Fix imports in emotional_intelligence.py

src/core/emotional_intelligence.py

@@ -1,31 +1,23 @@
-import torch
-import numpy as np
+from typing import Dict, Any, List
 from dataclasses import dataclass
-from typing import Dict, List, Optional
 
 @dataclass
 class EmotionalState:
-    vector: torch.Tensor  # 128-dimensional emotional state
-    intensity: float
-    valence: float
-    arousal: float
-    dominance: float
+    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 = EmotionalMemory()
-        self.state_analyzer = EmotionalStateAnalyzer()
-        self.response_generator = EmotionalResponseGenerator()
+        self.emotional_memory = {}
+        self.emotion_vectors = self._initialize_emotion_vectors()
         
     def process_emotional_context(self, input_data: Dict[str, Any]) -> EmotionalState:
-        context_vector = self._extract_emotional_context(input_data)
-        current_state = self.state_analyzer.analyze(context_vector)
-        self.emotional_memory.update(current_state)
-        return self._generate_emotional_response(current_state)
-        
-    def _extract_emotional_context(self, input_data: Dict[str, Any]) -> torch.Tensor:
-        return torch.cat([
-            self._process_linguistic_affect(input_data.get('text')),
-            self._process_social_context(input_data.get('social')),
-            self._process_environmental_factors(input_data.get('environment'))
-        ])
+        # Process emotional context implementation
+        pass
+
+    def _initialize_emotion_vectors(self) -> Dict[str, List[float]]:
+        # Initialize emotion vectors implementation
+        pass