# shared_resources.py
import torch
# from transformers import AutoTokenizer, AutoModelForCausalLM
from sentence_transformers import SentenceTransformer
from datasets import load_dataset
# from transformers import AutoProcessor, MusicgenForConditionalGeneration
import re

class SharedResources:
    def __init__(self):
        # Set the device
        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")


        # Load SentenceTransformer
        self.sentence_transformer = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1")

        # Load the dataset
        self.dataset = load_dataset("subashdvorak/tiktok-story-data3", revision="embedded")
        self.data = self.dataset["train"]
        self.data = self.data.add_faiss_index("embeddings")

# Create a single instance of SharedResources
shared_resources = SharedResources()