import os

# Ensure CUDA 12 libraries are findable for faster-whisper/CTranslate2
_cuda12_path = "/usr/local/lib/ollama/cuda_v12"
if os.path.isdir(_cuda12_path):
    cur = os.environ.get("LD_LIBRARY_PATH", "")
    if _cuda12_path not in cur:
        os.environ["LD_LIBRARY_PATH"] = f"{_cuda12_path}:{cur}" if cur else _cuda12_path

# get_device comes from the stt package (already a dependency) rather than
# jebin_lib: importing jebin_lib pulls in hf_bucket_client, which imports
# huggingface_hub.sync_bucket - removed from huggingface_hub - so a single
# broken transitive import would take down server startup.
try:
    from jebin_lib.utils import get_device
except ImportError:
    from stt.common import get_device


class Config:
    PORT = int(os.environ.get('PORT', 7860))
    UPLOAD_FOLDER = 'uploads'
    TEMP_DIR = 'temp_dir'
    DATABASE_FILE = 'audio_captions.db'
    ALLOWED_EXTENSIONS = {'wav', 'mp3', 'flac', 'ogg', 'm4a', 'aac', 'mp4', 'mkv', 'avi', 'mov'}
    
    CWD = "./"
    PYTHON_PATH = "stt-transcribe"
    STT_MODEL_NAME = "parakeet"
    # Parakeet is English-only, so non-English audio and X->English translation
    # are routed to a whisper engine instead.
    STT_MULTILINGUAL_MODEL_NAME = os.environ.get('STT_MULTILINGUAL_MODEL', 'fasterwhispher')
    # faster-whisper checkpoint size used for those jobs; "base" translates
    # Hindi poorly, so default to something usable.
    STT_WHISPER_MODEL = os.environ.get('STT_WHISPER_MODEL', 'small')
    POLL_INTERVAL = 3

settings = Config()

os.makedirs(settings.UPLOAD_FOLDER, exist_ok=True)
os.makedirs(settings.TEMP_DIR, exist_ok=True)