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import streamlit as st | |
import requests | |
import io | |
from PIL import Image | |
import os | |
hf_token = os.environ.get("hf_token") | |
API_URL = "https://api-inference.huggingface.co/models/xinsir/controlnet-union-sdxl-1.0" | |
headers = {"Authorization": f"Bearer hf_token"} | |
def query(payload): | |
response = requests.post(API_URL, headers=headers, json=payload) | |
return response.content | |
st.title("text to image model") | |
st.write("Enter a prompt") | |
model = st.selectbox( | |
"choose model", | |
("stable diffusion") | |
) | |
prompt = st.text_input("Enter prompt") | |
if prompt: | |
if model == "stable diffusion": | |
API_URL = API_URL_SD | |
image_bytes = query({ | |
"inputs": prompt, | |
}) | |
st.image(image_bytes, caption="Generated image") | |
st.info("Image generated successfully") | |