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"""
AgentAI Integration Module for InklyAI
Provides seamless integration between InklyAI signature verification and AgentAI systems.
"""
import asyncio
import logging
from typing import Dict, List, Optional, Union, Any
from dataclasses import dataclass
from datetime import datetime
import json
import hashlib
import base64
from src.models.siamese_network import SignatureVerifier
from src.data.preprocessing import SignaturePreprocessor
@dataclass
class AgentSignature:
"""Represents a signature associated with an AI agent."""
agent_id: str
signature_template: str # Path to signature template
created_at: datetime
last_verified: Optional[datetime] = None
verification_count: int = 0
is_active: bool = True
@dataclass
class VerificationResult:
"""Result of signature verification."""
is_verified: bool
similarity_score: float
confidence: float
agent_id: str
timestamp: datetime
verification_id: str
class AgentAISignatureManager:
"""
Manages signature verification for AgentAI systems.
"""
def __init__(self,
model_path: Optional[str] = None,
threshold: float = 0.75,
device: str = 'auto'):
"""
Initialize the AgentAI signature manager.
Args:
model_path: Path to trained model
threshold: Verification threshold
device: Device to run inference on
"""
self.verifier = SignatureVerifier(
model_path=model_path,
device=device
)
self.threshold = threshold
self.preprocessor = SignaturePreprocessor()
# Agent signature registry
self.agent_signatures: Dict[str, AgentSignature] = {}
# Verification history
self.verification_history: List[VerificationResult] = []
# Configuration
self.config = {
'max_verification_attempts': 3,
'signature_timeout': 300, # seconds
'enable_audit_logging': True,
'encrypt_signatures': True
}
# Setup logging
self.logger = logging.getLogger('AgentAISignatureManager')
self.logger.setLevel(logging.INFO)
if not self.logger.handlers:
handler = logging.StreamHandler()
formatter = logging.Formatter(
'%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
handler.setFormatter(formatter)
self.logger.addHandler(handler)
def register_agent_signature(self,
agent_id: str,
signature_template_path: str) -> bool:
"""
Register a signature template for an AI agent.
Args:
agent_id: Unique identifier for the agent
signature_template_path: Path to signature template image
Returns:
True if registration successful, False otherwise
"""
try:
# Validate signature template
if not self._validate_signature_template(signature_template_path):
self.logger.error(f"Invalid signature template for agent {agent_id}")
return False
# Create agent signature record
agent_signature = AgentSignature(
agent_id=agent_id,
signature_template=signature_template_path,
created_at=datetime.now(),
is_active=True
)
# Store in registry
self.agent_signatures[agent_id] = agent_signature
self.logger.info(f"Registered signature for agent {agent_id}")
return True
except Exception as e:
self.logger.error(f"Failed to register signature for agent {agent_id}: {e}")
return False
def verify_agent_signature(self,
agent_id: str,
signature_image: Union[str, bytes],
context: Optional[Dict[str, Any]] = None) -> VerificationResult:
"""
Verify a signature for a specific agent.
Args:
agent_id: Agent identifier
signature_image: Signature image (path or bytes)
context: Additional context for verification
Returns:
VerificationResult object
"""
verification_id = self._generate_verification_id()
try:
# Check if agent is registered
if agent_id not in self.agent_signatures:
return VerificationResult(
is_verified=False,
similarity_score=0.0,
confidence=0.0,
agent_id=agent_id,
timestamp=datetime.now(),
verification_id=verification_id
)
agent_signature = self.agent_signatures[agent_id]
# Check if agent is active
if not agent_signature.is_active:
self.logger.warning(f"Agent {agent_id} is not active")
return VerificationResult(
is_verified=False,
similarity_score=0.0,
confidence=0.0,
agent_id=agent_id,
timestamp=datetime.now(),
verification_id=verification_id
)
# Perform signature verification
similarity, is_genuine = self.verifier.verify_signatures(
signature_image,
agent_signature.signature_template,
threshold=self.threshold
)
# Calculate confidence based on similarity and context
confidence = self._calculate_confidence(similarity, context)
# Create verification result
result = VerificationResult(
is_verified=is_genuine,
similarity_score=float(similarity),
confidence=confidence,
agent_id=agent_id,
timestamp=datetime.now(),
verification_id=verification_id
)
# Update agent signature record
agent_signature.last_verified = datetime.now()
agent_signature.verification_count += 1
# Log verification
if self.config['enable_audit_logging']:
self._log_verification(result, context)
# Store in history
self.verification_history.append(result)
return result
except Exception as e:
self.logger.error(f"Verification failed for agent {agent_id}: {e}")
return VerificationResult(
is_verified=False,
similarity_score=0.0,
confidence=0.0,
agent_id=agent_id,
timestamp=datetime.now(),
verification_id=verification_id
)
def batch_verify_agents(self,
verification_requests: List[Dict[str, Any]]) -> List[VerificationResult]:
"""
Verify signatures for multiple agents in batch.
Args:
verification_requests: List of verification requests
Returns:
List of verification results
"""
results = []
for request in verification_requests:
agent_id = request['agent_id']
signature_image = request['signature_image']
context = request.get('context', {})
result = self.verify_agent_signature(agent_id, signature_image, context)
results.append(result)
return results
def get_agent_verification_stats(self, agent_id: str) -> Dict[str, Any]:
"""
Get verification statistics for an agent.
Args:
agent_id: Agent identifier
Returns:
Dictionary with verification statistics
"""
if agent_id not in self.agent_signatures:
return {}
agent_history = [
result for result in self.verification_history
if result.agent_id == agent_id
]
if not agent_history:
return {
'total_verifications': 0,
'successful_verifications': 0,
'success_rate': 0.0,
'average_similarity': 0.0,
'last_verification': None
}
successful = sum(1 for result in agent_history if result.is_verified)
total = len(agent_history)
avg_similarity = sum(result.similarity_score for result in agent_history) / total
return {
'total_verifications': total,
'successful_verifications': successful,
'success_rate': successful / total,
'average_similarity': avg_similarity,
'last_verification': agent_history[-1].timestamp.isoformat() if agent_history else None
}
def deactivate_agent(self, agent_id: str) -> bool:
"""
Deactivate an agent's signature verification.
Args:
agent_id: Agent identifier
Returns:
True if successful, False otherwise
"""
if agent_id in self.agent_signatures:
self.agent_signatures[agent_id].is_active = False
self.logger.info(f"Deactivated agent {agent_id}")
return True
return False
def reactivate_agent(self, agent_id: str) -> bool:
"""
Reactivate an agent's signature verification.
Args:
agent_id: Agent identifier
Returns:
True if successful, False otherwise
"""
if agent_id in self.agent_signatures:
self.agent_signatures[agent_id].is_active = True
self.logger.info(f"Reactivated agent {agent_id}")
return True
return False
def _validate_signature_template(self, template_path: str) -> bool:
"""Validate signature template file."""
try:
# Try to load and preprocess the template
self.preprocessor.preprocess_image(template_path)
return True
except Exception:
return False
def _calculate_confidence(self, similarity: float, context: Optional[Dict[str, Any]]) -> float:
"""Calculate confidence score based on similarity and context."""
base_confidence = similarity
# Adjust confidence based on context
if context:
# Higher confidence for recent signatures
if 'time_since_last_verification' in context:
time_factor = min(1.0, context['time_since_last_verification'] / 3600) # 1 hour
base_confidence *= (0.8 + 0.2 * time_factor)
# Lower confidence for suspicious patterns
if 'suspicious_activity' in context and context['suspicious_activity']:
base_confidence *= 0.5
return min(1.0, max(0.0, base_confidence))
def _generate_verification_id(self) -> str:
"""Generate unique verification ID."""
timestamp = datetime.now().isoformat()
hash_input = f"{timestamp}_{len(self.verification_history)}"
return hashlib.md5(hash_input.encode()).hexdigest()[:12]
def _log_verification(self, result: VerificationResult, context: Optional[Dict[str, Any]]):
"""Log verification result for audit purposes."""
log_entry = {
'verification_id': result.verification_id,
'agent_id': result.agent_id,
'is_verified': result.is_verified,
'similarity_score': result.similarity_score,
'confidence': result.confidence,
'timestamp': result.timestamp.isoformat(),
'context': context or {}
}
self.logger.info(f"Verification logged: {json.dumps(log_entry)}")
class AgentAISignatureAPI:
"""
REST API wrapper for AgentAI signature verification.
"""
def __init__(self, signature_manager: AgentAISignatureManager):
"""
Initialize the API wrapper.
Args:
signature_manager: AgentAISignatureManager instance
"""
self.signature_manager = signature_manager
self.logger = logging.getLogger('AgentAISignatureAPI')
def verify_signature_endpoint(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
"""
API endpoint for signature verification.
Args:
request_data: Request data containing agent_id and signature_image
Returns:
API response dictionary
"""
try:
agent_id = request_data['agent_id']
signature_image = request_data['signature_image']
context = request_data.get('context', {})
result = self.signature_manager.verify_agent_signature(
agent_id, signature_image, context
)
return {
'success': True,
'verification_id': result.verification_id,
'is_verified': result.is_verified,
'similarity_score': result.similarity_score,
'confidence': result.confidence,
'timestamp': result.timestamp.isoformat()
}
except Exception as e:
self.logger.error(f"API verification failed: {e}")
return {
'success': False,
'error': str(e),
'timestamp': datetime.now().isoformat()
}
def register_agent_endpoint(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
"""
API endpoint for agent registration.
Args:
request_data: Request data containing agent_id and signature_template
Returns:
API response dictionary
"""
try:
agent_id = request_data['agent_id']
signature_template = request_data['signature_template']
success = self.signature_manager.register_agent_signature(
agent_id, signature_template
)
return {
'success': success,
'agent_id': agent_id,
'timestamp': datetime.now().isoformat()
}
except Exception as e:
self.logger.error(f"API registration failed: {e}")
return {
'success': False,
'error': str(e),
'timestamp': datetime.now().isoformat()
}
def get_stats_endpoint(self, agent_id: str) -> Dict[str, Any]:
"""
API endpoint for agent statistics.
Args:
agent_id: Agent identifier
Returns:
API response dictionary
"""
try:
stats = self.signature_manager.get_agent_verification_stats(agent_id)
return {
'success': True,
'agent_id': agent_id,
'stats': stats,
'timestamp': datetime.now().isoformat()
}
except Exception as e:
self.logger.error(f"API stats failed: {e}")
return {
'success': False,
'error': str(e),
'timestamp': datetime.now().isoformat()
}
# Example usage and integration patterns
def create_agentai_integration_example():
"""Create an example AgentAI integration."""
# Initialize signature manager
signature_manager = AgentAISignatureManager(
threshold=0.75,
device='auto'
)
# Register some example agents
signature_manager.register_agent_signature(
'agent_001',
'data/samples/john_doe_1.png'
)
signature_manager.register_agent_signature(
'agent_002',
'data/samples/jane_smith_1.png'
)
# Create API wrapper
api = AgentAISignatureAPI(signature_manager)
return signature_manager, api
if __name__ == "__main__":
# Example usage
signature_manager, api = create_agentai_integration_example()
# Test verification
result = signature_manager.verify_agent_signature(
'agent_001',
'data/samples/john_doe_2.png'
)
print(f"Verification result: {result}")
# Get stats
stats = signature_manager.get_agent_verification_stats('agent_001')
print(f"Agent stats: {stats}")
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