src/council/experts.py

import torch
import torch.nn as nn
from .base_expert import BaseExpert

class Asmoday(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "code", "python_development")
        self.code_bias = nn.Parameter(torch.ones(1) * 0.5)

class Istaroth(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "systems", "os_networking")

class Ronova(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "reasoning", "math_logic")
        self.logic_bias = nn.Parameter(torch.ones(1) * 0.3)

class Naberius(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "memory", "retrieval")
        self.memory_gate = nn.Linear(dim, 1)

class Phanes(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "creation", "writing")
        self.creative_temp = nn.Parameter(torch.ones(1) * 1.2)

class Barbeloth(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "analysis", "data_patterns")

class Tacet(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "silence", "filtering")
        self.noise_gate = nn.Linear(dim, 1)

class Abby(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "empathy", "user_context")
        self.empathy_bias = nn.Parameter(torch.ones(1) * 0.2)

class Reindoter(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "validation", "testing")

class Zestial(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "vision", "visualization")

class Alice(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "exploration", "novelty")
        self.exploration_temp = nn.Parameter(torch.ones(1) * 1.5)

class Rover(BaseExpert):
    def __init__(self, dim: int, expert_dim: int):
        super().__init__(dim, expert_dim, "execution", "terminal")

EXPERT_REGISTRY = {
    "Asmoday": Asmoday,
    "Istaroth": Istaroth,
    "Ronova": Ronova,
    "Naberius": Naberius,
    "Phanes": Phanes,
    "Barbeloth": Barbeloth,
    "Tacet": Tacet,
    "Abby": Abby,
    "Reindoter": Reindoter,
    "Zestial": Zestial,
    "Alice": Alice,
    "Rover": Rover,
}