created backend/database.py

backend/database.py

@@ -0,0 +1,65 @@
+import os
+import cloudinary
+import cloudinary.uploader
+import cloudinary.api
+from motor.motor.asyncio import AsyncIOMotorClient
+from dotenv import load_dotenv
+import logging
+
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logging.info('Environment variables loaded successfully.')
+
+# MongoDB configuration
+MONGODB_URI = os.getenv('MONGODB_URI')
+DB_NAME = os.getenv('DATABASE_NAME')
+
+# Cloudinary Configuration
+cloudinary.config(
+    cloud_name=os.getenv('CLOUDINARY_CLOUD_NAME'),
+    api_key=os.getenv('CLOUDINARY_API_KEY'),
+    api_secret=os.getenv('CLOUDINARY_API_SECRET'),
+    secure=True
+)
+
+def upload_image_to_cloud(file_byte: bytes, folder_name: str='xrays') -> str:
+    """
+    Uploads an image to Cloudinary and returns the URL of the uploaded image.
+
+    Args:
+        file_byte (bytes): The byte content of the image to be uploaded.
+        folder_name (str): The folder in Cloudinary where the image will be stored.
+
+    Returns:
+        str: The URL of the uploaded image.
+        
+    Raises:
+        Exception: If there is an error during the upload process.
+        
+    """
+    try:
+        logging.info('Uploading image to Cloudinary...')
+        response = cloudinary.uploader.upload(file_byte,
+                                        folder=f'precision_diagnostics/{folder_name}')
+        logging.info('Image uploaded successfully.')
+        return response.get('secure_url')
+    except Exception as e:
+        logging.error(f'Error uploading image: {e}')
+        raise e
+    
+    
+    
+# Initialize MongoDB client
+try:
+    client = AsyncIOMotorClient(MONGODB_URI)
+    db = client[DB_NAME]
+    logging.info('Connected to MongoDB successfully.')
+except Exception as e:
+    logging.error(f'Error connecting to MongoDB: {e}')
+    raise e
+
+diagnostic_records = db['records']