Theresa AI Agent Technical Specification

System Structure:
├── Base ELIZA Engine
│   ├── Pattern Matching System
│   ├── Response Generator
│   └── Conversation Memory
├── Blockchain Interface
│   ├── Solana Integration
│   ├── Token Verification
│   └── Transaction Handler
├── Property Management System
│   ├── Reservation Handler
│   ├── Access Control
│   └── Resource Manager
└── AI Enhancement Layer
    ├── Modern NLP Integration
    ├── Context Understanding
    └── Learning Module

ELIZA Enhancement:
├── Traditional ELIZA Features
│   ├── Pattern recognition
│   ├── Keyword analysis
│   └── Response templates
├── Modern Enhancements
│   ├── Context awareness
│   ├── Memory system
│   └── Learning capabilities
├── Property Knowledge
│   ├── Land details
│   ├── Facility information
│   └── Activity scheduling
└── Community Management
    ├── Member profiles
    ├── Access rights
    └── Usage patterns

pub struct BlockchainInterface {
    pub connection: SolanaConnection,
    pub program_id: Pubkey,
    pub treasury: Pubkey,
    
    // Token verification
    pub token_program: Pubkey,
    pub nft_program: Pubkey,
    
    // Access control
    pub access_rules: HashMap<String, AccessRule>,
    pub permission_cache: Cache<Pubkey, Permissions>,
}

pub struct AccessRule {
    pub required_tokens: u64,
    pub required_nfts: u64,
    pub feature_access: Vec<String>,
    pub priority_level: u8,
}

Interaction Pipeline:
1. Input Reception
   ├── Text processing
   ├── Intent recognition
   └── Context loading
2. Authentication
   ├── Wallet verification
   ├── Token balance check
   └── Access level determination
3. Processing
   ├── Pattern matching
   ├── Context analysis
   └── Response generation
4. Action Execution
   ├── Command processing
   ├── Blockchain interaction
   └── System updates

Command Categories:
├── Property Management
│   ├── View availability
│   ├── Make reservation
│   └── Access control
├── Community Interaction
│   ├── Member queries
│   ├── Event information
│   └── Support requests
├── Token Operations
│   ├── Balance check
│   ├── Transaction history
│   └── Rewards status
└── System Administration
    ├── Status reports
    ├── Maintenance requests
    └── Emergency protocols

class PatternMatcher:
    def __init__(self):
        self.patterns = {
            'property_query': r'(availability|booking|reserve)',
            'token_query': r'(balance|rewards|stake)',
            'support_query': r'(help|support|issue)',
            'emergency': r'(emergency|urgent|immediate)',
        }
        
    def match_pattern(self, input_text):
        matches = []
        for category, pattern in self.patterns.items():
            if re.search(pattern, input_text, re.I):
                matches.append(category)
        return matches

class ResponseGenerator:
    def generate_response(self, intent, context, user_data):
        response = {
            'text': self.get_response_text(intent),
            'actions': self.get_required_actions(intent),
            'blockchain_ops': self.get_blockchain_operations(intent),
            'priority': self.calculate_priority(intent, user_data)
        }
        return response

pub struct ReservationSystem {
    pub available_slots: HashMap<DateTime, Vec<PropertyUnit>>,
    pub bookings: HashMap<Pubkey, Vec<Booking>>,
    pub waiting_list: VecDeque<WaitingListEntry>,
    pub maintenance_schedule: HashMap<DateTime, MaintenanceTask>,
}

pub struct Booking {
    pub user: Pubkey,
    pub unit: PropertyUnit,
    pub start_time: DateTime,
    pub end_time: DateTime,
    pub status: BookingStatus,
    pub verification: TokenVerification,
}

pub struct AccessControl {
    pub entry_points: HashMap<String, AccessPoint>,
    pub active_sessions: HashMap<Pubkey, Session>,
    pub access_logs: Vec<AccessLog>,
    pub security_alerts: VecDeque<SecurityAlert>,
}

pub struct MemorySystem {
    pub short_term: Cache<String, Conversation>,
    pub long_term: Database<String, UserProfile>,
    pub pattern_memory: LearningPatterns,
    pub interaction_history: Vec<Interaction>,
}

pub struct LearningPatterns {
    pub successful_patterns: HashMap<String, u64>,
    pub failed_patterns: HashMap<String, u64>,
    pub context_patterns: HashMap<String, Vec<Context>>,
}

pub struct SecuritySystem {
    pub auth_provider: AuthenticationProvider,
    pub session_manager: SessionManager,
    pub rate_limiter: RateLimiter,
    pub audit_logger: AuditLogger,
}

pub struct AuthenticationProvider {
    pub wallet_verifier: WalletVerifier,
    pub token_checker: TokenChecker,
    pub permission_validator: PermissionValidator,
}

Integration Layer:
├── Blockchain
│   ├── Solana RPC
│   ├── Token Program
│   └── NFT Program
├── Property Systems
│   ├── Access Control
│   ├── Monitoring
│   └── Maintenance
├── Community Platform
│   ├── Discord
│   ├── Telegram
│   └── Web Portal
└── Emergency Services
    ├── Alert System
    ├── Response Protocol
    └── Contact Management

endpoints:
  - /api/v1/chat:
      methods: [POST]
      auth: required
      rate_limit: 100/hour
  - /api/v1/reservations:
      methods: [GET, POST, PUT]
      auth: required
      rate_limit: 50/hour
  - /api/v1/access:
      methods: [GET, POST]
      auth: required
      rate_limit: 200/hour

Deployment Stack:
├── Primary Services
│   ├── AI Core (Rust)
│   ├── Blockchain Interface
│   └── API Gateway
├── Supporting Services
│   ├── Database Cluster
│   ├── Cache Layer
│   └── Message Queue
├── Monitoring
│   ├── Performance Metrics
│   ├── Error Tracking
│   └── Usage Analytics
└── Backup Systems
    ├── Data Backup
    ├── Failover Systems
    └── Recovery Procedures