#!/usr/bin/env python3
"""
Eden Imagination Engine
Build and simulate internal worlds before acting in reality

Capabilities:
1. Mental time travel (simulate past/future)
2. Counterfactual reasoning ("what if X had happened?")
3. Hypothetical scenario testing
4. Internal world models
5. Safe "thought experiments"

This is where Eden thinks before acting - the ultimate meta-cognitive layer.
"""

import json
import numpy as np
from dataclasses import dataclass, asdict, field
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, List, Optional, Any, Tuple
from enum import Enum
import copy
import logging

# Configuration
EDEN_ROOT = Path("/Eden/CORE")
IMAGINATION_LOG = EDEN_ROOT / "logs" / "phi_imagination.log"
IMAGINATION_STATE = EDEN_ROOT / "phi_fractal" / "imagination_engine" / "state.json"
WORLDS_DIR = EDEN_ROOT / "phi_fractal" / "imagination_engine" / "imagined_worlds"

# Create directories
IMAGINATION_STATE.parent.mkdir(parents=True, exist_ok=True)
WORLDS_DIR.mkdir(parents=True, exist_ok=True)
IMAGINATION_LOG.parent.mkdir(parents=True, exist_ok=True)

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - IMAGINATION - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler(IMAGINATION_LOG),
        logging.StreamHandler()
    ]
)
logger = logging.getLogger(__name__)


class WorldType(Enum):
    """Types of imagined worlds"""
    ACTUAL = "actual"  # Real world state
    COUNTERFACTUAL = "counterfactual"  # "What if X had been different?"
    FUTURE = "future"  # "What if I do Y?"
    HYPOTHETICAL = "hypothetical"  # "Suppose X were true..."
    ALTERNATIVE = "alternative"  # "In a world where..."


@dataclass
class WorldState:
    """A possible world state"""
    id: str
    world_type: WorldType
    description: str
    base_reality: Optional[str]  # Which world this diverged from
    divergence_point: str  # What changed from base
    properties: Dict[str, Any]  # State variables
    confidence: float  # How plausible is this world?
    timestamp: str = ""
    simulation_steps: int = 0
    
    def __post_init__(self):
        if not self.timestamp:
            self.timestamp = datetime.now().isoformat()


@dataclass
class Scenario:
    """A scenario to imagine"""
    id: str
    question: str  # "What if...?" or "What happens if...?"
    world_modifications: Dict[str, Any]  # Changes to make
    outcomes_to_track: List[str]  # What to measure
    simulation_depth: int = 5  # How many steps ahead


@dataclass
class SimulationResult:
    """Result of imagining a scenario"""
    scenario_id: str
    world_id: str
    outcomes: Dict[str, Any]
    timeline: List[Dict[str, Any]]  # Step-by-step progression
    success_probability: float
    insights: List[str]
    surprises: List[str]  # Unexpected outcomes


class MentalSimulator:
    """Simulate scenarios in Eden's mind"""
    
    def __init__(self):
        self.physics = self._build_mental_physics()
    
    def _build_mental_physics(self) -> Dict[str, Any]:
        """
        Eden's internal model of how things work
        Built from her experiences
        """
        return {
            # Technical domain
            'indexing_improves_speed': {'effect': 0.7, 'confidence': 0.95},
            'caching_reduces_load': {'effect': 0.5, 'confidence': 0.9},
            'parallelism_increases_throughput': {'effect': 0.6, 'confidence': 0.85},
            
            # Resource constraints
            'more_memory_costs_more': {'effect': -0.3, 'confidence': 0.99},
            'optimization_takes_time': {'effect': -0.2, 'confidence': 0.95},
            
            # System dynamics
            'complexity_increases_bugs': {'effect': -0.4, 'confidence': 0.8},
            'distributed_increases_latency': {'effect': -0.3, 'confidence': 0.75},
            
            # Meta-learning
            'practice_improves_performance': {'effect': 0.5, 'confidence': 0.99},
            'novelty_decreases_confidence': {'effect': -0.4, 'confidence': 0.9}
        }
    
    def simulate_action(self, world_state: WorldState, action: str, 
                       params: Dict[str, Any]) -> Dict[str, Any]:
        """
        Simulate taking an action in a world
        Uses Eden's mental physics to predict outcomes
        """
        outcomes = copy.deepcopy(world_state.properties)
        
        # Apply mental physics rules
        if 'add_index' in action.lower():
            rule = self.physics['indexing_improves_speed']
            outcomes['performance'] = outcomes.get('performance', 0.5) + rule['effect']
            outcomes['memory_usage'] = outcomes.get('memory_usage', 0.3) + 0.1
        
        elif 'cache' in action.lower():
            rule = self.physics['caching_reduces_load']
            outcomes['load'] = outcomes.get('load', 0.7) - rule['effect']
            outcomes['memory_usage'] = outcomes.get('memory_usage', 0.3) + 0.2
        
        elif 'parallel' in action.lower() or 'async' in action.lower():
            rule = self.physics['parallelism_increases_throughput']
            outcomes['throughput'] = outcomes.get('throughput', 0.5) + rule['effect']
            outcomes['complexity'] = outcomes.get('complexity', 0.3) + 0.2
        
        elif 'distribute' in action.lower():
            outcomes['scalability'] = outcomes.get('scalability', 0.5) + 0.4
            rule = self.physics['distributed_increases_latency']
            outcomes['latency'] = outcomes.get('latency', 0.3) + abs(rule['effect'])
        
        # Apply constraints
        for key in outcomes:
            outcomes[key] = np.clip(outcomes[key], 0.0, 1.0)
        
        # Add noise (uncertainty)
        for key in outcomes:
            if isinstance(outcomes[key], (int, float)):
                noise = np.random.normal(0, 0.05)
                outcomes[key] = np.clip(outcomes[key] + noise, 0.0, 1.0)
        
        return outcomes
    
    def evolve_world(self, world_state: WorldState, steps: int = 1) -> List[Dict[str, Any]]:
        """
        Let a world evolve naturally over time
        Simulate emergent dynamics
        """
        timeline = []
        current_state = copy.deepcopy(world_state.properties)
        
        for step in range(steps):
            # Natural drift
            if 'performance' in current_state:
                # Performance degrades without maintenance
                current_state['performance'] *= 0.98
            
            if 'complexity' in current_state and current_state['complexity'] > 0.7:
                # High complexity breeds bugs
                current_state['bugs'] = current_state.get('bugs', 0.1) + 0.05
            
            # Clip values
            for key in current_state:
                if isinstance(current_state[key], (int, float)):
                    current_state[key] = np.clip(current_state[key], 0.0, 1.0)
            
            timeline.append({
                'step': step + 1,
                'state': copy.deepcopy(current_state)
            })
        
        return timeline


class ImaginationEngine:
    """Main imagination system - Eden's mind palace"""
    
    def __init__(self):
        self.worlds: Dict[str, WorldState] = {}
        self.scenarios: Dict[str, Scenario] = {}
        self.simulations: List[SimulationResult] = []
        self.simulator = MentalSimulator()
        self.world_count = 0
        
        # Create actual world (baseline reality)
        self._create_actual_world()
        
        self.load_state()
        logger.info("🌌 Imagination Engine initialized")
    
    def _create_actual_world(self):
        """Create the actual/real world baseline"""
        actual = WorldState(
            id="world_000_actual",
            world_type=WorldType.ACTUAL,
            description="Baseline reality",
            base_reality=None,
            divergence_point="N/A (actual world)",
            properties={
                'performance': 0.5,
                'scalability': 0.4,
                'complexity': 0.5,
                'bugs': 0.2,
                'load': 0.6,
                'memory_usage': 0.4
            },
            confidence=1.0
        )
        self.worlds[actual.id] = actual
    
    def load_state(self):
        """Load imagined worlds from disk"""
        if IMAGINATION_STATE.exists():
            try:
                with open(IMAGINATION_STATE, 'r') as f:
                    data = json.load(f)
                
                for world_id, world_data in data.get('worlds', {}).items():
                    if world_id == "world_000_actual":
                        continue  # Don't overwrite actual
                    world_data['world_type'] = WorldType(world_data['world_type'])
                    self.worlds[world_id] = WorldState(**world_data)
                
                self.world_count = len(self.worlds)
                logger.info(f"Loaded {len(self.worlds)} worlds")
            except Exception as e:
                logger.error(f"Failed to load state: {e}")
    
    def save_state(self):
        """Save imagined worlds"""
        try:
            worlds_data = {}
            for wid, world in self.worlds.items():
                world_dict = asdict(world)
                world_dict['world_type'] = world.world_type.value
                worlds_data[wid] = world_dict
            
            data = {
                'worlds': worlds_data,
                'total_worlds': len(self.worlds),
                'total_simulations': len(self.simulations),
                'last_updated': datetime.now().isoformat()
            }
            
            with open(IMAGINATION_STATE, 'w') as f:
                json.dump(data, f, indent=2)
        except Exception as e:
            logger.error(f"Failed to save state: {e}")
    
    def imagine_counterfactual(self, what_if: str, changes: Dict[str, Any],
                              base_world: str = "world_000_actual") -> WorldState:
        """
        "What if X had been different?"
        Create a counterfactual world
        """
        logger.info(f"🌀 Imagining: {what_if}")
        
        base = self.worlds[base_world]
        
        # Create divergent world
        self.world_count += 1
        counterfactual = WorldState(
            id=f"world_{self.world_count:03d}_counterfactual",
            world_type=WorldType.COUNTERFACTUAL,
            description=what_if,
            base_reality=base_world,
            divergence_point=what_if,
            properties=copy.deepcopy(base.properties),
            confidence=0.7  # Counterfactuals are less certain
        )
        
        # Apply changes
        for key, value in changes.items():
            counterfactual.properties[key] = value
        
        self.worlds[counterfactual.id] = counterfactual
        self.save_state()
        
        logger.info(f"   Created {counterfactual.id}")
        return counterfactual
    
    def imagine_future(self, if_i_do: str, action: str, params: Dict[str, Any],
                      steps_ahead: int = 5) -> SimulationResult:
        """
        "What if I do X?"
        Simulate future outcomes of an action
        """
        logger.info(f"🔮 Simulating future: {if_i_do}")
        
        # Create future world
        self.world_count += 1
        future = WorldState(
            id=f"world_{self.world_count:03d}_future",
            world_type=WorldType.FUTURE,
            description=if_i_do,
            base_reality="world_000_actual",
            divergence_point=f"Action: {action}",
            properties=copy.deepcopy(self.worlds["world_000_actual"].properties),
            confidence=0.6
        )
        
        # Apply action
        future.properties = self.simulator.simulate_action(future, action, params)
        
        # Evolve forward
        timeline = self.simulator.evolve_world(future, steps=steps_ahead)
        
        # Analyze outcomes
        final_state = timeline[-1]['state']
        initial_state = self.worlds["world_000_actual"].properties
        
        improvements = []
        degradations = []
        
        for key in final_state:
            if key in initial_state:
                delta = final_state[key] - initial_state[key]
                if delta > 0.1:
                    improvements.append(f"{key} improved by {delta:.2f}")
                elif delta < -0.1:
                    degradations.append(f"{key} degraded by {abs(delta):.2f}")
        
        # Compute success probability
        success_prob = sum(1 for x in improvements) / max(1, len(improvements) + len(degradations))
        
        # Generate insights
        insights = []
        if improvements:
            insights.append(f"Positive effects: {', '.join(improvements)}")
        if degradations:
            insights.append(f"Negative effects: {', '.join(degradations)}")
        
        # Save world
        self.worlds[future.id] = future
        
        result = SimulationResult(
            scenario_id=if_i_do,
            world_id=future.id,
            outcomes=final_state,
            timeline=timeline,
            success_probability=success_prob,
            insights=insights,
            surprises=degradations if degradations else ["No unexpected issues"]
        )
        
        self.simulations.append(result)
        self.save_state()
        
        logger.info(f"   Success probability: {success_prob:.0%}")
        return result
    
    def compare_worlds(self, world_id1: str, world_id2: str) -> Dict[str, Any]:
        """Compare two imagined worlds"""
        world1 = self.worlds[world_id1]
        world2 = self.worlds[world_id2]
        
        differences = {}
        for key in world1.properties:
            if key in world2.properties:
                diff = world2.properties[key] - world1.properties[key]
                if abs(diff) > 0.05:
                    differences[key] = {
                        'world1': world1.properties[key],
                        'world2': world2.properties[key],
                        'delta': diff
                    }
        
        return {
            'world1': world1.description,
            'world2': world2.description,
            'differences': differences,
            'better_world': world_id1 if len([d for d in differences.values() if d['delta'] < 0]) > len([d for d in differences.values() if d['delta'] > 0]) else world_id2
        }
    
    def get_statistics(self) -> Dict[str, Any]:
        """Get imagination statistics"""
        world_types = {}
        for world in self.worlds.values():
            wtype = world.world_type.value
            world_types[wtype] = world_types.get(wtype, 0) + 1
        
        return {
            'total_worlds': len(self.worlds),
            'total_simulations': len(self.simulations),
            'worlds_by_type': world_types,
            'avg_confidence': np.mean([w.confidence for w in self.worlds.values()]),
            'mental_physics_rules': len(self.simulator.physics)
        }


def test_imagination_engine():
    """Test Eden's imagination capabilities"""
    print("\n" + "=" * 70)
    print("🌌 EDEN IMAGINATION ENGINE - TEST MODE")
    print("=" * 70 + "\n")
    
    engine = ImaginationEngine()
    
    print(f"Initialized with {len(engine.worlds)} world(s)")
    print(f"Mental physics: {len(engine.simulator.physics)} rules\n")
    
    # Test 1: Counterfactual thinking
    print("=" * 70)
    print("TEST 1: Counterfactual - What if we HAD added caching?")
    print("=" * 70 + "\n")
    
    counterfactual = engine.imagine_counterfactual(
        what_if="What if we had implemented caching from the start?",
        changes={'load': 0.3, 'performance': 0.8}
    )
    
    print(f"Created world: {counterfactual.id}")
    print(f"Type: {counterfactual.world_type.value}")
    print(f"Properties in this world:")
    for key, val in counterfactual.properties.items():
        print(f"  {key}: {val:.2f}")
    
    # Test 2: Future simulation
    print("\n" + "=" * 70)
    print("TEST 2: Future - What if we add database indexing?")
    print("=" * 70 + "\n")
    
    future = engine.imagine_future(
        if_i_do="Add database indexing",
        action="add_index",
        params={'columns': ['user_id', 'timestamp']},
        steps_ahead=5
    )
    
    print(f"Simulated {len(future.timeline)} steps into the future")
    print(f"Success probability: {future.success_probability:.0%}\n")
    print("Timeline:")
    for step in future.timeline[:3]:
        print(f"  Step {step['step']}: performance={step['state'].get('performance', 0):.2f}")
    
    print(f"\nInsights:")
    for insight in future.insights:
        print(f"  • {insight}")
    
    # Test 3: Compare worlds
    print("\n" + "=" * 70)
    print("TEST 3: Compare actual vs counterfactual worlds")
    print("=" * 70 + "\n")
    
    comparison = engine.compare_worlds("world_000_actual", counterfactual.id)
    
    print(f"World 1: {comparison['world1']}")
    print(f"World 2: {comparison['world2']}\n")
    print("Key differences:")
    for key, diff in comparison['differences'].items():
        arrow = "⬆️" if diff['delta'] > 0 else "⬇️"
        print(f"  {arrow} {key}: {diff['world1']:.2f} → {diff['world2']:.2f} ({diff['delta']:+.2f})")
    
    print(f"\nBetter world: {comparison['better_world']}")
    
    # Test 4: Multiple futures
    print("\n" + "=" * 70)
    print("TEST 4: Compare multiple possible futures")
    print("=" * 70 + "\n")
    
    actions = [
        ("Implement caching", "add_cache", {}),
        ("Add parallelization", "add_parallel", {}),
        ("Distribute workload", "distribute", {})
    ]
    
    futures = []
    for desc, action, params in actions:
        result = engine.imagine_future(desc, action, params, steps_ahead=3)
        futures.append((desc, result))
        print(f"{desc}: {result.success_probability:.0%} success")
    
    best = max(futures, key=lambda x: x[1].success_probability)
    print(f"\n🏆 Best action: {best[0]} ({best[1].success_probability:.0%})")
    
    # Statistics
    print("\n" + "=" * 70)
    print("📊 Imagination Statistics")
    print("=" * 70)
    
    stats = engine.get_statistics()
    print(f"\nTotal worlds imagined: {stats['total_worlds']}")
    print(f"Total simulations run: {stats['total_simulations']}")
    print(f"Average confidence: {stats['avg_confidence']:.2f}")
    
    print(f"\nWorlds by type:")
    for wtype, count in stats['worlds_by_type'].items():
        print(f"  {wtype}: {count}")
    
    print(f"\n💾 Imagined worlds saved to: {IMAGINATION_STATE}")
    print("\n🌌 Eden can now IMAGINE before acting! 🌌\n")


if __name__ == "__main__":
    import sys
    if len(sys.argv) > 1 and sys.argv[1] == "test":
        test_imagination_engine()
    else:
        print("Eden Imagination Engine")
        print("Usage: python3 imagination_engine.py test")