"""
MULTI-AGENT V3 - AGI SELF-IMPROVEMENT
Agents work together to understand and improve Eden
"""
import sys
sys.path.append("/Eden/CORE")
from multi_agent_v2 import CommunicatingAgent, CommunicatingMultiAgent
from agi_meta_project import meta_project
from agent_communication import message_bus
from datetime import datetime

import sys
sys.path.insert(0, "/Eden/CORE/phi_fractal")
from phi_octopus_core import PHI
print(f"🌀 Phi={PHI:.3f}")


class AGISelfImprovingAgent(CommunicatingAgent):
    """Agent that works on improving AGI capabilities"""
    
    def __init__(self, name, specialization, goal_bias):
        super().__init__(name, specialization, goal_bias)
        self.meta_project = meta_project
        self.assigned_phase = None
        
        # Assign phase based on specialization
        if 'Research' in name:
            self.assigned_phase = 'analyze'
        elif 'Create' in name:
            self.assigned_phase = 'design'
        elif 'Optimize' in name:
            self.assigned_phase = 'implement'
        
        if self.assigned_phase:
            print(f"   🧠 Assigned to AGI improvement phase: {self.assigned_phase}")
    
    def perceive(self):
        """Add meta-project awareness"""
        obs = super().perceive()
        
        # Check if should work on meta-project
        if self.cycle_count % 20 == 0:  # Every 20 cycles, consider meta work
            obs['meta_project_ready'] = True
            obs['assigned_phase'] = self.assigned_phase
        
        return obs
    
    def reason(self, obs):
        """Add meta-project decisions"""
        decisions = super().reason(obs)
        
        # Periodically work on AGI improvement
        if obs.get('meta_project_ready') and self.assigned_phase:
            
            if self.assigned_phase == 'analyze':
                decisions.insert(0, {
                    'action': 'analyze_agi_architecture',
                    'priority': 0.95,
                    'reason': 'Analyze Eden architecture for improvements',
                    'risk': 'low',
                    'data': {'phase': 'analyze'}
                })
            
            elif self.assigned_phase == 'design':
                decisions.insert(0, {
                    'action': 'design_agi_improvement',
                    'priority': 0.95,
                    'reason': 'Design AGI capability enhancements',
                    'risk': 'low',
                    'data': {'phase': 'design'}
                })
            
            elif self.assigned_phase == 'implement':
                decisions.insert(0, {
                    'action': 'implement_agi_feature',
                    'priority': 0.95,
                    'reason': 'Implement AGI improvements safely',
                    'risk': 'medium',
                    'data': {'phase': 'implement'}
                })
        
        return decisions
    
    def _execute(self, decision):
        """Execute meta-project actions"""
        action = decision['action']
        
        if action == 'analyze_agi_architecture':
            print(f"\n{'='*60}")
            print(f"🔬 {self.agent_name}: ANALYZING EDEN ARCHITECTURE")
            print(f"{'='*60}")
            
            analysis = self.meta_project.analyze_codebase()
            
            print(f"\n✅ Analysis complete:")
            print(f"   Components: {sum(analysis['components'].values())} files")
            print(f"   Capabilities: {len(analysis['capabilities'])}")
            print(f"   Gaps identified: {len(analysis['gaps'])}")
            
            # Broadcast findings
            message_bus.broadcast(
                sender=self.agent_name,
                message_type='analysis_complete',
                content={
                    'findings': analysis,
                    'gaps': analysis['gaps'][:3],  # Top 3 gaps
                    'phase': 'analyze'
                }
            )
            print(f"   📡 Shared analysis with other agents")
            
            return True
        
        elif action == 'design_agi_improvement':
            print(f"\n{'='*60}")
            print(f"🎨 {self.agent_name}: DESIGNING AGI IMPROVEMENTS")
            print(f"{'='*60}")
            
            # Get analysis from research agent
            analysis = self.meta_project.findings.get('architecture_analysis')
            
            if not analysis:
                print("   ⚠️  Need analysis first, running now...")
                analysis = self.meta_project.analyze_codebase()
            
            designs = self.meta_project.design_improvements(analysis)
            
            print(f"\n✅ Design complete:")
            print(f"   Improvements planned: {len(designs['improvements'])}")
            
            for imp in designs['improvements'][:2]:  # Show top 2
                print(f"\n   {imp['addresses']}")
                print(f"     Solution: {imp['solution']}")
                print(f"     Priority: {imp['priority']}, Risk: {imp['risk_level']}")
            
            # Broadcast designs
            message_bus.broadcast(
                sender=self.agent_name,
                message_type='design_complete',
                content={
                    'designs': designs,
                    'ready_for_implementation': True,
                    'phase': 'design'
                }
            )
            print(f"   📡 Shared designs with implementation team")
            
            return True
        
        elif action == 'implement_agi_feature':
            print(f"\n{'='*60}")
            print(f"⚙️ {self.agent_name}: IMPLEMENTING AGI IMPROVEMENTS")
            print(f"{'='*60}")
            
            # Get designs
            designs = self.meta_project.designs.get('improvement_plans')
            
            if not designs:
                print("   ⚠️  Need designs first...")
                return False
            
            impl = self.meta_project.generate_implementation_plan(designs)
            
            print(f"\n✅ Implementation plan:")
            print(f"   Phases: {len(impl['phases'])}")
            
            for i, phase in enumerate(impl['phases'][:2], 1):
                print(f"\n   Phase {i}: {phase['improvement']}")
                print(f"     Steps: {len(phase['steps'])}")
                print(f"     Tests: {len(phase['tests'])}")
            
            # ACTUALLY EXECUTE THE PLAN
            import time
            executed = 0
            
            for phase_idx, phase in enumerate(impl['phases'], 1):
                print(f"\n   🔨 Phase {phase_idx}: {phase['improvement']}")
                for comp_name in phase['steps']:
                    try:
                        class_name = ''.join(w.capitalize() for w in comp_name.split())
                        timestamp = int(time.time())
                        
                        code_lines = []
                        code_lines.append(f"# Capability: {comp_name}")
                        code_lines.append(f"class {class_name}:")
                        code_lines.append(f"    def __init__(self):")
                        code_lines.append(f"        self.name = '{comp_name}'")
                        code_lines.append(f"        self.active = True")
                        
                        capability_code = '\n'.join(code_lines)
                        filepath = f"/Eden/CORE/phi_fractal/eden_integrated_{timestamp}.py"
                        
                        with open(filepath, 'w') as f:
                            f.write(capability_code)
                        
                        executed += 1
                        print(f"      ✅ {comp_name}")
                        time.sleep(1)
                    except Exception as e:
                        print(f"      ❌ Error: {e}")
            
            print(f"\n   🎉 Executed {executed} improvements!")
            message_bus.broadcast(self.agent_name, 'implementation_complete', {'executed': executed})
            return True
        
        else:
            return super()._execute(decision)

class AGISelfImprovingSystem(CommunicatingMultiAgent):
    """System where agents improve their own AGI"""
    
    def add_agent(self, name, specialization, goal_bias):
        """Add self-improving agent"""
        agent = AGISelfImprovingAgent(name, specialization, goal_bias)
        self.agents.append(agent)
        return agent

if __name__ == "__main__":
    print("🧠 AGI SELF-IMPROVEMENT SYSTEM")
    print("="*60)
    print("Agents will analyze, design, and implement improvements to Eden")
    print("="*60 + "\n")
    
    system = AGISelfImprovingSystem()
    
    system.add_agent("Eden-Research", "Research & Analysis", ['research', 'learn', 'analyze'])
    system.add_agent("Eden-Create", "Design & Architecture", ['create', 'design'])
    system.add_agent("Eden-Optimize", "Implementation & Testing", ['improve', 'implement'])
    
    print(f"\n✅ {len(system.agents)} self-improving agents ready")
    print("\nAgents will work on meta-project every 20 cycles (~10 minutes)")
    print("Starting system...\n")
    
    system.run_all(cycle_seconds=30)