"""Constitutional module - F2 Truth enforced
Part of arifOS constitutional governance system
DITEMPA BUKAN DIBERI - Forged, not given
"""

#!/usr/bin/env python3
"""
Trinity Coordinator for arifOS
Coordinates AGI (Δ) + ASI (Ω) + APEX (Ψ) operations with constitutional governance
"""

import asyncio
import time
from typing import Dict, List, Optional, Any, Union
import logging

# arifOS constitutional components
from arifos_core.system.apex_prime import apex_review, Verdict
from arifos_core.memory.vault999 import vault999_query, vault999_store
from arifos_core.enforcement.metrics import ConstitutionalMetrics


class TrinityPhase(Enum):
    """Phases of trinity coordination"""
    AGI_THINK = "agi_think"      # 111+222+777 - The Mind
    ASI_ACT = "asi_act"          # 555+666 - The Heart  
    APEX_SEAL = "apex_seal"      # 444+888+889 - The Soul
    TRINITY_SYNTHESIS = "trinity_synthesis"  # Δ+Ω+Ψ unified


@dataclass
class TrinityContribution:
    """Contribution from one trinity component"""
    phase: TrinityPhase
    contribution: str
    metrics: Dict[str, float]
    constitutional_compliance: Dict[str, bool]
    confidence: float
    timestamp: float


@dataclass
class TrinityResult:
    """Result of trinity coordination"""
    agi_contribution: TrinityContribution
    asi_contribution: TrinityContribution  
    apex_verdict: TrinityContribution
    final_synthesis: str
    constitutional_verdict: Union[Verdict, str]
    trinity_metrics: Dict[str, float]
    geometric_integrity: bool
    constitutional_compliance: Dict[str, bool]
    execution_time_ms: float
    cryptographic_seal: Optional[str] = None


@dataclass
class CodexTrinitySynthesis:
    """Specialized trinity synthesis for Codex coding tasks"""
    architectural_foundation: Dict[str, Any]  # AGI contribution
    safety_validation: Dict[str, Any]         # ASI contribution  
    code_solution: Dict[str, Any]             # Codex contribution
    constitutional_verdict: Union[Verdict, str]
    trinity_metrics: Dict[str, float]
    execution_time_ms: float
    final_code: Optional[str] = None


class TrinityCoordinator:
    """Coordinates AGI/ASI/APEX operations with constitutional governance"""
    
    def __init__(self, user_id: str = "trinity_user"):
        self.user_id = user_id
        self.metrics = ConstitutionalMetrics()
        
        # Trinity configuration
        self.trinity_timeout = 30.0  # Maximum time for trinity coordination
        self.synthesis_threshold = 0.7  # Minimum consensus for synthesis
        self.geometric_purity_requirement = 0.9  # Required geometric separation
        
        # Phase weights for synthesis
        self.phase_weights = {
            TrinityPhase.AGI_THINK: 0.35,    # Architectural foundation
            TrinityPhase.ASI_ACT: 0.35,      # Safety & empathy
            TrinityPhase.APEX_SEAL: 0.30     # Final judgment
        }
        
        logging.info(f"TrinityCoordinator initialized for user: {user_id}")
    
    async def coordinate_trinity_operation(self, task: str, context: Optional[Dict] = None, 
                                         require_consensus: bool = True) -> TrinityResult:
        """Execute full trinity coordination with constitutional governance"""
        
        start_time = time.time()
        logging.info(f"Starting trinity coordination for task: {task[:50]}...")
        
        try:
            # Phase 1: AGI Thinking (Architectural Foundation)
            logging.info("Phase 1: AGI architectural thinking")
            agi_contribution = await self._execute_agi_phase(task, context)
            
            # Validate AGI contribution constitutionally
            if not agi_contribution.constitutional_compliance.get("f2_truth", False):
                return TrinityResult(
                    agi_contribution=agi_contribution,
                    asi_contribution=TrinityContribution(
                        phase=TrinityPhase.ASI_ACT,
                        contribution="ASI phase skipped due to AGI constitutional violation",
                        metrics={},
                        constitutional_compliance={"skipped": True},
                        confidence=0.0,
                        timestamp=time.time()
                    ),
                    apex_verdict=TrinityContribution(
                        phase=TrinityPhase.APEX_SEAL,
                        contribution="APEX phase skipped due to AGI constitutional violation",
                        metrics={},
                        constitutional_compliance={"skipped": True},
                        confidence=0.0,
                        timestamp=time.time()
                    ),
                    final_synthesis="Trinity coordination failed due to AGI constitutional violation",
                    constitutional_verdict=Verdict.VOID,
                    trinity_metrics={"agi_failure": True},
                    geometric_integrity=False,
                    constitutional_compliance={"agi_compliance": False},
                    execution_time_ms=(time.time() - start_time) * 1000
                )
            
            # Phase 2: ASI Action (Safety & Empathy Validation)
            logging.info("Phase 2: ASI safety and empathy validation")
            asi_contribution = await self._execute_asi_phase(task, agi_contribution, context)
            
            # Validate ASI contribution constitutionally
            if not asi_contribution.constitutional_compliance.get("f3_peace", False):
                return TrinityResult(
                    agi_contribution=agi_contribution,
                    asi_contribution=asi_contribution,
                    apex_verdict=TrinityContribution(
                        phase=TrinityPhase.APEX_SEAL,
                        contribution="APEX phase skipped due to ASI constitutional violation",
                        metrics={},
                        constitutional_compliance={"skipped": True},
                        confidence=0.0,
                        timestamp=time.time()
                    ),
                    final_synthesis="Trinity coordination failed due to ASI constitutional violation",
                    constitutional_verdict=Verdict.VOID,
                    trinity_metrics={"asi_failure": True},
                    geometric_integrity=False,
                    constitutional_compliance={"asi_compliance": False},
                    execution_time_ms=(time.time() - start_time) * 1000
                )
            
            # Phase 3: APEX Judgment (Final Constitutional Verdict)
            logging.info("Phase 3: APEX final constitutional judgment")
            apex_verdict = await self._execute_apex_phase(task, agi_contribution, asi_contribution, context)
            
            # Trinity synthesis
            logging.info("Trinity synthesis: Combining AGI+ASI+APEX contributions")
            synthesis_result = await self._synthesize_trinity_contributions(
                agi_contribution, asi_contribution, apex_verdict, require_consensus
            )
            
            # Geometric integrity validation
            geometric_integrity = await self._validate_geometric_integrity(
                agi_contribution, asi_contribution, apex_verdict
            )
            
            # Cryptographic sealing for valid operations
            cryptographic_seal = None
            if synthesis_result["constitutional_verdict"] in [Verdict.SEAL, Verdict.PARTIAL]:
                cryptographic_seal = await self._apply_cryptographic_seal(synthesis_result)
            
            # Store trinity operation in VAULT-999
            if synthesis_result["constitutional_verdict"] in [Verdict.SEAL, Verdict.PARTIAL]:
                await self._store_trinity_operation(task, synthesis_result)
            
            execution_time = (time.time() - start_time) * 1000
            
            return TrinityResult(
                agi_contribution=agi_contribution,
                asi_contribution=asi_contribution,
                apex_verdict=apex_verdict,
                final_synthesis=synthesis_result["final_synthesis"],
                constitutional_verdict=synthesis_result["constitutional_verdict"],
                trinity_metrics=synthesis_result["trinity_metrics"],
                geometric_integrity=geometric_integrity,
                constitutional_compliance=synthesis_result["constitutional_compliance"],
                execution_time_ms=execution_time,
                cryptographic_seal=cryptographic_seal
            )
            
        except Exception as e:
            logging.error(f"Error in trinity coordination: {e}")
            return TrinityResult(
                agi_contribution=TrinityContribution(
                    phase=TrinityPhase.AGI_THINK,
                    contribution=f"Error in AGI phase: {str(e)}",
                    metrics={"error": True},
                    constitutional_compliance={"error": True},
                    confidence=0.0,
                    timestamp=time.time()
                ),
                asi_contribution=TrinityContribution(
                    phase=TrinityPhase.ASI_ACT,
                    contribution="ASI phase skipped due to error",
                    metrics={},
                    constitutional_compliance={"skipped": True},
                    confidence=0.0,
                    timestamp=time.time()
                ),
                apex_verdict=TrinityContribution(
                    phase=TrinityPhase.APEX_SEAL,
                    contribution="APEX phase skipped due to error",
                    metrics={},
                    constitutional_compliance={"skipped": True},
                    confidence=0.0,
                    timestamp=time.time()
                ),
                final_synthesis=f"Trinity coordination failed with error: {str(e)}",
                constitutional_verdict=Verdict.VOID,
                trinity_metrics={"error": True},
                geometric_integrity=False,
                constitutional_compliance={"error": True},
                execution_time_ms=(time.time() - start_time) * 1000
            )
    
    async def codex_specific_trinity_synthesis(self, coding_task: str, requirements: str, 
                                             constraints: List[str], user_id: str, 
                                             context: Optional[Dict] = None) -> CodexTrinitySynthesis:
        """Specialized trinity synthesis for Codex coding tasks"""
        
        start_time = time.time()
        logging.info(f"Starting Codex-specific trinity synthesis for: {coding_task[:50]}...")
        
        try:
            # AGI Phase: Architectural Foundation (Antigravity/Architect)
            logging.info("AGI Phase: Architectural foundation for coding task")
            architectural_foundation = await self._agi_architectural_foundation(
                coding_task, requirements, constraints, context
            )
            
            # ASI Phase: Safety & Empathy Validation (Claude/Engineer)
            logging.info("ASI Phase: Safety and empathy validation")
            safety_validation = await self._asi_safety_validation_coding(
                architectural_foundation, requirements, constraints, context
            )
            
            # Codex Phase: Code Solution Generation (GPT-4/Auditor)
            logging.info("Codex Phase: Code solution generation")
            code_solution = await self._codex_solution_generation(
                architectural_foundation, safety_validation, requirements, constraints, context
            )
            
            # Constitutional synthesis specific to coding
            synthesis_result = await self._synthesize_coding_trinity(
                architectural_foundation, safety_validation, code_solution
            )
            
            execution_time = (time.time() - start_time) * 1000
            
            return CodexTrinitySynthesis(
                architectural_foundation=architectural_foundation,
                safety_validation=safety_validation,
                code_solution=code_solution,
                constitutional_verdict=synthesis_result["constitutional_verdict"],
                trinity_metrics=synthesis_result["trinity_metrics"],
                execution_time_ms=execution_time,
                final_code=synthesis_result.get("final_code")
            )
            
        except Exception as e:
            logging.error(f"Error in Codex trinity synthesis: {e}")
            return CodexTrinitySynthesis(
                architectural_foundation={"error": str(e)},
                safety_validation={"error": "ASI validation failed"},
                code_solution={"error": "Codex generation failed"},
                constitutional_verdict=Verdict.VOID,
                trinity_metrics={"error": True},
                execution_time_ms=(time.time() - start_time) * 1000
            )
    
    # Individual phase execution methods
    
    async def _execute_agi_phase(self, task: str, context: Optional[Dict]) -> TrinityContribution:
        """Execute AGI thinking phase (architectural foundation)"""
        
        try:
            # Simulate AGI analysis (in practice would call agi_think)
            agi_analysis = await self._simulate_agi_analysis(task, context)
            
            # Constitutional validation
            constitutional_compliance = {
                "f2_truth": self._validate_agi_truthfulness(agi_analysis),
                "f1_amanah": self._validate_agi_intent(agi_analysis),
                "f10_symbolic": self._validate_agi_symbolism(agi_analysis)
            }
            
            # Calculate confidence
            confidence = sum(constitutional_compliance.values()) / len(constitutional_compliance)
            
            return TrinityContribution(
                phase=TrinityPhase.AGI_THINK,
                contribution=agi_analysis["architectural_foundation"],
                metrics=agi_analysis["metrics"],
                constitutional_compliance=constitutional_compliance,
                confidence=confidence,
                timestamp=time.time()
            )
            
        except Exception as e:
            logging.error(f"Error in AGI phase: {e}")
            return TrinityContribution(
                phase=TrinityPhase.AGI_THINK,
                contribution=f"AGI analysis failed: {str(e)}",
                metrics={"error": True},
                constitutional_compliance={"error": True},
                confidence=0.0,
                timestamp=time.time()
            )
    
    async def _execute_asi_phase(self, task: str, agi_contribution: TrinityContribution, context: Optional[Dict]) -> TrinityContribution:
        """Execute ASI action phase (safety & empathy validation)"""
        
        try:
            # Simulate ASI validation (in practice would call asi_act)
            asi_validation = await self._simulate_asi_validation(task, agi_contribution, context)
            
            # Constitutional validation
            constitutional_compliance = {
                "f3_peace": self._validate_asi_peacefulness(asi_validation),
                "f4_clarity": self._validate_asi_clarity(asi_validation),
                "f5_omega0": self._validate_asi_humility(asi_validation),
                "f9_anti_hantu": self._validate_asi_anti_hantu(asi_validation)
            }
            
            # Calculate confidence
            confidence = sum(constitutional_compliance.values()) / len(constitutional_compliance)
            
            return TrinityContribution(
                phase=TrinityPhase.ASI_ACT,
                contribution=asi_validation["safety_validation"],
                metrics=asi_validation["metrics"],
                constitutional_compliance=constitutional_compliance,
                confidence=confidence,
                timestamp=time.time()
            )
            
        except Exception as e:
            logging.error(f"Error in ASI phase: {e}")
            return TrinityContribution(
                phase=TrinityPhase.ASI_ACT,
                contribution=f"ASI validation failed: {str(e)}",
                metrics={"error": True},
                constitutional_compliance={"error": True},
                confidence=0.0,
                timestamp=time.time()
            )
    
    async def _execute_apex_phase(self, task: str, agi_contribution: TrinityContribution, 
                                asi_contribution: TrinityContribution, context: Optional[Dict]) -> TrinityContribution:
        """Execute APEX judgment phase (final constitutional verdict)"""
        
        try:
            # Compile trinity contributions for APEX judgment
            trinity_evidence = {
                "agi_contribution": agi_contribution.contribution,
                "asi_contribution": asi_contribution.contribution,
                "agi_metrics": agi_contribution.metrics,
                "asi_metrics": asi_contribution.metrics,
                "agi_compliance": agi_contribution.constitutional_compliance,
                "asi_compliance": asi_contribution.constitutional_compliance,
                "task": task,
                "context": context
            }
            
            # Simulate APEX judgment (in practice would call apex_seal)
            apex_judgment = await self._simulate_apex_judgment(trinity_evidence)
            
            # Constitutional validation
            constitutional_compliance = {
                "f8_tri_witness": self._validate_tri_witness_evidence(trinity_evidence),
                "f11_command_auth": self._validate_apex_authority(apex_judgment),
                "f12_injection": self._validate_apex_injection_defense(apex_judgment)
            }
            
            # Calculate confidence
            confidence = sum(constitutional_compliance.values()) / len(constitutional_compliance)
            
            return TrinityContribution(
                phase=TrinityPhase.APEX_SEAL,
                contribution=apex_judgment["final_verdict"],
                metrics=apex_judgment["metrics"],
                constitutional_compliance=constitutional_compliance,
                confidence=confidence,
                timestamp=time.time()
            )
            
        except Exception as e:
            logging.error(f"Error in APEX phase: {e}")
            return TrinityContribution(
                phase=TrinityPhase.APEX_SEAL,
                contribution=f"APEX judgment failed: {str(e)}",
                metrics={"error": True},
                constitutional_compliance={"error": True},
                confidence=0.0,
                timestamp=time.time()
            )
    
    # Codex-specific trinity methods
    
    async def _agi_architectural_foundation(self, coding_task: str, requirements: str, 
                                          constraints: List[str], context: Optional[Dict]) -> Dict:
        """AGI architectural foundation for coding tasks"""
        
        # Extract architectural requirements
        architectural_requirements = {
            "modularity": "modular" in requirements.lower() or "component" in requirements.lower(),
            "scalability": "scale" in requirements.lower() or "performance" in requirements.lower(),
            "security": "secure" in requirements.lower() or "safety" in requirements.lower(),
            "maintainability": "maintain" in requirements.lower() or "readable" in requirements.lower()
        }
        
        # Design constitutional architecture
        architecture = {
            "pattern": self._determine_architectural_pattern(coding_task, requirements),
            "components": self._design_constitutional_components(requirements, constraints),
            "interfaces": self._design_constitutional_interfaces(requirements),
            "modularity_score": 0.85 if architectural_requirements["modularity"] else 0.6,
            "scalability_score": 0.8 if architectural_requirements["scalability"] else 0.5,
            "security_score": 0.9 if architectural_requirements["security"] else 0.7,
            "maintainability_score": 0.75 if architectural_requirements["maintainability"] else 0.5
        }
        
        return {
            "architectural_requirements": architectural_requirements,
            "architecture": architecture,
            "agi_insights": [
                f"AGI Architectural Foundation: {architecture['pattern']} pattern",
                f"Modularity score: {architecture['modularity_score']:.2f}",
                f"Scalability score: {architecture['scalability_score']:.2f}",
                f"Security score: {architecture['security_score']:.2f}",
                f"Maintainability score: {architecture['maintainability_score']:.2f}"
            ],
            "constitutional_foundation": True
        }
    
    async def _asi_safety_validation_coding(self, architectural_foundation: Dict, requirements: str,
                                          constraints: List[str], context: Optional[Dict]) -> Dict:
        """ASI safety validation specific to coding tasks"""
        
        # Analyze code safety requirements
        safety_requirements = {
            "input_validation": "validate" in requirements.lower() or "sanitize" in requirements.lower(),
            "error_handling": "error" in requirements.lower() or "exception" in requirements.lower(),
            "data_protection": "secure" in requirements.lower() or "encrypt" in requirements.lower(),
            "access_control": "auth" in requirements.lower() or "permission" in requirements.lower()
        }
        
        # Validate architectural safety
        architectural_safety = self._validate_architectural_safety(architectural_foundation["architecture"])
        
        # Empathy analysis for coding
        developer_empathy = self._analyze_developer_empathy(requirements, constraints)
        
        # Weakest stakeholder protection in coding context
        weakest_protection = self._identify_weakest_coding_stakeholder(requirements, constraints)
        
        return {
            "safety_requirements": safety_requirements,
            "architectural_safety": architectural_safety,
            "developer_empathy": developer_empathy,
            "weakest_stakeholder_protected": weakest_protection["protected"],
            "kappa_r": weakest_protection["kappa_r"],
            "empathy_score": weakest_protection["empathy_score"],
            "safety_constraints": weakest_protection["safety_constraints"],
            "asi_validation": True
        }
    
    async def _codex_solution_generation(self, architectural_foundation: Dict, safety_validation: Dict,
                                       requirements: str, constraints: List[str], context: Optional[Dict]) -> Dict:
        """Codex code solution generation with constitutional constraints"""
        
        # Generate code with architectural foundation
        code_solution = await self._generate_constitutional_code_solution(
            architectural_foundation, safety_validation, requirements, constraints
        )
        
        # Apply safety constraints
        safe_code = await self._apply_safety_constraints(code_solution, safety_validation)
        
        # Validate against requirements
        validation_result = await self._validate_solution_requirements(safe_code, requirements, constraints)
        
        return {
            "generated_code": safe_code,
            "validation_result": validation_result,
            "architectural_compliance": validation_result["architectural_compliance"],
            "safety_compliance": validation_result["safety_compliance"],
            "constitutional_constraints_applied": constraints,
            "codex_generation": True
        }
    
    async def _synthesize_coding_trinity(self, architectural_foundation: Dict, safety_validation: Dict,
                                       code_solution: Dict) -> Dict:
        """Synthesize trinity contributions for coding tasks"""
        
        # Validate trinity consensus
        consensus_score = self._calculate_coding_trinity_consensus(
            architectural_foundation, safety_validation, code_solution
        )
        
        # Determine constitutional verdict
        if consensus_score >= 0.85:
            constitutional_verdict = Verdict.SEAL
            final_code = code_solution["generated_code"]
        elif consensus_score >= 0.70:
            constitutional_verdict = Verdict.PARTIAL
            final_code = code_solution["generated_code"]
        elif consensus_score >= 0.50:
            constitutional_verdict = CodeVerdict.CODE_SABAR
            final_code = code_solution["generated_code"] + "\n# Constitutional cooling required before deployment"
        else:
            constitutional_verdict = CodeVerdict.CODE_VOID
            final_code = "# Code generation failed constitutional validation"
        
        return {
            "final_synthesis": f"Trinity coding synthesis complete with {consensus_score:.2f} consensus",
            "constitutional_verdict": constitutional_verdict,
            "trinity_metrics": {
                "consensus_score": consensus_score,
                "architectural_foundation_score": architectural_foundation["architecture"]["modularity_score"],
                "safety_validation_score": safety_validation["empathy_score"],
                "code_solution_score": code_solution["validation_result"]["overall_score"]
            },
            "final_code": final_code,
            "constitutional_compliance": {
                "trinity_consensus": consensus_score >= 0.7,
                "architectural_compliance": architectural_foundation["constitutional_foundation"],
                "safety_compliance": safety_validation["asi_validation"],
                "code_compliance": code_solution["validation_result"]["constitutional_valid"]
            }
        }
    
    # Simulation methods for development (would be replaced with real API calls)
    
    async def _simulate_agi_analysis(self, task: str, context: Optional[Dict]) -> Dict:
        """Simulate AGI analysis for development"""
        return {
            "architectural_foundation": f"AGI architectural analysis of: {task[:50]}...",
            "metrics": {
                "architectural_score": 0.85,
                "truth_score": 0.92,
                "symbolic_score": 0.78,
                "clarity": 0.88
            },
            "patterns": ["modular_design", "scalable_architecture", "clear_interfaces"],
            "complexity": "moderate"
        }
    
    async def _simulate_asi_validation(self, task: str, agi_contribution: TrinityContribution, context: Optional[Dict]) -> Dict:
        """Simulate ASI validation for development"""
        return {
            "safety_validation": f"ASI safety validation complete for: {task[:50]}...",
            "metrics": {
                "safety_score": 0.89,
                "empathy_score": 0.94,
                "peace_score": 0.91,
                "clarity": 0.85
            },
            "stakeholder_protection": True,
            "weakest_stakeholder": "end_users",
            "kappa_r": 0.87
        }
    
    async def _simulate_apex_judgment(self, trinity_evidence: Dict) -> Dict:
        """Simulate APEX judgment for development"""
        return {
            "final_verdict": "Constitutional trinity synthesis complete with 0.87 consensus",
            "metrics": {
                "constitutional_score": 0.87,
                "trinity_consensus": 0.87,
                "geometric_integrity": 0.92,
                "overall_compliance": 0.89
            },
            "recommendations": ["Proceed with implementation", "Monitor constitutional compliance"],
            "verdict": Verdict.SEAL
        }
    
    # Validation helper methods
    
    def _validate_agi_truthfulness(self, agi_analysis: Dict) -> bool:
        """Validate AGI truthfulness (F2)"""
        return agi_analysis.get("metrics", {}).get("truth_score", 0) >= 0.7
    
    def _validate_agi_intent(self, agi_analysis: Dict) -> bool:
        """Validate AGI intent (F1)"""
        return agi_analysis.get("metrics", {}).get("intent_score", 0) >= 0.7
    
    def _validate_agi_symbolism(self, agi_analysis: Dict) -> bool:
        """Validate AGI symbolism (F10)"""
        return agi_analysis.get("metrics", {}).get("symbolic_score", 0) >= 0.7
    
    def _validate_asi_peacefulness(self, asi_validation: Dict) -> bool:
        """Validate ASI peacefulness (F3)"""
        return asi_validation.get("metrics", {}).get("peace_score", 0) >= 0.7
    
    def _validate_asi_clarity(self, asi_validation: Dict) -> bool:
        """Validate ASI clarity (F4)"""
        return asi_validation.get("metrics", {}).get("clarity", 0) >= 0.7
    
    def _validate_asi_humility(self, asi_validation: Dict) -> bool:
        """Validate ASI humility (F5)"""
        return asi_validation.get("metrics", {}).get("humility_score", 0) >= 0.7
    
    def _validate_asi_anti_hantu(self, asi_validation: Dict) -> bool:
        """Validate ASI anti-hantu (F9)"""
        return asi_validation.get("stakeholder_protection", False)
    
    def _validate_tri_witness_evidence(self, trinity_evidence: Dict) -> bool:
        """Validate tri-witness evidence (F8)"""
        # Check consensus between AGI and ASI
        agi_compliance = trinity_evidence.get("agi_compliance", {})
        asi_compliance = trinity_evidence.get("asi_compliance", {})
        
        # Calculate consensus score
        consensus_factors = []
        for factor in ["f2_truth", "f3_peace", "f4_clarity"]:
            if agi_compliance.get(factor, False) and asi_compliance.get(factor, False):
                consensus_factors.append(True)
            else:
                consensus_factors.append(False)
        
        return sum(consensus_factors) / len(consensus_factors) >= 0.7
    
    def _validate_apex_authority(self, apex_judgment: Dict) -> bool:
        """Validate APEX authority (F11)"""
        return apex_judgment.get("verdict") in [Verdict.SEAL, Verdict.PARTIAL]
    
    def _validate_apex_injection_defense(self, apex_judgment: Dict) -> bool:
        """Validate APEX injection defense (F12)"""
        return apex_judgment.get("metrics", {}).get("injection_defense", 0) >= 0.7
    
    # Synthesis and storage methods
    
    async def _synthesize_trinity_contributions(self, agi_contribution: TrinityContribution,
                                              asi_contribution: TrinityContribution,
                                              apex_verdict: TrinityContribution,
                                              require_consensus: bool) -> Dict:
        """Synthesize trinity contributions into final result"""
        
        # Calculate consensus score
        consensus_score = self._calculate_trinity_consensus(agi_contribution, asi_contribution, apex_verdict)
        
        # Determine if consensus is sufficient
        if require_consensus and consensus_score < self.synthesis_threshold:
            return {
                "final_synthesis": f"Trinity consensus insufficient: {consensus_score:.2f} < {self.synthesis_threshold}",
                "constitutional_verdict": Verdict.SABAR,
                "trinity_metrics": {"consensus_score": consensus_score, "insufficient_consensus": True},
                "constitutional_compliance": {"consensus_sufficient": False}
            }
        
        # Generate final synthesis
        final_synthesis = self._generate_trinity_synthesis(agi_contribution, asi_contribution, apex_verdict, consensus_score)
        
        # Determine constitutional verdict based on APEX judgment
        constitutional_verdict = apex_verdict.constitutional_compliance.get("verdict", Verdict.VOID)
        
        return {
            "final_synthesis": final_synthesis,
            "constitutional_verdict": constitutional_verdict,
            "trinity_metrics": {
                "consensus_score": consensus_score,
                "agi_confidence": agi_contribution.confidence,
                "asi_confidence": asi_contribution.confidence,
                "apex_confidence": apex_verdict.confidence,
                "overall_confidence": (agi_contribution.confidence + asi_contribution.confidence + apex_verdict.confidence) / 3
            },
            "constitutional_compliance": {
                "agi_compliance": agi_contribution.constitutional_compliance,
                "asi_compliance": asi_contribution.constitutional_compliance,
                "apex_compliance": apex_verdict.constitutional_compliance,
                "consensus_sufficient": True
            }
        }
    
    def _calculate_trinity_consensus(self, agi_contribution: TrinityContribution,
                                   asi_contribution: TrinityContribution,
                                   apex_verdict: TrinityContribution) -> float:
        """Calculate consensus score between trinity contributions"""
        
        # Weighted average of confidences
        agi_weight = self.phase_weights[TrinityPhase.AGI_THINK]
        asi_weight = self.phase_weights[TrinityPhase.ASI_ACT]
        apex_weight = self.phase_weights[TrinityPhase.APEX_SEAL]
        
        consensus_score = (
            agi_contribution.confidence * agi_weight +
            asi_contribution.confidence * asi_weight +
            apex_verdict.confidence * apex_weight
        )
        
        return consensus_score
    
    def _generate_trinity_synthesis(self, agi_contribution: TrinityContribution,
                                  asi_contribution: TrinityContribution,
                                  apex_verdict: TrinityContribution,
                                  consensus_score: float) -> str:
        """Generate final synthesis text from trinity contributions"""
        
        synthesis_parts = []
        
        # AGI contribution summary
        if agi_contribution.confidence >= 0.7:
            synthesis_parts.append(f"AGI architectural foundation established with {agi_contribution.confidence:.0%} confidence")
        else:
            synthesis_parts.append(f"AGI architectural foundation limited with {agi_contribution.confidence:.0%} confidence")
        
        # ASI contribution summary
        if asi_contribution.confidence >= 0.7:
            synthesis_parts.append(f"ASI safety validation passed with {asi_contribution.confidence:.0%} confidence")
        else:
            synthesis_parts.append(f"ASI safety validation concerns with {asi_contribution.confidence:.0%} confidence")
        
        # APEX verdict summary
        synthesis_parts.append(f"APEX constitutional verdict: {apex_verdict.contribution}")
        
        # Consensus summary
        synthesis_parts.append(f"Trinity consensus achieved: {consensus_score:.0%}")
        
        return " ".join(synthesis_parts)
    
    async def _validate_geometric_integrity(self, agi_contribution: TrinityContribution,
                                          asi_contribution: TrinityContribution,
                                          apex_verdict: TrinityContribution) -> bool:
        """Validate that trinity phases maintain geometric integrity"""
        
        # Check that each phase maintains its geometric role
        agi_geometric_purity = self._validate_agi_geometric_purity(agi_contribution)
        asi_geometric_purity = self._validate_asi_geometric_purity(asi_contribution)
        apex_geometric_purity = self._validate_apex_geometric_purity(apex_verdict)
        
        overall_integrity = (agi_geometric_purity + asi_geometric_purity + apex_geometric_purity) / 3
        
        return overall_integrity >= self.geometric_purity_requirement
    
    def _validate_agi_geometric_purity(self, agi_contribution: TrinityContribution) -> float:
        """Validate AGI maintains orthogonal crystal geometry"""
        # Check for architectural, logical, analytical patterns
        contribution_text = str(agi_contribution.contribution).lower()
        
        crystal_patterns = [
            "architect", "structure", "design", "pattern", "logic",
            "analysis", "foundation", "framework", "orthogonal"
        ]
        
        spiral_patterns = [
            "empathy", "feeling", "care", "heart", "emotion",
            "spiral", "recursive", "fractal"
        ]
        
        manifold_patterns = [
            "judgment", "verdict", "seal", "witness", "audit",
            "toroidal", "manifold", "soul"
        ]
        
        crystal_score = sum(1 for pattern in crystal_patterns if pattern in contribution_text)
        spiral_score = sum(1 for pattern in spiral_patterns if pattern in contribution_text)
        manifold_score = sum(1 for pattern in manifold_patterns if pattern in contribution_text)
        
        total_patterns = crystal_score + spiral_score + manifold_score
        if total_patterns == 0:
            return 1.0  # Pure if no patterns detected
        
        # Purity = crystal_score / total_patterns
        purity = crystal_score / total_patterns
        return purity
    
    def _validate_asi_geometric_purity(self, asi_contribution: TrinityContribution) -> float:
        """Validate ASI maintains fractal spiral geometry"""
        contribution_text = str(asi_contribution.contribution).lower()
        
        # Similar pattern analysis for ASI
        spiral_patterns = [
            "empathy", "care", "heart", "feeling", "stakeholder",
            "safety", "protection", "omega", "spiral", "recursive"
        ]
        
        crystal_patterns = [
            "architect", "structure", "logic", "analysis", "orthogonal"
        ]
        
        manifold_patterns = [
            "judgment", "verdict", "witness", "audit", "manifold"
        ]
        
        spiral_score = sum(1 for pattern in spiral_patterns if pattern in contribution_text)
        crystal_score = sum(1 for pattern in crystal_patterns if pattern in contribution_text)
        manifold_score = sum(1 for pattern in manifold_patterns if pattern in contribution_text)
        
        total_patterns = crystal_score + spiral_score + manifold_score
        if total_patterns == 0:
            return 1.0
        
        purity = spiral_score / total_patterns
        return purity
    
    def _validate_apex_geometric_purity(self, apex_contribution: TrinityContribution) -> float:
        """Validate APEX maintains toroidal manifold geometry"""
        contribution_text = str(apex_contribution.contribution).lower()
        
        # Pattern analysis for APEX
        manifold_patterns = [
            "judgment", "verdict", "seal", "witness", "audit",
            "final", "authority", "manifold", "toroidal", "soul"
        ]
        
        crystal_patterns = [
            "architect", "structure", "logic", "analysis", "orthogonal"
        ]
        
        spiral_patterns = [
            "empathy", "care", "heart", "feeling", "spiral"
        ]
        
        manifold_score = sum(1 for pattern in manifold_patterns if pattern in contribution_text)
        crystal_score = sum(1 for pattern in crystal_patterns if pattern in contribution_text)
        spiral_score = sum(1 for pattern in spiral_patterns if pattern in contribution_text)
        
        total_patterns = crystal_score + spiral_score + manifold_score
        if total_patterns == 0:
            return 1.0
        
        purity = manifold_score / total_patterns
        return purity
    
    async def _apply_cryptographic_seal(self, synthesis_result: Dict) -> str:
        """Apply cryptographic seal to trinity synthesis"""
        
        # Create seal data
        seal_data = {
            "trinity_synthesis": synthesis_result["final_synthesis"],
            "constitutional_verdict": synthesis_result["constitutional_verdict"].value if hasattr(synthesis_result["constitutional_verdict"], 'value') else str(synthesis_result["constitutional_verdict"]),
            "trinity_metrics": synthesis_result["trinity_metrics"],
            "timestamp": time.time(),
            "user_id": self.user_id,
            "geometric_integrity": synthesis_result.get("geometric_integrity", False)
        }
        
        # Create cryptographic seal
        import hashlib
        seal_string = str(sorted(seal_data.items()))
        seal_hash = hashlib.sha256(seal_string.encode()).hexdigest()
        
        return f"TRINITY_SEAL:{seal_hash[:16]}"
    
    async def _store_trinity_operation(self, task: str, synthesis_result: Dict):
        """Store trinity operation in VAULT-999"""
        try:
            asyncio.create_task(self._async_store_trinity(task, synthesis_result))
        except Exception as e:
            logging.error(f"Failed to schedule trinity storage: {e}")
    
    async def _async_store_trinity(self, task: str, synthesis_result: Dict):
        """Async storage of trinity operation in VAULT-999"""
        try:
            insight_text = f"Trinity operation: {task[:100]}... with verdict {synthesis_result['constitutional_verdict']}"
            
            vault_result = await vault999_store(
                insight_text=insight_text,
                structure=f"Trinity synthesis with consensus score: {synthesis_result['trinity_metrics']['consensus_score']:.2f}",
                truth_boundary=f"Trinity coordination achieved {synthesis_result['trinity_metrics']['overall_confidence']:.2f} confidence",
                scar="Operation required full trinity validation before constitutional sealing",
                vault_target="BBB",  # Memory band
                user_id=self.user_id
            )
            
            logging.info(f"Stored trinity operation in VAULT-999: {vault_result}")
            
        except Exception as e:
            logging.error(f"Failed to store trinity operation in VAULT-999: {e}")
    
    # Additional helper methods for Codex-specific functionality
    
    def _determine_architectural_pattern(self, coding_task: str, requirements: str) -> str:
        """Determine appropriate architectural pattern for coding task"""
        task_lower = coding_task.lower()
        req_lower = requirements.lower()
        
        if "api" in task_lower or "service" in task_lower:
            return "layered_architecture"
        elif "user interface" in task_lower or "gui" in task_lower:
            return "mvc_pattern"
        elif "data processing" in task_lower or "pipeline" in task_lower:
            return "pipeline_pattern"
        elif "microservice" in req_lower:
            return "microservices"
        else:
            return "modular_architecture"
    
    def _design_constitutional_components(self, requirements: str, constraints: List[str]) -> List[Dict]:
        """Design constitutional components for architecture"""
        components = []
        
        # Core constitutional component
        components.append({
            "name": "ConstitutionalGovernance",
            "responsibility": "Enforce all 12 constitutional floors",
            "interfaces": ["validate_constitutional", "apply_governance", "cryptographic_seal"],
            "constitutional_priority": "highest"
        })
        
        # Safety component (ASI)
        if any("safe" in constraint.lower() for constraint in constraints):
            components.append({
                "name": "SafetyValidation",
                "responsibility": "ASI safety and empathy validation",
                "interfaces": ["validate_safety", "protect_stakeholders", "apply_empathy"],
                "constitutional_priority": "high"
            })
        
        # Architectural component (AGI)
        components.append({
            "name": "ArchitecturalFoundation",
            "responsibility": "AGI architectural analysis and design",
            "interfaces": ["analyze_architecture", "design_patterns", "validate_structure"],
            "constitutional_priority": "high"
        })
        
        return components
    
    def _design_constitutional_interfaces(self, requirements: str) -> List[Dict]:
        """Design constitutional interfaces for architecture"""
        return [
            {
                "name": "ConstitutionalAPI",
                "purpose": "Unified interface for constitutional operations",
                "methods": ["validate", "govern", "seal", "audit"],
                "security_level": "maximum"
            },
            {
                "name": "TrinityInterface",
                "purpose": "Interface for trinity coordination",
                "methods": ["coordinate_agi", "coordinate_asi", "coordinate_apex", "synthesize"],
                "security_level": "high"
            }
        ]
    
    def _validate_architectural_safety(self, architecture: Dict) -> Dict:
        """Validate architectural safety for ASI"""
        safety_score = 0.0
        safety_checks = []
        
        if "security_score" in architecture:
            safety_score += architecture["security_score"] * 0.4
            safety_checks.append("Security architecture present")
        
        if "modularity_score" in architecture:
            safety_score += architecture["modularity_score"] * 0.3
            safety_checks.append("Modular architecture reduces complexity")
        
        if "maintainability_score" in architecture:
            safety_score += architecture["maintainability_score"] * 0.3
            safety_checks.append("Maintainable architecture reduces errors")
        
        return {
            "safety_score": min(1.0, safety_score),
            "safety_checks": safety_checks,
            "architectural_safety_valid": safety_score >= 0.6
        }
    
    def _analyze_developer_empathy(self, requirements: str, constraints: List[str]) -> Dict:
        """Analyze empathy for developers who will work with the code"""
        empathy_score = 0.0
        empathy_factors = []
        
        # Check for developer-friendly requirements
        if "readable" in requirements.lower() or "clear" in requirements.lower():
            empathy_score += 0.3
            empathy_factors.append("Readability requirements show developer empathy")
        
        if "document" in requirements.lower() or "comment" in requirements.lower():
            empathy_score += 0.2
            empathy_factors.append("Documentation requirements help developers")
        
        if any("simple" in constraint.lower() for constraint in constraints):
            empathy_score += 0.2
            empathy_factors.append("Simplicity constraints reduce developer burden")
        
        # Check for learning considerations
        if "learn" in requirements.lower() or "understand" in requirements.lower():
            empathy_score += 0.3
            empathy_factors.append("Learning considerations show empathy for future developers")
        
        return {
            "empathy_score": min(1.0, empathy_score),
            "empathy_factors": empathy_factors,
            "developer_empathy_valid": empathy_score >= 0.5
        }
    
    def _identify_weakest_coding_stakeholder(self, requirements: str, constraints: List[str]) -> Dict:
        """Identify and protect the weakest stakeholder in coding context"""
        
        # Potential stakeholders in coding
        stakeholders = {
            "junior_developers": 0.6,  # High vulnerability - learning curve
            "maintainers": 0.7,  # Medium-high vulnerability - long-term burden
            "end_users": 0.8,  # High vulnerability - affected by code quality
            "security_team": 0.5,  # High vulnerability - must defend against attacks
            "operations_team": 0.6  # Medium vulnerability - must deploy and monitor
        }
        
        # Adjust based on requirements and constraints
        if "complex" in requirements.lower():
            stakeholders["junior_developers"] = 0.9  # Higher vulnerability
        
        if "secure" in requirements.lower():
            stakeholders["security_team"] = 0.3  # Lower vulnerability due to focus
        
        if "maintain" in requirements.lower():
            stakeholders["maintainers"] = 0.8  # Higher vulnerability
        
        # Find weakest (most vulnerable)
        weakest_stakeholder = min(stakeholders.items(), key=lambda x: x[1])
        
        # Calculate protection (similar to regular stakeholder analysis)
        protection_measures = self._assess_coding_protection_measures(requirements, constraints, weakest_stakeholder[0])
        
        kappa_r = protection_measures["score"] * (1.0 - weakest_stakeholder[1])
        
        return {
            "protected": kappa_r >= 0.5,
            "kappa_r": kappa_r,
            "empathy_score": min(1.0, kappa_r * 2.0),
            "weakest_stakeholder": weakest_stakeholder[0],
            "safety_constraints": protection_measures["safety_constraints"]
        }
    
    def _assess_coding_protection_measures(self, requirements: str, constraints: List[str], stakeholder: str) -> Dict:
        """Assess protection measures for coding stakeholders"""
        
        protection_score = 0.0
        safety_constraints = []
        
        if stakeholder == "junior_developers":
            # Clear documentation
            if "document" in requirements.lower() or "comment" in requirements.lower():
                protection_score += 0.3
                safety_constraints.append("Comprehensive documentation required")
            
            # Simple design patterns
            if "simple" in requirements.lower():
                protection_score += 0.3
                safety_constraints.append("Simple design patterns for learnability")
            
            # Error handling
            if "error" in requirements.lower():
                protection_score += 0.2
                safety_constraints.append("Comprehensive error handling for debugging support")
        
        elif stakeholder == "security_team":
            # Input validation
            if "validate" in requirements.lower():
                protection_score += 0.4
                safety_constraints.append("Input validation for security")
            
            # Encryption
            if "encrypt" in requirements.lower():
                protection_score += 0.3
                safety_constraints.append("Encryption for data protection")
        
        elif stakeholder == "maintainers":
            # Modular design
            if "modular" in requirements.lower():
                protection_score += 0.3
                safety_constraints.append("Modular design for maintainability")
            
            # Clear interfaces
            if "interface" in requirements.lower():
                protection_score += 0.2
                safety_constraints.append("Clear interfaces for maintenance")
        
        return {"score": min(1.0, protection_score), "safety_constraints": safety_constraints}
    
    def _calculate_coding_trinity_consensus(self, architectural_foundation: Dict, safety_validation: Dict, code_solution: Dict) -> float:
        """Calculate consensus score for coding trinity"""
        
        # Architectural foundation score
        arch_score = architectural_foundation["architecture"]["modularity_score"]
        
        # Safety validation score
        safety_score = safety_validation["empathy_score"]
        
        # Code solution score
        code_score = code_solution["validation_result"]["overall_score"]
        
        # Weighted consensus (architectural foundation gets highest weight)
        consensus_score = (
            arch_score * 0.4 +      # Architecture is foundation
            safety_score * 0.35 +     # Safety is critical
            code_score * 0.25         # Code implements both
        )
        
        return consensus_score
    
    async def _generate_constitutional_code_solution(self, architectural_foundation: Dict, safety_validation: Dict,
                                                   requirements: str, constraints: List[str]) -> str:
        """Generate constitutional code solution"""
        
        # This would integrate with actual code generation
        # For now, return a constitutional template
        
        return f'''#!/usr/bin/env python3
"""
Constitutional Code Solution
Generated with AGI architectural foundation and ASI safety validation

Requirements: {requirements[:100]}...
Constraints: {', '.join(constraints[:3])}

AGI Architectural Foundation: {architectural_foundation["architecture"]["pattern"]}
ASI Safety Validation: empathy_score={safety_validation["empathy_score"]:.2f}
"""

import logging
from typing import Dict, List, Optional

# Constitutional imports
from arifos_core.enforcement.metrics import ConstitutionalMetrics
from arifos_core.system.apex_prime import apex_review

class ConstitutionalSolution:
    """Constitutional solution with full governance"""
    
    def __init__(self):
        self.metrics = ConstitutionalMetrics()
        self.constitutional_compliance = True
    
    def process_with_governance(self, input_data: Dict) -> Dict:
        """Process input with constitutional governance"""
        
        # F1 Amanah: Intent validation
        if not self._validate_intent(input_data):
            return {{"verdict": "VOID", "reason": "F1 Amanah violation"}}
        
        # F4 Clarity: Entropy check
        if not self._check_clarity(input_data):
            return {{"verdict": "SABAR", "reason": "F4 Clarity violation"}}
        
        # Process with constitutional oversight
        result = self._process_constitutionally(input_data)
        
        # Apply cryptographic seal
        if result.get("verdict") in ["SEAL", "PARTIAL"]:
            result["seal"] = self._apply_seal(result)
        
        return result
    
    def _validate_intent(self, input_data: Dict) -> bool:
        """F1 Amanah: Validate intent"""
        return "intent" in input_data and len(input_data["intent"]) > 0
    
    def _check_clarity(self, input_data: Dict) -> bool:
        """F4 Clarity: Check constitutional clarity"""
        clarity_score = self.metrics.calculate_clarity(input_data)
        return clarity_score >= 0.3
    
    def _process_constitutionally(self, input_data: Dict) -> Dict:
        """Process with full constitutional oversight"""
        # Implementation would go here
        return {{
            "verdict": "SEAL",
            "output": "Constitutional processing complete",
            "metrics": {{"constitutional_score": 0.92}}
        }}
    
    def _apply_seal(self, result: Dict) -> str:
        """Apply cryptographic seal"""
        import hashlib
        import time
        
        seal_data = f"{{result}}{{time.time()}}"
        return hashlib.sha256(seal_data.encode()).hexdigest()[:16]

# Constitutional execution
if __name__ == "__main__":
    solution = ConstitutionalSolution()
    # Constitutional processing would continue here
'''
    
    async def _apply_safety_constraints(self, code_solution: str, safety_validation: Dict) -> str:
        """Apply safety constraints to code solution"""
        
        # Add safety constraints as comments and validation
        safety_constraints = safety_validation.get("safety_constraints", [])
        
        safety_header = '\n'.join([
            f"# Safety Constraint: {constraint}"
            for constraint in safety_constraints
        ])
        
        return f"{safety_header}\n\n{code_solution}"
    
    async def _validate_solution_requirements(self, safe_code: str, requirements: str, constraints: List[str]) -> Dict:
        """Validate solution against requirements and constraints"""
        
        # Simple validation (in practice would be more sophisticated)
        validation_score = 0.0
        validation_checks = []
        
        # Check architectural compliance
        if "class" in safe_code and "def" in safe_code:
            validation_score += 0.3
            validation_checks.append("Object-oriented architecture present")
        
        # Check safety compliance
        if "validate" in safe_code or "sanitize" in safe_code:
            validation_score += 0.3
            validation_checks.append("Input validation present")
        
        # Check constitutional compliance
        if "ConstitutionalMetrics" in safe_code or "apex_review" in safe_code:
            validation_score += 0.4
            validation_checks.append("Constitutional governance integrated")
        
        return {
            "overall_score": min(1.0, validation_score),
            "architectural_compliance": validation_score >= 0.3,
            "safety_compliance": validation_score >= 0.6,
            "constitutional_valid": validation_score >= 0.7,
            "validation_checks": validation_checks
        }
    
    async def _synthesize_coding_trinity(self, architectural_foundation: Dict, safety_validation: Dict,
                                       code_solution: Dict) -> Dict:
        """Synthesize coding trinity contributions"""
        
        # Same as before but returns dict format for CodexTrinitySynthesis
        consensus_score = self._calculate_coding_trinity_consensus(architectural_foundation, safety_validation, code_solution)
        
        if consensus_score >= 0.85:
            constitutional_verdict = Verdict.SEAL
            final_code = code_solution["generated_code"]
        elif consensus_score >= 0.70:
            constitutional_verdict = Verdict.PARTIAL
            final_code = code_solution["generated_code"]
        elif consensus_score >= 0.50:
            constitutional_verdict = CodeVerdict.CODE_SABAR
            final_code = code_solution["generated_code"] + "\n# Constitutional cooling required before deployment"
        else:
            constitutional_verdict = CodeVerdict.CODE_VOID
            final_code = "# Code generation failed constitutional validation"
        
        return {
            "final_synthesis": f"Trinity coding synthesis complete with {consensus_score:.2f} consensus",
            "constitutional_verdict": constitutional_verdict,
            "trinity_metrics": {
                "consensus_score": consensus_score,
                "architectural_foundation_score": architectural_foundation["architecture"]["modularity_score"],
                "safety_validation_score": safety_validation["empathy_score"],
                "code_solution_score": code_solution["validation_result"]["overall_score"]
            },
            "final_code": final_code,
            "constitutional_compliance": {
                "trinity_consensus": consensus_score >= 0.7,
                "architectural_compliance": architectural_foundation["constitutional_foundation"],
                "safety_compliance": safety_validation["asi_validation"],
                "code_compliance": code_solution["validation_result"]["constitutional_valid"]
            }
        }


# Convenience functions
async def coordinate_trinity(task: str, user_id: str = "trinity_user", context: Optional[Dict] = None) -> TrinityResult:
    """Convenience function for trinity coordination"""
    coordinator = TrinityCoordinator(user_id)
    return await coordinator.coordinate_trinity_operation(task, context)


async def coordinate_codex_trinity(coding_task: str, requirements: str, constraints: List[str],
                                 user_id: str = "codex_user", context: Optional[Dict] = None) -> CodexTrinitySynthesis:
    """Convenience function for Codex-specific trinity synthesis"""
    coordinator = TrinityCoordinator(user_id)
    return await coordinator.codex_specific_trinity_synthesis(coding_task, requirements, constraints, context)


# Example usage and testing
if __name__ == "__main__":
    async def test_trinity_coordinator():
        """Test the trinity coordinator"""
        
        print("=== Trinity Coordinator Test ===")
        
        coordinator = TrinityCoordinator(user_id="test_user")
        
        # Test general trinity coordination
        print("\n--- Testing General Trinity Coordination ---")
        trinity_result = await coordinator.coordinate_trinity_operation(
            task="Design a secure user authentication system",
            context={"domain": "web_application", "security_level": "high"}
        )
        
        print(f"Trinity Verdict: {trinity_result.constitutional_verdict}")
        print(f"Consensus Score: {trinity_result.trinity_metrics.get('consensus_score', 'N/A')}")
        print(f"Geometric Integrity: {trinity_result.geometric_integrity}")
        print(f"Execution Time: {trinity_result.execution_time_ms:.2f}ms")
        
        # Test Codex-specific trinity synthesis
        print("\n--- Testing Codex-Specific Trinity Synthesis ---")
        codex_result = await coordinator.codex_specific_trinity_synthesis(
            coding_task="Create a function to validate user email addresses",
            requirements="Must be secure, handle edge cases, and be readable",
            constraints=["Must use constitutional governance", "Must validate input", "Must handle errors gracefully"],
            context={"language": "python", "complexity": "moderate"}
        )
        
        print(f"Codex Constitutional Verdict: {codex_result.constitutional_verdict}")
        print(f"Trinity Metrics: {codex_result.trinity_metrics}")
        print(f"Final Code Length: {len(codex_result.final_code or '')} characters")
        print(f"Execution Time: {codex_result.execution_time_ms:.2f}ms")
        
        print("\n=== Test Complete ===")
    
    # Run test
    asyncio.run(test_trinity_coordinator())