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from typing import Dict, Any, List
from dataclasses import dataclass
import torch
import torch.nn as nn
import asyncio
@dataclass
class EmotionalState:
valence: float # Positive/negative dimension
arousal: float # Energy/activation level
dominance: float # Control/power dimension
emotions: List[str] # Primary emotions present
intensity: Dict[str, float] # Intensity of each emotion
class EmotionalProcessor:
def __init__(self):
self.emotional_memory = {}
self.emotion_vectors = self._initialize_emotion_vectors()
def process_emotional_context(self, input_data: Dict[str, Any]) -> EmotionalState:
# Process emotional context implementation
# Returning a default emotional state to fix the return type error
return EmotionalState(
valence=0.0,
arousal=0.0,
dominance=0.0,
emotions=[],
intensity={}
)
def _initialize_emotion_vectors(self) -> Dict[str, List[float]]:
# Initialize emotion vectors implementation
# Returning an empty dictionary to fix the return type error
return {}
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