chatbot_config.py

from dataclasses import dataclass
from pathlib import Path
from typing import Dict

@dataclass
class ChatbotConfig:
    """RetrievalChatbot Config"""
    max_context_token_limit: int = 512
    embedding_dim: int = 384  # Match Sentence Transformer dimension
    learning_rate: float = 0.0005
    min_text_length: int = 3
    max_context_turns: int = 20
    pretrained_model: str = 'sentence-transformers/all-MiniLM-L6-v2'
    cross_encoder_model: str = 'cross-encoder/ms-marco-MiniLM-L-12-v2'
    summarizer_model: str = 't5-small'
    embedding_batch_size: int = 64
    search_batch_size: int = 64
    max_batch_size: int = 64
    max_retries: int = 3

    def to_dict(self) -> Dict:
        """Convert config to dictionary."""
        return {k: (str(v) if isinstance(v, Path) else v) 
                for k, v in self.__dict__.items()}

    @classmethod
    def from_dict(cls, config_dict: Dict) -> 'ChatbotConfig':
        """Create config from dictionary."""
        return cls(**{k: v for k, v in config_dict.items() 
                     if k in cls.__dataclass_fields__})