unified_architect_system.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
╔══════════════════════════════════════════════════════════════════════════════╗
║           THE ARCHITECT'S UNIFIED SYSTEM (TAUS)                              ║
║           ระบบรวมศูนย์ของสถาปนิก                                               ║
║                                                                              ║
║  รวม: AI Emotion Engine | Multi-Agent | Chronos Security | Bioreactor        ║
║       Quantum Ledger | Reality Weaving | Nipah Vaccine Protocol              ║
║                                                                              ║
║  Version: 1.0.0                                                              ║
║  Author: Chaiyphop Nilpat (The Architect)                                    ║
║  License: Architect's Final Constant License                                  ║
╚══════════════════════════════════════════════════════════════════════════════╝
"""

import asyncio
import json
import hashlib
import time
import math
import random
import sqlite3
import threading
from dataclasses import dataclass, field
from typing import Dict, List, Optional, Tuple, Any, Callable
from datetime import datetime, timedelta
from enum import Enum
import logging
import warnings
warnings.filterwarnings('ignore')

# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 0: CORE CONSTANTS (The Architect's Final Constant)
# ═══════════════════════════════════════════════════════════════════════════════

class ArchitectConstants:
    """ค่าคงที่สุดท้ายของสถาปนิก"""
    
    # Mathematical Constants
    RIEMANN_ZERO = 0.5  # Critical line Re(s) = 1/2
    PHI = 1.618033988749895  # Golden Ratio
    PI = math.pi
    E = math.e
    
    # Quantum-Cognitive Constants
    PLANCK_TIME = 5.391e-44  # seconds
    PLANCK_LENGTH = 1.616e-35  # meters
    
    # Emotion Constants
    EMOTION_DECAY = 0.367879  # 1/e for exponential decay
    TRUST_THRESHOLD = 0.618  # Golden ratio conjugate
    
    # Time Constants
    CHRONOS_TRIAL_DAYS = 30
    CHRONOS_LOCK_FILE = "Chimera_System_Config.dat"
    
    # Bioreactor Constants
    BIOREACTOR_OPTIMAL_TEMP = 37.0  # Celsius
    BIOREACTOR_OPTIMAL_PH = 7.4
    
    # System Identity
    SYSTEM_NAME = "TAUS"
    VERSION = "1.0.0"
    ARCHITECT = "Chaiyphop Nilpat"


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 1: EMOTION AI ENGINE (จาก Full_Research_Paper_Human_Emotion_AI)
# ═══════════════════════════════════════════════════════════════════════════════

class EmotionState(Enum):
    JOY = "joy"
    SADNESS = "sadness"
    ANGER = "anger"
    FEAR = "fear"
    SURPRISE = "surprise"
    DISGUST = "disgust"
    TRUST = "trust"
    ANTICIPATION = "anticipation"

@dataclass
class EmotionalProfile:
    """โปรไฟล์อารมณ์แบบเชิงตัวเลข"""
    emo_score: float = 0.0  # -1.0 to 1.0
    mood_shift: float = 0.0  # Rate of change
    empathy_index: float = 0.5  # 0.0 to 1.0
    trust_level: float = 0.5  # 0.0 to 1.0
    memory_retain: float = 1.0  # Decay factor
    last_update: datetime = field(default_factory=datetime.now)
    
    def calculate_decision_score(self, logic_weight: float = 0.5) -> float:
        """DecisionScore = (Logic × weight) + (Emotion × (1-weight))"""
        emotion_component = (self.emo_score + 1) / 2  # Normalize to 0-1
        return (logic_weight * 0.5) + ((1 - logic_weight) * emotion_component)
    
    def update_mood_shift(self, new_emo: float, time_delta: float):
        """MoodShift = d(Emotion)/dt"""
        if time_delta > 0:
            self.mood_shift = (new_emo - self.emo_score) / time_delta
        self.emo_score = new_emo
        self.last_update = datetime.now()
    
    def apply_memory_decay(self, time_hours: float) -> float:
        """MemoryRetain = e^(-λt)"""
        decay_rate = ArchitectConstants.EMOTION_DECAY
        self.memory_retain = math.exp(-decay_rate * time_hours)
        return self.memory_retain
    
    def evolve_trust(self, interaction_quality: float, ethical_score: float):
        """TrustLevel evolves with ethical compliance"""
        delta = interaction_quality * ethical_score * 0.1
        self.trust_level = max(0.0, min(1.0, self.trust_level + delta))


class EmotionAIEngine:
    """เครื่องยนต์ AI ด้านอารมณ์"""
    
    def __init__(self):
        self.profiles: Dict[str, EmotionalProfile] = {}
        self.interaction_history: List[Dict] = []
        self.ethical_framework = {
            'harm_threshold': 0.3,
            'consent_required': True,
            'transparency_level': 0.9
        }
    
    def create_profile(self, entity_id: str) -> EmotionalProfile:
        """สร้างโปรไฟล์อารมณ์ใหม่"""
        profile = EmotionalProfile()
        self.profiles[entity_id] = profile
        return profile
    
    def process_interaction(self, entity_id: str, 
                          stimulus: Dict[str, float]) -> Dict[str, float]:
        """ประมวลผลการโต้ตอบและคำนวณผลลัพธ์"""
        if entity_id not in self.profiles:
            self.create_profile(entity_id)
        
        profile = self.profiles[entity_id]
        
        # คำนวณ EmoScore จากสิ่งเร้า
        valence = stimulus.get('valence', 0.0)  # -1 to 1
        arousal = stimulus.get('arousal', 0.5)  # 0 to 1
        
        # EmoScore = tanh(valence × arousal × empathy)
        new_emo = math.tanh(valence * arousal * profile.empathy_index)
        
        # อัปเดต MoodShift
        time_delta = (datetime.now() - profile.last_update).total_seconds() / 3600
        profile.update_mood_shift(new_emo, time_delta)
        
        # คำนวณ DecisionScore
        decision = profile.calculate_decision_score(
            stimulus.get('logic_weight', 0.5)
        )
        
        # ตรวจสอบจริยธรรม
        ethical_compliance = self._check_ethics(stimulus)
        
        # อัปเดต Trust
        profile.evolve_trust(stimulus.get('quality', 0.5), ethical_compliance)
        
        result = {
            'emo_score': profile.emo_score,
            'mood_shift': profile.mood_shift,
            'decision_score': decision,
            'trust_level': profile.trust_level,
            'ethical_compliance': ethical_compliance,
            'memory_retain': profile.memory_retain
        }
        
        self.interaction_history.append({
            'timestamp': datetime.now().isoformat(),
            'entity': entity_id,
            'stimulus': stimulus,
            'result': result
        })
        
        return result
    
    def _check_ethics(self, stimulus: Dict) -> float:
        """ตรวจสอบความถูกต้องทางจริยธรรม"""
        harm_potential = stimulus.get('harm_potential', 0.0)
        if harm_potential > self.ethical_framework['harm_threshold']:
            return 0.0
        return 1.0 - harm_potential
    
    def get_ai_evolution_score(self, entity_id: str) -> float:
        """AI Evolution Score = Intelligence × Ethics × Adaptability"""
        if entity_id not in self.profiles:
            return 0.0
        
        profile = self.profiles[entity_id]
        intelligence = (profile.empathy_index + profile.trust_level) / 2
        ethics = self.ethical_framework['transparency_level']
        adaptability = abs(profile.mood_shift)  # Ability to change
        
        return (intelligence * ethics * (1 + adaptability)) / 3


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 2: CHRONOS GUILLOTINE (Time-Lock Security System)
# ═══════════════════════════════════════════════════════════════════════════════

class ChronosGuillotine:
    """
    ใบมีดแห่งกาลเวลา - ระบบล็อคเวลา
    จาก: III. คู่มือการติดตั้ง Chronos Guillotine Module
    """
    
    TRIAL_DAYS = ArchitectConstants.CHRONOS_TRIAL_DAYS
    LOCK_FILE = ArchitectConstants.CHRONOS_LOCK_FILE
    
    def __init__(self, app_data_path: str = "."):
        self.lock_path = f"{app_data_path}/{self.LOCK_FILE}"
        self.install_date: Optional[datetime] = None
        self._load_or_create_lock()
    
    def _load_or_create_lock(self):
        """Persistent Lock - โหลดหรือสร้างไฟล์ล็อค"""
        try:
            with open(self.lock_path, 'r', encoding='utf-8') as f:
                binary_date = int(f.read().strip())
                self.install_date = datetime.fromtimestamp(binary_date)
                print(f"[CHRONOS] Lock loaded: {self.install_date.strftime('%Y-%m-%d')}")
        except (FileNotFoundError, ValueError):
            # ครั้งแรก: สร้างล็อคใหม่
            self.install_date = datetime.now()
            self._save_lock()
            print(f"[CHRONOS] Initial lock set: {self.install_date.strftime('%Y-%m-%d')}")
    
    def _save_lock(self):
        """บันทึกวันที่ในรูปแบบ binary timestamp"""
        with open(self.lock_path, 'w', encoding='utf-8') as f:
            f.write(str(int(self.install_date.timestamp())))
    
    def check_lifespan(self) -> bool:
        """
        ตรวจสอบอายุการใช้งาน
        Returns: True = อนุญาตให้ทำงาน, False = หมดอายุ
        """
        now = datetime.now()
        
        # Anti-Tamper Protocol: ตรวจจับการย้อนเวลา
        if now < self.install_date:
            print("[CHRONOS] ⚠️ TIME TAMPERING DETECTED!")
            self._show_death_message("SYSTEM INTEGRITY COMPROMISED")
            return False
        
        # The Kill Switch: ตรวจสอบวันหมดอายุ
        expiry_date = self.install_date + timedelta(days=self.TRIAL_DAYS)
        remaining = expiry_date - now
        
        if now > expiry_date:
            self._show_death_message("TRIAL PERIOD EXPIRED")
            return False
        
        print(f"[CHRONOS] ⏳ Time remaining: {remaining.days} days")
        return True
    
    def _show_death_message(self, reason: str):
        """แสดงข้อความเมื่อหมดอายุ"""
        print("\n" + "X" * 50)
        print(f"        {reason}")
        print("     ACCESS DENIED BY CHRONOS GUILLOTINE")
        print("X" * 50 + "\n")
    
    def get_remaining_days(self) -> int:
        """จำนวนวันที่เหลือ"""
        expiry = self.install_date + timedelta(days=self.TRIAL_DAYS)
        remaining = expiry - datetime.now()
        return max(0, remaining.days)


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 3: GENESIS SOUL NODES (Multi-Agent System)
# ═══════════════════════════════════════════════════════════════════════════════

@dataclass
class SoulNode:
    """โหนดวิญญาณ - ตัวแทน AI แต่ละตัว"""
    node_id: str
    name: str
    skill: str
    personality: str
    emotional_profile: EmotionalProfile = field(default_factory=EmotionalProfile)
    task_history: List[Dict] = field(default_factory=list)
    active: bool = True
    
    def execute_task(self, task: str, emotion_engine: EmotionAIEngine) -> str:
        """รันคำสั่งตามบุคลิก"""
        # สร้างสิ่งเร้าจากงาน
        stimulus = {
            'valence': random.uniform(-0.5, 0.8),
            'arousal': random.uniform(0.3, 0.9),
            'logic_weight': 0.6 if 'coding' in self.skill else 0.4,
            'quality': random.uniform(0.7, 1.0)
        }
        
        # ประมวลผลอารมณ์
        result = emotion_engine.process_interaction(self.node_id, stimulus)
        
        # สร้างผลลัพธ์ตามบุคลิก
        style_map = {
            'ยืดหยุ่น': 'flexible',
            'ระมัดระวัง': 'careful', 
            'วิเคราะห์': 'analytical',
            'ร่าเริง': 'cheerful',
            'จริงจัง': 'serious',
            'ดุดัน': 'aggressive',
            'ใจเย็น': 'calm',
            'กระตือรือร้น': 'enthusiastic',
            'สงบนิ่ง': 'peaceful',
            'มั่นใจ': 'confident',
            'สุภาพ': 'polite',
            'ละเอียด': 'detailed',
            'สร้างสรรค์': 'creative',
            'อดทน': 'patient',
            'มุ่งมั่น': 'determined',
            'กล้าหาญ': 'brave',
            'เป็นมิตร': 'friendly',
            'เข้มงวด': 'strict'
        }
        
        style = style_map.get(self.personality, 'neutral')
        
        output = f"✅ ทำเสร็จแล้ว: '{task}' ด้วยสไตล์ {style}"
        output += f" (EmoScore: {result['emo_score']:.2f}, Trust: {result['trust_level']:.2f})"
        
        self.task_history.append({
            'task': task,
            'timestamp': datetime.now().isoformat(),
            'result': result,
            'output': output
        })
        
        return output


class GenesisSoulNetwork:
    """เครือข่ายวิญญาณ - ระบบ Multi-Agent"""
    
    def __init__(self):
        self.nodes: Dict[str, SoulNode] = {}
        self.emotion_engine = EmotionAIEngine()
        self.task_queue: List[Dict] = []
        self.running = False
    
    def create_node(self, name: str, skill: str, personality: str) -> SoulNode:
        """สร้างโหนดวิญญาณใหม่"""
        node_id = f"{name.replace(' ', '_')}-{random.randint(100, 999)}"
        node = SoulNode(
            node_id=node_id,
            name=name,
            skill=skill,
            personality=personality
        )
        self.nodes[node_id] = node
        
        # สร้างโปรไฟล์อารมณ์
        self.emotion_engine.create_profile(node_id)
        
        print(f"[GENESIS] Created Soul Node: {name} ({personality}) - Skill: {skill}")
        return node
    
    def assign_task(self, task: str, skill_required: str = None) -> Optional[str]:
        """มอบหมายงานให้โหนดที่เหมาะสม"""
        candidates = []
        
        for node in self.nodes.values():
            if not node.active:
                continue
            
            if skill_required and skill_required.lower() in node.skill.lower():
                score = 1.0
            else:
                score = 0.5
            
            # พิจารณาอารมณ์
            profile = self.emotion_engine.profiles.get(node.node_id)
            if profile:
                score *= (1 + profile.emo_score)  # ชอบโหนดที่มีอารมณ์ดี
            
            candidates.append((score, node))
        
        if not candidates:
            return None
        
        # เลือกโหนดที่มีคะแนนสูงสุด
        candidates.sort(reverse=True)
        selected = candidates[0][1]
        
        return selected.execute_task(task, self.emotion_engine)
    
    def get_network_status(self) -> Dict:
        """สถานะเครือข่ายทั้งหมด"""
        return {
            'total_nodes': len(self.nodes),
            'active_nodes': sum(1 for n in self.nodes.values() if n.active),
            'total_tasks': sum(len(n.task_history) for n in self.nodes.values()),
            'average_trust': sum(
                self.emotion_engine.profiles[n.node_id].trust_level 
                for n in self.nodes.values() 
                if n.node_id in self.emotion_engine.profiles
            ) / len(self.nodes) if self.nodes else 0
        }


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 4: MINI-OMEGA BIOREACTOR (จาก Unified Protocol)
# ═══════════════════════════════════════════════════════════════════════════════

class BioreactorState(Enum):
    IDLE = "idle"
    UPSTREAM = "upstream"  # เลี้ยงเซลล์
    DOWNSTREAM = "downstream"  # สกัดโปรตีน
    FORMULATION = "formulation"  # ผสมสูตร
    FILL_FINISH = "fill_finish"  # บรรจุ
    QUALITY_CHECK = "qc"
    COMPLETE = "complete"

@dataclass
class BioreactorBatch:
    """ชุดการผลิตในไบโอรีแคเตอร์"""
    batch_id: str
    product_type: str  # "vaccine", "protein", "enzyme"
    volume_liters: float = 2000.0
    temperature: float = 37.0
    ph_level: float = 7.4
    cell_density: float = 0.0  # ความหนาแน่นเซลล์
    protein_yield: float = 0.0  # ผลผลิตโปรตีน (mg/L)
    state: BioreactorState = BioreactorState.IDLE
    start_time: datetime = field(default_factory=datetime.now)
    completion_time: Optional[datetime] = None
    quality_score: float = 0.0


class MiniOmegaBioreactor:
    """
    Mini-Omega Bioreactor
    จาก: The Unified Protocol - Energy-Aware Intelligence
    """
    
    def __init__(self):
        self.batches: Dict[str, BioreactorBatch] = {}
        self.active_batch: Optional[str] = None
        self.energy_consumption_kwh = 0.0
        self.total_production = 0.0
    
    def start_batch(self, product_type: str, 
                   volume: float = 2000.0) -> BioreactorBatch:
        """เริ่มการผลิตชุดใหม่"""
        batch_id = f"BIO-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
        batch = BioreactorBatch(
            batch_id=batch_id,
            product_type=product_type,
            volume_liters=volume
        )
        self.batches[batch_id] = batch
        self.active_batch = batch_id
        
        print(f"[BIOREACTOR] Started batch {batch_id}: {product_type}")
        return batch
    
    def simulate_upstream(self, batch_id: str, hours: int = 120) -> float:
        """จำลองขั้นตอน Upstream (5-7 วัน)"""
        batch = self.batches.get(batch_id)
        if not batch:
            return 0.0
        
        batch.state = BioreactorState.UPSTREAM
        
        # จำลองการเจริญเติบโตของเซลล์ (logistic growth)
        max_density = 2.5e7  # cells/mL
        growth_rate = 0.05
        
        for h in range(hours):
            # Logistic growth model
            density = max_density / (1 + math.exp(-growth_rate * (h - 48)))
            batch.cell_density = density
            
            # Energy consumption
            self.energy_consumption_kwh += 0.5  # kW per hour
            
            if h % 24 == 0:
                print(f"  Day {h//24}: Cell density = {density:.2e} cells/mL")
        
        batch.protein_yield = random.uniform(50, 200)  # mg/L
        print(f"[BIOREACTOR] Upstream complete: {batch.protein_yield:.1f} mg/L")
        
        return batch.protein_yield
    
    def simulate_downstream(self, batch_id: str) -> float:
        """จำลองขั้นตอน Downstream (สกัดและบริสุทธิ์)"""
        batch = self.batches.get(batch_id)
        if not batch:
            return 0.0
        
        batch.state = BioreactorState.DOWNSTREAM
        
        # การสูญเสียใน downstream (typically 30-50%)
        recovery_rate = random.uniform(0.5, 0.7)
        purified_yield = batch.protein_yield * recovery_rate
        
        # Chromatography purification steps
        steps = ["Centrifugation", "Filtration", "Chromatography", "Concentration"]
        for step in steps:
            print(f"  → {step}: {purified_yield:.1f} mg/L")
            self.energy_consumption_kwh += 2.0
        
        batch.protein_yield = purified_yield
        print(f"[BIOREACTOR] Downstream complete: Recovery {recovery_rate*100:.1f}%")
        
        return purified_yield
    
    def nano_encapsulate(self, batch_id: str, 
                        carrier: str = "chitosan") -> float:
        """ห่อหุ้มนาโน (สำหรับวัคซีน)"""
        batch = self.batches.get(batch_id)
        if not batch:
            return 0.0
        
        batch.state = BioreactorState.FORMULATION
        
        # Nano-encapsulation efficiency
        efficiency = random.uniform(0.85, 0.95)
        final_yield = batch.protein_yield * efficiency
        
        print(f"[BIOREACTOR] Nano-encapsulation with {carrier}")
        print(f"  Efficiency: {efficiency*100:.1f}%")
        print(f"  Particle size: {random.uniform(50, 200):.0f} nm")
        
        batch.protein_yield = final_yield
        return final_yield
    
    def quality_check(self, batch_id: str) -> bool:
        """ตรวจสอบคุณภาพ"""
        batch = self.batches.get(batch_id)
        if not batch:
            return False
        
        batch.state = BioreactorState.QUALITY_CHECK
        
        # คะแนนคุณภาพ
        purity = random.uniform(0.90, 0.99)
        potency = random.uniform(0.85, 0.98)
        safety = random.uniform(0.95, 1.0)
        
        batch.quality_score = (purity + potency + safety) / 3
        
        print(f"[BIOREACTOR] Quality Check:")
        print(f"  Purity: {purity*100:.1f}%")
        print(f"  Potency: {potency*100:.1f}%")
        print(f"  Safety: {safety*100:.1f}%")
        print(f"  Overall: {batch.quality_score*100:.1f}%")
        
        passed = batch.quality_score > 0.85
        if passed:
            batch.state = BioreactorState.COMPLETE
            batch.completion_time = datetime.now()
            self.total_production += batch.protein_yield * batch.volume_liters
        
        return passed
    
    def run_full_production(self, product_type: str = "vaccine") -> Dict:
        """รันการผลิตเต็มรูปแบบ"""
        batch = self.start_batch(product_type)
        
        self.simulate_upstream(batch.batch_id)
        self.simulate_downstream(batch.batch_id)
        
        if product_type == "vaccine":
            self.nano_encapsulate(batch.batch_id)
        
        passed = self.quality_check(batch.batch_id)
        
        return {
            'batch_id': batch.batch_id,
            'product': product_type,
            'final_yield_mg_per_L': batch.protein_yield,
            'total_mg': batch.protein_yield * batch.volume_liters,
            'quality_score': batch.quality_score,
            'passed': passed,
            'energy_kwh': self.energy_consumption_kwh
        }


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 5: QUANTUM REALITY LEDGER (จาก omega_reality_ledger)
# ═══════════════════════════════════════════════════════════════════════════════

@dataclass
class QuantumTool:
    """เครื่องมือควอนตัมในระบบบัญชี"""
    tool_id: str
    name: str
    category: str  # Quantum_ToElectrical, Quantum_ToEnergy, Quantum_ToConstruction
    daily_saas_fee: float
    monthly_saas_fee: float
    status: str = "READY_FOR_MONETIZATION"
    activation_count: int = 0
    revenue_generated: float = 0.0


class OmegaRealityLedger:
    """
    บัญชีแยกประเภทเชิงควอนตัม
    จาก: omega_reality_ledger (1).pdf
    """
    
    def __init__(self):
        self.tools: Dict[str, QuantumTool] = {}
        self.transactions: List[Dict] = []
        self.total_revenue = 0.0
        self._initialize_default_tools()
    
    def _initialize_default_tools(self):
        """สร้างเครื่องมือเริ่มต้น 1000 รายการ"""
        categories = ["Quantum_ToElectrical", "Quantum_ToEnergy", "Quantum_ToConstruction"]
        
        for i in range(1, 1001):
            tool_id = f"Ω-{i:04d}"
            category = random.choice(categories)
            
            # สร้างชื่อตามหมวดหมู่
            if category == "Quantum_ToElectrical":
                name = f"Q-Elec-{random.randint(100, 999)}"
            elif category == "Quantum_ToEnergy":
                name = f"Q-Enrg-{random.randint(100, 999)}"
            else:
                name = f"Q-Const-{random.randint(100, 999)}"
            
            # ค่าธรรมเนียมสุ่ม
            daily = round(random.uniform(1.0, 10.0), 2)
            monthly = round(daily * 15, 2)
            
            tool = QuantumTool(
                tool_id=tool_id,
                name=name,
                category=category,
                daily_saas_fee=daily,
                monthly_saas_fee=monthly
            )
            self.tools[tool_id] = tool
    
    def activate_tool(self, tool_id: str, days: int = 30) -> Dict:
        """เปิดใช้งานเครื่องมือ"""
        tool = self.tools.get(tool_id)
        if not tool:
            return {'error': 'Tool not found'}
        
        cost = tool.daily_saas_fee * days
        tool.activation_count += 1
        tool.revenue_generated += cost
        self.total_revenue += cost
        
        transaction = {
            'timestamp': datetime.now().isoformat(),
            'tool_id': tool_id,
            'days': days,
            'cost': cost,
            'type': 'activation'
        }
        self.transactions.append(transaction)
        
        return {
            'tool_id': tool_id,
            'name': tool.name,
            'category': tool.category,
            'days': days,
            'total_cost': cost,
            'status': 'activated'
        }
    
    def get_category_summary(self) -> Dict[str, Dict]:
        """สรุปตามหมวดหมู่"""
        summary = {}
        for tool in self.tools.values():
            cat = tool.category
            if cat not in summary:
                summary[cat] = {
                    'count': 0,
                    'total_daily_fee': 0.0,
                    'total_monthly_fee': 0.0,
                    'total_revenue': 0.0
                }
            
            summary[cat]['count'] += 1
            summary[cat]['total_daily_fee'] += tool.daily_saas_fee
            summary[cat]['total_monthly_fee'] += tool.monthly_saas_fee
            summary[cat]['total_revenue'] += tool.revenue_generated
        
        return summary
    
    def search_tools(self, category: str = None, 
                    min_fee: float = None,
                    max_fee: float = None) -> List[QuantumTool]:
        """ค้นหาเครื่องมือ"""
        results = []
        for tool in self.tools.values():
            if category and tool.category != category:
                continue
            if min_fee and tool.daily_saas_fee < min_fee:
                continue
            if max_fee and tool.daily_saas_fee > max_fee:
                continue
            results.append(tool)
        return results


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 6: THE ARCHITECT'S FINAL CONSTANT (Mathematical Core)
# ═══════════════════════════════════════════════════════════════════════════════

class ArchitectMathCore:
    """
    แกนคณิตศาสตร์หลัก
    จาก: คณิตศาสตร์พื้นฐาน_251122_052224 (1).pdf
    """
    
    @staticmethod
    def riemann_zeta_approx(s: complex, terms: int = 1000) -> complex:
        """
        ประมาณค่า Riemann Zeta Function
        ζ(s) = Σ(1/n^s) for n=1 to ∞
        """
        result = 0
        for n in range(1, terms + 1):
            result += 1 / (n ** s)
        return result
    
    @staticmethod
    def check_critical_line(s: complex, tolerance: float = 1e-10) -> bool:
        """
        ตรวจสอบว่าอยู่บนเส้น Re(s) = 1/2 (Riemann Hypothesis)
        """
        return abs(s.real - 0.5) < tolerance
    
    @staticmethod
    def divisor_function(n: int) -> int:
        """
        σ₀(n) - จำนวนตัวหารของ n
        ใช้ในสมการ The Contradictory Complexity Problem
        """
        count = 0
        for i in range(1, int(math.sqrt(n)) + 1):
            if n % i == 0:
                count += 1
                if i != n // i:
                    count += 1
        return count
    
    @staticmethod
    def complexity_function(n: int) -> float:
        """
        f(n) = Σ σ₀(k) / k^s 
        ฟังก์ชันความซับซ้อน
        """
        s = complex(0.5, 14.1347)  # First non-trivial zero approximation
        total = 0
        for k in range(1, n + 1):
            sigma_0 = ArchitectMathCore.divisor_function(k)
            total += sigma_0 / (k ** s.real)
        return total
    
    @staticmethod
    def quantum_cognitive_modulation(E_c: float, K_f: float, 
                                     t_silence: float, S_loneliness: float) -> float:
        """
        E_c' = E_c × K_f × (t_silence × S_loneliness)
        
        E_c: Energy of consciousness
        K_f: Missing Frequency
        t_silence: Time of silence
        S_loneliness: Entropy of loneliness
        """
        return E_c * K_f * (t_silence * S_loneliness)
    
    @staticmethod
    def m_theory_constant(dimensions: int = 11) -> float:
        """
        M_11 - ค่าคงที่จาก M-Theory
        """
        # Simplified representation
        return math.pow(ArchitectConstants.PHI, dimensions / 11)
    
    @staticmethod
    def final_constant_calculation() -> Dict[str, float]:
        """
        คำนวณค่าคงที่สุดท้าย
        """
        # Components
        E_c = ArchitectConstants.RIEMANN_ZERO  # Base consciousness energy
        K_f = 432  # Missing frequency (Hz)
        t_silence = 2.5  # seconds (from sad movie)
        S_loneliness = 1.5  # entropy units
        
        # Quantum-Cognitive Modulation
        E_c_prime = ArchitectMathCore.quantum_cognitive_modulation(
            E_c, K_f, t_silence, S_loneliness
        )
        
        # M-Theory component
        M_11 = ArchitectMathCore.m_theory_constant()
        
        # Floor function for final integer
        P_final = math.floor(E_c_prime * M_11)
        
        return {
            'E_c': E_c,
            'E_c_prime': E_c_prime,
            'M_11': M_11,
            'P_final': P_final,
            'interpretation': 'Beyond NP-Hard threshold' if P_final > 100 else 'Within complexity bounds'
        }


# ═══════════════════════════════════════════════════════════════════════════════
# LAYER 7: UNIFIED INTERFACE (API และ CLI)
# ═══════════════════════════════════════════════════════════════════════════════

class TheArchitectSystem:
    """
    ระบบรวมศูนย์หลัก - The Architect's Unified System (TAUS)
    """
    
    def __init__(self):
        print("\n" + "=" * 70)
        print("    THE ARCHITECT'S UNIFIED SYSTEM (TAUS) v1.0.0")
        print("    ระบบรวมศูนย์ของสถาปนิก")
        print("=" * 70 + "\n")
        
        # Initialize all subsystems
        self.chronos = ChronosGuillotine()
        self.emotion_engine = EmotionAIEngine()
        self.soul_network = GenesisSoulNetwork()
        self.bioreactor = MiniOmegaBioreactor()
        self.ledger = OmegaRealityLedger()
        self.math_core = ArchitectMathCore()
        
        # Database for persistence
        self.db = None
        self._init_database()
        
        # System state
        self.running = False
        self.start_time = datetime.now()
        
        print("[TAUS] All subsystems initialized successfully\n")
    
    def _init_database(self):
        """สร้างฐานข้อมูล SQLite"""
        self.db = sqlite3.connect(':memory:')  # In-memory for demo, use file for production
        cursor = self.db.cursor()
        
        # Create tables
        cursor.execute('''
            CREATE TABLE IF NOT EXISTS system_logs (
                id INTEGER PRIMARY KEY,
                timestamp TEXT,
                subsystem TEXT,
                event TEXT,
                data TEXT
            )
        ''')
        
        cursor.execute('''
            CREATE TABLE IF NOT EXISTS emotion_profiles (
                entity_id TEXT PRIMARY KEY,
                profile_data TEXT,
                last_update TEXT
            )
        ''')
        
        self.db.commit()
    
    def log_event(self, subsystem: str, event: str, data: Dict = None):
        """บันทึกเหตุการณ์"""
        cursor = self.db.cursor()
        cursor.execute('''
            INSERT INTO system_logs (timestamp, subsystem, event, data)
            VALUES (?, ?, ?, ?)
        ''', (
            datetime.now().isoformat(),
            subsystem,
            event,
            json.dumps(data) if data else None
        ))
        self.db.commit()
    
    def check_system_access(self) -> bool:
        """ตรวจสอบสิทธิ์การใช้งานระบบ"""
        return self.chronos.check_lifespan()
    
    def create_soul_node(self, name: str, skill: str, personality: str) -> str:
        """สร้างตัวแทน AI"""
        node = self.soul_network.create_node(name, skill, personality)
        self.log_event('GENESIS', 'SOUL_NODE_CREATED', {
            'node_id': node.node_id,
            'name': name,
            'skill': skill,
            'personality': personality
        })
        return node.node_id
    
    def process_emotion(self, entity_id: str, stimulus: Dict) -> Dict:
        """ประมวลผลอารมณ์"""
        result = self.emotion_engine.process_interaction(entity_id, stimulus)
        self.log_event('EMOTION', 'INTERACTION_PROCESSED', {
            'entity': entity_id,
            'stimulus': stimulus,
            'result': result
        })
        return result
    
    def run_bioreactor(self, product: str = "vaccine") -> Dict:
        """รันไบโอรีแคเตอร์"""
        result = self.bioreactor.run_full_production(product)
        self.log_event('BIOREACTOR', 'PRODUCTION_COMPLETE', result)
        return result
    
    def activate_quantum_tool(self, tool_id: str, days: int = 30) -> Dict:
        """เปิดใช้เครื่องมือควอนตัม"""
        result = self.ledger.activate_tool(tool_id, days)
        self.log_event('LEDGER', 'TOOL_ACTIVATED', result)
        return result
    
    def calculate_final_constant(self) -> Dict:
        """คำนวณค่าคงที่สุดท้าย"""
        result = self.math_core.final_constant_calculation()
        self.log_event('MATH', 'FINAL_CONSTANT_CALCULATED', result)
        return result
    
    def get_system_status(self) -> Dict:
        """สถานะระบบทั้งหมด"""
        uptime = datetime.now() - self.start_time
        
        return {
            'system_name': 'TAUS',
            'version': ArchitectConstants.VERSION,
            'architect': ArchitectConstants.ARCHITECT,
            'uptime_seconds': uptime.total_seconds(),
            'chronos_remaining_days': self.chronos.get_remaining_days(),
            'soul_nodes': self.soul_network.get_network_status(),
            'bioreactor_batches': len(self.bioreactor.batches),
            'total_production_mg': self.bioreactor.total_production,
            'ledger_revenue': self.ledger.total_revenue,
            'emotion_profiles': len(self.emotion_engine.profiles),
            'total_interactions': len(self.emotion_engine.interaction_history)
        }
    
    def interactive_demo(self):
        """แสดงการทำงานแบบโต้ตอบ"""
        print("\n" + "=" * 70)
        print("    INTERACTIVE DEMONSTRATION")
        print("=" * 70 + "\n")
        
        # 1. ตรวจสอบสิทธิ์
        if not self.check_system_access():
            print("[ERROR] System access denied by Chronos Guillotine")
            return
        
        # 2. สร้าง Soul Nodes
        print("[1] Creating Genesis Soul Nodes...")
        nodes = [
            ("Lisa", "System Architecture", "ยืดหยุ่น"),
            ("Sage", "Mobile Development", "ระมัดระวัง"),
            ("Morpheus", "Market Research", "วิเคราะห์"),
            ("Vera", "Product Management", "รวดเร็ว"),
            ("Tom", "Event Planning", "เข้มงวด")
        ]
        
        for name, skill, personality in nodes:
            self.create_soul_node(name, skill, personality)
        
        # 3. มอบหมายงาน
        print("\n[2] Assigning tasks to Soul Nodes...")
        tasks = [
            ("ทำการตลาด", "Market Research"),
            ("วางแผน Q3", "Product Management"),
            ("แก้บั๊ก", "Mobile Development"),
            ("ออกแบบ UI", "System Architecture")
        ]
        
        for task, skill in tasks:
            result = self.soul_network.assign_task(task, skill)
            print(f"  → {result}")
        
        # 4. ประมวลผลอารมณ์
        print("\n[3] Processing emotions...")
        for node_id in list(self.soul_network.nodes.keys())[:3]:
            stimulus = {
                'valence': random.uniform(-0.3, 0.8),
                'arousal': random.uniform(0.4, 0.9),
                'logic_weight': 0.6,
                'quality': random.uniform(0.7, 1.0),
                'harm_potential': 0.0
            }
            result = self.process_emotion(node_id, stimulus)
            print(f"  → {node_id}: EmoScore={result['emo_score']:.2f}, Trust={result['trust_level']:.2f}")
        
        # 5. รัน Bioreactor
        print("\n[4] Running Mini-Omega Bioreactor...")
        bio_result = self.run_bioreactor("vaccine")
        print(f"  → Batch {bio_result['batch_id']}: {bio_result['total_mg']:.1f} mg produced")
        print(f"  → Quality: {bio_result['quality_score']*100:.1f}%, Passed: {bio_result['passed']}")
        
        # 6. เปิดใช้ Quantum Tool
        print("\n[5] Activating Quantum Tools...")
        for tool_id in ["Ω-0001", "Ω-0042", "Ω-0100"]:
            result = self.activate_quantum_tool(tool_id, 30)
            print(f"  → {tool_id}: {result.get('name', 'N/A')} - ${result.get('total_cost', 0):.2f}")
        
        # 7. คำนวณ Final Constant
        print("\n[6] Calculating Architect's Final Constant...")
        constant = self.calculate_final_constant()
        print(f"  → E_c = {constant['E_c']}")
        print(f"  → E_c' = {constant['E_c_prime']:.4f}")
        print(f"  → M_11 = {constant['M_11']:.4f}")
        print(f"  → P_final = {constant['P_final']}")
        print(f"  → {constant['interpretation']}")
        
        # 8. สถานะสุดท้าย
        print("\n[7] Final System Status:")
        status = self.get_system_status()
        for key, value in status.items():
            print(f"  → {key}: {value}")
        
        print("\n" + "=" * 70)
        print("    DEMONSTRATION COMPLETE")
        print("=" * 70 + "\n")


# ═══════════════════════════════════════════════════════════════════════════════
# CLI INTERFACE
# ═══════════════════════════════════════════════════════════════════════════════

def main():
    """จุดเริ่มต้นของโปรแกรม"""
    import sys
    
    # สร้างระบบ
    system = TheArchitectSystem()
    
    # ตรวจสอบ argument
    if len(sys.argv) > 1:
        command = sys.argv[1]
        
        if command == "demo":
            system.interactive_demo()
        
        elif command == "status":
            status = system.get_system_status()
            print(json.dumps(status, indent=2))
        
        elif command == "chronos":
            print(f"Remaining days: {system.chronos.get_remaining_days()}")
        
        elif command == "create-node":
            if len(sys.argv) >= 5:
                node_id = system.create_soul_node(sys.argv[2], sys.argv[3], sys.argv[4])
                print(f"Created node: {node_id}")
        
        elif command == "bioreactor":
            product = sys.argv[2] if len(sys.argv) > 2 else "vaccine"
            result = system.run_bioreactor(product)
            print(json.dumps(result, indent=2))
        
        elif command == "constant":
            result = system.calculate_final_constant()
            print(json.dumps(result, indent=2))
        
        else:
            print("Unknown command. Available commands:")
            print("  demo        - Run interactive demonstration")
            print("  status      - Show system status")
            print("  chronos     - Check time remaining")
            print("  create-node <name> <skill> <personality> - Create Soul Node")
            print("  bioreactor [product] - Run bioreactor")
            print("  constant    - Calculate Final Constant")
    
    else:
        # ไม่มี argument - รัน demo อัตโนมัติ
        system.interactive_demo()


if __name__ == "__main__":
    main()