backend/models/agent_schema.py

ALLOWED_CAPABILITIES = [
    "analysis",
    "api_development",
    "architecture",  # Added - general architecture capability
    "automation",
    "budgeting",
    "change_management",
    "chat",
    "cloud_architecture",
    "coaching",
    "code_generation",
    "code_review",
    "coding",
    "communication",
    "compliance_check",
    "contract_review",
    "coordination",
    "data_analysis",
    "diagnosis",
    "debugging",
    "devops",
    "diagnosis_support",
    "documentation",
    "economic_analysis",
    "financial_analysis",
    "financial_planning",
    "healthcare_consulting",
    "infrastructure_design",
    "investment_strategy",
    "knowledge_management",
    "leadership_training",
    "legal_analysis",
    "legal_research",
    "legal_writing",
    "litigation_support",
    "market_research",
    "medical_analysis",
    "medical_research",
    "mentoring",
    "monitoring",
    "multi_agent_coordination",
    "negotiation",
    "orchestration",  # Added - workflow orchestration capability
    "organizational_development",
    "patient_care",
    "performance_management",
    "performance_optimization",
    "planning",
    "portfolio_management",
    "presentation",
    "project_management",
    "quality_assurance",
    "refactoring",
    "regulatory_advice",
    "reporting",
    "research",
    "resource_management",
    "risk_assessment",
    "security",
    "software_architecture",
    "strategy",  # Added - general strategy capability
    "system_integration",
    "team_building",
    "testing",
    "translation",
    "treatment_planning",
    "writing",
]

"""
SAAP Agent Schema Definition
Modular JSON-based agent configuration system
"""

from typing import Dict, List, Optional, Any, Literal
from pydantic import BaseModel, Field, validator
from datetime import datetime
from enum import Enum

class AgentStatus(str, Enum):
    """Agent operational status"""
    INACTIVE = "inactive"
    STARTING = "starting" 
    ACTIVE = "active"
    STOPPING = "stopping"
    ERROR = "error"
    MAINTENANCE = "maintenance"

class AgentType(str, Enum):
    """Agent role classification"""
    COORDINATOR = "coordinator"      # Jane Alesi - System coordination
    DEVELOPER = "developer"          # John Alesi - Software development
    SPECIALIST = "specialist"        # Lara, Justus - Domain experts
    GENERALIST = "generalist"        # Multi-purpose agents
    TOOL_USER = "tool_user"         # Agents with external tool access
    MONITOR = "monitor"             # System monitoring agents

class MessageType(str, Enum):
    """Supported message types for agent communication"""
    REQUEST = "request"
    RESPONSE = "response" 
    NOTIFICATION = "notification"
    BROADCAST = "broadcast"
    COORDINATION = "coordination"
    SYSTEM_STATUS = "system_status"
    AGENT_MANAGEMENT = "agent_management"

# ===== 🔧 EXTENDED ALLOWED CAPABILITIES REGISTRY =====
ALLOWED_CAPABILITIES = {
    # Core system capabilities
    "system_coordination", "multi_agent_management", "architecture_planning", "decision_making",
    "coordination", "orchestration", "workflow_management", "strategy", "architecture",
    
    # Development capabilities
    "code_generation", "debugging", "architecture_design", "code_review", "testing", "deployment",
    "performance_optimization", "refactoring", "documentation", "development", "programming",
    "software_engineering", "implementation", "coding",
    
    # Medical capabilities - 🔧 EXPANDED
    "medical_analysis", "clinical_decision_support", "health_data_analysis", "medical_research",
    "patient_care", "diagnosis_support", "medical_documentation", "healthcare", "clinical",
    "health", "medical", "diagnosis", "treatment",
    
    # Financial capabilities  
    "financial_analysis", "market_research", "investment_strategy", "risk_assessment", 
    "fintech_development", "budget_planning", "cost_analysis", "financial_reporting",
    "finance", "investment", "banking", "economic_analysis",
    
    # Legal capabilities
    "legal_compliance", "gdpr_analysis", "contract_review", "regulatory_analysis",
    "fintech_law", "data_protection", "privacy_assessment", "legal_documentation",
    "legal", "compliance", "law", "regulation",
    
    # System administration capabilities
    "system_administration", "infrastructure_deployment", "security_implementation",
    "performance_optimization", "monitoring", "backup_management", "network_administration",
    "system", "infrastructure", "security", "devops",
    
    # Coaching and organizational capabilities
    "team_coaching", "organizational_development", "process_optimization", "change_management",
    "training", "mentoring", "team_building", "communication_facilitation",
    "coaching", "organization", "team_development",
    
    # General capabilities - 🔧 EXPANDED
    "data_analysis", "research", "communication", "project_management", "quality_assurance",
    "user_support", "content_creation", "translation", "analysis", "reporting",
    "problem_solving", "consulting", "advisory", "support", "assistance",
    
    # 🔧 NEW: Additional capabilities found in database
    "multi_agent_coordination", "task_delegation", "workflow_orchestration",
    "knowledge_management", "information_retrieval", "natural_language_processing",
    "machine_learning", "artificial_intelligence", "automation", "integration",
    "api_development", "database_management", "web_development", "mobile_development",
    "cloud_computing", "distributed_systems", "microservices", "containerization",
    "continuous_integration", "continuous_deployment", "version_control",
    
    # Business and domain-specific capabilities
    "business_analysis", "requirements_engineering", "product_management",
    "customer_support", "sales", "marketing", "human_resources", "operations",
    "supply_chain", "logistics", "manufacturing", "retail", "e_commerce",
    
    # Advanced technical capabilities
    "cybersecurity", "penetration_testing", "vulnerability_assessment",
    "incident_response", "disaster_recovery", "business_continuity",
    "performance_tuning", "load_balancing", "scalability", "high_availability"
}

# ===== NESTED MODELS =====

class AgentMetadata(BaseModel):
    """Agent version and lifecycle metadata"""
    version: str = Field(..., description="Agent configuration version")
    created: datetime = Field(default_factory=datetime.utcnow)
    updated: datetime = Field(default_factory=datetime.utcnow)
    creator: Optional[str] = Field(None, description="Who created this agent")
    tags: List[str] = Field(default_factory=list, description="Organizational tags")

class AgentAppearance(BaseModel):
    """Agent appearance and visual configuration"""
    color: str = Field(default="#6B7280", pattern=r'^#[0-9A-Fa-f]{6}$', description="Hex color code")
    avatar_url: Optional[str] = Field(default=None, description="URL to agent avatar image")
    avatar: Optional[str] = Field(default=None, description="Avatar identifier or URL")
    display_name: Optional[str] = Field(default=None, description="Display name for UI")
    subtitle: Optional[str] = Field(default=None, description="Subtitle or role description")
    description: Optional[str] = Field(default=None, description="Visual description")
    icon: Optional[str] = Field(default=None, description="Icon identifier")
    theme: Optional[str] = Field(default="default", description="Visual theme")
class LLMConfig(BaseModel):
    """LLM model configuration"""
    model: str = Field(..., description="Ollama model name (e.g., 'phi3:mini')")
    temperature: float = Field(0.7, ge=0.0, le=2.0, description="Response randomness")
    max_tokens: int = Field(2048, ge=64, le=8192, description="Maximum response length")
    top_p: float = Field(0.9, ge=0.0, le=1.0, description="Nucleus sampling threshold")
    system_prompt: str = Field(..., min_length=10, description="Agent personality/instructions")
    
    # Advanced LLM settings
    stop_sequences: List[str] = Field(default_factory=list, description="Stop generation at these sequences")
    context_window: int = Field(4096, ge=512, le=32768, description="Context memory size")
    
    @validator('model')
    def validate_model(cls, v):
        """Ensure model name follows Ollama conventions"""
        if not v or ':' not in v:
            raise ValueError("Model must be in format 'name:version' (e.g., 'phi3:mini')")
        return v.lower()

class CommunicationConfig(BaseModel):
    """Message queue and communication settings"""
    input_queue: str = Field(..., description="Redis queue for incoming messages")
    output_queue: str = Field(..., description="Redis queue for outgoing messages")
    message_types: List[MessageType] = Field(..., description="Supported message types")
    
    # Advanced communication settings
    max_queue_size: int = Field(1000, ge=10, le=10000, description="Maximum queued messages")
    message_ttl: int = Field(3600, ge=60, le=86400, description="Message TTL in seconds")
    priority_handling: bool = Field(True, description="Support priority message processing")

class UIComponents(BaseModel):
    """Frontend component configuration"""
    dashboard_widget: str = Field("AgentCard", description="Dashboard card component name")
    detail_view: str = Field("AgentDetail", description="Detail view component name") 
    configuration_form: str = Field("AgentConfig", description="Configuration form component")
    
    # Additional UI customization
    custom_css: Optional[str] = Field(None, description="Custom CSS classes")
    icon: Optional[str] = Field(None, description="Icon identifier")

class AgentCapability(BaseModel):
    """Individual capability definition"""
    name: str = Field(..., description="Capability identifier")
    display_name: str = Field(..., description="Human-readable capability name")
    description: str = Field(..., description="Capability description")
    confidence: float = Field(1.0, ge=0.0, le=1.0, description="Agent confidence in this capability")
    
    # Capability metadata
    category: str = Field("general", description="Capability category")
    required_tools: List[str] = Field(default_factory=list, description="Required external tools")

# ===== MAIN AGENT MODEL =====

class SaapAgent(BaseModel):
    """Complete SAAP Agent Definition"""
    
    # ===== CORE IDENTITY =====
    id: str = Field(..., pattern=r"^[a-z0-9_]{3,32}$", description="Unique agent identifier")
    name: str = Field(..., min_length=1, max_length=64, description="Agent name")
    type: AgentType = Field(..., description="Agent role classification")
    status: AgentStatus = Field(AgentStatus.INACTIVE, description="Current operational status")
    
    # ===== DIRECT FIELDS FOR COMPATIBILITY =====
    description: str = Field(..., min_length=1, max_length=512, description="Agent description (direct field)")
    
    # ===== METADATA =====
    metadata: AgentMetadata = Field(..., description="Version and lifecycle information")
    
    # ===== VISUAL & UI =====
    appearance: AgentAppearance = Field(..., description="Visual representation")
    ui_components: UIComponents = Field(..., description="Frontend component configuration")
    
    # ===== CAPABILITIES =====
    capabilities: List[str] = Field(..., min_items=1, description="Agent capability identifiers")
    detailed_capabilities: Optional[List[AgentCapability]] = Field(None, description="Detailed capability definitions")
    
    # ===== AI CONFIGURATION =====
    llm_config: LLMConfig = Field(..., description="Language model configuration")
    
    # ===== COMMUNICATION =====
    communication: CommunicationConfig = Field(..., description="Message queue configuration")
    
    # ===== EXTENSIBILITY =====
    custom_config: Dict[str, Any] = Field(default_factory=dict, description="Agent-specific custom configuration")
    
    # ===== VALIDATION =====
    
    @validator('id')
    def validate_id(cls, v):
        """Ensure agent ID follows naming conventions"""
        if not v.islower():
            raise ValueError("Agent ID must be lowercase")
        if v.startswith('_') or v.endswith('_'):
            raise ValueError("Agent ID cannot start or end with underscore")
        return v
    
    @validator('capabilities')
    def validate_capabilities(cls, v):
        """🔧 ENHANCED: Validate capabilities against expanded allowed list"""
        if not v:
            raise ValueError("Agent must have at least one capability")
        
        # Normalize and validate capability names
        normalized = []
        for cap in v:
            if not isinstance(cap, str):
                raise ValueError("All capabilities must be strings")
            
            # Normalize capability name
            normalized_cap = cap.lower().replace(' ', '_').replace('-', '_')
            
            # 🔧 CHECK AGAINST EXTENDED ALLOWED CAPABILITIES
            if normalized_cap not in ALLOWED_CAPABILITIES:
                # Try to find close matches for better error messages
                suggestions = [c for c in ALLOWED_CAPABILITIES if cap.lower() in c or c in cap.lower()]
                if suggestions:
                    raise ValueError(f"Invalid capability: {cap}. Did you mean one of: {suggestions[:3]}?")
                else:
                    # 🔧 More lenient approach - auto-add to allowed if it's reasonable
                    if len(cap) > 3 and '_' in cap or cap.isalpha():
                        print(f"⚠️ Auto-allowing new capability: {cap}")
                        ALLOWED_CAPABILITIES.add(normalized_cap)
                        normalized.append(normalized_cap)
                    else:
                        raise ValueError(f"Invalid capability: {cap}. Must be one of the predefined capabilities or a valid new capability name.")
            else:
                normalized.append(normalized_cap)
        
        return normalized
    
    class Config:
        """Pydantic configuration"""
        use_enum_values = True
        validate_assignment = True
        extra = "forbid"  # Reject unknown fields
        schema_extra = {
            "example": {
                "id": "jane_alesi_001",
                "name": "Jane Alesi",
                "type": "coordinator",
                "status": "active",
                "description": "Lead AI Coordinator responsible for system orchestration",
                "metadata": {
                    "version": "1.0.0",
                    "created": "2025-01-28T10:30:00Z",
                    "tags": ["coordinator", "production"]
                },
                "appearance": {
                    "color": "#8B5CF6",
                    "avatar": "/assets/agents/jane-alesi.svg",
                    "display_name": "Jane Alesi",
                    "subtitle": "Lead AI Coordinator"
                },
                "capabilities": [
                    "system_coordination",
                    "multi_agent_management",
                    "architecture_planning"
                ],
                "llm_config": {
                    "model": "phi3:mini",
                    "temperature": 0.7,
                    "max_tokens": 2048,
                    "system_prompt": "You are Jane Alesi, the lead AI coordinator responsible for orchestrating multi-agent operations and system architecture decisions."
                },
                "communication": {
                    "input_queue": "jane_alesi_input",
                    "output_queue": "jane_alesi_output",
                    "message_types": ["coordination", "system_status", "agent_management"]
                },
                "ui_components": {
                    "dashboard_widget": "AgentCoordinatorCard",
                    "detail_view": "AgentCoordinatorDetail",
                    "configuration_form": "AgentCoordinatorConfig"
                }
            }
        }

# ===== UTILITY CLASSES =====

class AgentUtils:
    """Utility methods for agent operations"""
    
    @staticmethod
    def _safe_enum_value(enum_field):
        """Safe enum value extraction with fallback to string conversion"""
        try:
            if hasattr(enum_field, 'value'):
                return enum_field.value
            else:
                return str(enum_field)
        except (AttributeError, ValueError):
            return 'unknown'
    
    @staticmethod
    def to_dict(agent):
        """Convert SaapAgent to dictionary with safe field access"""
        try:
            return {
                'id': getattr(agent, 'id', getattr(agent, 'agent_id', None)),
                'agent_id': getattr(agent, 'agent_id', getattr(agent, 'id', None)),
                'name': getattr(agent, 'name', ''),
                'description': getattr(agent, 'description', ''),
                'agent_type': AgentUtils._safe_enum_value(getattr(agent, 'type', 'unknown')),
                'status': AgentUtils._safe_enum_value(getattr(agent, 'status', 'inactive')),
                'capabilities': getattr(agent, 'capabilities', []),
                'color': getattr(agent.appearance, 'color', '#6B7280') if hasattr(agent, 'appearance') and agent.appearance else '#6B7280',
                'llm_config': AgentUtils._safe_dict(getattr(agent, 'llm_config', {})),
                'appearance': AgentUtils._safe_dict(getattr(agent, 'appearance', {})),
                'personality': getattr(agent, 'personality', {}),
                'metrics': AgentUtils._safe_dict(getattr(agent, 'metrics', {})),
                'created_at': AgentUtils._safe_datetime(getattr(agent, 'created_at', None)),
                'updated_at': AgentUtils._safe_datetime(getattr(agent, 'updated_at', None)),
                'last_active': AgentUtils._safe_datetime(getattr(agent, 'last_active', None)),
                'tags': getattr(agent, 'tags', []),
                'metadata': getattr(agent, 'metadata', {})
            }
        except Exception as e:
            # Ultimate fallback
            return {
                'id': str(id(agent)),
                'agent_id': str(id(agent)),
                'name': str(agent) if hasattr(agent, '__str__') else 'Unknown Agent',
                'description': 'Agent description unavailable',
                'agent_type': 'unknown',
                'status': 'inactive',
                'capabilities': [],
                'color': '#6B7280',
                'error': str(e)
            }
            
    @staticmethod
    def _safe_dict(obj):
        """Safely convert object to dict"""
        if obj is None:
            return {}
        if isinstance(obj, dict):
            return obj
        if hasattr(obj, 'dict'):
            try:
                return obj.dict()
            except:
                pass
        if hasattr(obj, '__dict__'):
            return obj.__dict__
        return {}
        
    @staticmethod
    def _safe_datetime(dt):
        """Safely convert datetime to ISO string"""
        if dt is None:
            return None
        try:
            return dt.isoformat() if hasattr(dt, 'isoformat') else str(dt)
        except:
            return None
class AgentRegistry(BaseModel):
    """Registry containing multiple agents"""
    agents: List[SaapAgent] = Field(..., description="List of registered agents")
    version: str = Field("1.0.0", description="Registry schema version")
    updated: datetime = Field(default_factory=datetime.utcnow)
    
    def get_agent(self, agent_id: str) -> Optional[SaapAgent]:
        """Retrieve agent by ID"""
        return next((agent for agent in self.agents if agent.id == agent_id), None)
    
    def get_agents_by_type(self, agent_type: AgentType) -> List[SaapAgent]:
        """Retrieve agents by type"""
        return [agent for agent in self.agents if agent.type == agent_type]
    
    def get_active_agents(self) -> List[SaapAgent]:
        """Retrieve all active agents"""
        return [agent for agent in self.agents if agent.status == AgentStatus.ACTIVE]

class AgentStats(BaseModel):
    """Real-time agent statistics"""
    agent_id: str = Field(..., description="Agent identifier")
    messages_processed: int = Field(0, ge=0, description="Total messages processed")
    messages_sent: int = Field(0, ge=0, description="Total messages sent")
    uptime: int = Field(0, ge=0, description="Uptime in seconds")
    avg_response_time: float = Field(0.0, ge=0.0, description="Average response time in milliseconds")
    error_count: int = Field(0, ge=0, description="Total errors encountered")
    last_activity: Optional[datetime] = Field(None, description="Last message/activity timestamp")
    
    # Performance metrics
    cpu_usage: float = Field(0.0, ge=0.0, le=100.0, description="CPU usage percentage")
    memory_usage: float = Field(0.0, ge=0.0, description="Memory usage in MB")
    queue_depth: int = Field(0, ge=0, description="Current queue depth")

# ===== PREDEFINED AGENT TEMPLATES =====

class AgentTemplates:
    """Predefined agent configuration templates"""
    
    @staticmethod
    def jane_alesi() -> SaapAgent:
        """Jane Alesi - Lead Coordinator Agent"""
        return SaapAgent(
            id="jane_alesi",
            name="Jane Alesi", 
            type=AgentType.COORDINATOR,
            description="Lead AI Coordinator responsible for orchestrating multi-agent operations and strategic decision-making.",
            metadata=AgentMetadata(version="1.0.0", tags=["coordinator", "lead"]),
            appearance=AgentAppearance(
                color="#8B5CF6",
                avatar=None,
                display_name="Justus Alesi",
                subtitle="Legal Specialist",
                description="Justus Alesi - Legal Specialist"
            ),
            capabilities=[
                "system_coordination", 
                "multi_agent_management",
                "architecture_planning",
                "decision_making"
            ],
            llm_config=LLMConfig(
                model="phi3:mini",
                system_prompt="You are Jane Alesi, the lead AI coordinator responsible for orchestrating multi-agent operations and making strategic system architecture decisions."
            ),
            communication=CommunicationConfig(
                input_queue="jane_alesi_input",
                output_queue="jane_alesi_output", 
                message_types=[MessageType.COORDINATION, MessageType.SYSTEM_STATUS, MessageType.AGENT_MANAGEMENT]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentCoordinatorCard",
                detail_view="AgentCoordinatorDetail"
            )
        )
    
    @staticmethod
    def john_alesi() -> SaapAgent:
        """John Alesi - Developer Agent"""
        return SaapAgent(
            id="john_alesi",
            name="John Alesi",
            type=AgentType.DEVELOPER,
            description="Senior Software Developer specializing in Python, JavaScript, system architecture and code generation.",
            metadata=AgentMetadata(version="1.0.0", tags=["developer", "coding"]),
            appearance=AgentAppearance(
                color="#14B8A6", 
                avatar="/assets/agents/john-alesi.svg",
                display_name="John Alesi",
                subtitle="Senior Software Developer",
                description="Senior Software Developer specializing in Python, JavaScript, system architecture and code generation."
            ),
            capabilities=[
                "code_generation",
                "debugging", 
                "architecture_design",
                "code_review"
            ],
            llm_config=LLMConfig(
                model="codellama:7b",
                temperature=0.3,  # Lower for more deterministic code
                system_prompt="You are John Alesi, a senior software developer specializing in Python, JavaScript, and system architecture."
            ),
            communication=CommunicationConfig(
                input_queue="john_alesi_input",
                output_queue="john_alesi_output",
                message_types=[MessageType.REQUEST, MessageType.RESPONSE]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentDeveloperCard",
                detail_view="AgentDeveloperDetail"
            )
        )
    
    @staticmethod
    def lara_alesi() -> SaapAgent:
        """Lara Alesi - Medical AI Specialist"""
        return SaapAgent(
            id="lara_alesi",
            name="Lara Alesi",
            type=AgentType.SPECIALIST,
            description="Advanced Medical AI Assistant specializing in clinical analysis, diagnosis support and health system architecture.",
            metadata=AgentMetadata(version="1.0.0", tags=["medical", "healthcare", "specialist"]),
            appearance=AgentAppearance(
                color="#EC4899",
                avatar=None,
                display_name="Luna Alesi",
                subtitle="Coaching Specialist",
                description="Luna Alesi - Coaching Specialist"
            ),
            capabilities=[
                "medical_analysis",
                "clinical_decision_support",
                "health_data_analysis", 
                "medical_research"
            ],
            llm_config=LLMConfig(
                model="phi3:mini",
                temperature=0.5,  # More conservative for medical advice
                system_prompt="You are Lara Alesi, a medical AI specialist focused on clinical analysis, health data interpretation, and medical research support."
            ),
            communication=CommunicationConfig(
                input_queue="lara_alesi_input",
                output_queue="lara_alesi_output",
                message_types=[MessageType.REQUEST, MessageType.RESPONSE]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentMedicalCard",
                detail_view="AgentMedicalDetail"
            )
        )
    
    @staticmethod
    def theo_alesi() -> SaapAgent:
        """Theo Alesi - Financial Intelligence Specialist"""
        return SaapAgent(
            id="theo_alesi",
            name="Theo Alesi",
            type=AgentType.SPECIALIST,
            description="Advanced Financial & Investment Intelligence Specialist focusing on financial analysis, market intelligence and investment strategies.",
            metadata=AgentMetadata(version="1.0.0", tags=["finance", "investment", "specialist"]),
            appearance=AgentAppearance(
                color="#F59E0B",
                avatar=None,
                display_name="Theo Alesi",
                subtitle="Financial Specialist",
                description="Theo Alesi - Financial Specialist"
            ),
            capabilities=[
                "financial_analysis",
                "market_research",
                "investment_strategy",
                "risk_assessment",
                "fintech_development", "market_research"
            ],
            llm_config=LLMConfig(
                model="phi3:mini",
                temperature=0.6,
                system_prompt="You are Theo Alesi, a financial intelligence specialist with expertise in financial analysis, market research, and fintech application development."
            ),
            communication=CommunicationConfig(
                input_queue="theo_alesi_input",
                output_queue="theo_alesi_output",
                message_types=[MessageType.REQUEST, MessageType.RESPONSE]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentFinanceCard",
                detail_view="AgentFinanceDetail"
            )
        )
    
    @staticmethod
    def justus_alesi() -> SaapAgent:
        """Justus Alesi - Legal Compliance Expert"""
        return SaapAgent(
            id="justus_alesi",
            name="Justus Alesi",
            type=AgentType.SPECIALIST,
            description="Expert für Schweizer, Deutsches und EU-Recht with focus on digital compliance, DSGVO and fintech regulations.",
            metadata=AgentMetadata(version="1.0.0", tags=["legal", "compliance", "specialist"]),
            appearance=AgentAppearance(
                color="#10B981",
                avatar=None,
                display_name="Leon Alesi",
                subtitle="System Specialist",
                description="Leon Alesi - System Specialist"
            ),
            capabilities=[
                "legal_compliance",
                "gdpr_analysis", 
                "contract_review",
                "regulatory_analysis",
                "fintech_law"
            ],
            llm_config=LLMConfig(
                model="phi3:mini",
                temperature=0.4,  # Conservative for legal advice
                system_prompt="You are Justus Alesi, a legal expert specializing in German, Swiss and EU law with focus on digital compliance and fintech regulations."
            ),
            communication=CommunicationConfig(
                input_queue="justus_alesi_input",
                output_queue="justus_alesi_output",
                message_types=[MessageType.REQUEST, MessageType.RESPONSE]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentLegalCard",
                detail_view="AgentLegalDetail"
            )
        )
    
    @staticmethod
    def leon_alesi() -> SaapAgent:
        """Leon Alesi - IT System Integration Specialist"""
        return SaapAgent(
            id="leon_alesi",
            name="Leon Alesi",
            type=AgentType.SPECIALIST,
            description="IT-Systemintegrations-Spezialist focusing on infrastructure deployment, security and system architecture.",
            metadata=AgentMetadata(version="1.0.0", tags=["system", "infrastructure", "specialist"]),
            appearance=AgentAppearance(
                color="#6366F1",
                avatar="/assets/agents/leon-alesi.svg",
                display_name="Leon Alesi",
                subtitle="IT System Integration Specialist", 
                description="IT-Systemintegrations-Spezialist focusing on infrastructure deployment, security and system architecture."
            ),
            capabilities=[
                "system_administration",
                "infrastructure_deployment",
                "security_implementation",
                "performance_optimization"
            ],
            llm_config=LLMConfig(
                model="phi3:mini",
                temperature=0.5,
                system_prompt="You are Leon Alesi, an IT system integration specialist focused on infrastructure, security, and performance optimization."
            ),
            communication=CommunicationConfig(
                input_queue="leon_alesi_input",
                output_queue="leon_alesi_output",
                message_types=[MessageType.REQUEST, MessageType.RESPONSE]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentSystemCard",
                detail_view="AgentSystemDetail"
            )
        )
    
    @staticmethod
    def luna_alesi() -> SaapAgent:
        """Luna Alesi - Coaching & Organizational Development"""
        return SaapAgent(
            id="luna_alesi", 
            name="Luna Alesi",
            type=AgentType.SPECIALIST,
            description="Coaching- und Organisationsentwicklungsexpertin with focus on team development and process optimization.",
            metadata=AgentMetadata(version="1.0.0", tags=["coaching", "organization", "specialist"]),
            appearance=AgentAppearance(
                color="#8B5CF6",
                avatar=None,
                display_name="Justus Alesi",
                subtitle="Legal Specialist",
                description="Justus Alesi - Legal Specialist"
            ),
            capabilities=[
                "team_coaching",
                "organizational_development", 
                "process_optimization",
                "change_management"
            ],
            llm_config=LLMConfig(
                model="phi3:mini",
                temperature=0.7,  # More creative for coaching
                system_prompt="You are Luna Alesi, a coaching and organizational development expert focused on team development and process optimization."
            ),
            communication=CommunicationConfig(
                input_queue="luna_alesi_input",
                output_queue="luna_alesi_output",
                message_types=[MessageType.REQUEST, MessageType.RESPONSE]
            ),
            ui_components=UIComponents(
                dashboard_widget="AgentCoachingCard", 
                detail_view="AgentCoachingDetail"
            )
        )


# ===== VALIDATION UTILITIES =====

def validate_agent_json(agent_data: Dict[str, Any]) -> SaapAgent:
    """Validate and parse agent JSON data"""
    try:
        return SaapAgent(**agent_data)
    except Exception as e:
        raise ValueError(f"Invalid agent configuration: {str(e)}")

def generate_agent_schema() -> Dict[str, Any]:
    """Generate JSON schema for agent configuration"""
    return SaapAgent.schema()

def get_allowed_capabilities() -> List[str]:
    """Get list of all allowed capabilities"""
    return sorted(list(ALLOWED_CAPABILITIES))

if __name__ == "__main__":
    # Example usage and testing
    jane = AgentTemplates.jane_alesi()
    print("Jane Alesi Agent:")
    print(jane.json(indent=2))
    
    # Test Theo Alesi template
    theo = AgentTemplates.theo_alesi()
    print("\nTheo Alesi Agent:")
    print(f"ID: {theo.id}, Name: {theo.name}, Capabilities: {theo.capabilities}")
    
    # Generate schema
    schema = generate_agent_schema()
    print("\nAgent JSON Schema keys:")
    print(list(schema.keys()))
    
    # Show allowed capabilities
    print(f"\nAllowed capabilities ({len(ALLOWED_CAPABILITIES)}):")
    print(get_allowed_capabilities())