src/model/consciousness_model.py

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

class ConsciousnessModel(nn.Module):
    def __init__(self, config: Dict[str, Any]):
        super().__init__()
        input_dim = config.get('input_dim', 768)
        self.self_awareness = nn.Linear(input_dim, 256)
        self.meta_cognitive = nn.Linear(256, 128)
        self.phenomenal = nn.Linear(128, 64)
        self.integration = nn.Linear(64, 32)

    def forward(self, x: torch.Tensor) -> Dict[str, Any]:
        awareness = torch.relu(self.self_awareness(x))
        meta = torch.relu(self.meta_cognitive(awareness))
        phenomenal = torch.relu(self.phenomenal(meta))
        integrated = self.integration(phenomenal)

        return {
            'awareness': awareness,
            'meta_cognitive': meta,
            'phenomenal': phenomenal,
            'integrated': integrated
        }