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"""
Cyber-LLM Learning Module
This module implements advanced learning capabilities for continuous intelligence
and evolution of the Cyber-LLM system.
Components:
- online_learning: Real-time learning from operational feedback
- federated_learning: Secure multi-organization collaborative learning
- meta_learning: Rapid adaptation to new threats and attack patterns
- research_collaboration: Framework for sharing cybersecurity insights
- constitutional_ai: Ethical constraints and safety guardrails
- continuous_intelligence: Orchestration of all learning components
Author: Muzan Sano <[email protected]>
"""
from .online_learning import (
OnlineLearningManager,
LearningEvent,
LearningEventType,
ThreatIntelligenceProcessor,
create_online_learning_manager
)
from .federated_learning import (
FederatedLearningCoordinator,
FederatedLearningParticipant,
FederatedLearningRound,
SecureCommunicationManager,
ModelAggregator,
create_federated_learning_coordinator
)
from .meta_learning import (
MetaLearningManager,
MetaLearningStrategy,
MetaTask,
TaskType,
CyberSecurityTaskGenerator,
create_meta_learning_manager
)
from .research_collaboration import (
ResearchCollaborationManager,
CollaborationType,
ResearchInsight,
CollaborationParticipant,
CollaborationProject,
ParticipantRole,
SensitivityLevel,
create_research_collaboration_manager
)
from .constitutional_ai import (
ConstitutionalAIManager,
EthicalPrinciple,
ViolationType,
ActionType,
ConstitutionalRule,
ConstitutionalViolation,
create_constitutional_ai_manager
)
from .continuous_intelligence import (
ContinuousIntelligenceOrchestrator,
ContinuousIntelligenceConfig,
ContinuousIntelligenceMode,
create_continuous_intelligence_config,
create_continuous_intelligence_orchestrator
)
__all__ = [
# Online Learning
'OnlineLearningManager',
'LearningEvent',
'LearningEventType',
'ThreatIntelligenceProcessor',
'create_online_learning_manager',
# Federated Learning
'FederatedLearningCoordinator',
'FederatedLearningParticipant',
'FederatedLearningRound',
'SecureCommunicationManager',
'ModelAggregator',
'create_federated_learning_coordinator',
# Meta Learning
'MetaLearningManager',
'MetaLearningStrategy',
'MetaTask',
'TaskType',
'CyberSecurityTaskGenerator',
'create_meta_learning_manager',
# Research Collaboration
'ResearchCollaborationManager',
'CollaborationType',
'ResearchInsight',
'CollaborationParticipant',
'CollaborationProject',
'ParticipantRole',
'SensitivityLevel',
'create_research_collaboration_manager',
# Constitutional AI
'ConstitutionalAIManager',
'EthicalPrinciple',
'ViolationType',
'ActionType',
'ConstitutionalRule',
'ConstitutionalViolation',
'create_constitutional_ai_manager',
# Continuous Intelligence
'ContinuousIntelligenceOrchestrator',
'ContinuousIntelligenceConfig',
'ContinuousIntelligenceMode',
'create_continuous_intelligence_config',
'create_continuous_intelligence_orchestrator'
]
# Module metadata
__version__ = "1.0.0"
__author__ = "Muzan Sano <[email protected]>"
__description__ = "Advanced learning and adaptation capabilities for Cyber-LLM"
# Convenience functions for common use cases
def create_full_continuous_intelligence_system(model,
tokenizer,
organization_name: str = "CyberLLM-Default",
mode: ContinuousIntelligenceMode = ContinuousIntelligenceMode.BALANCED):
"""
Create a complete continuous intelligence system with all components enabled.
Args:
model: The language model to enhance with continuous intelligence
tokenizer: Tokenizer for the model
organization_name: Name of the organization using the system
mode: Operating mode for the continuous intelligence system
Returns:
ContinuousIntelligenceOrchestrator: Fully configured orchestrator
"""
config = create_continuous_intelligence_config(
mode=mode,
organization_name=organization_name,
enable_online_learning=True,
enable_federated_learning=True,
enable_meta_learning=True,
enable_research_collaboration=True,
enable_constitutional_ai=True
)
return create_continuous_intelligence_orchestrator(model, tokenizer, config)
def create_research_focused_system(model,
tokenizer,
organization_name: str):
"""
Create a research-focused continuous intelligence system optimized for
collaborative research and knowledge sharing.
Args:
model: The language model
tokenizer: Tokenizer for the model
organization_name: Name of the research organization
Returns:
ContinuousIntelligenceOrchestrator: Research-optimized orchestrator
"""
return create_full_continuous_intelligence_system(
model=model,
tokenizer=tokenizer,
organization_name=organization_name,
mode=ContinuousIntelligenceMode.RESEARCH
)
def create_production_system(model,
tokenizer,
organization_name: str):
"""
Create a production-ready continuous intelligence system with conservative
settings optimized for stability and safety.
Args:
model: The language model
tokenizer: Tokenizer for the model
organization_name: Name of the organization
Returns:
ContinuousIntelligenceOrchestrator: Production-optimized orchestrator
"""
return create_full_continuous_intelligence_system(
model=model,
tokenizer=tokenizer,
organization_name=organization_name,
mode=ContinuousIntelligenceMode.PRODUCTION
)
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