import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import joblib
import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

MINILM_PATH = "/home/office-7/Downloads/minilm_v2/models/minilm"
XLM_ROBERTA_PATH = "/home/office-7/Downloads/xlm_roberta_v2/models/xlm_roberta"
ML_MODEL_PATH = "/home/office-7/support-intelligence-backend/core/services/models/spam_detection_model.pkl"

try:
    logger.info("Loading MiniLM...")
    tokenizer1 = AutoTokenizer.from_pretrained(MINILM_PATH)
    model1 = AutoModelForSequenceClassification.from_pretrained(MINILM_PATH)
    logger.info("MiniLM loaded.")

    logger.info("Loading XLM-Roberta...")
    tokenizer2 = AutoTokenizer.from_pretrained(XLM_ROBERTA_PATH)
    model2 = AutoModelForSequenceClassification.from_pretrained(XLM_ROBERTA_PATH)
    logger.info("XLM-Roberta loaded.")

    logger.info("Loading ML Model...")
    ml_model = joblib.load(ML_MODEL_PATH)
    logger.info("ML Model loaded.")
except Exception as e:
    logger.error(f"Error: {e}")