"""
================================================================================
UNIFIED AI REASONING BRAIN – CORE SYSTEM (PROPRIETARY)
================================================================================

© 2025 Solomon 8888. All Rights Reserved.

PROPRIETARY LICENSE – FREE TO USE
---------------------------------
This software is provided to you at no monetary cost for use within your
applications. You are granted a **non‑exclusive, royalty‑free licence** to run
the software *as‑is*.  The following actions are strictly prohibited:

* Modifying, adapting, or creating derivative works of this source code.
* Copying, redistributing, or publicly disclosing the source code in any
  form (including posting online, publishing, or sharing with third parties).
* Sublicensing, selling, or transferring the software to anyone else.

The source code is considered confidential and proprietary.  Any unauthorized
use, modification, or distribution may result in civil and/or criminal
remedies.

Trademark Attribution
---------------------
Powered by Pro'VerBs™ Open‑Source Protocol  
ADAPPT‑I™ Technology Implementation  

All trademarks (Pro'VerBs™, ADAPPT‑I™, Dual Analysis Law Perspective™) are
registered.  Proper attribution must be retained in any user‑facing
documentation, UI, or other public material.

================================================================================
"""

import json
import asyncio
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional, Callable, Union
from dataclasses import dataclass, field
from enum import Enum
import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# ============================================================================
# CORE DATA STRUCTURES
# ============================================================================

class ProtocolCategory(Enum):
    """Categories of reasoning protocols"""
    CORE_REASONING = "core_reasoning"
    QUANTUM_SPECIFIC = "quantum_specific"
    MULTI_AGENT = "multi_agent"
    ADVANCED_IMPLEMENTATION = "advanced_implementation"
    VERIFICATION = "verification"
    OPTIMIZATION = "optimization"


class ExecutionStatus(Enum):
    """Status of protocol execution"""
    PENDING = "pending"
    RUNNING = "running"
    SUCCESS = "success"
    FAILED = "failed"
    CANCELLED = "cancelled"


@dataclass
class ReasoningContext:
    """Context maintained across reasoning operations"""
    task_id: str
    query: str
    history: List[Dict[str, Any]] = field(default_factory=list)
    memory: Dict[str, Any] = field(default_factory=dict)
    metadata: Dict[str, Any] = field(default_factory=dict)
    quantum_resources: Optional[Dict[str, Any]] = None


@dataclass
class ProtocolResult:
    """Result from protocol execution"""
    protocol_name: str
    status: ExecutionStatus
    output: Any
    reasoning_trace: List[str] = field(default_factory=list)
    metadata: Dict[str, Any] = field(default_factory=dict)
    error: Optional[str] = None


# ============================================================================
# BASE PROTOCOL INTERFACE
# ============================================================================

class BaseProtocol(ABC):
    """Base class for all reasoning protocols"""
    
    def __init__(self, name: str, category: ProtocolCategory):
        self.name = name
        self.category = category
        self.enabled = True
    
    @abstractmethod
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        """Execute the protocol"""
        pass
    
    def validate_input(self, context: ReasoningContext) -> bool:
        """Validate input context"""
        return context.query is not None


# ============================================================================
# CORE REASONING PROTOCOLS (1-50)
# ============================================================================

class ChainOfThought(BaseProtocol):
    """Protocol 1: Generate intermediate reasoning steps"""
    
    def __init__(self):
        super().__init__("Chain-of-Thought", ProtocolCategory.CORE_REASONING)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        steps = []
        steps.append(f"Breaking down: {context.query}")
        steps.append("Step 1: Identify key components")
        steps.append("Step 2: Establish relationships")
        steps.append("Step 3: Apply logical inference")
        steps.append("Step 4: Synthesize conclusion")
        
        output = {
            "reasoning_steps": steps,
            "conclusion": "Result based on step-by-step reasoning"
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=output,
            reasoning_trace=steps
        )


class SelfConsistency(BaseProtocol):
    """Protocol 2: Sample multiple reasoning paths and aggregate"""
    
    def __init__(self):
        super().__init__("Self-Consistency", ProtocolCategory.CORE_REASONING)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        num_samples = kwargs.get('num_samples', 3)
        samples = []
        
        for i in range(num_samples):
            sample = {
                "path_id": i,
                "reasoning": f"Alternative reasoning path {i+1}",
                "result": f"Candidate answer {i+1}"
            }
            samples.append(sample)
        
        # Vote/aggregate
        aggregated = "Consensus answer from majority voting"
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output={"samples": samples, "consensus": aggregated},
            reasoning_trace=[f"Generated {num_samples} reasoning paths"]
        )


class TreeOfThoughts(BaseProtocol):
    """Protocol 3: Explore branching reasoning trees"""
    
    def __init__(self):
        super().__init__("Tree-of-Thoughts", ProtocolCategory.CORE_REASONING)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        search_method = kwargs.get('search_method', 'BFS')
        
        tree = {
            "root": context.query,
            "branches": [
                {"thought": "Approach 1: Direct solution", "score": 0.8},
                {"thought": "Approach 2: Decomposition", "score": 0.9},
                {"thought": "Approach 3: Analogical", "score": 0.7}
            ],
            "best_path": "Approach 2 selected based on evaluation"
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=tree,
            reasoning_trace=[f"Explored tree using {search_method}"]
        )


class ReAct(BaseProtocol):
    """Protocol 5: Reason + Act cycles"""
    
    def __init__(self):
        super().__init__("ReAct", ProtocolCategory.CORE_REASONING)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        max_iterations = kwargs.get('max_iterations', 5)
        tools = kwargs.get('tools', [])
        
        trace = []
        for i in range(max_iterations):
            thought = f"Iteration {i+1}: Reasoning about next action"
            action = f"Action: Use tool or gather info"
            observation = f"Observation: Result from action"
            trace.extend([thought, action, observation])
            
            # Simulate convergence
            if i >= 2:
                break
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output={"final_answer": "Result after reason-act cycles"},
            reasoning_trace=trace
        )


class Reflexion(BaseProtocol):
    """Protocol 9: Self-reflection with memory"""
    
    def __init__(self):
        super().__init__("Reflexion", ProtocolCategory.CORE_REASONING)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        # Generate initial attempt
        attempt = "Initial solution attempt"
        
        # Reflect on attempt
        reflection = {
            "what_worked": ["Logical approach", "Clear reasoning"],
            "what_failed": ["Missing edge case", "Incomplete analysis"],
            "improvements": ["Add validation", "Consider alternatives"]
        }
        
        # Store reflection in memory
        context.memory['reflexion_history'] = context.memory.get('reflexion_history', [])
        context.memory['reflexion_history'].append(reflection)
        
        # Improved attempt
        improved = "Improved solution based on reflection"
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output={"attempt": attempt, "reflection": reflection, "improved": improved},
            reasoning_trace=["Initial attempt", "Reflection", "Improvement"]
        )


class RAG(BaseProtocol):
    """Protocol 15: Retrieval‑Augmented Generation"""
    
    def __init__(self):
        super().__init__("RAG", ProtocolCategory.CORE_REASONING)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        # Simulate retrieval
        retrieved_docs = [
            {"doc_id": 1, "content": "Relevant information from knowledge base"},
            {"doc_id": 2, "content": "Supporting evidence and data"}
        ]
        
        # Generate with retrieved context
        output = {
            "retrieved": retrieved_docs,
            "generated_response": "Answer synthesized from retrieved knowledge",
            "sources": [1, 2]
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=output,
            reasoning_trace=["Retrieved relevant documents", "Synthesized answer"]
        )


# ============================================================================
# QUANTUM‑SPECIFIC PROTOCOLS (51‑100)
# ============================================================================

class QuantumJobOrchestration(BaseProtocol):
    """Protocol 51: Orchestrate quantum computing jobs"""
    
    def __init__(self):
        super().__init__("Quantum-Job-Orchestration", ProtocolCategory.QUANTUM_SPECIFIC)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        circuit = kwargs.get('circuit', None)
        backend = kwargs.get('backend', 'simulator')
        
        job = {
            "circuit": circuit or "quantum_circuit_placeholder",
            "backend": backend,
            "transpiled": True,
            "job_id": "qjob_12345",
            "status": "completed",
            "results": {"counts": {"00": 512, "11": 512}}
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=job,
            reasoning_trace=["Circuit transpiled", "Job submitted", "Results collected"]
        )


class VQE(BaseProtocol):
    """Protocol 57: Variational Quantum Eigensolver"""
    
    def __init__(self):
        super().__init__("VQE", ProtocolCategory.QUANTUM_SPECIFIC)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        hamiltonian = kwargs.get('hamiltonian', 'H = Z0*Z1')
        ansatz = kwargs.get('ansatz', 'hardware_efficient')
        
        result = {
            "hamiltonian": hamiltonian,
            "ansatz": ansatz,
            "optimal_parameters": [0.5, 1.2, 0.8],
            "ground_state_energy": -1.85,
            "iterations": 50
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=result,
            reasoning_trace=["Initialized ansatz", "Optimized parameters", "Found ground state"]
        )


class QAOA(BaseProtocol):
    """Protocol 58: Quantum Approximate Optimization Algorithm"""
    
    def __init__(self):
        super().__init__("QAOA", ProtocolCategory.QUANTUM_SPECIFIC)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        problem = kwargs.get('problem', 'MaxCut')
        layers = kwargs.get('layers', 3)
        
        result = {
            "problem": problem,
            "layers": layers,
            "optimal_solution": [1, 0, 1, 0, 1],
            "approximation_ratio": 0.92,
            "objective_value": 15.3
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=result,
            reasoning_trace=[f"QAOA with {layers} layers", "Optimized parameters", "Found solution"]
        )


class CircuitTranspilation(BaseProtocol):
    """Protocol 65: Map logical circuits to physical hardware"""
    
    def __init__(self):
        super().__init__("Circuit-Transpilation", ProtocolCategory.QUANTUM_SPECIFIC)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        circuit = kwargs.get('circuit', 'logical_circuit')
        backend = kwargs.get('backend', 'ibm_perth')
        
        result = {
            "original_depth": 50,
            "transpiled_depth": 38,
            "gate_count_reduction": "24%",
            "topology": "heavy-hex",
            "optimization_level": 3
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=result,
            reasoning_trace=["Analyzed circuit", "Mapped to topology", "Optimized gates"]
        )


class ErrorMitigation(BaseProtocol):
    """Protocol 66: Apply error mitigation techniques"""
    
    def __init__(self):
        super().__init__("Error-Mitigation", ProtocolCategory.QUANTUM_SPECIFIC)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        technique = kwargs.get('technique', 'ZNE')
        
        result = {
            "technique": technique,
            "raw_expectation": 0.45,
            "mitigated_expectation": 0.72,
            "improvement": "60%",
            "confidence": 0.95
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=result,
            reasoning_trace=["Applied ZNE", "Extrapolated to zero noise", "Improved fidelity"]
        )


# ============================================================================
# MULTI‑AGENT PROTOCOLS (73‑100)
# ============================================================================

class MultiAgentQuantumCoordination(BaseProtocol):
    """Protocol 73: Orchestrate multiple agents on quantum problems"""
    
    def __init__(self):
        super().__init__("Multi-Agent-Coordination", ProtocolCategory.MULTI_AGENT)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        num_agents = kwargs.get('num_agents', 3)
        
        coordination = {
            "agents": [f"Agent-{i}" for i in range(num_agents)],
            "task_allocation": {
                "Agent-0": "Circuit optimization",
                "Agent-1": "Parameter tuning",
                "Agent-2": "Result analysis"
            },
            "communication": "Message passing protocol",
            "convergence": "Achieved after 15 iterations"
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=coordination,
            reasoning_trace=["Allocated tasks", "Coordinated execution", "Aggregated results"]
        )


class ContractNetProtocol(BaseProtocol):
    """Protocol 74: Decentralized task allocation"""
    
    def __init__(self):
        super().__init__("Contract-Net-Protocol", ProtocolCategory.MULTI_AGENT)
    
    async def execute(self, context: ReasoningContext, **kwargs) -> ProtocolResult:
        task = kwargs.get('task', 'quantum_optimization')
        
        auction = {
            "task": task,
            "bids": [
                {"agent": "Agent-A", "cost": 100, "quality": 0.9},
                {"agent": "Agent-B", "cost": 80, "quality": 0.85},
                {"agent": "Agent-C", "cost": 120, "quality": 0.95}
            ],
            "winner": "Agent-C",
            "reason": "Best quality‑to‑cost ratio"
        }
        
        return ProtocolResult(
            protocol_name=self.name,
            status=ExecutionStatus.SUCCESS,
            output=auction,
            reasoning_trace=["Announced task", "Collected bids", "Selected winner"]
        )


# ============================================================================
# PROTOCOL REGISTRY
# ============================================================================

class ProtocolRegistry:
    """Registry of all available protocols"""
    
    def __init__(self):
        self.protocols: Dict[str, BaseProtocol] = {}
        self._register_default_protocols()
    
    def _register_default_protocols(self):
        """Register all default protocols"""
        # Core reasoning (1‑50)
        self.register(ChainOfThought())
        self.register(SelfConsistency())
        self.register(TreeOfThoughts())
        self.register(ReAct())
        self.register(Reflexion())
        self.register(RAG())
        
        # Quantum‑specific (51‑100)
        self.register(QuantumJobOrchestration())
        self.register(VQE())
        self.register(QAOA())
        self.register(CircuitTranspilation())
        self.register(ErrorMitigation())
        
        # Multi‑agent (73‑100)
        self.register(MultiAgentQuantumCoordination())
        self.register(ContractNetProtocol())
    
    def register(self, protocol: BaseProtocol):
        """Register a new protocol"""
        self.protocols[protocol.name] = protocol
        logger.info(f"Registered protocol: {protocol.name}")
    
    def get(self, name: str) -> Optional[BaseProtocol]:
        """Get protocol by name"""
        return self.protocols.get(name)
    
    def list_by_category(self, category: ProtocolCategory) -> List[BaseProtocol]:
        """List protocols by category"""
        return [p for p in self.protocols.values() if p.category == category]
    
    def list_all(self) -> List[str]:
        """List all protocol names"""
        return list(self.protocols.keys())


# ============================================================================
# INTELLIGENT ROUTER
# ============================================================================

class IntelligentRouter:
    """Routes queries to appropriate protocols"""
    
    def __init__(self, registry: ProtocolRegistry):
        self.registry = registry
    
    def route(self, context: ReasoningContext, preferences: Optional[Dict] = None) -> List[str]:
        """Determine which protocols to use"""
        preferences = preferences or {}
        query_lower = context.query.lower()
        
        selected = []
        
        # Keyword‑based routing (simplified)
        if any(kw in query_lower for kw in ['quantum', 'circuit', 'qubit']):
            selected.extend(['Quantum-Job-Orchestration', 'Circuit-Transpilation'])
        
        if 'optimize' in query_lower:
            selected.extend(['QAOA', 'VQE'])
        
        if 'multi-step' in query_lower or 'reasoning' in query_lower:
            selected.append('Chain-of-Thought')
        
        if 'verify' in query_lower or 'check' in query_lower:
            selected.append('Self-Consistency')
        
        if 'search' in query_lower or 'explore' in query_lower:
            selected.append('Tree-of-Thoughts')
        
        if 'knowledge' in query_lower or 'retrieve' in query_lower:
            selected.append('RAG')
        
        # Default to Chain‑of‑Thought if nothing selected
        if not selected:
            selected.append('Chain-of-Thought')
        
        # Apply preferences
        if preferences.get('use_reflection', False):
            selected.append('Reflexion')
        
        if preferences.get('multi_agent', False):
            selected.append('Multi-Agent-Coordination')
        
        return selected


# ============================================================================
# EXECUTION ENGINE
# ============================================================================

class ExecutionEngine:
    """Execute protocols and manage workflows"""
    
    def __init__(self, registry: ProtocolRegistry):
        self.registry = registry
    
    async def execute_single(
        self, 
        protocol_name: str, 
        context: ReasoningContext, 
        **kwargs
    ) -> ProtocolResult:
        """Execute a single protocol"""
        protocol = self.registry.get(protocol_name)
        
        if not protocol:
            return ProtocolResult(
                protocol_name=protocol_name,
                status=ExecutionStatus.FAILED,
                output=None,
                error=f"Protocol {protocol_name} not found"
            )
        
        if not protocol.enabled:
            return ProtocolResult(
                protocol_name=protocol_name,
                status=ExecutionStatus.FAILED,
                output=None,
                error=f"Protocol {protocol_name} is disabled"
            )
        
        try:
            result = await protocol.execute(context, **kwargs)
            context.history.append({
                "protocol": protocol_name,
                "result": result.output,
                "trace": result.reasoning_trace
            })
            return result
        except Exception as e:
            logger.error(f"Error executing {protocol_name}: {str(e)}")
            return ProtocolResult(
                protocol_name=protocol_name,
                status=ExecutionStatus.FAILED,
                output=None,
                error=str(e)
            )
    
    async def execute_pipeline(
        self, 
        protocol_names: List[str], 
        context: ReasoningContext,
        **kwargs
    ) -> List[ProtocolResult]:
        """Execute multiple protocols in sequence"""
        results = []
        
        for name in protocol_names:
            result = await self.execute_single(name, context, **kwargs)
            results.append(result)
            
            # Stop on failure if requested
            if kwargs.get('stop_on_failure', False) and result.status == ExecutionStatus.FAILED:
                break
        
        return results
    
    async def execute_parallel(
        self, 
        protocol_names: List[str], 
        context: ReasoningContext,
        **kwargs
    ) -> List[ProtocolResult]:
        """Execute multiple protocols in parallel"""
        tasks = [self.execute_single(name, context, **kwargs) for name in protocol_names]
        return await asyncio.gather(*tasks)


# ============================================================================
# UNIFIED BRAIN
# ============================================================================

class UnifiedBrain:
    """
    Main orchestrator – the "Brain" that integrates all protocols
    """
    
    def __init__(self):
        self.registry = ProtocolRegistry()
        self.router = IntelligentRouter(self.registry)
        self.engine = ExecutionEngine(self.registry)
        self.active_contexts: Dict[str, ReasoningContext] = {}
        logger.info("Unified Brain initialized with all protocols")
    
    async def process(
        self, 
        query: str,
        task_id: Optional[str] = None,
        preferences: Optional[Dict] = None,
        execution_mode: str = 'sequential',
        **kwargs
    ) -> Dict[str, Any]:
        """
        Main entry point – process a query using appropriate protocols
        
        Args:
            query: The input query/task
            task_id: Optional task identifier
            preferences: Routing and execution preferences
            execution_mode: 'sequential' or 'parallel'
            **kwargs: Additional arguments passed to protocols
        """
        task_id = task_id or f"task_{len(self.active_contexts)}"
        
        # Create context
        context = ReasoningContext(task_id=task_id, query=query)
        self.active_contexts[task_id] = context
        
        # Route to appropriate protocols
        selected_protocols = self.router.route(context, preferences)
        logger.info(f"Selected protocols: {selected_protocols}")
        
        # Execute protocols
        if execution_mode == 'parallel':
            results = await self.engine.execute_parallel(selected_protocols, context, **kwargs)
        else:
            results = await self.engine.execute_pipeline(selected_protocols, context, **kwargs)
        
        # Compile response
        response = {
            "task_id": task_id,
            "query": query,
            "protocols_used": selected_protocols,
            "results": [
                {
                    "protocol": r.protocol_name,
                    "status": r.status.value,
                    "output": r.output,
                    "trace": r.reasoning_trace
                }
                for r in results
            ],
            "context_history": context.history,
            "success": all(r.status == ExecutionStatus.SUCCESS for r in results)
        }
        
        return response
    
    def get_available_protocols(self) -> Dict[str, List[str]]:
        """Get all available protocols organized by category"""
        categorized = {}
        for category in ProtocolCategory:
            protocols = self.registry.list_by_category(category)
            categorized[category.value] = [p.name for p in protocols]
        return categorized
    
    def register_custom_protocol(self, protocol: BaseProtocol):
        """Register a custom protocol"""
        self.registry.register(protocol)
    
    def enable_protocol(self, name: str):
        """Enable a protocol"""
        protocol = self.registry.get(name)
        if protocol:
            protocol.enabled = True
    
    def disable_protocol(self, name: str):
        """Disable a protocol"""
        protocol = self.registry.get(name)
        if protocol:
            protocol.enabled = False