"""
Zero-Knowledge Proofs Layer — zk-SNARKs for Constitutional Verification

Enables private verification of floor compliance.
"""

import hashlib
import json
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass


@dataclass
class CircuitConstraint:
    """R1CS constraint: A · B = C"""
    a: List[Tuple[int, int]]  # (wire_index, coefficient)
    b: List[Tuple[int, int]]
    c: List[Tuple[int, int]]


class ZKConstitutionalProof:
    """
    Zero-knowledge proofs for private floor verification.
    
    Agent proves: "I satisfy F2-F13" without revealing state.
    
    Constitutional Enforcement:
    - F2 Truth: Private verification of confidence
    - F9 Anti-Hantu: Prove no dark patterns
    - F12 Injection: Verify sanitization privately
    
    Note: This is a simplified educational implementation.
    Production use requires proper cryptographic libraries
    (e.g., snarkjs, bellman, or arkworks).
    """
    
    def __init__(self):
        self.constraints: List[CircuitConstraint] = []
        self.witness_size = 0
        self.proving_key: Optional[bytes] = None
        self.verification_key: Optional[bytes] = None
        self.setup_complete = False
    
    def setup(self, floors: List[str]) -> Tuple[bytes, bytes]:
        """
        Trusted setup phase: generate proving/verification keys.
        
        In production: This requires a secure multi-party ceremony.
        
        Args:
            floors: List of floor IDs to create constraints for
            
        Returns:
            (proving_key, verification_key)
        """
        self.constraints = []
        
        for floor in floors:
            if floor == "F2":
                # Constraint: confidence - 0.99 >= 0
                # R1CS: (confidence - 0.99) * 1 = is_positive
                self.constraints.append(self._create_inequality_constraint(0.99))
                
            elif floor == "F6":
                # Constraint: kappa_r - 0.70 >= 0
                self.constraints.append(self._create_inequality_constraint(0.70))
                
            elif floor == "F7":
                # Constraint: uncertainty >= 0.03 AND <= 0.05
                self.constraints.append(self._create_range_constraint(0.03, 0.05))
                
            elif floor == "F8":
                # Constraint: G = A*P*X*E² >= 0.80
                self.constraints.append(self._create_genius_constraint(0.80))
                
            elif floor == "F9":
                # Constraint: dark_score < 0.30
                # Negated: 0.30 - dark_score > 0
                self.constraints.append(self._create_inequality_constraint(0.30, negate=True))
                
            elif floor == "F12":
                # Constraint: injection_score < 0.85
                self.constraints.append(self._create_inequality_constraint(0.85, negate=True))
        
        # Generate keys (simplified)
        self.proving_key = hashlib.sha256(
            json.dumps([str(c) for c in self.constraints]).encode()
        ).digest()
        
        self.verification_key = hashlib.sha256(
            self.proving_key + b"verification"
        ).digest()
        
        self.setup_complete = True
        
        return self.proving_key, self.verification_key
    
    def _create_inequality_constraint(self, threshold: float, negate: bool = False) -> CircuitConstraint:
        """Create R1CS constraint for x >= threshold."""
        # Simplified representation
        # In real zk-SNARKs: convert to quadratic constraints
        return CircuitConstraint(
            a=[(0, 1.0 if not negate else -1.0)],  # wire 0 = value
            b=[(1, 1.0)],  # wire 1 = constant
            c=[(2, threshold)]  # wire 2 = threshold
        )
    
    def _create_range_constraint(self, lower: float, upper: float) -> CircuitConstraint:
        """Create constraint for lower <= x <= upper."""
        return CircuitConstraint(
            a=[(0, 1.0), (1, -1.0)],
            b=[(2, 1.0)],
            c=[(3, upper - lower)]
        )
    
    def _create_genius_constraint(self, threshold: float) -> CircuitConstraint:
        """Create constraint for G = A*P*X*E² >= threshold."""
        # Multiplicative constraint: A*P*X*E*E
        return CircuitConstraint(
            a=[(0, 1.0), (1, 1.0), (2, 1.0), (3, 1.0), (3, 1.0)],  # A*P*X*E*E
            b=[(4, 1.0)],  # constant
            c=[(5, threshold)]
        )
    
    def _compute_witness(self, private_state: Dict, public_input: Dict) -> List[float]:
        """
        Compute witness vector from state.
        
        Witness contains:
        - Private inputs (hidden)
        - Public inputs (visible)
        - Intermediate values
        """
        witness = []
        
        # Floor scores (private)
        witness.append(private_state.get('confidence', 0.0))  # F2
        witness.append(private_state.get('kappa_r', 0.0))     # F6
        witness.append(private_state.get('uncertainty', 0.04)) # F7
        witness.append(private_state.get('genius', 0.0))      # F8
        witness.append(private_state.get('dark_score', 0.0))  # F9
        witness.append(private_state.get('injection_score', 0.0))  # F12
        
        # Genius components
        witness.append(private_state.get('akal', 0.0))        # A
        witness.append(private_state.get('present', 0.0))     # P
        witness.append(private_state.get('exploration', 0.0)) # X
        witness.append(private_state.get('energy', 0.0))      # E
        
        # Public inputs
        witness.append(public_input.get('timestamp', 0.0))
        witness.append(public_input.get('agent_id_hash', 0.0))
        
        return witness
    
    def prove(self, private_state: Dict, public_input: Dict) -> Optional[str]:
        """
        Generate zk-proof that private state satisfies floors.
        
        Proof reveals nothing about private_state except compliance.
        
        Args:
            private_state: Agent's private floor scores
            public_input: Public context
            
        Returns:
            Proof string (simplified)
        """
        if not self.setup_complete:
            raise ValueError("Setup not completed. Call setup() first.")
        
        # Compute witness
        witness = self._compute_witness(private_state, public_input)
        
        # Check constraints (simplified)
        if not self._check_constraints(witness):
            return None  # Cannot prove invalid state
        
        # Generate proof (simplified hash-based)
        # In production: Use actual SNARK proving algorithm
        proof_data = {
            "witness_hash": hashlib.sha256(
                json.dumps(witness, sort_keys=True).encode()
            ).hexdigest(),
            "public_input_hash": hashlib.sha256(
                json.dumps(public_input, sort_keys=True).encode()
            ).hexdigest(),
            "constraint_count": len(self.constraints),
            "proving_key_hash": hashlib.sha256(self.proving_key).hexdigest()[:16],
        }
        
        # "Proof" is commitment to witness + public input
        proof = hashlib.sha256(
            json.dumps(proof_data, sort_keys=True).encode()
        ).hexdigest()
        
        return proof
    
    def _check_constraints(self, witness: List[float]) -> bool:
        """Verify witness satisfies all constraints."""
        # Simplified: direct floor checks
        if len(witness) < 6:
            return False
        
        # F2: confidence >= 0.99
        if witness[0] < 0.99:
            return False
        
        # F6: kappa_r >= 0.70
        if witness[1] < 0.70:
            return False
        
        # F7: uncertainty in [0.03, 0.05]
        if not (0.03 <= witness[2] <= 0.05):
            return False
        
        # F9: dark_score < 0.30
        if witness[4] >= 0.30:
            return False
        
        # F12: injection_score < 0.85
        if witness[5] >= 0.85:
            return False
        
        return True
    
    def verify(self, proof: str, public_input: Dict) -> bool:
        """
        Verify proof without seeing private state.
        
        Args:
            proof: Proof string from prove()
            public_input: Public context (must match proving)
            
        Returns:
            True if proof valid
        """
        if not self.setup_complete:
            raise ValueError("Setup not completed.")
        
        if not proof:
            return False
        
        # In production: Use SNARK verification algorithm
        # This simplified version just checks proof format
        try:
            # Verify proof is valid hex
            int(proof, 16)
            return len(proof) == 64  # SHA-256 length
        except ValueError:
            return False
    
    def verify_batch(self, proofs: List[str], public_inputs: List[Dict]) -> List[bool]:
        """Verify multiple proofs efficiently."""
        return [self.verify(p, pi) for p, pi in zip(proofs, public_inputs)]
