from huggingface_hub import HfApi, create_repo
import os

    # --- Configuration ---
    # 1. Set the path to the local folder containing your clean LoRA adapter.
    #    (Ensure you have removed checkpoints and optimizer files).
LOCAL_LORA_PATH = "./gemma-grammar-lora"

    # 2. Define the name for your new model repository on the Hub.
    #    It's standard to use "YourUsername/YourModelName".
REPO_ID = "enoch10jason/gemma-grammar-lora"

    # --- Upload Script ---
def main():
        # Ensure the local path exists
    if not os.path.isdir(LOCAL_LORA_PATH):
        print(f"❌ Error: Local LoRA path not found at '{LOCAL_LORA_PATH}'")
        print("Please ensure your clean 'gemma-grammar-lora' folder is inside your project directory.")
        return

    api = HfApi()

        # Create the repository on the Hugging Face Hub (can be private)
    create_repo(repo_id=REPO_ID, repo_type="model", exist_ok=True, private=True)

    print(f"Uploading files from '{LOCAL_LORA_PATH}' to '{REPO_ID}'...")

        # Upload the entire folder. This will automatically use Git LFS for large files.
    api.upload_folder(
        folder_path=LOCAL_LORA_PATH,
        repo_id=REPO_ID,
        repo_type="model",
    )

    print(f"✅ LoRA adapter uploaded successfully to: https://huggingface.co/{REPO_ID}")

if __name__ == "__main__":
    main()