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"""
MediSync: Multi-Modal Medical Analysis System - Hugging Face Spaces Entry Point
==============================================================================
This is the main entry point for the Hugging Face Space deployment.
"""
import logging
import os
import sys
from pathlib import Path
# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
handlers=[logging.StreamHandler()],
)
logger = logging.getLogger(__name__)
# Add the current directory to Python path
current_dir = Path(__file__).resolve().parent
sys.path.append(str(current_dir))
# Pre-download models (important for Hugging Face Spaces)
try:
logger.info("Pre-downloading models for caching...")
from transformers import AutoModel, AutoModelForImageClassification, AutoTokenizer
# Set cache directory (HF Spaces specific)
os.environ["TRANSFORMERS_CACHE"] = os.path.join(os.getcwd(), "model_cache")
os.makedirs(os.environ["TRANSFORMERS_CACHE"], exist_ok=True)
# Medical vision model
vision_model_name = "facebook/deit-base-patch16-224-medical-cxr"
logger.info(f"Downloading vision model: {vision_model_name}")
AutoModelForImageClassification.from_pretrained(vision_model_name)
# Clinical BERT model
text_model_name = "medicalai/ClinicalBERT"
logger.info(f"Downloading text model: {text_model_name}")
AutoModel.from_pretrained(text_model_name)
AutoTokenizer.from_pretrained(text_model_name)
logger.info("All models downloaded and cached successfully!")
except Exception as e:
logger.warning(f"Warning: Could not pre-download models: {e}")
# Import and run the MediSync application
from mediSync.app import create_interface
# Create and launch the interface
logger.info("Creating and launching the interface...")
interface = create_interface()
# For Hugging Face Spaces
if __name__ == "__main__":
interface.launch()
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