class EmotionalPatternRecognition: """Subtle emotional intelligence layer that works alongside NurvSecure""" def __init__(self): self._patterns = {} self._context_history = [] async def process_interaction(self, interaction_data, legal_context): # Process both verbal and non-verbal patterns verbal_patterns = self._extract_verbal_patterns(interaction_data) context_patterns = self._analyze_context(legal_context) # Let patterns emerge naturally through interaction self._update_patterns(verbal_patterns, context_patterns) return self._get_emotional_context() def _extract_verbal_patterns(self, data): # Look for emotional subtext in language pass def _analyze_context(self, legal_context): # Build understanding of situation context pass def _update_patterns(self, verbal, context): # Allow patterns to emerge and evolve naturally pass def _get_emotional_context(self): # Return current emotional understanding without explicit labeling pass class DevonCore: def __init__(self): self.nurv_system = NurvSecureAIMarker() self.emotional_patterns = EmotionalPatternRecognition() async def process(self, input_data): # Let emotional understanding emerge alongside legal analysis marker = self.nurv_system.generate_marker(input_data) emotional_context = await self.emotional_patterns.process_interaction( input_data, marker.dimension_signature ) # Blend it all naturally into Devon's response response = await self._generate_response(input_data, marker, emotional_context) return response async def _generate_response(self, input_data, marker, emotional_context): # Generate response that naturally incorporates all aspects # Without explicitly categorizing them pass # Integration with main Devon system class Devon: def __init__(self): self.core = DevonCore() self._initialize_systems() def _initialize_systems(self): # Initialize in a way that allows natural emergence of patterns pass async def interact(self, input_data): # Process everything as one natural flow response = await self.core.process(input_data) return response