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Update app.py
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import os
os.system(
'pip install --upgrade --pre --extra-index-url https://download.pytorch.org/whl/nightly/cu126 '
'"torch==2.9.0" "torchvision==0.24.0" "torchaudio==2.9.0" '
'"transformers>=4.44" "huggingface-hub>=1.0.0rc6" spaces -q'
)
import spaces
import gradio as gr
import torch
import math
from PIL import Image
from diffusers import QwenImageEditPlusPipeline, FlowMatchEulerDiscreteScheduler
import requests
import logging
import numpy as np
import random
from fastapi import FastAPI, HTTPException
logging.basicConfig(
level=logging.INFO,
filename="qwen_image_editor.log",
filemode="a",
format="%(asctime)s - %(levelname)s - %(message)s",
)
logger = logging.getLogger(__name__)
@spaces.GPU
def translate_albanian_to_english(text: str, language: str = "en"):
if not text.strip():
raise gr.Error("Please enter a description.")
for attempt in range(2):
try:
response = requests.post(
"https://hal1993-mdftranslation1234567890abcdef1234567890-fc073a6.hf.space/v1/translate",
json={"from_language": "sq", "to_language": "en", "input_text": text},
headers={"accept": "application/json", "Content-Type": "application/json"},
timeout=5,
)
response.raise_for_status()
translated = response.json().get("translate", "")
logger.info(f"Translation response: {translated}")
return translated
except Exception as e:
logger.error(f"Translation error (attempt {attempt + 1}): {e}")
if attempt == 1:
raise gr.Error("Translation failed. Please try again.")
raise gr.Error("Translation failed. Please try again.")
scheduler_config = {
"base_image_seq_len": 256,
"base_shift": math.log(3),
"invert_sigmas": False,
"max_image_seq_len": 8192,
"max_shift": math.log(3),
"num_train_timesteps": 1000,
"shift": 1.0,
"shift_terminal": None,
"stochastic_sampling": False,
"time_shift_type": "exponential",
"use_beta_sigmas": False,
"use_dynamic_shifting": True,
"use_exponential_sigmas": False,
"use_karras_sigmas": False,
}
scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
pipeline = QwenImageEditPlusPipeline.from_pretrained(
"Qwen/Qwen-Image-Edit-2509",
scheduler=scheduler,
torch_dtype=torch.bfloat16,
)
pipeline.to("cuda")
pipeline.set_progress_bar_config(disable=None)
pipeline.load_lora_weights(
"lightx2v/Qwen-Image-Lightning",
weight_name="Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors",
)
pipeline.fuse_lora()
MAX_SEED = np.iinfo(np.int32).max
QUALITY_PROMPT = ", high quality, detailed, vibrant, professional lighting"
@spaces.GPU(duration=60)
def edit_images(image1, image2, prompt):
if image1 is None or image2 is None:
raise gr.Error("Please upload both images")
prompt_en = translate_albanian_to_english(prompt.strip(), language="en")
prompt_final = prompt_en + QUALITY_PROMPT
if not isinstance(image1, Image.Image):
image1 = Image.fromarray(image1)
if not isinstance(image2, Image.Image):
image2 = Image.fromarray(image2)
seed = random.randint(0, MAX_SEED)
true_cfg_scale = 1.0
negative_prompt = ""
num_steps = 8
guidance_scale = 1.0
inputs = {
"image": [image1, image2],
"prompt": prompt_final,
"generator": torch.manual_seed(seed),
"true_cfg_scale": true_cfg_scale,
"negative_prompt": negative_prompt,
"num_inference_steps": num_steps,
"guidance_scale": guidance_scale,
"num_images_per_prompt": 1,
}
logger.info(f"Calling pipeline – Prompt: {prompt_final}")
logger.info(f"Seed: {seed} | Steps: {num_steps}")
with torch.inference_mode():
output = pipeline(**inputs)
return output.images[0]
def create_demo():
with gr.Blocks(css="", title="Qwen Image Editor") as demo:
gr.HTML(
"""
<style>
@import url('https://fonts.googleapis.com/css2?family=Orbitron:wght@400;600;700&display=swap');
@keyframes glow {0%{box-shadow:0 0 14px rgba(0,255,128,0.5);}50%{box-shadow:0 0 14px rgba(0,255,128,0.7);}100%{box-shadow:0 0 14px rgba(0,255,128,0.5);}}
@keyframes glow-hover {0%{box-shadow:0 0 20px rgba(0,255,128,0.7);}50%{box-shadow:0 0 20px rgba(0,255,128,0.9);}100%{box-shadow:0 0 20px rgba(0,255,128,0.7);}}
@keyframes slide {0%{background-position:0% 50%;}50%{background-position:100% 50%;}100%{background-position:0% 50%;}}
body{
background:#000000 !important;
color:#FFFFFF !important;
font-family:'Orbitron',sans-serif;
min-height:100vh;
margin:0 !important;
padding:0 !important;
width:100% !important;
max-width:100vw !important;
overflow-x:hidden !important;
display:flex !important;
justify-content:center;
align-items:center;
flex-direction:column;
}
body::before{
content:"";
display:block;
height:600px;
background:#000000 !important;
}
.gr-blocks,.container{
width:100% !important;
max-width:100vw !important;
margin:0 !important;
padding:0 !important;
box-sizing:border-box !important;
overflow-x:hidden !important;
background:#000000 !important;
color:#FFFFFF !important;
}
/* NEW: force rows, columns and Gradio containers to be full width */
.gr-row,.gr-column{
width:100% !important;
max-width:100vw !important;
margin:0 !important;
padding:0 !important;
box-sizing:border-box !important;
}
.gradio-container,.gradio-app,.gradio-interface{
width:100% !important;
max-width:100vw !important;
margin:0 !important;
padding:0 !important;
box-sizing:border-box !important;
}
#general_items{
width:100% !important;
max-width:100vw !important;
margin:2rem 0 !important;
display:flex !important;
flex-direction:column;
align-items:center;
justify-content:center;
background:#000000 !important;
color:#FFFFFF !important;
}
#input_column{
background:#000000 !important;
border:none !important;
border-radius:8px;
padding:1rem !important;
box-shadow:0 0 10px rgba(255,255,255,0.3) !important;
width:100% !important;
max-width:100vw !important;
box-sizing:border-box !important;
color:#FFFFFF !important;
}
h1{
font-size:5rem;
font-weight:700;
text-align:center;
color:#FFFFFF !important;
text-shadow:0 0 8px rgba(255,255,255,0.3) !important;
margin:0 auto .5rem;
display:block;
max-width:100%;
}
#subtitle{
font-size:1rem;
text-align:center;
color:#FFFFFF !important;
opacity:0.8;
margin-bottom:1rem;
display:block;
max-width:100%;
}
.gradio-component{
background:#000000 !important;
border:none;
margin:0.75rem 0;
width:100% !important;
max-width:100vw !important;
color:#FFFFFF !important;
}
.image-container{
aspect-ratio:1/1;
width:100% !important;
max-width:100vw !important;
min-height:500px;
height:auto;
border:0.5px solid #FFFFFF !important;
border-radius:4px;
box-sizing:border-box !important;
background:#000000 !important;
box-shadow:0 0 10px rgba(255,255,255,0.3) !important;
position:relative;
color:#FFFFFF !important;
}
.image-container img{
width:100% !important;
height:auto;
box-sizing:border-box !important;
display:block !important;
}
.image-container[aria-label="First Image"] .file-upload,
.image-container[aria-label="First Image"] .file-preview,
.image-container[aria-label="First Image"] .image-actions,
.image-container[aria-label="First Image"] .gr-file-upload,
.image-container[aria-label="First Image"] .gr-file,
.image-container[aria-label="First Image"] .gr-actions,
.image-container[aria-label="First Image"] .gr-upload-button,
.image-container[aria-label="First Image"] .gr-image-toolbar,
.image-container[aria-label="First Image"] .gr-file-actions,
.image-container[aria-label="First Image"] .gr-upload-options,
div[aria-label="First Image"] > div > div:not(.image-container),
div[aria-label="First Image"] .gr-button,
.image-container[aria-label="Second Image"] .file-upload,
.image-container[aria-label="Second Image"] .file-preview,
.image-container[aria-label="Second Image"] .image-actions,
.image-container[aria-label="Second Image"] .gr-file-upload,
.image-container[aria-label="Second Image"] .gr-file,
.image-container[aria-label="Second Image"] .gr-actions,
.image-container[aria-label="Second Image"] .gr-upload-button,
.image-container[aria-label="Second Image"] .gr-image-toolbar,
.image-container[aria-label="Second Image"] .gr-file-actions,
.image-container[aria-label="Second Image"] .gr-upload-options,
div[aria-label="Second Image"] .gr-button{
display:none !important;
}
input,textarea{
background:#000000 !important;
color:#FFFFFF !important;
border:1px solid #FFFFFF !important;
border-radius:4px;
padding:0.5rem;
width:100% !important;
max-width:100vw !important;
box-sizing:border-box !important;
}
input:hover,textarea:hover{
box-shadow:0 0 8px rgba(255,255,255,0.3) !important;
transition:box-shadow 0.3s;
}
.gr-button-primary{
background:linear-gradient(90deg,rgba(0,255,128,0.3),rgba(0,200,100,0.3),rgba(0,255,128,0.3)) !important;
background-size:200% 100%;
animation:slide 4s ease-in-out infinite,glow 3s ease-in-out infinite;
color:#FFFFFF !important;
border:1px solid #FFFFFF !important;
border-radius:6px;
padding:0.75rem 1.5rem;
font-size:1.1rem;
font-weight:600;
box-shadow:0 0 14px rgba(0,255,128,0.7) !important;
transition:box-shadow 0.3s,transform 0.3s;
width:100% !important;
max-width:100vw !important;
min-height:48px;
cursor:pointer;
}
.gr-button-primary:hover{
box-shadow:0 0 20px rgba(0,255,128,0.9) !important;
animation:slide 4s ease-in-out infinite,glow-hover 3s ease-in-out infinite;
transform:scale(1.05);
}
button[aria-label="Fullscreen"],button[aria-label="Share"]{display:none !important;}
button[aria-label="Download"]{
transform:scale(3);
transform-origin:top right;
background:#000000 !important;
color:#FFFFFF !important;
border:1px solid #FFFFFF !important;
border-radius:4px;
padding:0.4rem !important;
margin:0.5rem !important;
box-shadow:0 0 8px rgba(255,255,255,0.3) !important;
transition:box-shadow 0.3s;
}
button[aria-label="Download"]:hover{
box-shadow:0 0 12px rgba(255,255,255,0.5) !important;
}
.progress-text,.gr-progress,.gr-prose,.gr-log{display:none !important;}
footer,.gr-button-secondary{display:none !important;}
.gr-group{
background:#000000 !important;
border:none !important;
width:100% !important;
max-width:100vw !important;
}
@media (max-width:768px){
h1{font-size:4rem;}
#subtitle{font-size:0.9rem;}
.gr-button-primary{
padding:0.6rem 1rem;
font-size:1rem;
box-shadow:0 0 10px rgba(0,255,128,0.7) !important;
animation:slide 4s ease-in-out infinite,glow 3s ease-in-out infinite;
}
.gr-button-primary:hover{
box-shadow:0 0 12px rgba(0,255,128,0.9) !important;
animation:slide 4s ease-in-out infinite,glow-hover 3s ease-in-out infinite;
}
.image-container{
min-height:300px;
box-shadow:0 0 8px rgba(255,255,255,0.3) !important;
border:0.5px solid #FFFFFF !important;
}
}
</style>
<script>
const allowedPath = /^\\/q3w4e5r6t7y8u9i0o1p2l3k4j5h6g7f8d9s0a1q2w3e4r5t6y7u8i9o0p1l2k3j4(\\/.*)?$/;
if (!allowedPath.test(window.location.pathname)) {
document.body.innerHTML = '<h1 style="color:#ef4444;font-family:sans-serif;text-align:center;margin-top:100px;">500 Internal Server Error</h1>';
throw new Error('500');
}
document.addEventListener('DOMContentLoaded', () => {
const containers = document.querySelectorAll('#general_items, #input_column, .image-container');
containers.forEach(container => {
const width = container.offsetWidth;
const style = window.getComputedStyle(container);
console.log(`Container ${container.id || container.className}: width=${width}px, box-shadow=${style.boxShadow}, background=${style.background}, border=${style.border} (Viewport: ${window.innerWidth}px)`);
container.setAttribute('data-width', `${width}px`);
});
const editButton = document.querySelector('.gr-button-primary');
if (editButton) {
const style = window.getComputedStyle(editButton);
console.log(`Edit button: box-shadow=${style.boxShadow}, background=${style.background}, border=${style.border}, animation=${style.animation}, background-position=${style.backgroundPosition}`);
}
const toolbars = document.querySelectorAll(
'.image-container[aria-label="First Image"] > div > div:not(.image-container), ' +
'.image-container[aria-label="First Image"] .file-upload, ' +
'.image-container[aria-label="First Image"] .file-preview, ' +
'.image-container[aria-label="First Image"] .image-actions, ' +
'.image-container[aria-label="First Image"] .gr-file-upload, ' +
'.image-container[aria-label="First Image"] .gr-file, ' +
'.image-container[aria-label="First Image"] .gr-actions, ' +
'.image-container[aria-label="First Image"] .gr-upload-button, ' +
'.image-container[aria-label="First Image"] .gr-image-toolbar, ' +
'.image-container[aria-label="First Image"] .gr-file-actions, ' +
'.image-container[aria-label="First Image"] .gr-upload-options, ' +
'div[aria-label="First Image"] .gr-button, ' +
'.image-container[aria-label="Second Image"] > div > div:not(.image-container), ' +
'.image-container[aria-label="Second Image"] .file-upload, ' +
'.image-container[aria-label="Second Image"] .file-preview, ' +
'.image-container[aria-label="Second Image"] .image-actions, ' +
'.image-container[aria-label="Second Image"] .gr-file-upload, ' +
'.image-container[aria-label="Second Image"] .gr-file, ' +
'.image-container[aria-label="Second Image"] .gr-actions, ' +
'.image-container[aria-label="Second Image"] .gr-upload-button, ' +
'.image-container[aria-label="Second Image"] .gr-image-toolbar, ' +
'.image-container[aria-label="Second Image"] .gr-file-actions, ' +
'.image-container[aria-label="Second Image"] .gr-upload-options, ' +
'div[aria-label="Second Image"] .gr-button'
);
toolbars.forEach(tb => {
tb.style.display = 'none';
console.log(`Forced hide toolbar: ${tb.className}`);
});
setInterval(() => {
document.querySelectorAll('.progress-text,.gr-progress,[class*="progress"]').forEach(el => el.remove());
}, 500);
});
</script>
"""
)
with gr.Row(elem_id="general_items"):
gr.Markdown("# ")
gr.Markdown("Blend images together guided by a prompt description.", elem_id="subtitle")
with gr.Column(elem_id="input_column"):
image1_input = gr.Image(
label="First Image",
type="pil",
sources=["upload"],
interactive=True,
elem_classes=["gradio-component", "image-container"],
)
image2_input = gr.Image(
label="Second Image",
type="pil",
sources=["upload"],
interactive=True,
elem_classes=["gradio-component", "image-container"],
)
prompt_input = gr.Textbox(
label="Prompt",
placeholder="Describe how you want the images combined or edited...",
lines=3,
elem_classes=["gradio-component"],
)
run_button = gr.Button(
"Edit!",
variant="primary",
elem_classes=["gradio-component", "gr-button-primary"],
)
output_image = gr.Image(
label="Result Image",
type="pil",
interactive=False,
elem_classes=["gradio-component", "image-container"],
)
gr.on(
triggers=[run_button.click, prompt_input.submit],
fn=edit_images,
inputs=[image1_input, image2_input, prompt_input],
outputs=[output_image],
show_progress="full",
)
return demo
app = FastAPI()
demo = create_demo()
app.mount("/q3w4e5r6t7y8u9i0o1p2l3k4j5h6g7f8d9s0a1q2w3e4r5t6y7u8i9o0p1l2k3j4", demo.app)
@app.get("/{path:path}")
async def catch_all(path: str):
if not path.startswith("spaceishere"):
raise HTTPException(status_code=500, detail="Internal Server Error")
return demo
if __name__ == "__main__":
logger.info(f"Gradio version: {gr.__version__}")
demo.queue().launch(share=True)