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import gradio as gr
import requests
from PIL import Image
from io import BytesIO
import os
from huggingface_hub import InferenceClient
API_TOKEN = os.getenv("HF_API_TOKEN") # Ensure you've set this environment variable
API_URL = "https://api-inference.huggingface.co/models/enhanceaiteam/Flux-uncensored"
enhancer = InferenceClient(api_key =API_TOKEN)
for message in enhancer.chat_completion(
model="meta-llama/Llama-3.2-1B-Instruct",
messages=[{"role": "user", "content": "What is the capital of France?"}],
max_tokens=500,
stream=True,
):
print(message.choices[0].delta.content, end="")
# Load API Token from environment variable
# Hugging Face Inference API URL
# Function to call Hugging Face API and get the generated image
def generate_image(prompt):
headers = {"Authorization": f"Bearer {API_TOKEN}"}
data = {"inputs": prompt}
response = requests.post(API_URL, headers=headers, json=data)
if response.status_code == 200:
image_bytes = BytesIO(response.content)
image = Image.open(image_bytes)
return image
else:
return f"Error: {response.status_code}, {response.text}"
title_html="""
<center>
<div id="title-container">
<h1 id="title-text">FLUX Capacitor</h1>
</div>
</center>
"""
css = """
.gradio-container {
background: url(https://huggingface.co/spaces/K00B404/FLUX.1-Dev-Serverless-darn-enhanced-prompt/resolve/main/edge.png);
background-size: 900px 880px;
background-repeat: no-repeat;
background-position: center;
background-attachment: fixed;
color:#000;
}
.dark\:bg-gray-950:is(.dark *) {
--tw-bg-opacity: 1;
background-color: rgb(157, 17, 142);
}
.gradio-container-4-41-0 .prose :last-child {
margin-top: 8px !important;
}
.gradio-container-4-41-0 .prose :last-child {
margin-bottom: -7px !important;
}
.dark {
--button-primary-background-fill: #09e60d70;
--button-primary-background-fill-hover: #00000070;
--background-fill-primary: #000;
--background-fill-secondary: #000;
}
.hide-container {
margin-top;-2px;
}
#app-container3 {
background-color: rgba(255, 255, 255, 0.001); /* Corrected to make semi-transparent */
max-width: 600px;
margin-left: auto;
margin-right: auto;
margin-bottom: 10px;
border-radius: 125px;
box-shadow: 0 0 10px rgba(0,0,0,0.1); /* Adjusted shadow opacity */
}
#app-container {
background-color: rgba(255, 255, 255, 0.001); /* Semi-transparent background */
max-width: 600px;
margin: 0 auto; /* Center horizontally */
padding-bottom: 10px;
border-radius: 25px;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.1); /* Adjusted shadow opacity */
}
#title-container {
display: flex;
align-items: center
margin-bottom:10px;
justify-content: center;
}
#title-icon {
width: 32px;
height: auto;
margin-right: 10px;
}
#title-text {
font-size: 30px;
font-weight: bold;
color: #000;
}
"""
# Create Gradio interface
def create_ui():
with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as ui:
gr.Markdown("## Flux Uncensored - Text to Image Generator")
with gr.Row():
prompt_input = gr.Textbox(label="Enter a Prompt", placeholder="Describe the image you want to generate", lines=3)
generate_button = gr.Button("Generate Image")
with gr.Row():
output_image = gr.Image(label="Generated Image")
# Link the button to the function
generate_button.click(fn=generate_image, inputs=prompt_input, outputs=output_image)
return ui
# Run the interface
if __name__ == "__main__":
create_ui().launch()
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