src/core/emotional_intelligence.py

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 {}