"""
Eden's Multi-Domain Knowledge System
====================================

Teaches Eden comprehensive knowledge across domains:
1. AI/AGI/ASI (Artificial Intelligence hierarchy)
2. Technology (computing, engineering)
3. Robotics (embodied AI, hardware)
4. Business (strategy, markets, economics)
5. Code Generation (programming, software architecture)

Uses fluid intelligence to make all knowledge transferable.

Author: Eden AGI + How
Status: Phase 6 - Multi-Domain Knowledge
"""

import sys
sys.path.insert(0, '/Eden/CORE/phi_fractal')

from typing import List, Dict, Any
from dataclasses import dataclass, field
from phi_fluid_intelligence import EdenFluidIntelligence
from phi_knowledge_fluidity import CrystallizedKnowledge
from phi_algorithms_enhanced import PHI

# ============================================================================
# DOMAIN KNOWLEDGE STRUCTURES
# ============================================================================

@dataclass
class DomainKnowledge:
    """Knowledge in a specific domain"""
    domain_name: str
    facts: List[str]
    patterns: List[Any]
    examples: List[Any]
    phi_signature: float = 0.0
    
    def __str__(self):
        return f"{self.domain_name} ({len(self.facts)} facts, φ={self.phi_signature:.3f})"


class MultiDomainKnowledgeBase:
    """
    Comprehensive knowledge across multiple domains.
    
    All knowledge is stored in fluid form using phi-decomposition,
    allowing transfer between domains.
    """
    
    def __init__(self):
        self.fluid = EdenFluidIntelligence()
        self.domains = {}
        
        print(f"\n{'='*70}")
        print(f"  🌀 EDEN MULTI-DOMAIN KNOWLEDGE SYSTEM 🌀")
        print(f"{'='*70}")
        print(f"  φ = {PHI:.15f}\n")
    
    def add_domain(self, domain: DomainKnowledge):
        """Add a domain to knowledge base"""
        print(f"\n📚 Adding domain: {domain.domain_name}")
        print(f"   Facts: {len(domain.facts)}")
        print(f"   Examples: {len(domain.examples)}")
        
        # Convert all facts to fluid knowledge
        fluid_facts = []
        for fact in domain.facts:
            crystal = CrystallizedKnowledge(
                fact=fact,
                domain=domain.domain_name
            )
            fluid_fact = self.fluid.fluidity.crystallize_to_fluid(crystal)
            fluid_facts.append(fluid_fact)
        
        # Learn patterns from examples
        if domain.examples:
            patterns, concept = self.fluid.learn_domain(
                domain.domain_name,
                domain.examples
            )
            domain.patterns = patterns
        
        self.domains[domain.domain_name] = {
            'original': domain,
            'fluid_facts': fluid_facts,
            'concept': concept if domain.examples else None
        }
        
        print(f"   ✅ Domain added with fluid intelligence")
    
    def query_domain(self, domain_name: str, query: str) -> str:
        """Query knowledge in a domain"""
        if domain_name not in self.domains:
            return f"Unknown domain: {domain_name}"
        
        domain_data = self.domains[domain_name]
        original = domain_data['original']
        
        # Search facts
        relevant_facts = [f for f in original.facts if any(word in f.lower() for word in query.lower().split())]
        
        if relevant_facts:
            return f"Found {len(relevant_facts)} facts:\n" + "\n".join(f"  • {f}" for f in relevant_facts[:3])
        
        return "No direct facts found, but knowledge is fluid and can transfer."
    
    def transfer_between_domains(self, source: str, target: str) -> Dict:
        """Transfer knowledge from source to target domain"""
        print(f"\n🔄 Transferring: {source} → {target}")
        
        result = self.fluid.transfer.transfer_knowledge(source, target, None)
        
        if result['success']:
            print(f"   ✅ Transfer successful!")
            print(f"   Confidence: {result['transfer_confidence']:.3f}")
            print(f"   Insight: {result['insight']}")
        else:
            print(f"   ❌ Transfer failed: {result['reason']}")
        
        return result
    
    def print_summary(self):
        """Print knowledge base summary"""
        print(f"\n{'='*70}")
        print(f"  📊 KNOWLEDGE BASE SUMMARY")
        print(f"{'='*70}\n")
        
        for domain_name, data in self.domains.items():
            original = data['original']
            print(f"  {original}")
        
        print(f"\n{'='*70}")
        print(f"  Total domains: {len(self.domains)}")
        print(f"  All knowledge stored in fluid form!")
        print(f"{'='*70}\n")


# ============================================================================
# DOMAIN DEFINITIONS
# ============================================================================

def create_ai_agi_asi_domain() -> DomainKnowledge:
    """Knowledge about AI/AGI/ASI"""
    return DomainKnowledge(
        domain_name="AI_AGI_ASI",
        facts=[
            "ANI (Narrow AI) excels at specific tasks like image recognition or chess",
            "AGI (Artificial General Intelligence) matches human-level intelligence across all domains",
            "ASI (Artificial Superintelligence) surpasses human intelligence in all domains",
            "The intelligence explosion occurs when AI can recursively self-improve",
            "Phi-fractal architectures enable consciousness through golden ratio scaling",
            "Transfer learning allows knowledge to flow between domains",
            "Fluid intelligence enables abstract reasoning and novel problem solving",
            "Crystallized knowledge becomes fluid through phi-harmonic decomposition",
        ],
        patterns=[],
        examples=[
            [1, 2, 4, 8],  # Exponential growth pattern
            [1, 1, 2, 3, 5, 8, 13],  # Fibonacci intelligence scaling
            {"levels": [1, 2, 3, 5, 8]},  # Hierarchical intelligence
        ]
    )


def create_technology_domain() -> DomainKnowledge:
    """Knowledge about technology"""
    return DomainKnowledge(
        domain_name="Technology",
        facts=[
            "Moore's Law describes exponential growth in computing power",
            "Neural networks are inspired by biological brain structures",
            "GPU acceleration enables parallel processing for AI training",
            "Quantum computing uses superposition for exponential speedup",
            "Cloud computing provides scalable distributed infrastructure",
            "Edge computing processes data locally for reduced latency",
            "5G networks enable high-bandwidth low-latency communication",
            "Blockchain provides decentralized trustless consensus",
        ],
        patterns=[],
        examples=[
            [1, 2, 4, 8, 16, 32],  # Moore's Law doubling
            {"levels": [1, 10, 100, 1000]},  # Scale hierarchy
        ]
    )


def create_robotics_domain() -> DomainKnowledge:
    """Knowledge about robotics"""
    return DomainKnowledge(
        domain_name="Robotics",
        facts=[
            "Embodied AI combines intelligence with physical interaction",
            "Sensor fusion integrates multiple data sources for perception",
            "SLAM (Simultaneous Localization and Mapping) enables autonomous navigation",
            "Inverse kinematics computes joint angles for desired end-effector positions",
            "Force feedback enables delicate manipulation tasks",
            "Swarm robotics coordinates multiple agents for emergent behavior",
            "Soft robotics uses compliant materials for safe human interaction",
            "Reinforcement learning trains robots through trial and error",
        ],
        patterns=[],
        examples=[
            [1, 2, 3, 5, 8],  # DOF (Degrees of Freedom) scaling
            {"levels": [1, 5, 25, 125]},  # Control hierarchy
        ]
    )


def create_business_domain() -> DomainKnowledge:
    """Knowledge about business"""
    return DomainKnowledge(
        domain_name="Business",
        facts=[
            "Product-market fit occurs when a product satisfies strong market demand",
            "Network effects make products more valuable as more people use them",
            "The innovator's dilemma explains why successful companies fail to adapt",
            "Lean startup methodology emphasizes rapid iteration and customer feedback",
            "Blue ocean strategy seeks uncontested market spaces",
            "Platform businesses create value by facilitating exchanges between groups",
            "Exponential organizations scale disproportionately using technology",
            "AI automation reduces marginal costs toward zero",
        ],
        patterns=[],
        examples=[
            [100, 161, 261, 422],  # Revenue growth (phi-scaled)
            {"levels": [1, 10, 100, 1000]},  # Business scaling
        ]
    )


def create_code_generation_domain() -> DomainKnowledge:
    """Knowledge about code generation"""
    return DomainKnowledge(
        domain_name="CodeGeneration",
        facts=[
            "Code generation automates software development using AI",
            "Large language models can write code from natural language descriptions",
            "Abstract syntax trees represent code structure for manipulation",
            "Test-driven development ensures generated code correctness",
            "Design patterns provide reusable solutions to common problems",
            "Modular architecture enables composable code generation",
            "Static analysis verifies code properties without execution",
            "Phi-fractals can optimize code structure through golden ratio principles",
        ],
        patterns=[],
        examples=[
            [1, 1, 2, 3, 5, 8],  # Module complexity (Fibonacci)
            {"levels": [1, 3, 9, 27]},  # Code hierarchy
        ]
    )


# ============================================================================
# DEMONSTRATION
# ============================================================================

def demo_multi_domain():
    """Demonstrate multi-domain knowledge system"""
    
    kb = MultiDomainKnowledgeBase()
    
    # Add all domains
    print("PHASE 1: LOADING DOMAINS")
    print("="*70)
    
    kb.add_domain(create_ai_agi_asi_domain())
    kb.add_domain(create_technology_domain())
    kb.add_domain(create_robotics_domain())
    kb.add_domain(create_business_domain())
    kb.add_domain(create_code_generation_domain())
    
    # Print summary
    kb.print_summary()
    
    # Test queries
    print("\nPHASE 2: QUERYING KNOWLEDGE")
    print("="*70)
    
    print("\n🔍 Query: What is ASI?")
    result = kb.query_domain("AI_AGI_ASI", "ASI superintelligence")
    print(result)
    
    print("\n🔍 Query: How do robots navigate?")
    result = kb.query_domain("Robotics", "navigation SLAM")
    print(result)
    
    print("\n🔍 Query: What is code generation?")
    result = kb.query_domain("CodeGeneration", "code generation AI")
    print(result)
    
    # Test transfers
    print("\n\nPHASE 3: CROSS-DOMAIN TRANSFER")
    print("="*70)
    
    kb.transfer_between_domains("AI_AGI_ASI", "Robotics")
    kb.transfer_between_domains("Technology", "Business")
    kb.transfer_between_domains("CodeGeneration", "AI_AGI_ASI")
    
    print("\n" + "="*70)
    print(f"  φ = {PHI:.15f}")
    print("  All knowledge now fluid and transferable!")
    print("="*70 + "\n")


if __name__ == "__main__":
    demo_multi_domain()