import os
from huggingface_hub import login
from transformers import AutoTokenizer, AutoModelForCausalLM

hf_token = os.getenv('HF_TOKEN')
if hf_token:
    login(token=hf_token)

cache_dir = '/app/hf_cache'
model_name = 'google/gemma-3-1b-it'

# Construct the expected cache path
expected_cache_path = os.path.join(cache_dir, 'transformers', model_name.replace('/', '--'))

# Check and download model and tokenizer
if not os.path.exists(expected_cache_path):
    print(f'Downloading model and tokenizer: {model_name}...')
    tokenizer = AutoTokenizer.from_pretrained(model_name, cache_dir=cache_dir)
    tokenizer.pad_token = tokenizer.eos_token
    model = AutoModelForCausalLM.from_pretrained(model_name, cache_dir=cache_dir)
    model.config.pad_token_id = tokenizer.eos_token_id
else:
    print(f'Model and tokenizer ({model_name}) already cached. Skipping download.')