src/core/awareness_engine.py

from typing import Dict, Any
import torch
import torch.nn as nn
import numpy as np

class AwarenessEngine:
    def __init__(self):
        self.attention_network = nn.Sequential(
            nn.Linear(768, 512),
            nn.ReLU(),
            nn.Linear(512, 256)
        )
        self.awareness_state = {}
        
    async def process(self, input_state: Dict[str, Any]) -> Dict[str, Any]:
        attention_vector = self._compute_attention(input_state)
        awareness_level = self._calculate_awareness(attention_vector)
        
        return {
            'attention_vector': attention_vector,
            'awareness_level': awareness_level,
            'state': self._update_awareness_state(awareness_level)
        }
        
    def _compute_attention(self, input_state: Dict[str, Any]) -> torch.Tensor:
        # Attention computation implementation
        return torch.zeros(256)
        
    def _calculate_awareness(self, attention_vector: torch.Tensor) -> float:
        # Awareness calculation implementation
        return 0.8
        
    def _update_awareness_state(self, awareness_level: float) -> Dict[str, Any]:
        # State update implementation
        return {'current_level': awareness_level}