation |
GitHub / Slack / Local Bash / MCP Servers / Web
|
v (MCP Standard Protocol)
+-------------------------------+
| ddos-local-server.py | <-- Tool Execution Layer
| (Python / MCP Host) |
+---------------+---------------+
| (HTTP REST API)
+---------------+---------------+
| ReAct Execution Engine | <-- Task Orchestration
| Reflexion | Critic | Genes |
+---------------+---------------+
|
+---------------+---------------+
| Nexus Context Engine | <-- Memory & Context
| L1-Hot | L1-Cold | L0 |
| File Registry | Gene Pool |
+---------------+---------------+
|
[LLM API: GPT-4o / DeepSeek / Claude / ...]
Each Nexus is not just a prompt template -- it's an evolvable workflow node with its own brain.
- Level Progression: XP earned per execution, visual upgrades on level-up
- Independent Scoring: 0-100 scale with streak bonuses and tool-dimension tracking
- Bound Skills: Compose multiple SKILLs into specialized workflows
- SOP Memory: Standard operating procedures that persist across sessions
- Per-Nexus Context Engine: Each Nexus maintains its own L1 memory and context budget
- Custom Model Assignment: Different LLMs for different Nexuses
DD-OS implements a biologically-inspired memory architecture:
L1 Memory (Per-Nexus, Private)
- L1-Hot: Last 5 turns as structured action snapshots (metadata only, not raw output)
- L1-Cold: Semantic RAG retrieval via FTS5 + vector similarity + temporal decay
L0 Memory (Global, Shared)
- High-confidence L1 memories get promoted to L0 after passing multi-signal validation
- Promotion requires:
confidence >= 0.7AND3+ independent signals - L0 memories accessible by ALL Nexuses, enabling cross-domain knowledge transfer
Confidence Signals:
| Signal | Delta | Source |
|---|---|---|
| Environment Assertion | +0.15 | Critic verifies tool output |
| Human Approval | +0.15 | User approves high-risk operation |
| Human Rejection | -0.15 | User rejects operation |
| System Failure | -0.20 | Tool execution fails |
File Registry -- Every file operation is auto-registered with O(1) lookup. The agent never wastes turns re-exploring known paths.
The execution engine goes beyond basic plan-act loops:
- Task Decomposition: Complex tasks auto-split into executable sub-steps
- Tool Calling: File I/O, shell commands, web search, MCP tools, and 90+ skills
- Reflexion: On failure, triggers structured self-reflection with error analysis -- not blind retry
- Critic Verification: After file writes and shell commands, automatically verifies the result
- Digital Immune System: Failure pattern signatures matched against self-healing scripts
- Dangerous Operation Approval: 3-tier risk classification (critical/high/medium) with user approval flow
- Gene Pool Harvesting: Successful execution patterns extracted as reusable "genes" with confidence tracking
| Dependency | Version |
|---|---|
| Node.js | >= 18 (v20+ recommended) |
| Python | >= 3.10 |
| Git | Latest |
git clone https://github.com/FatBy/DD-OS.git
cd DD-OS# Frontend
npm install
# Python (optional, for YAML support)
pip install pyyamlWindows:
Double-click start.bat in the project root.
macOS:
Double-click DD-OS.command in Finder.
Manual Launch (all platforms):
# Terminal 1 -- Backend
python ddos-local-server.py --path ~/.ddos --port 3001
# Terminal 2 -- Frontend
npm run devOpen http://localhost:5173 in your browser.
- Click Settings in the left sidebar
- Fill in Base URL, API Key, and Model name
| Provider | Recommended Models | Base URL |
|---|---|---|
| OpenAI | gpt-4o, gpt-4o-mini | https://api.openai.com/v1 |
| DeepSeek | deepseek-chat, deepseek-reasoner | https://api.deepseek.com/v1 |
| Claude | claude-3.5-sonnet | Via compatible proxy |
| Moonshot | moonshot-v1-8k | https://api.moonshot.cn/v1 |
| SiliconFlow | Various open-source models | https://api.siliconflow.cn/v1 |
See the examples/ directory for real-world use cases:
| Example | Description |
|---|---|
| Novel Writing | Using the novel-master Nexus to plan and write a chapter |
| Code Project | Building a utility library with ReAct execution |
| Research Report | Web search + structured report generation |
| Tool | Description |
|---|---|
readFile / writeFile |
File I/O with auto File Registry tracking |
runCmd |
Shell commands (with 3-tier safety approval) |
webSearch / webFetch |
Web search and page fetching |
saveMemory / searchMemory |
Two-tier memory read/write |
listDir |
Directory listing with auto-registration |
DD-OS ships with 90+ skills covering code generation, document writing, image creation, stock analysis, PPT generation, and more. Skills are defined as SKILL.md files and hot-reload without restart.
~/.ddos/skills/my-skill/SKILL.md
---
name: my-skill
description: My custom skill
version: 1.0.0
---
# Instructions
What this skill does and how it works...| Module | Description |
|---|---|
| World View | Nexus node map with drag interaction and theme switching |
| Task Monitor | Running/completed tasks with real-time execution step tracking |
| Skill Tree | AI capability radar with particle visualization |
| Memory Palace | Adventure logs, memory playback, AI narrative generation |
| Soul Tower | AI personality config (SOUL.md), core values and behavior boundaries |
~/.ddos/
├── SOUL.md # AI personality config
├── USER.md # User preferences
├── skills/ # Skill definitions (SKILL.md)
├── nexuses/ # Nexus workflow data + SOPs
├── memory/ # Two-tier memory storage
│ └── exec_traces/ # JSONL execution traces
└── logs/ # Conversation logs
| Layer | Technology |
|---|---|
| Frontend | React 18 + TypeScript + Vite + Zustand + Tailwind CSS + Framer Motion |
| Rendering | Canvas 2D (GameCanvas engine) |
| Backend | Python (ddos-local-server.py) with SQLite + FTS5 |
| Memory | SQLite (FTS5 full-text search) + JSONL traces + localStorage |
| Protocol | HTTP REST API + MCP Standard Protocol |
We welcome contributions! Check out our open issues for good first issue labels.
- All API keys stored in browser localStorage, never uploaded
- Backend binds to
127.0.0.1(localhost only) - 3-tier dangerous command classification with approval dialogs
- File operations sandboxed to workspace directory
- Sensitive data auto-redacted in execution traces
- Run
python ddos-local-server.py --doctorto check security config
MIT