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import streamlit as st | |
import requests | |
from PIL import Image | |
import io | |
import os | |
token = os.getenv("HF_TOKEN") | |
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" | |
headers = {"Authorization": f"Bearer {token}"} | |
def query(payload): | |
response = requests.post(API_URL, headers=headers, json=payload) | |
if response.status_code != 200: | |
st.error(f"Error: {response.status_code} - {response.text}") | |
return None | |
return response.content | |
def generate_image(prompt): | |
image_bytes = query({"inputs": prompt}) | |
if image_bytes: | |
return Image.open(io.BytesIO(image_bytes)) | |
return None | |
def main(): | |
st.title("Stable Diffusion XL 1.0") | |
prompt = st.text_input("Enter a prompt for image generation:") | |
if st.button("Generate Image"): | |
if prompt: | |
image = generate_image(prompt) | |
if image: | |
st.image(image, caption="Generated Image") | |
else: | |
st.warning("Please enter a prompt.") | |
if __name__ == "__main__": | |
main() | |