import boto3

def generate_tagging_rules(policy_description):
    """AI generates tagging rules from policy description."""
    # In practice, this calls an AI service to translate
    # natural language policy into AWS Config rule definitions
    pass

def apply_compliance_rules(rules):
    config = boto3.client('config')
    for rule in rules:
        config.put_config_rule(ConfigRule=rule)

# Example: AI-generated rule requires 'Environment' tag
rules = generate_tagging_rules(
    "All resources must have Environment tag with values prod, staging, or dev"
)
apply_compliance_rules(rules)

class CloudTagMapper:
    """Maps tags across cloud providers with AI-assisted inference."""

    def __init__(self, ai_service):
        self.ai = ai_service

    def normalize_tags(self, resource, provider):
        """Convert provider-specific tags to standardized schema."""
        standard_schema = {
            'environment': ['Environment', 'env', 'stage'],
            'team': ['Owner', 'Team', 'department'],
            'cost_center': ['CostCenter', 'cost-center', 'billingcode']
        }

        # AI infers which native tags map to standard schema
        return self.ai.infer_tag_mapping(resource.tags, standard_schema)

import boto3
from anthropic import Anthropic

class EnterpriseTaggingOrchestrator:
    """AI-assisted tagging enforcement across AWS accounts."""

    def __init__(self, region: str = "us-east-1"):
        self.ec2 = boto3.client("ec2", region_name=region)
        self.client = Anthropic()
        self.compliance_policy = self._load_compliance_policy()

    def _load_compliance_policy(self) -> str:
        return """All AWS resources must have:
- Environment: dev, staging, prod
- CostCenter: valid cost center code
- Owner: team name or email
- Application: application name
- DataClassification: public, internal, confidential, restricted
"""

    def infer_tags_from_resource(self, resource: dict) -> dict:
        """Use Claude to infer appropriate tags from resource attributes."""

        prompt = f"""Given this AWS resource:
Name: {resource.get('Name', 'unknown')}
Type: {resource.get('Type', 'unknown')}
Created: {resource.get('CreatedTime', 'unknown')}

And this tagging policy:
{self.compliance_policy}

Suggest appropriate tags as JSON."""

        message = self.client.messages.create(
            model="claude-3-5-sonnet-20241022",
            max_tokens=500,
            messages=[{"role": "user", "content": prompt}]
        )

        return self._parse_tag_suggestions(message.content[0].text)

    def audit_tagging_compliance(self, account_id: str) -> dict:
        """Scan all resources and identify tagging gaps."""

        resources = self.ec2.describe_instances()
        non_compliant = []

        required_tags = ["Environment", "CostCenter", "Owner", "Application"]

        for reservation in resources["Reservations"]:
            for instance in reservation["Instances"]:
                tags = {t["Key"]: t["Value"] for t in instance.get("Tags", [])}
                missing = [t for t in required_tags if t not in tags]

                if missing:
                    non_compliant.append({
                        "resource_id": instance["InstanceId"],
                        "resource_type": "EC2",
                        "missing_tags": missing,
                        "current_tags": tags
                    })

        return {
            "account": account_id,
            "total_non_compliant": len(non_compliant),
            "resources": non_compliant,
            "compliance_percentage": 100 * (1 - len(non_compliant) / len(resources["Reservations"]))
        }

    def auto_remediate_tags(self, resources: list) -> dict:
        """Automatically apply inferred tags to non-compliant resources."""

        remediated = []
        failed = []

        for resource in resources:
            try:
                inferred_tags = self.infer_tags_from_resource(resource)
                self.ec2.create_tags(
                    Resources=[resource["id"]],
                    Tags=[
                        {"Key": k, "Value": v}
                        for k, v in inferred_tags.items()
                    ]
                )
                remediated.append(resource["id"])
            except Exception as e:
                failed.append({"resource": resource["id"], "error": str(e)})

        return {
            "remediated": len(remediated),
            "failed": len(failed),
            "details": {"success": remediated, "errors": failed}
        }

    def _parse_tag_suggestions(self, response: str) -> dict:
        """Extract tags from Claude response."""
        import json
        import re
        match = re.search(r'\{[^}]+\}', response, re.DOTALL)
        if match:
            try:
                return json.loads(match.group())
            except json.JSONDecodeError:
                return {}
        return {}

# Usage
orchestrator = EnterpriseTaggingOrchestrator()

# Audit compliance
audit_results = orchestrator.audit_tagging_compliance("123456789012")
print(f"Compliance: {audit_results['compliance_percentage']:.1f}%")

# Auto-remediate non-compliant resources
if audit_results['resources']:
    remediation = orchestrator.auto_remediate_tags(audit_results['resources'][:10])
    print(f"Remediated: {remediation['remediated']} resources")

class MultiCloudTagSynchronizer:
    """Synchronize and normalize tags across AWS, Azure, and GCP."""

    def __init__(self):
        self.aws = boto3.client("ec2")
        self.azure = None  # Azure SDK client
        self.gcp = None    # GCP client
        self.client = Anthropic()

    def normalize_cross_cloud_tags(self, aws_tags: dict, azure_tags: dict) -> dict:
        """Use Claude to normalize tags from different clouds."""

        prompt = f"""Normalize these tags from different cloud providers:
AWS tags: {aws_tags}
Azure tags: {azure_tags}

Provide normalized tags that work across both platforms."""

        message = self.client.messages.create(
            model="claude-3-5-sonnet-20241022",
            max_tokens=300,
            messages=[{"role": "user", "content": prompt}]
        )

        return self._parse_normalized_tags(message.content[0].text)

    def _parse_normalized_tags(self, response: str) -> dict:
        """Extract normalized tags from response."""
        import json
        import re
        match = re.search(r'\{[^}]+\}', response, re.DOTALL)
        if match:
            try:
                return json.loads(match.group())
            except json.JSONDecodeError:
                return {}
        return {}

    def sync_tags_across_providers(self, resource_id: str, source_tags: dict):
        """Apply the same tags across multiple cloud providers."""
        normalized = self.normalize_cross_cloud_tags(source_tags, {})

        # Apply to AWS
        self.aws.create_tags(
            Resources=[resource_id],
            Tags=[{"Key": k, "Value": v} for k, v in normalized.items()]
        )

        # Apply to Azure, GCP with same normalized tags
        # ... additional cloud provider updates