Stablecoin Regulatory Compliance: Ollama MiCA and Global Standards Tracker

# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Create compliance tracking directory
mkdir -p /opt/compliance-tracker/{logs,models,reports}
chmod 755 /opt/compliance-tracker

# Set environment variables for compliance logging
export OLLAMA_DEBUG=1
export OLLAMA_VERBOSE=1
export OLLAMA_LOG_LEVEL=debug
export OLLAMA_LOG_DIR=/opt/compliance-tracker/logs

# Pull models for different compliance tasks
ollama pull llama3.1:8b        # General compliance analysis
ollama pull codellama:7b       # Regulatory code analysis
ollama pull mistral:7b         # Multi-language regulatory documents

#!/usr/bin/env python3
"""
MiCA Stablecoin Compliance Monitor
Tracks regulatory requirements using local Ollama instance
"""

import requests
import json
import logging
from datetime import datetime, timedelta
import asyncio

class MiCAComplianceMonitor:
    def __init__(self, ollama_url="http://localhost:11434"):
        self.ollama_url = ollama_url
        self.setup_logging()
        
    def setup_logging(self):
        """Configure compliance audit logging"""
        logging.basicConfig(
            level=logging.INFO,
            format='%(asctime)s - %(levelname)s - %(message)s',
            handlers=[
                logging.FileHandler('/opt/compliance-tracker/logs/mica_compliance.log'),
                logging.StreamHandler()
            ]
        )
        self.logger = logging.getLogger(__name__)
    
    async def check_reserve_requirements(self, stablecoin_data):
        """Monitor MiCA reserve requirements (30% liquid assets)"""
        prompt = f"""
        Analyze the following stablecoin reserve data for MiCA compliance:
        
        Reserve Data: {json.dumps(stablecoin_data, indent=2)}
        
        Check:
        1. Are at least 30% of reserves in highly liquid assets?
        2. Is the 1:1 backing ratio maintained?
        3. Are reserves held in EU financial institutions?
        
        Provide compliance status and recommendations.
        """
        
        response = requests.post(f"{self.ollama_url}/api/generate", 
                               json={
                                   "model": "llama3.1:8b",
                                   "prompt": prompt,
                                   "stream": False
                               })
        
        result = response.json()
        self.logger.info(f"Reserve compliance check completed: {result['response'][:100]}...")
        return result['response']
    
    async def monitor_transaction_limits(self, daily_volume):
        """Track daily transaction volume against €200M limit"""
        if daily_volume > 200_000_000:  # €200 million
            alert_msg = f"ALERT: Daily volume {daily_volume:,.2f} EUR exceeds MiCA limit"
            self.logger.warning(alert_msg)
            return {
                "status": "VIOLATION",
                "message": alert_msg,
                "action_required": "Implement volume controls or seek systemic designation"
            }
        
        return {
            "status": "COMPLIANT",
            "volume": daily_volume,
            "remaining_capacity": 200_000_000 - daily_volume
        }
    
    async def generate_compliance_report(self, compliance_data):
        """Generate automated MiCA compliance report"""
        prompt = f"""
        Generate a comprehensive MiCA compliance report based on:
        
        {json.dumps(compliance_data, indent=2)}
        
        Include:
        - Executive summary of compliance status
        - Key regulatory requirements assessment
        - Risk factors and mitigation strategies
        - Recommendations for ongoing compliance
        
        Format as structured markdown report.
        """
        
        response = requests.post(f"{self.ollama_url}/api/generate",
                               json={
                                   "model": "llama3.1:8b",
                                   "prompt": prompt,
                                   "stream": False
                               })
        
        # Save report to file
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        report_path = f"/opt/compliance-tracker/reports/mica_report_{timestamp}.md"
        
        with open(report_path, 'w') as f:
            f.write(response.json()['response'])
        
        self.logger.info(f"Compliance report generated: {report_path}")
        return report_path

# Usage example
async def main():
    monitor = MiCAComplianceMonitor()
    
    # Sample stablecoin data
    sample_data = {
        "reserves": {
            "total_value_eur": 100_000_000,
            "liquid_assets_eur": 35_000_000,  # 35% liquid
            "government_bonds_eur": 50_000_000,
            "bank_deposits_eur": 15_000_000
        },
        "daily_volume_eur": 150_000_000,
        "token_holders": 500_000
    }
    
    # Run compliance checks
    reserve_check = await monitor.check_reserve_requirements(sample_data["reserves"])
    volume_check = await monitor.monitor_transaction_limits(sample_data["daily_volume_eur"])
    
    # Generate report
    compliance_data = {
        "reserve_analysis": reserve_check,
        "volume_analysis": volume_check,
        "timestamp": datetime.now().isoformat()
    }
    
    report_path = await monitor.generate_compliance_report(compliance_data)
    print(f"Compliance monitoring complete. Report saved to: {report_path}")

if __name__ == "__main__":
    asyncio.run(main())

class GlobalRegulatoryMonitor:
    def __init__(self, ollama_url="http://localhost:11434"):
        self.ollama_url = ollama_url
        self.jurisdictions = ["EU", "US", "UK", "HK", "SG", "JP"]
        
    async def scan_regulatory_updates(self, jurisdiction):
        """Scan for new regulatory developments"""
        prompt = f"""
        Analyze recent regulatory developments for stablecoins in {jurisdiction}.
        
        Focus on:
        - New legislation or guidance
        - Implementation deadlines
        - Compliance requirement changes
        - Enforcement actions
        
        Provide structured analysis with action items.
        """
        
        response = requests.post(f"{self.ollama_url}/api/generate",
                               json={
                                   "model": "llama3.1:8b",
                                   "prompt": prompt,
                                   "stream": False
                               })
        
        return {
            "jurisdiction": jurisdiction,
            "analysis": response.json()['response'],
            "timestamp": datetime.now().isoformat()
        }
    
    async def compliance_gap_analysis(self, current_compliance, target_jurisdiction):
        """Identify compliance gaps for new jurisdictions"""
        prompt = f"""
        Perform gap analysis for expanding stablecoin operations to {target_jurisdiction}.
        
        Current compliance status: {json.dumps(current_compliance, indent=2)}
        
        Identify:
        - Additional requirements for {target_jurisdiction}
        - Timeline for compliance implementation
        - Resource requirements
        - Risk assessment
        """
        
        response = requests.post(f"{self.ollama_url}/api/generate",
                               json={
                                   "model": "llama3.1:8b",
                                   "prompt": prompt,
                                   "stream": False
                               })
        
        return response.json()['response']

class ComplianceAlertSystem:
    def __init__(self):
        self.alert_thresholds = {
            "reserve_ratio": 0.30,  # 30% minimum liquid assets
            "daily_volume_eur": 200_000_000,  # €200M daily limit
            "reporting_deadline_days": 7  # 7 days before deadlines
        }
    
    def check_critical_alerts(self, metrics):
        """Check for critical compliance violations"""
        alerts = []
        
        # Reserve ratio check
        liquid_ratio = metrics.get("liquid_assets_ratio", 0)
        if liquid_ratio < self.alert_thresholds["reserve_ratio"]:
            alerts.append({
                "type": "CRITICAL",
                "message": f"Liquid assets ratio {liquid_ratio:.2%} below MiCA requirement",
                "action": "Increase liquid asset allocation immediately"
            })
        
        # Volume limit check
        daily_volume = metrics.get("daily_volume_eur", 0)
        if daily_volume > self.alert_thresholds["daily_volume_eur"]:
            alerts.append({
                "type": "WARNING",
                "message": f"Daily volume {daily_volume:,.0f} EUR approaching €200M limit",
                "action": "Consider volume controls or systemic designation"
            })
        
        return alerts

compliance_matrix = {
    "EU_MiCA": {
        "liquid_assets_min": 0.30,
        "daily_volume_limit": 200_000_000,
        "reporting_frequency": "real_time",
        "authorization_required": True
    },
    "US_GENIUS": {
        "reserve_backing": 1.0,
        "audit_frequency": "quarterly",
        "licensing_required": True,
        "interest_permitted": True
    },
    "UK_Framework": {
        "fiat_backing_required": True,
        "payment_focus": True,
        "boe_oversight": True
    }
}

async def calculate_compliance_score(self, jurisdiction, current_status):
    """Calculate compliance score for specific jurisdiction"""
    prompt = f"""
    Calculate compliance score (0-100) for {jurisdiction} based on:
    
    Current Status: {json.dumps(current_status, indent=2)}
    
    Consider:
    - Regulatory requirement fulfillment
    - Documentation completeness
    - Operational compliance
    - Risk mitigation measures
    
    Provide score with detailed breakdown.
    """
    
    response = requests.post(f"{self.ollama_url}/api/generate",
                           json={
                               "model": "llama3.1:8b",
                               "prompt": prompt,
                               "stream": False
                           })
    
    return response.json()['response']

# Secure Ollama deployment
# Create dedicated compliance user
sudo useradd -m -s /bin/bash compliance-monitor

# Set up firewall rules
sudo ufw allow from 10.0.0.0/8 to any port 11434
sudo ufw deny from any to any port 11434

# Configure reverse proxy with authentication
# nginx.conf snippet
location /api/ {
    auth_basic "Compliance API";
    auth_basic_user_file /etc/nginx/.htpasswd;
    proxy_pass http://localhost:11434;
}

def log_compliance_action(self, action_type, details):
    """Log all compliance-related actions for audit"""
    audit_entry = {
        "timestamp": datetime.now().isoformat(),
        "action_type": action_type,
        "details": details,
        "user": os.getenv("USER"),
        "system": "ollama_compliance_tracker"
    }
    
    with open("/opt/compliance-tracker/logs/audit.log", "a") as f:
        f.write(json.dumps(audit_entry) + "\n")

# docker-compose.yml for production deployment
version: '3.8'
services:
  ollama:
    image: ollama/ollama:latest
    volumes:
      - ./models:/root/.ollama
      - ./logs:/var/log/ollama
    environment:
      - OLLAMA_DEBUG=1
      - OLLAMA_LOG_LEVEL=info
    ports:
      - "127.0.0.1:11434:11434"
    restart: unless-stopped
    
  compliance-monitor:
    build: ./compliance-monitor
    depends_on:
      - ollama
    volumes:
      - ./compliance-data:/data
      - ./reports:/reports
    environment:
      - OLLAMA_URL=http://ollama:11434
    restart: unless-stopped

# Prometheus metrics for compliance monitoring
from prometheus_client import Counter, Histogram, Gauge

compliance_checks = Counter('compliance_checks_total', 'Total compliance checks performed')
compliance_violations = Counter('compliance_violations_total', 'Total compliance violations detected')
processing_time = Histogram('compliance_processing_seconds', 'Time spent processing compliance checks')
current_compliance_score = Gauge('compliance_score', 'Current compliance score', ['jurisdiction'])