MetalOS - Autonomous Cognitive Operating System 🧠

Production-grade agentic operating system - Manages Attention, Context, Intent, and Meaning instead of traditional hardware resources. Orchestrates autonomous workflows, content creation, and audience engagement through a quadripartite governance model.

🎯 What It Does

MetalOS is a revolutionary approach to operating systems that replaces hardware resource management with cognitive resource management:

Instead of managing CPU, RAM, and disk, MetalOS manages:

Attention - What deserves focus and why
Context - Historical and situational awareness
Intent - Goals and desired outcomes
Meaning - Understanding and interpretation

💡 Core Capabilities

✅ Autonomous content ideation and generation
✅ AI-powered engagement analysis and response
✅ Intelligent workflow orchestration (n8n + Ollama)
✅ Content Intent Objects (CIO) for structured planning
✅ Work Intent Objects (WIO) for project management
✅ Universal signal inbox for all communication
✅ Vector embeddings for semantic search and memory
✅ Human-in-the-loop governance model
✅ Real-time performance metrics tracking
✅ Lessons learned compounding system

🏛️ Governance Model

MetalOS implements a Quadripartite Governance System:

┌─────────────────────────────────────────────────────┐
│           MetalOS Governance Model                  │
├─────────────────────────────────────────────────────┤
│                                                     │
│  Legislature (LLMs)                                 │
│  ├─ Ollama (Local): Knowledge & Meaning            │
│  ├─ Gemini (Cloud): Advanced Reasoning             │
│  └─ Purpose: Interpret reality & generate options  │
│                                                     │
│  Executive (n8n)                                    │
│  ├─ Workflow Orchestration                         │
│  ├─ Decision Execution                             │
│  └─ Purpose: Execute decisions autonomously        │
│                                                     │
│  Judiciary (Human)                                  │
│  ├─ Review & Approval                              │
│  ├─ Override & Direction                           │
│  └─ Purpose: Governance & safety                   │
│                                                     │
│  People (Signals)                                   │
│  ├─ Feedback & Market Signals                      │
│  ├─ Content Performance Data                       │
│  └─ Purpose: Continuous learning & adaptation      │
│                                                     │
└─────────────────────────────────────────────────────┘

🏗️ Architecture

MetalOS uses a distributed fortress architecture for reliability:

┌─────────────────────────────────────────────────────────┐
│                  MetalOS Fortress                       │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  ┌──────────────┐    ┌──────────────┐    ┌─────────┐  │
│  │ n8n-editor   │───▶│    Redis     │◀───│ n8n-    │  │
│  │ (Brain)      │    │  (Nervous)   │    │ worker  │  │
│  │ :5679        │    │  :6379       │    │(Muscle) │  │
│  └──────────────┘    └──────────────┘    └─────────┘  │
│         │                 │                    │        │
│         └─────────────────┼────────────────────┘        │
│                           ▼                             │
│                  ┌──────────────────┐                   │
│                  │   PostgreSQL     │                   │
│                  │    (Memory)      │                   │
│                  │     :5432        │                   │
│                  └──────────────────┘                   │
│                                                         │
└─────────────────────────────────────────────────────────┘
                           │
                           ▼
                  ┌──────────────────┐
                  │     Ollama       │
                  │  (Legislature)   │
                  │   :11434         │
                  │                  │
                  │  Local LLM       │
                  │  (Host Metal)    │
                  └──────────────────┘

Service Breakdown

Service	Purpose	Port	Status
n8n-editor	Workflow builder & UI	5679	Dashboard
n8n-worker	Async job execution	N/A	Background
PostgreSQL	Primary data store	5432	Database
Redis	Queue & cache	6379	In-Memory
Ollama	Local LLM inference	11434	Host-based

📋 Core Database Schema

Content Intent Objects (CIO)

Manages creative content workflows:

Intent - Goal, message, audience, tone
Context - Source, urgency, strategic pillar
Execution - Platforms, format, constraints
Learning - Predicted vs actual impact
Embeddings - Vector storage for RAG

Work Intent Objects (WIO)

Manages technical/freelance deliverables:

Domain & Client - Project tracking
Scope - In-scope/out-of-scope items
Risk - Profiling and mitigation
Success - Criteria and metrics
Embeddings - Semantic search capability

Signal Objects

Universal inbox for incoming communication:

Source - YouTube, Email, Twitch, etc.
Classification - SPAM, NOISE, OPPORTUNITY, CRITICAL
Raw Payload - Full signal data
Processing - Status and outcome

Lessons Learned

Vector memory for compounding improvement:

Lesson - What was learned
Context - When and why
Impact - Score and measurement
Embeddings - For semantic recall

Execution Metrics

Performance tracking:

Links to CIO/WIO - Context
Metric Name - What's being measured
Time Series - Historical data points

🚀 Quick Start

Prerequisites

Docker Desktop (Mac) or Docker Engine (Linux)
Ollama (for local LLM inference)
16GB+ RAM recommended
50GB+ free disk space

Installation

# Clone repository
git clone https://github.com/slingvector/ai-augmented-live-streaming.git
cd ai-augmented-live-streaming

# Copy environment template
cp .env.example .env

# Generate secure credentials
export DB_PASSWORD=$(openssl rand -base64 32)
export ENCRYPTION_KEY=$(openssl rand -hex 32)

# Update .env with values
nano .env  # Edit and save

Configuration

Edit .env:

# PostgreSQL
DB_USER=n8n
DB_PASSWORD=<generated-above>
DB_NAME=n8n
POSTGRES_HOST=postgres
POSTGRES_PORT=5432

# n8n
N8N_HOST=localhost
N8N_PORT=5679
N8N_PROTOCOL=http
N8N_WEBHOOK_TUNNEL_URL=http://localhost/

# Redis
REDIS_HOST=redis
REDIS_PORT=6379

# Encryption
ENCRYPTION_KEY=<generated-above>

# Ollama
OLLAMA_HOST=http://host.docker.internal:11434
OLLAMA_MODEL=llama3

Launch MetalOS

1. Start Ollama on host:

# macOS
OLLAMA_HOST=0.0.0.0 ollama serve

# Linux/Docker
docker run -d --gpus all -v ollama:/root/.ollama -p 11434:11434 ollama/ollama
ollama run llama3

2. Start the Fortress:

docker-compose up -d

3. Verify services:

docker-compose ps
# All should show "healthy" status

4. Access n8n: Open http://localhost:5679 in your browser

🔐 Environment Setup

Development (Sandbox)

Port: 5678
Database: SQLite
Mode: Monolithic
Use Case: Rapid prototyping

Production (Fortress)

Port: 5679
Database: PostgreSQL
Mode: Queue Mode (distributed)
Use Case: Stable execution

📁 Project Structure

streaming-prod/
├── docs/
│   ├── ARCHITECTURE_SPEC.md      # Deep technical spec
│   ├── BACKEND_STANDARDS.md      # Code standards
│   ├── FRONTEND_STANDARDS.md     # UI/UX standards
│   ├── PRODUCT_REQUIREMENTS.md   # PRD & roadmap
│   └── GOVERNANCE_MODEL.md       # Philosophy & design
├── database/
│   ├── README.md                 # Schema docs
│   ├── schemas/
│   │   ├── content_intent_objects.sql
│   │   ├── work_intent_objects.sql
│   │   ├── signal_objects.sql
│   │   ├── lessons_learned.sql
│   │   └── execution_metrics.sql
│   └── scripts/
│       └── init-database.sh
├── python-bridge/
│   ├── README.md                 # EOE (Emotional Orchestration Engine)
│   ├── eoe_engine.py
│   ├── state_evaluator.py
│   ├── obs_controller.py
│   ├── chat_monitor.py
│   └── audio_monitor.py
├── docker-compose.yml            # Infrastructure definition
├── .env.example                  # Environment template
├── .env.production               # Production config
└── README.md                     # This file

🔄 Implementation Phases

Phase	Status	Component	Purpose
Phase 0	✅ Complete	Fortress Construction	Docker, PostgreSQL, Redis, n8n
Phase 1	🔄 In Progress	Sensory Integration	Universal Inbox, Python Bridge
Phase 2	⏳ Planned	Cognitive Layer	Ollama, Gatekeeper Agent
Phase 3	⏳ Planned	Governance Kernel	CIO Schema, Priority Engine
Phase 4	⏳ Planned	Feedback Loop	Analyst Agent, Vector DB

🛠️ Workflow Examples

Basic Content Generation Flow

{
  "name": "Generate LinkedIn Content",
  "trigger": "Manual",
  "steps": [
    {
      "node": "Ollama - Generate Ideas",
      "action": "POST /api/generate",
      "prompt": "Generate 5 LinkedIn post ideas about AI"
    },
    {
      "node": "Human - Review",
      "action": "Wait for approval"
    },
    {
      "node": "PostgreSQL - Save CIO",
      "action": "Store in content_intent_objects"
    }
  ]
}

Engagement Monitoring Flow

{
  "name": "Monitor & React to Signals",
  "trigger": "Webhook (new signal)",
  "steps": [
    {
      "node": "Signal Classifier",
      "action": "Classify by importance"
    },
    {
      "node": "Ollama - Generate Response",
      "action": "Create contextual reply"
    },
    {
      "node": "Human - Final Check",
      "action": "Approval before posting"
    }
  ]
}

📊 Database Operations

Initialize Database

cd database
./scripts/init-database.sh

Query Content Intent Objects

docker-compose exec postgres psql -U n8n -d n8n -c \
  'SELECT id, primary_goal, core_message FROM content_intent_objects;'

Search via Vector Embeddings

SELECT id, primary_goal, core_message
FROM content_intent_objects
ORDER BY embedding <=> '[your_embedding_vector]'
LIMIT 5;

🚢 Deployment

Docker Compose (Local/Staging)

docker-compose -f docker-compose.yml up -d

Production with Docker Swarm

docker stack deploy -c docker-compose.yml metalos

Production with Kubernetes

kubectl apply -f k8s/namespace.yaml
kubectl apply -f k8s/configmap.yaml
kubectl apply -f k8s/secrets.yaml
kubectl apply -f k8s/deployments.yaml

📈 Monitoring

View All Logs

docker-compose logs -f

Specific Service Logs

docker-compose logs -f n8n-worker
docker-compose logs -f postgres
docker-compose logs -f redis

Health Check

curl http://localhost:5679/healthz

🔧 Troubleshooting

Redis Connection Issues

docker-compose restart redis
docker-compose exec redis redis-cli ping

PostgreSQL Locked

docker-compose exec postgres pg_isready -U n8n

Ollama Not Accessible

curl http://host.docker.internal:11434/api/tags

🛠️ Tech Stack

Component	Technology	Purpose
Orchestration	n8n	Workflow automation
Database	PostgreSQL	Primary data store
Cache/Queue	Redis	State & job queue
LLM	Ollama + Gemini	Intelligence layer
Container	Docker Compose	Infrastructure as Code
Programming	Python + Node.js	Backend & plugins

🤝 Contributing

See CONTRIBUTING.md for guidelines.

📄 License

👨‍💻 Author

Slingvector

GitHub: @slingvector
LinkedIn: Slingvector

🙏 Acknowledgments

Built with:

n8n for workflow orchestration
Ollama for local LLM inference
PostgreSQL for reliable data storage
Redis for high-performance caching
Google Gemini API for advanced reasoning

📞 Support

For issues and questions:

Check Issues
Review Architecture Spec
Check logs with docker-compose logs -f
Open detailed issue with logs and screenshots

🗺️ Roadmap

Phase 0: Fortress Construction
Phase 1: Sensory Integration (Signal inbox, Python bridge)
Phase 2: Cognitive Layer (Ollama agents, reasoning)
Phase 3: Governance Kernel (Priority engine, CIO schema)
Phase 4: Feedback Loop (Analytics, vector memory)
Multi-modal understanding (Vision + Audio)
Predictive analytics
Autonomous decision-making with human oversight

⭐ If you find this useful, please star the repository!

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
database		database
docs		docs
python-bridge		python-bridge
scripts		scripts
workflows		workflows
.env.example		.env.example
.env.production.example		.env.production.example
.gitignore		.gitignore
MILESTONE_COMPLETE.md		MILESTONE_COMPLETE.md
PROJECT_COMPLETE.md		PROJECT_COMPLETE.md
README.md		README.md
RELEASE_NOTES.md		RELEASE_NOTES.md
STATUS.md		STATUS.md
SYSTEM_REVIEW.md		SYSTEM_REVIEW.md
docker-compose.prod.yml		docker-compose.prod.yml
docker-compose.yml		docker-compose.yml
execution_24.json		execution_24.json
streaming-prod.code-workspace		streaming-prod.code-workspace

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MetalOS - Autonomous Cognitive Operating System 🧠

🎯 What It Does

💡 Core Capabilities

🏛️ Governance Model

🏗️ Architecture

Service Breakdown

📋 Core Database Schema

Content Intent Objects (CIO)

Work Intent Objects (WIO)

Signal Objects

Lessons Learned

Execution Metrics

🚀 Quick Start

Prerequisites

Installation

Configuration

Launch MetalOS

🔐 Environment Setup

Development (Sandbox)

Production (Fortress)

📁 Project Structure

🔄 Implementation Phases

🛠️ Workflow Examples

Basic Content Generation Flow

Engagement Monitoring Flow

📊 Database Operations

Initialize Database

Query Content Intent Objects

Search via Vector Embeddings

🚢 Deployment

Docker Compose (Local/Staging)

Production with Docker Swarm

Production with Kubernetes

📈 Monitoring

View All Logs

Specific Service Logs

Health Check

🔧 Troubleshooting

Redis Connection Issues

PostgreSQL Locked

Ollama Not Accessible

🛠️ Tech Stack

🤝 Contributing

📄 License

👨‍💻 Author

🙏 Acknowledgments

📞 Support

🗺️ Roadmap

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