Lightweight AI Cognitive Engine Framework — give your AI a memory
Project description
Aelvoxim — Cognitive Self-Learning AI Brain
pip install aelvoxim— Not a chatbot. A brain that learns.
Quick Start
# Install
pip install aelvoxim
# Start the server
aelvoxim server --port 9701
# Open in browser
open http://localhost:9701
# Or use the ChatAEL frontend (dedicated chat UI)
python serve_chatael.py
# Open http://localhost:9702
From source
git clone https://github.com/macor24/aelvoxim.git
cd aelvoxim
pip install -e .
python src/run_server.py 9701
Use Cases
Aelvoxim's layered memory, autonomous learning, and meta-cognition unlock scenarios that ordinary LLM wrappers and RAG pipelines cannot handle.
🧑🤝🧑 Long-Living Virtual Character
Most AI agents lose everything on restart — Aelvoxim doesn't.
- Conversations are stored in episodic memory and never reset
- User preferences and speaking style are extracted into semantic memory (persist across sessions)
- The forgetting curve naturally prioritizes recent interactions while preserving core facts
- After weeks of use, the character grows to genuinely know the user, instead of starting from scratch every session
📚 Living Code Documentation
Hook Aelvoxim into your Git workflow and let it maintain your project docs automatically.
- Connect via GitHub/GitLab webhook — every PR merge triggers re-learning
- Aelvoxim scans new code, extracts module APIs, and updates its knowledge base
- Conflict detection flags when an interface changed but docs weren't updated
- Team members ask "how does this function work?" and get answers grounded in actual code, not stale docs
🔍 Continuous Compliance Monitoring (Medical / Legal)
Meta-cognition + auto-validation as a regulatory watchdog.
- Store regulations, guidelines, or protocols in the knowledge base
- Curiosity-driven discovery periodically searches for new versions or updates
- Conflict detection catches contradictions between new and old knowledge automatically
- Output validation ensures every answer stays within compliance boundaries
- No manual review cycles needed — the system watches itself
🧠 Personal Learning Companion
Unlike ChatGPT where every conversation is isolated, Aelvoxim builds a persistent model of what you know.
- Tracks what you've learned and which concepts you find confusing
- Forgetting curve schedules review reminders at optimal intervals
- Extracts knowledge triples from your notes automatically (knowledge distillation)
- Gap analysis identifies blind spots and suggests what to study next
- Over time it becomes a second brain that knows your knowledge landscape
📊 Automated Business Intelligence
Turn curiosity-driven learning into a competitive radar.
- Define interest directions (competitor moves, industry news, tech trends)
- Curiosity engine autonomously discovers and fetches relevant content
- Extracted insights are stored as structured knowledge
- Conflict alerts fire when new information contradicts existing beliefs (e.g. a competitor changed pricing)
- No manual keyword rules — the AI decides what's worth learning
⚙️ Self-Tuning Service Bot
Deploy a support bot that tunes itself — no DevOps babysitting required.
- Out of the box it works with conservative defaults
- Auto calibration monitors real response quality and adjusts parameters (temperature, expert weights, memory thresholds) based on what actually works
- When traffic patterns shift (e.g. more technical questions at certain hours), the system adapts without a config push
- Knowledge gap analysis spots missing answers and automatically initiates learning
- Over weeks the bot silently improves — your only job is to keep it running
Features
🧠 Memory System
Your AI remembers like a human — with layers, decay, and doubt.
| Capability | Description |
|---|---|
| 4-layer memory | Working / Episodic / Semantic / Procedural |
| MemoryFusion | Inverted index + multi-layer retrieval |
| Forgetting curve | Knowledge decays naturally (Ebbinghaus) |
| Conflict detection | Finds contradictions, alerts the user |
| Confidence Matrix | 5-dimensional trust score on every response |
🔧 Expert System
A team of specialized AI experts working together.
| Expert | Role | Community | Pro |
|---|---|---|---|
| LogicExpert | Rule reasoning, contradiction detection | ✅ | ✅ |
| MemoryExpert | Memory retrieval, fusion search | ✅ | ✅ |
| EthicsExpert | 15 ethical rules, transparent & auditable | ✅ | ✅ |
| SafetyExpert | Local keyword + regex safety checks | ✅ | ✅ |
| CodeReviewExpert | Code style, complexity, secret scanning | ✅ | ✅ |
| EmotionExpert | Sentiment analysis, empathetic response | ❌ | ✅ |
| CreativeExpert | Creative writing, content generation | ❌ | ✅ |
| IntrospectionExpert | Self-reflection, quality audit | ❌ | ✅ |
| HypothesisEngine | Root cause hypothesis & validation | ❌ | ✅ |
📚 Learning System
| Capability | Community | Pro |
|---|---|---|
| Manual learning (API trigger) | ✅ | ✅ |
| 7×24 auto-learning loop | ❌ | ✅ |
| Curiosity-driven discovery | ❌ | ✅ |
| Auto parameter tuning | ❌ | ✅ |
| Knowledge gap analysis | ❌ | ✅ |
| Post-validation audit | ❌ | ✅ |
🔌 API & Integration
- RESTful API — FastAPI, Swagger docs at
/docs - SSE streaming — Real-time token-by-token output
- Multi-user auth — Email/password registration + API Keys
- Knowledge base CRUD — Add, search, update, delete knowledge entries
- Session management — Persistent conversations with history
Architecture
aelvoxim/
├── src/aelvoxim/
│ ├── core/ Cognitive engine (belief, metacog, reasoner, judge, DGM-H)
│ ├── learn/ Learning engine (learner, KB, validator, search, curiosity)
│ ├── memory/ Memory system (4 layers, fusion, decay, conflict, scoring)
│ ├── server/ API server (FastAPI, auth, chat pipeline, sessions)
│ ├── cortex/ Brain cortex (intent routing, scheduler)
│ ├── experts/ Expert system (orchestrator, 5+ experts, registry)
│ ├── storage/ Dual storage (SQLite local, PostgreSQL production)
│ ├── utils/ Helpers (i18n, paths, JSON)
│ └── edition.py Edition gating (community/pro config control)
├── frontend/
│ └── chatael-v2/ ChatAEL — React + Tailwind chat UI
├── tests/ 130+ test cases
├── docs/
├── CONTRIBUTING.md
├── SECURITY.md
└── LICENSE (MIT)
Community vs Pro
| Dimension | Community (free, MIT) | Pro (license key) |
|---|---|---|
| Learning | Manual trigger | 7×24 auto loop |
| Discovery | User-specified | Curiosity-driven |
| Tuning | Static defaults | Dynamic auto-tune |
| Experts | 5 core | 12 total (incl. advanced) |
| Validation | None | Scheduled auto-scan |
| Security | Local rules | SentriKit deep engine |
| License | MIT | License key |
External Dependencies
Only 3 external packages — everything else is Python standard library.
| Package | Purpose |
|---|---|
bcrypt |
Password hashing |
fastapi |
API framework |
uvicorn |
ASGI server |
Why Aelvoxim?
- Lightweight — 3 deps, 34k lines of Python, no Docker required
- Self-contained — SQLite for single-user, PostgreSQL for multi-user
- Private by design — Your data stays on your machine, no telemetry
- Dual storage — SQLite for dev, PostgreSQL for production, same code
- Built-in safety — Ethics rules, safety checks, meta-cognition monitoring
License
MIT License — Copyright (c) 2026 macor24
See LICENSE for details.
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