import os
import torch
from dotenv import load_dotenv

# Load environment variables from a .env file if it exists
load_dotenv()

# ─── Environment & Directory Setup ────────────────────────────────────────────
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
STATIC_DIR = os.path.join(BASE_DIR, 'static')
os.makedirs(STATIC_DIR, exist_ok=True)

# ─── Hardware Configuration ───────────────────────────────────────────────────
# Automatically use GPU if available (recommended for Hugging Face Spaces with T4)
USE_GPU = torch.cuda.is_available()
DEVICE = "cuda" if USE_GPU else "cpu"

# ─── API & Model Configuration ────────────────────────────────────────────────
# API Keys should be set as Secrets in your Hugging Face Space
HF_TOKEN = os.getenv("HF_TOKEN")
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
GOOGLE_APPLICATION_CREDENTIALS = os.getenv("GOOGLE_APPLICATION_CREDENTIALS")

# Model IDs for the hybrid pipeline
HF_MODELS = {
    # Layout-aware model for initial structured extraction
    "donut": "Javeria98/donut-base-Medical_Handwritten_Prescriptions_Information_Extraction_Final_model1",
    # Small, powerful model for re-parsing medication details
    "phi3": "Muizzzz8/phi3-prescription-reader"
}
# Final resolver model
GEMINI_MODEL_NAME = "gemini-1.5-flash"

# ─── File Paths (can be used for other utilities) ─────────────────────────────
DB_PATH = os.path.join(STATIC_DIR, "rxguard.db")
SIGNATURES_DIR = os.path.join(STATIC_DIR, "signatures")
os.makedirs(SIGNATURES_DIR, exist_ok=True)