from sentence_transformers import SentenceTransformer
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

class ModelSingleton:
    _instance = None
    _initialized = False

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
        return cls._instance

    def __init__(self):
        if not self._initialized:
            # Sentence transformer model
            SENTENCE_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
            self.similarity_tokenizer = AutoTokenizer.from_pretrained(SENTENCE_MODEL)
            self.similarity_model = SentenceTransformer(SENTENCE_MODEL)

            # Flan-T5-xl model only
            FLAN_MODEL = "google/flan-t5-xl"
            self.flan_tokenizer = AutoTokenizer.from_pretrained(FLAN_MODEL)
            self.flan_model = AutoModelForSeq2SeqLM.from_pretrained(FLAN_MODEL)
            
            self._initialized = True

# Create a global instance
models = ModelSingleton()