zenai

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📌 This repository is a snapshot, not the living tree

The application code here was synced from the development tree on 8 May 2026; only documentation and CLI packaging changed after that, up to 25 May 2026. It is a faithful copy of what ZenAI was on that date — readable, citable and runnable — but it is not the current state of development, and it does not receive fixes.

The CI pipeline is set to manual dispatch for the same reason: it tests files that the development tree has since removed, so an automatic run reported a failure that nobody here could act on. That says nothing about the snapshot itself.

What is current: the memory library ZenBrain is actively developed and released to npm, and the research record behind both is kept up to date at zensation.ai/en/publikationen. The terminal agent in cli/ was published as @zensation/cli. It is retired: every version is deprecated on npm (1 October 2026), because it reads API_URL and VITE_API_KEY from the environment as undocumented fallbacks. Maintained memory tooling: @zensation/mcp.

Questions about the state of ZenAI: open-source@zensation.ai

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What is ZenAI?

ZenAI is a self-hosted AI platform with neuroscience-inspired memory. Unlike ChatGPT or Claude, ZenAI remembers your conversations, learns from your preferences, and improves over time — using the same mechanisms your brain uses.

Key Features

• 60 AI Tools across 14 categories (memory, web search, code execution, GitHub, maps, email, documents, and more)
• 7-Layer Memory (Working, Short-Term, Episodic, Semantic, Procedural, Core, Cross-Context) powered by ZenBrain
• FSRS Spaced Repetition — your AI never forgets what matters
• 4 Context Isolation — separate memory for personal, work, learning, and creative
• Multi-Agent System — researcher, writer, reviewer, coder agents with debate protocol
• RAG Pipeline — HyDE + Cross-Encoder reranking + GraphRAG hybrid retrieval
• Real-Time Voice — WebSocket STT/TTS pipeline with turn-taking
• Extended Thinking — visible AI reasoning with budget management
• Sleep-Time Compute — background memory consolidation and contradiction detection
• MCP Ecosystem — connect external tools via Model Context Protocol

Architecture

Frontend: React + TypeScript (Vite)
Backend:  Express.js + TypeScript
AI:       Claude API (primary), Mistral (fallback), Ollama (local)
Database: PostgreSQL + pgvector (4 isolated schemas)
Memory:   ZenBrain 7-layer architecture
Cache:    Redis (optional)

Quick Start

Prerequisites

• Node.js 20 (this snapshot declares "node": "20.x")
• PostgreSQL 15+ with pgvector extension
• Anthropic API key

Setup

# Clone
git clone https://github.com/zensation-ai/zenai.git
cd zenai

# Backend
cd backend
cp .env.example .env
# Edit .env with your DATABASE_URL and ANTHROPIC_API_KEY
npm install
npm run build
npm run dev

# Frontend (new terminal)
cd frontend
npm install
npm run dev

Open http://localhost:5173 in your browser.

Docker Compose

Two compose files ship with this snapshot.

# Self-hosting: Postgres (pgvector) + Redis + backend on :3000
cp .env.docker .env
docker compose up -d

# Infrastructure only — Postgres + Redis, run backend and frontend locally
docker compose -f docker-compose.dev.yml up -d

The frontend is not part of the compose stack; run it as shown under Setup.

API

ZenAI exposes 250+ API endpoints. Key areas:

Area	Endpoints	Description
Chat	/api/chat/*	Streaming chat with tool use, vision, artifacts
Memory	/api/:context/memory/*	FSRS review, procedures, hybrid search
Ideas	/api/:context/ideas/*	CRUD with semantic search, topics, drafts
Tasks	/api/:context/tasks/*	Kanban, Gantt, dependencies, projects
Email	/api/:context/emails/*	Send/receive with AI categorization
Agents	/api/agents/*	Multi-agent execution, templates, streaming
Knowledge Graph	/api/:context/graphrag/*	Entity extraction, hybrid retrieval
Voice	/api/:context/voice/*	Real-time STT/TTS pipeline

Full API documentation: /api-docs (Swagger UI when running)

Testing

# Backend (~11,500+ tests)
cd backend && npm test

# Frontend (~1,400+ tests)
cd frontend && npx vitest run

# CLI (108 tests)
cd cli && npm test

Memory System

ZenAI's memory is powered by ZenBrain — the neuroscience-inspired memory system:

Layer	Inspired By	Function
Working Memory	Baddeley (1974)	Active task focus (7±2 items)
Short-Term	Session context	Current conversation
Episodic	Tulving (1972)	Concrete experiences
Semantic	FSRS + Ebbinghaus	Facts with spaced repetition
Procedural	Cognitive psychology	"How to do X" skills
Core	Letta/MemGPT	Pinned, user-editable facts
Cross-Context	ZenBrain architecture	Shared knowledge across domains

Paper & Citation

The memory architecture underneath ZenAI is documented and peer-reviewable:

• arXiv preprint (cs.AI): arxiv.org/abs/2604.23878
• Open-access archive (Zenodo / CERN): doi.org/10.5281/zenodo.19353663
• ORCID: 0009-0001-1793-012X

@article{bering2026zenbrain,
  title         = {ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems},
  author        = {Bering, Alexander},
  year          = {2026},
  eprint        = {2604.23878},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2604.23878}
}

To cite this snapshot itself rather than the architecture, see CITATION.cff.

Contributing

See CONTRIBUTING.md for guidelines.

License

Apache 2.0

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