- Added Agent Lightning research section to researcher.html with Demo 2 results - Created comprehensive /integrations/agent-lightning.html page - Added Agent Lightning link in homepage hero section - Updated Discord invite links (Tractatus + semantipy) across all pages - Added feedback.js script to all key pages for live demonstration Phase 2 of Master Plan complete: Discord setup → Website completion 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
221 lines
7.5 KiB
Markdown
221 lines
7.5 KiB
Markdown
# Demo 3: Full-Stack Production Architecture
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## Purpose
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This demo shows a **production-ready** implementation of Agent Lightning + Tractatus integration with:
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- Complete observability (metrics, logging, tracing)
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- Error handling and recovery
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- Scaling considerations
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- Deployment architecture
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- Monitoring dashboards
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## Architecture
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```
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┌──────────────────────────────────────────────────────────┐
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│ PRODUCTION SYSTEM │
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├──────────────────────────────────────────────────────────┤
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│ │
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│ ┌─────────────────────────────────────────────────┐ │
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│ │ TRACTATUS GOVERNANCE LAYER │ │
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│ │ • BoundaryEnforcer │ │
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│ │ • PluralisticDeliberator │ │
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│ │ • CrossReferenceValidator │ │
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│ │ • ContextPressureMonitor │ │
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│ │ • MetacognitiveVerifier │ │
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│ └─────────────────────────────────────────────────┘ │
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│ ↓ │
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│ ┌─────────────────────────────────────────────────┐ │
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│ │ AGENT LIGHTNING PERFORMANCE LAYER │ │
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│ │ • AgentLightningClient (training) │ │
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│ │ • AgentLightningServer (serving) │ │
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│ │ • LightningStore (data repository) │ │
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│ └─────────────────────────────────────────────────┘ │
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│ ↓ │
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│ ┌─────────────────────────────────────────────────┐ │
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│ │ OBSERVABILITY LAYER │ │
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│ │ • Prometheus metrics │ │
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│ │ • OpenTelemetry tracing │ │
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│ │ • Structured logging │ │
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│ │ • Grafana dashboards │ │
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│ └─────────────────────────────────────────────────┘ │
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│ │
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└──────────────────────────────────────────────────────────┘
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```
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## Features
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### 1. Governance Features
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- ✓ Real-time boundary enforcement
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- ✓ Stakeholder deliberation workflows
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- ✓ Constraint validation
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- ✓ Audit trail (all decisions logged)
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- ✓ Emergency stop mechanisms
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### 2. Performance Features
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- ✓ RL-based optimization
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- ✓ Continuous learning
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- ✓ Multi-agent coordination
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- ✓ Horizontal scaling
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- ✓ Load balancing
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### 3. Observability Features
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- ✓ Metrics: Performance, governance, system health
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- ✓ Tracing: Request flows, decision paths
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- ✓ Logging: Structured, searchable
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- ✓ Dashboards: Real-time monitoring
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### 4. Production Features
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- ✓ Error recovery
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- ✓ Circuit breakers
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- ✓ Rate limiting
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- ✓ Health checks
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- ✓ Graceful degradation
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## Use Cases
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This architecture supports:
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1. **High-throughput AI applications** (e.g., content moderation at scale)
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2. **Safety-critical systems** (e.g., healthcare, finance)
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3. **Multi-stakeholder platforms** (e.g., social media, marketplaces)
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4. **Regulated industries** (e.g., legal, government)
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## Running the Demo
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### Prerequisites
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```bash
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# Docker & Docker Compose (for observability stack)
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docker --version
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docker-compose --version
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# Python environment
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python3 -m venv venv
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source venv/bin/activate
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pip install -r requirements.txt
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```
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### Start Observability Stack
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```bash
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# Start Prometheus, Grafana, Jaeger
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docker-compose up -d
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```
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### Run System
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```bash
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python main.py
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```
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### Access Dashboards
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- **Grafana**: http://localhost:3000 (admin/admin)
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- **Prometheus**: http://localhost:9090
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- **Jaeger**: http://localhost:16686
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## Directory Structure
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```
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demo3-full-stack/
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├── main.py # Main application entry point
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├── requirements.txt # Python dependencies
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├── docker-compose.yml # Observability stack
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├── governance/
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│ ├── __init__.py
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│ ├── boundary_enforcer.py # Production BoundaryEnforcer
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│ ├── deliberator.py # Production Deliberator
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│ └── validator.py # Production Validator
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├── performance/
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│ ├── __init__.py
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│ ├── al_client.py # AL client wrapper
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│ └── optimizer.py # Optimization logic
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├── observability/
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│ ├── __init__.py
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│ ├── metrics.py # Prometheus metrics
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│ ├── tracing.py # OpenTelemetry setup
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│ └── logging.py # Structured logging
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├── config/
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│ ├── governance_rules.yaml # Governance configuration
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│ ├── al_config.yaml # AL configuration
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│ └── observability.yaml # Metrics/tracing config
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└── dashboards/
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├── governance.json # Grafana dashboard
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├── performance.json # Performance metrics
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└── system-health.json # Overall health
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```
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## Key Metrics
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### Governance Metrics
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```
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tractatus_boundary_checks_total
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tractatus_approvals_total
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tractatus_rejections_total
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tractatus_deliberation_duration_seconds
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tractatus_constraint_violations_total
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```
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### Performance Metrics
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```
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al_training_rounds_total
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al_optimization_duration_seconds
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al_task_success_rate
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al_performance_improvement_percent
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```
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### System Metrics
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```
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system_request_duration_seconds
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system_error_rate
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system_throughput_requests_per_second
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```
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## Deployment
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### Docker
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```bash
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docker build -t governed-agent:latest .
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docker run -p 8000:8000 governed-agent:latest
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```
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### Kubernetes
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```yaml
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: governed-agent
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spec:
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replicas: 3
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selector:
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matchLabels:
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app: governed-agent
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template:
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metadata:
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labels:
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app: governed-agent
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spec:
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containers:
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- name: governed-agent
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image: governed-agent:latest
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ports:
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- containerPort: 8000
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env:
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- name: AL_SERVER_URL
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value: "http://al-server:8080"
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```
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## Next Steps
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- [ ] Deploy to staging environment
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- [ ] Load testing (target: 1000 req/s)
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- [ ] Security audit
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- [ ] Compliance review
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- [ ] Documentation finalization
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- [ ] Production deployment
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## Files
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All implementation files are in this directory. See code for production-grade examples.
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---
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**Last Updated**: November 2, 2025
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**Purpose**: Production-ready governed AI system
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**Status**: Reference architecture (implementation in progress)
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