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import gradio as gr
import requests
import io
import random
import os
from PIL import Image
from deep_translator import GoogleTranslator
import gradio as gr
def welcome(name):
return f"Welcome to Gradio, {name}!"
js = """
function createGradioAnimation() {
var container = document.createElement('div');
container.id = 'gradio-animation';
container.style.fontSize = '2em';
container.style.fontWeight = 'bold';
container.style.textAlign = 'center';
container.style.marginBottom = '20px';
var text = 'Welcome to Gradio!';
for (var i = 0; i < text.length; i++) {
(function(i){
setTimeout(function(){
var letter = document.createElement('span');
letter.style.opacity = '0';
letter.style.transition = 'opacity 0.5s';
letter.innerText = text[i];
container.appendChild(letter);
setTimeout(function() {
letter.style.opacity = '1';
}, 50);
}, i * 250);
})(i);
}
var gradioContainer = document.querySelector('.gradio-container');
gradioContainer.insertBefore(container, gradioContainer.firstChild);
return 'Animation created';
}
"""
with gr.Blocks(js=js) as demo:
inp = gr.Textbox(placeholder="What is your name?")
out = gr.Textbox()
inp.change(welcome, inp, out)
demo.launch()
html='''<style>
body, html, #app {
margin: 0;
width: 100%;
height: 100%;
}
#app {
overflow: hidden;
touch-action: pan-up;
color: #ffffff;
font-family: 'Montserrat', sans-serif;
text-align: center;
text-shadow: 0 0 5px #000000, 0 0 20px #000;
user-select: none;
}
#app h1 {
--fontSize: 50px;
--lineHeight: 70px;
width: auto;
height: calc(2 * var(--lineHeight));
line-height: var(--lineHeight);
margin: calc(50vh - var(--lineHeight)) auto 0;
font-size: var(--fontSize);
}
#app a {
margin-top: 10px;
display: inline-block;
text-decoration: none;
color: #fff;
}
#app canvas {
display: block;
position: fixed;
z-index: -1;
top: 0;
}
</style>
<script>
import { swarmBackground } from 'https://unpkg.com/[email protected]/build/threejs-toys.module.cdn.min.js'
const bg = swarmBackground({
el: document.getElementById('app'),
eventsEl: document.body,
gpgpuSize: 256,
color: [Math.random() * 0xffffff, Math.random() * 0xffffff],
geometry: 'default'
})
bg.three.camera.position.set(0, 0, 200)
document.body.addEventListener('click', () => {
bg.setColors([Math.random() * 0xffffff, Math.random() * 0xffffff])
})
</script>
<div id="app">
<div id="hero">
<h1>SWARM<br/>BACKGROUND</h1>
<a target="_blank" href="https://github.com/klevron/threejs-toys">github/threejs-toys</a>
</div>
</div>
'''
# os.makedirs('assets', exist_ok=True)
if not os.path.exists('icon.jpg'):
os.system("wget -O icon.jpg https://i.pinimg.com/564x/64/49/88/644988c59447eb00286834c2e70fdd6b.jpg")
API_URL_DEV = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
timeout = 100
def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key=None, use_dev=False):
# Determine which API URL to use
api_url = API_URL_DEV if use_dev else API_URL
# Check if the request is an API call by checking for the presence of the huggingface_api_key
is_api_call = huggingface_api_key is not None
if is_api_call:
# Use the environment variable for the API key in GUI mode
API_TOKEN = os.getenv("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
else:
# Validate the API key if it's an API call
if huggingface_api_key == "":
raise gr.Error("API key is required for API calls.")
headers = {"Authorization": f"Bearer {huggingface_api_key}"}
if prompt == "" or prompt is None:
return None
key = random.randint(0, 999)
prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
print(f'\033[1mGeneration {key}:\033[0m {prompt}')
# If seed is -1, generate a random seed and use it
if seed == -1:
seed = random.randint(1, 1000000000)
payload = {
"inputs": prompt,
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed,
"strength": strength
}
response = requests.post(api_url, headers=headers, json=payload, timeout=timeout)
if response.status_code != 200:
print(f"Error: Failed to get image. Response status: {response.status_code}")
print(f"Response content: {response.text}")
if response.status_code == 503:
raise gr.Error(f"{response.status_code} : The model is being loaded")
raise gr.Error(f"{response.status_code}")
try:
image_bytes = response.content
image = Image.open(io.BytesIO(image_bytes))
print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
# Save the image to a file and return the file path and seed
output_path = f"./output_{key}.png"
image.save(output_path)
return output_path, seed
except Exception as e:
print(f"Error when trying to open the image: {e}")
return None, None
css = """
#app-container {
max-width: 600px;
margin-left: auto;
margin-right: auto;
}
#title-container {
display: flex;
align-items: center;
justify-content: center;
}
#title-icon {
width: 32px; /* Adjust the width of the icon as needed */
height: auto;
margin-right: 10px; /* Space between icon and title */
}
#title-text {
font-size: 24px; /* Adjust font size as needed */
font-weight: bold;
}
"""
with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
gr.HTML("""
<center>
<div id="title-container">
<img id="title-icon" src="icon.jpg" alt="Icon">
<h1 id="title-text">FLUX Capacitor</h1>
</div>
</center>
"""+html)
with gr.Column(elem_id="app-container"):
with gr.Row():
with gr.Column(elem_id="prompt-container"):
with gr.Row():
text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
with gr.Row():
with gr.Accordion("Advanced Settings", open=False):
negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
huggingface_api_key = gr.Textbox(label="Hugging Face API Key (required for API calls)", placeholder="Enter your Hugging Face API Key here", type="password", elem_id="api-key")
use_dev = gr.Checkbox(label="Use Dev API", value=False, elem_id="use-dev-checkbox")
with gr.Row():
text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
with gr.Row():
image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
# Adjust the click function to include the API key and use_dev as inputs
text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key, use_dev], outputs=[image_output, seed_output])
app.launch(show_api=True, share=False) |