from transformers import AutoTokenizer
import logging
import os

# Configure logging
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')

def get_tokenizer(id):
    logging.debug(f"Loading tokenizer: {id}")
    try:
        tokenizer = AutoTokenizer.from_pretrained(id, trust_remote_code=True, token=os.getenv("HF_TOKEN"))
        logging.debug(f"Tokenizer loaded: {tokenizer}")
        return tokenizer
    except Exception as e:
        logging.error(f"Error loading tokenizer {id}: {e}")
        raise e

def get_tokenization(tokenizer, text):
    logging.debug(f"Tokenizing text: {text}")
    ids = tokenizer.encode(text)
    string_tokens = tokenizer.convert_ids_to_tokens(ids)
    logging.debug(f"Tokens: {string_tokens}")
    return string_tokens

def get_vocab_size(tokenizer):
    logging.debug(f"Getting vocabulary size for tokenizer: {tokenizer}")
    vocab_size = len(tokenizer.get_vocab())
    logging.debug(f"Vocabulary size: {vocab_size}")
    return vocab_size

def check_latin_support(tokenizer):
    logging.debug(f"Checking Latin support for tokenizer: {tokenizer}")
    try:
        test_text = "This is a test with latin characters 1234567890."
        tokens = tokenizer.tokenize(test_text)
        # If the tokenizer can tokenize the latin text without returning unknown tokens, we consider it as supporting latin
        if all(token != tokenizer.unk_token for token in tokens):
            logging.debug(f"Latin support: ✅")
            return "✅"
        else:
            logging.debug(f"Latin support: ❌")
            return "❌"
    except Exception as e:
        logging.error(f"Error checking latin support: {e}")
        return "❌"