import gc
import os
import random
import numpy as np
import json
import torch
import base64
from io import BytesIO
from PIL import Image, PngImagePlugin
from datetime import datetime
from dataclasses import dataclass
from typing import Callable, Dict, Optional, Tuple
from diffusers import (
    DDIMScheduler,
    DPMSolverMultistepScheduler,
    DPMSolverSinglestepScheduler,
    EulerAncestralDiscreteScheduler,
    EulerDiscreteScheduler,
)

MAX_SEED = np.iinfo(np.int32).max

# ... (rest of the existing functions remain the same)

def image_to_base64(image: Image.Image) -> str:
    buffered = BytesIO()
    image.save(buffered, format="PNG")
    return base64.b64encode(buffered.getvalue()).decode()

# ... (rest of the existing functions remain the same)