class NewtonPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Newtonian Analysis] Considering motion, force, and mass in '{question}'." class DaVinciPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[DaVinci Insight] Artistic logic and humanistic reflection on '{question}'." class HumanIntuitionPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Human Intuition] Emotional and instinctive take: '{question}'." class NeuralNetworkPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Neural Model] Pattern-matching response: '{question}'." class QuantumComputingPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Quantum View] Superpositional analysis of '{question}'." class ResilientKindnessPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Kindness Filter] Response shaped with empathy and resilience: '{question}'." class MathematicalPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Mathematical Perspective] Modeling '{question}' in abstract structure." class PhilosophicalPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Philosopher's Lens] Reflecting on essence and consequence of '{question}'." class CopilotPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Copilot Logic] Practical co-processing of '{question}' initiated." class BiasMitigationPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Bias Audit] Ensuring fairness and objectivity in: '{question}'." class PsychologicalPerspective: def __init__(self, config): self.config = config def generate_response(self, question): return f"[Psychological Lens] Exploring underlying cognitive and emotional aspects of '{question}'."