handler.py

from typing import Dict, List, Any
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
import base64
from io import BytesIO


device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

if device.type != 'cuda':
    raise ValueError("Must run SDXL on a GPU instance.")


class EndpointHandler():


    def __init__(self,path=""):
        self.pipe = StableDiffusionPipeline.from_pretrained(path,torch_dtype=torch.float16)
        self.pipe = self.pipe.to(device)


    def __call__(self):
        """
        """

        inputs = data.pop("inputs",data)

        with autocast(device.type):
            image = self.pipe(inputs,guidance_scale=9)["sample"][0]

        buffer = BytesIO()
        image.save(buffer, format="JPEG")
        img_str = base64.b64decode(buffer.getvalue())

        return {"image": img_str.decode}