app.py

# Python
import streamlit as st
import torch
from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
import requests
import io
from PIL import Image
import os
from dotenv import load_dotenv
load_dotenv()

API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-cascade-prior"
headers = {"Authorization": f"Bearer ${os.getenv('bearer_token')}"}

st.title("Image Generator with Diffusers")

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.content

prompt = st.text_input("Enter a prompt:", "batman hitting the griddy in gotham")

image_bytes = query({
	"inputs": prompt,
})
# You can access the image with PIL.Image for example
image = Image.open(io.BytesIO(image_bytes))