import boto3
import os

# 1. Credentials (Ready to use from your screenshot)
ACCESS_KEY = "a9f685d13afd9a290e54dca612ef83d2"
SECRET_KEY = "8284c338275d0e6ebb3e6e697ba5999f6409908cb92c08fe8351da4af728c875"
ACCOUNT_ID = "659b46b7d1773d3742cd10b2c9194dd3"
BUCKET_NAME = "oil-spill-detection"

# 2. Path to your model file 
# Note: Ensure oil_spill_unet_best.keras is in this same folder!
FILE_PATH = "oil_spill_unet_best.keras" 

def upload():
    # Setup the Cloudflare R2 Client via S3 API
    s3 = boto3.client(
        service_name='s3',
        endpoint_url=f'https://{ACCOUNT_ID}.r2.cloudflarestorage.com',
        aws_access_key_id=ACCESS_KEY,
        aws_secret_access_key=SECRET_KEY,
        region_name='auto'
    )

    print(f"Starting high-speed API upload of {FILE_PATH}...")
    
    if not os.path.exists(FILE_PATH):
        print(f"ERROR: File '{FILE_PATH}' not found in the current directory.")
        print("FIX: Make sure you have downloaded it from Google Drive to this folder.")
        return

    try:
        s3.upload_file(FILE_PATH, BUCKET_NAME, "oil_spill_unet_best.keras")
        print("\n" + "="*40)
        print("SUCCESS! Your model is now on Cloudflare R2.")
        print("="*40)
        print("You can now run 'docker-compose up --build' and the system will pull the model automatically.")
    except Exception as e:
        print(f"UPLOAD FAILED: {e}")

if __name__ == "__main__":
    upload()