# -*- coding: utf-8 -*-
"""HybriKo Configuration - Hugging Face Compatible"""

from transformers import PretrainedConfig


class HybriKoConfig(PretrainedConfig):
    """Configuration for HybriKo model.
    
    HybriKo is a hybrid RNN-Attention language model optimized for Korean.
    Uses a 2:1 ratio of RNN (Griffin) blocks to Attention blocks.

    Attributes:
        d_model: Hidden dimension size
        n_layers: Number of transformer layers
        vocab_size: Vocabulary size
        n_heads: Number of attention heads
        n_kv_heads: Number of key-value heads (for GQA)
        ff_mult: Feed-forward multiplier
        max_seq_len: Maximum sequence length
    """
    
    model_type = "hybridko"

    def __init__(
        self,
        d_model: int = 768,
        n_layers: int = 12,
        vocab_size: int = 32000,
        n_heads: int = 12,
        n_kv_heads: int = 3,
        ff_mult: int = 3,
        max_seq_len: int = 512,
        bos_token_id: int = 2,
        eos_token_id: int = 3,
        pad_token_id: int = 0,
        **kwargs
    ):
        super().__init__(
            bos_token_id=bos_token_id,
            eos_token_id=eos_token_id,
            pad_token_id=pad_token_id,
            **kwargs
        )
        self.d_model = d_model
        self.n_layers = n_layers
        self.vocab_size = vocab_size
        self.n_heads = n_heads
        self.n_kv_heads = n_kv_heads
        self.ff_mult = ff_mult
        self.max_seq_len = max_seq_len