work/Convergence_Engine/kernel/enhanced_synchrony_protocol.py

"""
Enhanced Synchrony Protocol - Phase 4.2 Implementation

This module implements the Enhanced Synchrony Protocol, which extends the Synchrony Phase Lock
protocol to include the SPL-Dialog layer. This enhancement provides cryptographic verification
of the entire interpretation pipeline—from raw dialogue to parsed plan to final kernel action—
ensuring that the human-kernel bridge is immutable and tamper-evident.

Key Features:
- SPL-Dialog layer for dialogue pipeline verification
- Cryptographic consistency checks for interpretation steps
- Tamper-evident audit trail verification
- Multi-stage pipeline integrity validation
- Enhanced temporal coordination for dialogue operations
- Immutable dialogue state preservation
"""

import time
import math
import hashlib
import threading
import asyncio
import json
from typing import Dict, List, Any, Optional, Tuple, Set, Callable, Union
from dataclasses import dataclass, field
from enum import Enum
import uuid
from datetime import datetime, timedelta
from collections import defaultdict, deque
import heapq

from synchrony_phase_lock_protocol import (
    ProductionSynchronySystem, SynchronizedOperation, SynchronyLevel, OperationPriority,
    ConsensusResult
)
from instruction_interpretation_layer import (
    InstructionInterpretationLayer, HumanInstruction, ParsedInstruction, KernelAction,
    AuditTrail, InstructionType, ProcessingStrategy
)
from arbitration_stack import ProductionArbitrationStack, ForbiddenZoneAccess
from advanced_trait_engine import AdvancedTraitEngine
from utm_kernel_design import UTMKernel
from event_driven_coordination import DjinnEventBus, EventType


class DialogPipelineStage(Enum):
    """Stages of the dialogue interpretation pipeline"""
    RAW_INPUT = "raw_input"                    # Initial human instruction
    PARSED_INTENT = "parsed_intent"            # Parsed instruction with intent
    VALIDATED_PLAN = "validated_plan"          # Validated execution plan
    KERNEL_ACTION = "kernel_action"            # Generated kernel action
    EXECUTION_RESULT = "execution_result"      # Final execution result
    AUDIT_COMPLETE = "audit_complete"          # Complete audit trail


class DialogIntegrityLevel(Enum):
    """Levels of dialogue integrity verification"""
    BASIC = "basic"                            # Basic hash verification
    ENHANCED = "enhanced"                      # Enhanced cryptographic verification
    COMPREHENSIVE = "comprehensive"            # Full pipeline verification
    IMMUTABLE = "immutable"                    # Immutable state verification


class DialogConsensusType(Enum):
    """Types of dialogue consensus"""
    SINGLE_AGENT = "single_agent"              # Single agent verification
    MULTI_AGENT = "multi_agent"                # Multi-agent consensus
    DISTRIBUTED = "distributed"                # Distributed consensus
    UNIVERSAL = "universal"                    # Universal consensus


@dataclass
class DialogPipelineState:
    """State of a dialogue pipeline stage"""
    stage: DialogPipelineStage
    content_hash: str
    timestamp: datetime
    agent_id: str
    verification_signature: Optional[str] = None
    integrity_checks: List[str] = field(default_factory=list)
    metadata: Dict[str, Any] = field(default_factory=dict)


@dataclass
class DialogIntegrityCheck:
    """Integrity check for dialogue pipeline"""
    check_id: str = field(default_factory=lambda: str(uuid.uuid4()))
    stage: DialogPipelineStage = DialogPipelineStage.RAW_INPUT
    content_hash: str = ""
    expected_hash: str = ""
    verification_result: bool = False
    timestamp: datetime = field(default_factory=datetime.utcnow)
    error_details: Optional[str] = None
    integrity_level: DialogIntegrityLevel = DialogIntegrityLevel.BASIC


@dataclass
class DialogConsensusResult:
    """Result of dialogue consensus verification"""
    consensus_id: str = field(default_factory=lambda: str(uuid.uuid4()))
    consensus_type: DialogConsensusType = DialogConsensusType.SINGLE_AGENT
    participating_agents: List[str] = field(default_factory=list)
    consensus_hash: str = ""
    agreement_threshold: float = 0.0
    agreement_ratio: float = 0.0
    consensus_reached: bool = False
    timestamp: datetime = field(default_factory=datetime.utcnow)
    verification_details: Dict[str, Any] = field(default_factory=dict)


@dataclass
class DialogTimelineEntry:
    """Timeline entry for dialogue operations"""
    entry_id: str = field(default_factory=lambda: str(uuid.uuid4()))
    instruction_id: str = ""
    pipeline_stages: List[DialogPipelineState] = field(default_factory=list)
    integrity_checks: List[DialogIntegrityCheck] = field(default_factory=list)
    consensus_results: List[DialogConsensusResult] = field(default_factory=list)
    final_hash: str = ""
    timestamp: datetime = field(default_factory=datetime.utcnow)
    verified: bool = False


@dataclass
class DialogSynchronizedOperation:
    """Synchronized operation for dialogue pipeline"""
    operation_id: str = field(default_factory=lambda: str(uuid.uuid4()))
    instruction_id: str = ""
    pipeline_stages: List[DialogPipelineState] = field(default_factory=list)
    integrity_level: DialogIntegrityLevel = DialogIntegrityLevel.ENHANCED
    consensus_type: DialogConsensusType = DialogConsensusType.MULTI_AGENT
    priority: OperationPriority = OperationPriority.NORMAL
    timestamp: datetime = field(default_factory=datetime.utcnow)
    completed: bool = False
    verification_result: Optional[bool] = None


class DialogPipelineVerifier:
    """Verifies the integrity of dialogue pipeline stages"""
    
    def __init__(self, integrity_level: DialogIntegrityLevel = DialogIntegrityLevel.ENHANCED):
        self.integrity_level = integrity_level
        self.verification_history: List[DialogIntegrityCheck] = []
        self.verification_cache: Dict[str, bool] = {}
    
    def verify_pipeline_stage(self, stage: DialogPipelineState) -> DialogIntegrityCheck:
        """Verify the integrity of a pipeline stage"""
        
        check = DialogIntegrityCheck(
            stage=stage.stage,
            content_hash=stage.content_hash,
            integrity_level=self.integrity_level
        )
        
        # Calculate expected hash based on stage content
        expected_hash = self._calculate_expected_hash(stage)
        check.expected_hash = expected_hash
        
        # Perform verification based on integrity level
        if self.integrity_level == DialogIntegrityLevel.BASIC:
            check.verification_result = (stage.content_hash == expected_hash)
        elif self.integrity_level == DialogIntegrityLevel.ENHANCED:
            check.verification_result = self._enhanced_verification(stage, expected_hash)
        elif self.integrity_level == DialogIntegrityLevel.COMPREHENSIVE:
            check.verification_result = self._comprehensive_verification(stage, expected_hash)
        elif self.integrity_level == DialogIntegrityLevel.IMMUTABLE:
            check.verification_result = self._immutable_verification(stage, expected_hash)
        
        if not check.verification_result:
            check.error_details = f"Hash mismatch: expected {expected_hash}, got {stage.content_hash}"
        
        self.verification_history.append(check)
        self.verification_cache[stage.content_hash] = check.verification_result
        
        return check
    
    def _calculate_expected_hash(self, stage: DialogPipelineState) -> str:
        """Calculate expected hash for a pipeline stage"""
        
        # Create content string for hashing
        content_parts = [
            stage.stage.value,
            str(stage.timestamp.isoformat()),
            stage.agent_id
        ]
        
        # Add metadata if present
        if stage.metadata:
            content_parts.append(json.dumps(stage.metadata, sort_keys=True))
        
        content_string = "|".join(content_parts)
        return hashlib.sha256(content_string.encode()).hexdigest()
    
    def _enhanced_verification(self, stage: DialogPipelineState, expected_hash: str) -> bool:
        """Enhanced verification with additional checks"""
        
        # Basic hash verification
        if stage.content_hash != expected_hash:
            return False
        
        # Check timestamp validity
        time_diff = abs((datetime.utcnow() - stage.timestamp).total_seconds())
        if time_diff > 300:  # 5 minutes tolerance
            return False
        
        # Check agent ID format
        if not stage.agent_id or len(stage.agent_id) < 3:
            return False
        
        return True
    
    def _comprehensive_verification(self, stage: DialogPipelineState, expected_hash: str) -> bool:
        """Comprehensive verification with full pipeline context"""
        
        # Enhanced verification
        if not self._enhanced_verification(stage, expected_hash):
            return False
        
        # Check stage sequence validity
        valid_stages = [s.value for s in DialogPipelineStage]
        if stage.stage.value not in valid_stages:
            return False
        
        # Check metadata integrity
        if stage.metadata:
            try:
                json.dumps(stage.metadata)  # Ensure JSON serializable
            except (TypeError, ValueError):
                return False
        
        return True
    
    def _immutable_verification(self, stage: DialogPipelineState, expected_hash: str) -> bool:
        """Immutable verification with cryptographic signatures"""
        
        # Comprehensive verification
        if not self._comprehensive_verification(stage, expected_hash):
            return False
        
        # Check for verification signature
        if not stage.verification_signature:
            return False
        
        # Verify signature (simplified - in production would use proper crypto)
        signature_content = f"{stage.content_hash}|{stage.timestamp.isoformat()}|{stage.agent_id}"
        expected_signature = hashlib.sha256(signature_content.encode()).hexdigest()
        
        return stage.verification_signature == expected_signature
    
    def get_verification_stats(self) -> Dict[str, Any]:
        """Get verification statistics"""
        
        total_checks = len(self.verification_history)
        successful_checks = sum(1 for check in self.verification_history if check.verification_result)
        failed_checks = total_checks - successful_checks
        
        stage_stats = defaultdict(lambda: {"total": 0, "successful": 0, "failed": 0})
        for check in self.verification_history:
            stage_stats[check.stage.value]["total"] += 1
            if check.verification_result:
                stage_stats[check.stage.value]["successful"] += 1
            else:
                stage_stats[check.stage.value]["failed"] += 1
        
        return {
            "total_checks": total_checks,
            "successful_checks": successful_checks,
            "failed_checks": failed_checks,
            "success_rate": successful_checks / total_checks if total_checks > 0 else 0.0,
            "stage_stats": dict(stage_stats),
            "integrity_level": self.integrity_level.value
        }


class DialogConsensusEngine:
    """Engine for achieving dialogue consensus across multiple agents"""
    
    def __init__(self, consensus_type: DialogConsensusType = DialogConsensusType.MULTI_AGENT):
        self.consensus_type = consensus_type
        self.consensus_history: List[DialogConsensusResult] = []
        self.agent_hashes: Dict[str, str] = {}
        self.consensus_cache: Dict[str, DialogConsensusResult] = {}
    
    def achieve_consensus(self, pipeline_states: List[DialogPipelineState], 
                         agreement_threshold: float = 0.75) -> DialogConsensusResult:
        """Achieve consensus on dialogue pipeline states"""
        
        consensus = DialogConsensusResult(
            consensus_type=self.consensus_type,
            agreement_threshold=agreement_threshold
        )
        
        if not pipeline_states:
            consensus.consensus_reached = False
            return consensus
        
        # Collect agent hashes
        agent_hashes = {}
        for state in pipeline_states:
            agent_hashes[state.agent_id] = state.content_hash
            consensus.participating_agents.append(state.agent_id)
        
        # Calculate consensus based on type
        if self.consensus_type == DialogConsensusType.SINGLE_AGENT:
            consensus = self._single_agent_consensus(pipeline_states, agreement_threshold)
        elif self.consensus_type == DialogConsensusType.MULTI_AGENT:
            consensus = self._multi_agent_consensus(agent_hashes, agreement_threshold)
        elif self.consensus_type == DialogConsensusType.DISTRIBUTED:
            consensus = self._distributed_consensus(agent_hashes, agreement_threshold)
        elif self.consensus_type == DialogConsensusType.UNIVERSAL:
            consensus = self._universal_consensus(agent_hashes, agreement_threshold)
        
        self.consensus_history.append(consensus)
        self.consensus_cache[consensus.consensus_id] = consensus
        
        return consensus
    
    def _single_agent_consensus(self, pipeline_states: List[DialogPipelineState], 
                               agreement_threshold: float) -> DialogConsensusResult:
        """Single agent consensus verification"""
        
        consensus = DialogConsensusResult(
            consensus_type=DialogConsensusType.SINGLE_AGENT,
            agreement_threshold=agreement_threshold
        )
        
        if len(pipeline_states) == 1:
            state = pipeline_states[0]
            consensus.consensus_hash = state.content_hash
            consensus.agreement_ratio = 1.0
            consensus.consensus_reached = True
            consensus.participating_agents = [state.agent_id]
        
        return consensus
    
    def _multi_agent_consensus(self, agent_hashes: Dict[str, str], 
                              agreement_threshold: float) -> DialogConsensusResult:
        """Multi-agent consensus verification"""
        
        consensus = DialogConsensusResult(
            consensus_type=DialogConsensusType.MULTI_AGENT,
            agreement_threshold=agreement_threshold
        )
        
        # Count hash frequencies
        hash_counts = defaultdict(int)
        for agent_id, content_hash in agent_hashes.items():
            hash_counts[content_hash] += 1
            consensus.participating_agents.append(agent_id)
        
        # Find most common hash
        if hash_counts:
            most_common_hash = max(hash_counts.items(), key=lambda x: x[1])
            consensus.consensus_hash = most_common_hash[0]
            consensus.agreement_ratio = most_common_hash[1] / len(agent_hashes)
            consensus.consensus_reached = consensus.agreement_ratio >= agreement_threshold
        
        return consensus
    
    def _distributed_consensus(self, agent_hashes: Dict[str, str], 
                              agreement_threshold: float) -> DialogConsensusResult:
        """Distributed consensus with weighted voting"""
        
        consensus = DialogConsensusResult(
            consensus_type=DialogConsensusType.DISTRIBUTED,
            agreement_threshold=agreement_threshold
        )
        
        # Weighted voting based on agent reliability (simplified)
        hash_weights = defaultdict(float)
        total_weight = 0.0
        
        for agent_id, content_hash in agent_hashes.items():
            weight = 1.0  # In production, this would be based on agent reliability
            hash_weights[content_hash] += weight
            total_weight += weight
            consensus.participating_agents.append(agent_id)
        
        # Find weighted consensus
        if hash_weights and total_weight > 0:
            most_weighted_hash = max(hash_weights.items(), key=lambda x: x[1])
            consensus.consensus_hash = most_weighted_hash[0]
            consensus.agreement_ratio = most_weighted_hash[1] / total_weight
            consensus.consensus_reached = consensus.agreement_ratio >= agreement_threshold
        
        return consensus
    
    def _universal_consensus(self, agent_hashes: Dict[str, str], 
                            agreement_threshold: float) -> DialogConsensusResult:
        """Universal consensus requiring unanimous agreement"""
        
        consensus = DialogConsensusResult(
            consensus_type=DialogConsensusType.UNIVERSAL,
            agreement_threshold=agreement_threshold
        )
        
        # Check for unanimous agreement
        unique_hashes = set(agent_hashes.values())
        consensus.participating_agents = list(agent_hashes.keys())
        
        if len(unique_hashes) == 1:
            consensus.consensus_hash = list(unique_hashes)[0]
            consensus.agreement_ratio = 1.0
            consensus.consensus_reached = True
        else:
            consensus.agreement_ratio = 0.0
            consensus.consensus_reached = False
        
        return consensus
    
    def get_consensus_stats(self) -> Dict[str, Any]:
        """Get consensus statistics"""
        
        total_consensus = len(self.consensus_history)
        successful_consensus = sum(1 for c in self.consensus_history if c.consensus_reached)
        failed_consensus = total_consensus - successful_consensus
        
        type_stats = defaultdict(lambda: {"total": 0, "successful": 0, "failed": 0})
        for consensus in self.consensus_history:
            type_stats[consensus.consensus_type.value]["total"] += 1
            if consensus.consensus_reached:
                type_stats[consensus.consensus_type.value]["successful"] += 1
            else:
                type_stats[consensus.consensus_type.value]["failed"] += 1
        
        return {
            "total_consensus": total_consensus,
            "successful_consensus": successful_consensus,
            "failed_consensus": failed_consensus,
            "success_rate": successful_consensus / total_consensus if total_consensus > 0 else 0.0,
            "type_stats": dict(type_stats),
            "consensus_type": self.consensus_type.value
        }


class DialogTimelineManager:
    """Manages the timeline of dialogue operations"""
    
    def __init__(self, max_entries: int = 10000):
        self.max_entries = max_entries
        self.timeline_entries: Dict[str, DialogTimelineEntry] = {}
        self.timeline_order: deque = deque(maxlen=max_entries)
        self.entry_counter = 0
    
    def add_timeline_entry(self, instruction_id: str, pipeline_states: List[DialogPipelineState],
                          integrity_checks: List[DialogIntegrityCheck],
                          consensus_results: List[DialogConsensusResult]) -> str:
        """Add a new timeline entry"""
        
        entry = DialogTimelineEntry(
            instruction_id=instruction_id,
            pipeline_stages=pipeline_states,
            integrity_checks=integrity_checks,
            consensus_results=consensus_results
        )
        
        # Calculate final hash
        entry.final_hash = self._calculate_final_hash(entry)
        
        # Verify entry integrity
        entry.verified = self._verify_entry_integrity(entry)
        
        # Store entry
        self.timeline_entries[entry.entry_id] = entry
        self.timeline_order.append(entry.entry_id)
        self.entry_counter += 1
        
        return entry.entry_id
    
    def _calculate_final_hash(self, entry: DialogTimelineEntry) -> str:
        """Calculate final hash for timeline entry"""
        
        content_parts = [
            entry.instruction_id,
            str(entry.timestamp.isoformat())
        ]
        
        # Add pipeline stage hashes
        for stage in entry.pipeline_stages:
            content_parts.append(stage.content_hash)
        
        # Add integrity check results
        for check in entry.integrity_checks:
            content_parts.append(f"{check.stage.value}:{check.verification_result}")
        
        # Add consensus results
        for consensus in entry.consensus_results:
            content_parts.append(f"{consensus.consensus_type.value}:{consensus.consensus_hash}")
        
        content_string = "|".join(content_parts)
        return hashlib.sha256(content_string.encode()).hexdigest()
    
    def _verify_entry_integrity(self, entry: DialogTimelineEntry) -> bool:
        """Verify the integrity of a timeline entry"""
        
        # Check that all pipeline stages have integrity checks
        stage_checks = {check.stage: check for check in entry.integrity_checks}
        for stage in entry.pipeline_stages:
            if stage.stage not in stage_checks:
                return False
            if not stage_checks[stage.stage].verification_result:
                return False
        
        # Check that consensus was reached
        if entry.consensus_results:
            for consensus in entry.consensus_results:
                if not consensus.consensus_reached:
                    return False
        
        return True
    
    def get_timeline_entry(self, entry_id: str) -> Optional[DialogTimelineEntry]:
        """Get a timeline entry by ID"""
        return self.timeline_entries.get(entry_id)
    
    def get_timeline_slice(self, start_time: datetime, end_time: datetime) -> List[DialogTimelineEntry]:
        """Get timeline entries within a time range"""
        
        entries = []
        for entry in self.timeline_entries.values():
            if start_time <= entry.timestamp <= end_time:
                entries.append(entry)
        
        return sorted(entries, key=lambda x: x.timestamp)
    
    def get_timeline_stats(self) -> Dict[str, Any]:
        """Get timeline statistics"""
        
        total_entries = len(self.timeline_entries)
        verified_entries = sum(1 for entry in self.timeline_entries.values() if entry.verified)
        unverified_entries = total_entries - verified_entries
        
        stage_counts = defaultdict(int)
        for entry in self.timeline_entries.values():
            for stage in entry.pipeline_stages:
                stage_counts[stage.stage.value] += 1
        
        return {
            "total_entries": total_entries,
            "verified_entries": verified_entries,
            "unverified_entries": unverified_entries,
            "verification_rate": verified_entries / total_entries if total_entries > 0 else 0.0,
            "stage_counts": dict(stage_counts),
            "entry_counter": self.entry_counter
        }


class EnhancedSynchronyProtocol:
    """Enhanced Synchrony Protocol with SPL-Dialog layer"""
    
    def __init__(self, instruction_layer: InstructionInterpretationLayer,
                 synchrony_system: ProductionSynchronySystem,
                 arbitration_stack: ProductionArbitrationStack,
                 trait_engine: AdvancedTraitEngine,
                 utm_kernel: UTMKernel):
        
        self.instruction_layer = instruction_layer
        self.synchrony_system = synchrony_system
        self.arbitration_stack = arbitration_stack
        self.trait_engine = trait_engine
        self.utm_kernel = utm_kernel
        
        # SPL-Dialog components
        self.pipeline_verifier = DialogPipelineVerifier(DialogIntegrityLevel.ENHANCED)
        self.consensus_engine = DialogConsensusEngine(DialogConsensusType.MULTI_AGENT)
        self.timeline_manager = DialogTimelineManager()
        
        # Enhanced synchrony state
        self.dialog_operations: Dict[str, DialogSynchronizedOperation] = {}
        self.pipeline_states: Dict[str, List[DialogPipelineState]] = defaultdict(list)
        self.integrity_checks: Dict[str, List[DialogIntegrityCheck]] = defaultdict(list)
        self.consensus_results: Dict[str, List[DialogConsensusResult]] = defaultdict(list)
        
        # Monitoring and metrics
        self.monitoring_active = True
        self.monitor_thread = threading.Thread(target=self._dialog_monitor, daemon=True)
        self.monitor_thread.start()
    
    def synchronize_dialog_operation(self, instruction_id: str, 
                                   integrity_level: DialogIntegrityLevel = DialogIntegrityLevel.ENHANCED,
                                   consensus_type: DialogConsensusType = DialogConsensusType.MULTI_AGENT,
                                   priority: OperationPriority = OperationPriority.NORMAL) -> str:
        """Synchronize a dialogue operation through the enhanced protocol"""
        
        # Create synchronized operation
        operation = DialogSynchronizedOperation(
            instruction_id=instruction_id,
            integrity_level=integrity_level,
            consensus_type=consensus_type,
            priority=priority
        )
        
        # Get instruction details
        instruction_status = self.instruction_layer.get_instruction_status(instruction_id)
        if not instruction_status:
            raise ValueError(f"Instruction {instruction_id} not found")
        
        # Create pipeline states for each stage
        pipeline_states = self._create_pipeline_states(instruction_id, instruction_status)
        operation.pipeline_stages = pipeline_states
        
        # Verify pipeline integrity
        integrity_checks = []
        for state in pipeline_states:
            check = self.pipeline_verifier.verify_pipeline_stage(state)
            integrity_checks.append(check)
        
        operation.integrity_checks = integrity_checks
        
        # Achieve consensus
        consensus_result = self.consensus_engine.achieve_consensus(pipeline_states)
        operation.consensus_results = [consensus_result]
        
        # Add to timeline
        timeline_entry_id = self.timeline_manager.add_timeline_entry(
            instruction_id, pipeline_states, integrity_checks, [consensus_result]
        )
        
        # Store operation
        self.dialog_operations[operation.operation_id] = operation
        self.pipeline_states[instruction_id] = pipeline_states
        self.integrity_checks[instruction_id] = integrity_checks
        self.consensus_results[instruction_id] = [consensus_result]
        
        # Synchronize with base synchrony system
        sync_operation = SynchronizedOperation(
            operation_id=operation.operation_id,
            operation_type="dialog_synchronization",
            operation_data={
                "instruction_id": instruction_id,
                "integrity_level": integrity_level.value,
                "consensus_type": consensus_type.value,
                "timeline_entry_id": timeline_entry_id
            },
            priority=priority,
            source_agent="dialog_synchrony_agent"
        )
        
        self.synchrony_system.submit_synchronized_operation(sync_operation)
        
        # Mark operation as completed
        operation.completed = True
        operation.verification_result = consensus_result.consensus_reached
        
        return operation.operation_id
    
    def _create_pipeline_states(self, instruction_id: str, 
                               instruction_status: Dict[str, Any]) -> List[DialogPipelineState]:
        """Create pipeline states for an instruction"""
        
        states = []
        agent_id = "dialog_synchrony_agent"
        
        # Raw input stage
        raw_state = DialogPipelineState(
            stage=DialogPipelineStage.RAW_INPUT,
            content_hash=hashlib.sha256(instruction_status['raw_text'].encode()).hexdigest(),
            timestamp=datetime.utcnow(),
            agent_id=agent_id,
            metadata={"instruction_type": instruction_status['instruction_type']}
        )
        states.append(raw_state)
        
        # Parsed intent stage
        parsed_state = DialogPipelineState(
            stage=DialogPipelineStage.PARSED_INTENT,
            content_hash=hashlib.sha256(instruction_status['parsed_intent'].encode()).hexdigest(),
            timestamp=datetime.utcnow(),
            agent_id=agent_id,
            metadata={"parsing_confidence": instruction_status['parsing_confidence']}
        )
        states.append(parsed_state)
        
        # Validated plan stage
        validated_state = DialogPipelineState(
            stage=DialogPipelineStage.VALIDATED_PLAN,
            content_hash=hashlib.sha256(str(instruction_status['processing_successful']).encode()).hexdigest(),
            timestamp=datetime.utcnow(),
            agent_id=agent_id,
            metadata={"processing_strategy": instruction_status['processing_strategy']}
        )
        states.append(validated_state)
        
        # Kernel action stage
        kernel_state = DialogPipelineState(
            stage=DialogPipelineStage.KERNEL_ACTION,
            content_hash=hashlib.sha256(str(instruction_status['kernel_actions_count']).encode()).hexdigest(),
            timestamp=datetime.utcnow(),
            agent_id=agent_id,
            metadata={"kernel_actions_count": instruction_status['kernel_actions_count']}
        )
        states.append(kernel_state)
        
        # Execution result stage
        execution_state = DialogPipelineState(
            stage=DialogPipelineStage.EXECUTION_RESULT,
            content_hash=hashlib.sha256(str(instruction_status['processing_successful']).encode()).hexdigest(),
            timestamp=datetime.utcnow(),
            agent_id=agent_id,
            metadata={"final_success": instruction_status['processing_successful']}
        )
        states.append(execution_state)
        
        # Audit complete stage
        audit_state = DialogPipelineState(
            stage=DialogPipelineStage.AUDIT_COMPLETE,
            content_hash=hashlib.sha256(instruction_id.encode()).hexdigest(),
            timestamp=datetime.utcnow(),
            agent_id=agent_id,
            metadata={"instruction_id": instruction_id}
        )
        states.append(audit_state)
        
        return states
    
    def verify_dialog_integrity(self, instruction_id: str) -> Dict[str, Any]:
        """Verify the integrity of a dialogue operation"""
        
        if instruction_id not in self.pipeline_states:
            return {"error": "Instruction not found in pipeline"}
        
        pipeline_states = self.pipeline_states[instruction_id]
        integrity_checks = self.integrity_checks[instruction_id]
        consensus_results = self.consensus_results[instruction_id]
        
        # Verify all pipeline stages
        stage_verifications = {}
        for i, state in enumerate(pipeline_states):
            stage_verifications[state.stage.value] = {
                "verified": integrity_checks[i].verification_result if i < len(integrity_checks) else False,
                "content_hash": state.content_hash,
                "timestamp": state.timestamp.isoformat(),
                "agent_id": state.agent_id
            }
        
        # Check consensus
        consensus_verified = all(result.consensus_reached for result in consensus_results)
        
        # Overall integrity
        all_stages_verified = all(check.verification_result for check in integrity_checks)
        overall_integrity = all_stages_verified and consensus_verified
        
        return {
            "instruction_id": instruction_id,
            "overall_integrity": overall_integrity,
            "stage_verifications": stage_verifications,
            "consensus_verified": consensus_verified,
            "all_stages_verified": all_stages_verified,
            "integrity_checks_count": len(integrity_checks),
            "consensus_results_count": len(consensus_results)
        }
    
    def get_dialog_timeline(self, start_time: Optional[datetime] = None, 
                           end_time: Optional[datetime] = None) -> List[Dict[str, Any]]:
        """Get dialogue timeline entries"""
        
        if start_time is None:
            start_time = datetime.utcnow() - timedelta(hours=24)
        if end_time is None:
            end_time = datetime.utcnow()
        
        timeline_entries = self.timeline_manager.get_timeline_slice(start_time, end_time)
        
        result = []
        for entry in timeline_entries:
            result.append({
                "entry_id": entry.entry_id,
                "instruction_id": entry.instruction_id,
                "timestamp": entry.timestamp.isoformat(),
                "verified": entry.verified,
                "final_hash": entry.final_hash,
                "pipeline_stages_count": len(entry.pipeline_stages),
                "integrity_checks_count": len(entry.integrity_checks),
                "consensus_results_count": len(entry.consensus_results)
            })
        
        return result
    
    def get_enhanced_synchrony_metrics(self) -> Dict[str, Any]:
        """Get enhanced synchrony metrics"""
        
        # Pipeline verifier stats
        verifier_stats = self.pipeline_verifier.get_verification_stats()
        
        # Consensus engine stats
        consensus_stats = self.consensus_engine.get_consensus_stats()
        
        # Timeline manager stats
        timeline_stats = self.timeline_manager.get_timeline_stats()
        
        # Dialog operations stats
        total_operations = len(self.dialog_operations)
        completed_operations = sum(1 for op in self.dialog_operations.values() if op.completed)
        verified_operations = sum(1 for op in self.dialog_operations.values() 
                                if op.verification_result is True)
        
        return {
            "dialog_operations": {
                "total_operations": total_operations,
                "completed_operations": completed_operations,
                "verified_operations": verified_operations,
                "completion_rate": completed_operations / total_operations if total_operations > 0 else 0.0,
                "verification_rate": verified_operations / total_operations if total_operations > 0 else 0.0
            },
            "pipeline_verifier": verifier_stats,
            "consensus_engine": consensus_stats,
            "timeline_manager": timeline_stats,
            "enhanced_synchrony_active": self.monitoring_active
        }
    
    def _dialog_monitor(self) -> None:
        """Background monitor for dialogue operations"""
        
        while self.monitoring_active:
            try:
                # Monitor for new instructions
                all_instructions = self.instruction_layer.instructions
                
                for instruction_id, instruction in all_instructions.items():
                    if instruction_id not in self.dialog_operations:
                        # Auto-synchronize new instructions
                        try:
                            self.synchronize_dialog_operation(
                                instruction_id,
                                integrity_level=DialogIntegrityLevel.ENHANCED,
                                consensus_type=DialogConsensusType.MULTI_AGENT,
                                priority=OperationPriority.NORMAL
                            )
                        except Exception as e:
                            print(f"Auto-synchronization failed for {instruction_id}: {e}")
                
                time.sleep(5.0)  # Check every 5 seconds
                
            except Exception as e:
                print(f"Dialog monitor error: {e}")
                time.sleep(10.0)
    
    def shutdown(self) -> None:
        """Shutdown the enhanced synchrony protocol"""
        
        self.monitoring_active = False
        if self.monitor_thread.is_alive():
            self.monitor_thread.join(timeout=5.0)


# Example usage and testing
if __name__ == "__main__":
    # This would be used in the main kernel initialization
    print("Enhanced Synchrony Protocol - Phase 4.2 Implementation")
    print("SPL-Dialog layer for cryptographic verification of interpretation pipeline")