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import spaces
import gradio as gr
import torch
from PIL import Image
from transformers import AutoProcessor
from longcat_image.models import LongCatImageTransformer2DModel
from longcat_image.pipelines import LongCatImageEditPipeline, LongCatImagePipeline
import numpy as np
# --- Model Loading (Kept for completeness) ---
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Text-to-Image Model
t2i_model_id = 'meituan-longcat/LongCat-Image'
print(f"🔄 Loading Text-to-Image model from {t2i_model_id}...")
t2i_text_processor = AutoProcessor.from_pretrained(
t2i_model_id,
subfolder='tokenizer'
)
t2i_transformer = LongCatImageTransformer2DModel.from_pretrained(
t2i_model_id,
subfolder='transformer',
torch_dtype=torch.bfloat16,
use_safetensors=True
).to(device)
t2i_pipe = LongCatImagePipeline.from_pretrained(
t2i_model_id,
transformer=t2i_transformer,
text_processor=t2i_text_processor,
)
t2i_pipe.to(device, torch.bfloat16)
print(f"✅ Text-to-Image model loaded successfully")
# Image Edit Model
edit_model_id = 'meituan-longcat/LongCat-Image-Edit'
print(f"🔄 Loading Image Edit model from {edit_model_id}...")
edit_text_processor = AutoProcessor.from_pretrained(
edit_model_id,
subfolder='tokenizer'
)
edit_transformer = LongCatImageTransformer2DModel.from_pretrained(
edit_model_id,
subfolder='transformer',
torch_dtype=torch.bfloat16,
use_safetensors=True
).to(device)
edit_pipe = LongCatImageEditPipeline.from_pretrained(
edit_model_id,
transformer=edit_transformer,
text_processor=edit_text_processor,
)
edit_pipe.to(device, torch.bfloat16)
print(f"✅ Image Edit model loaded successfully on {device}")
# --- Core Functions (Kept for completeness) ---
@spaces.GPU(duration=120)
def generate_image(
prompt: str,
width: int,
height: int,
seed: int,
progress=gr.Progress()
):
"""Generate image from text prompt"""
if not prompt or prompt.strip() == "":
raise gr.Error("Please enter a prompt")
try:
progress(0.1, desc="Preparing generation...")
progress(0.2, desc="Generating image...")
generator = torch.Generator("cuda" if torch.cuda.is_available() else "cpu").manual_seed(seed)
with torch.inference_mode():
output = t2i_pipe(
prompt,
negative_prompt="",
height=height,
width=width,
guidance_scale=4.5,
num_inference_steps=50,
num_images_per_prompt=1,
generator=generator,
enable_cfg_renorm=True,
enable_prompt_rewrite=True
)
progress(1.0, desc="Done!")
return output.images[0]
except Exception as e:
raise gr.Error(f"Error during image generation: {str(e)}")
@spaces.GPU(duration=120)
def edit_image(
input_image: Image.Image,
prompt: str,
seed: int,
progress=gr.Progress()
):
"""Edit image based on text prompt"""
if input_image is None:
raise gr.Error("Please upload an image first")
if not prompt or prompt.strip() == "":
raise gr.Error("Please enter an edit instruction")
try:
progress(0.1, desc="Preparing image...")
if input_image.mode != 'RGB':
input_image = input_image.convert('RGB')
progress(0.2, desc="Generating edited image...")
generator = torch.Generator("cuda" if torch.cuda.is_available() else "cpu").manual_seed(seed)
with torch.inference_mode():
output = edit_pipe(
input_image,
prompt,
negative_prompt="",
guidance_scale=4.5,
num_inference_steps=50,
num_images_per_prompt=1,
generator=generator
)
progress(1.0, desc="Done!")
return output.images[0]
except Exception as e:
raise gr.Error(f"Error during image editing: {str(e)}")
# --- Examples (Kept for completeness) ---
edit_example_image_url = "https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.png"
edit_example_data = [
[edit_example_image_url, "Add a mustache", 42],
]
t2i_example_prompts = [
["一个年轻的亚裔女性,身穿黄色针织衫,搭配白色项链。她的双手放在膝盖上,表情恬静。背景是一堵粗糙的砖墙,午后的阳光温暖地洒在她身上,营造出一种宁静而温馨的氛围。", 1344, 768, 43],
["A serene mountain landscape at sunset with golden clouds", 1344, 768, 42],
["A cute robot sitting at a desk, digital art style", 1024, 1024, 44],
]
# --- Custom CSS (Cleaned up for maximum layout flexibility) ---
custom_css = """
@import url('https://fonts.googleapis.com/css2?family=SF+Pro+Display:wght@300;400;500;600;700&display=swap');
* {
font-family: -apple-system, BlinkMacSystemFont, 'SF Pro Display', 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif;
}
/* Base styling relying on fill_width=True and Gradio's structure */
.gradio-container {
max-width: 100% !important; /* Allow full width */
margin: auto !important;
}
/* Background gradient for the overall app */
#component-0 {
background: linear-gradient(180deg, #f5f5f7 0%, #ffffff 100%) !important;
}
/* Tab bar styling for the segmented control look */
.tabs {
border: none !important;
background: transparent !important;
}
.tab-nav {
border: none !important;
background: rgba(255, 255, 255, 0.8) !important;
backdrop-filter: blur(20px) !important;
border-radius: 12px !important;
padding: 4px !important;
gap: 4px !important;
}
button.selected {
background: white !important;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08) !important;
border-radius: 8px !important;
font-weight: 500 !important;
}
/* Image and input component styling */
.input-image, .output-image {
border-radius: 16px !important;
overflow: hidden !important;
box-shadow: 0 4px 16px rgba(0, 0, 0, 0.06) !important;
}
textarea, input[type="text"] {
border: 1px solid #d2d2d7 !important;
border-radius: 12px !important;
padding: 12px 16px !important;
font-size: 15px !important;
transition: all 0.2s ease !important;
}
textarea:focus, input[type="text"]:focus {
border-color: #007aff !important;
box-shadow: 0 0 0 3px rgba(0, 122, 255, 0.1) !important;
}
/* Primary Button Styling */
.primary-btn {
background: linear-gradient(180deg, #007aff 0%, #0051d5 100%) !important;
border: none !important;
border-radius: 12px !important;
padding: 14px 28px !important;
font-size: 16px !important;
font-weight: 500 !important;
color: white !important;
box-shadow: 0 4px 12px rgba(0, 122, 255, 0.3) !important;
transition: all 0.2s ease !important;
}
.primary-btn:hover {
transform: translateY(-2px) !important;
box-shadow: 0 6px 16px rgba(0, 122, 255, 0.4) !important;
}
/* Card Style (targets gr-panel when variant="panel" is used) */
.card {
background: white !important;
border-radius: 16px !important;
padding: 24px !important;
box-shadow: 0 2px 12px rgba(0, 0, 0, 0.04) !important;
}
/* Mobile adjustments (retains padding) */
@media (max-width: 768px) {
.gradio-container {
padding: 0 8px !important;
}
.card {
padding: 16px !important;
}
}
"""
# Build Gradio interface
# Using fill_width=True on Blocks to maximize available horizontal space
with gr.Blocks(fill_width=True) as demo:
gr.HTML("""
<div style="text-align: center; padding: 40px 20px 30px 20px;">
<h1 style="font-size: 48px; font-weight: 700; margin: 0; background: linear-gradient(90deg, #007aff 0%, #5856d6 100%); -webkit-background-clip: text; -webkit-text-fill-color: transparent;">
LongCat Studio
</h1>
<p style="font-size: 20px; color: #86868b; margin-top: 12px; font-weight: 400;">
AI-powered image generation and editing
</p>
</div>
""")
with gr.Tabs(selected=0):
# Image Edit Tab (Responsive Layout: Row on Desktop, Column on Mobile)
with gr.TabItem("Edit Image", id=0):
with gr.Row():
# Left Column (Inputs)
with gr.Column(scale=1, min_width=0, variant="panel"):
gr.Markdown("### 🖼️ Input Image & Controls")
input_image = gr.Image(
label="Upload Image",
type="pil",
sources=["upload", "clipboard"],
height=450,
elem_classes=["input-image"]
)
prompt = gr.Textbox(
label="What would you like to change?",
placeholder="e.g., Add a mustache, Change to sunset, Make it vintage...",
lines=2,
max_lines=3
)
seed = gr.Slider(
minimum=0,
maximum=999999,
value=42,
step=1,
label="Seed",
visible=False
)
edit_btn = gr.Button("Edit Image", variant="primary", size="lg", elem_classes=["primary-btn"])
# Right Column (Output)
with gr.Column(scale=1, min_width=0, variant="panel"):
gr.Markdown("### ✨ Result")
output_image = gr.Image(
label="Result",
type="pil",
height=450,
elem_classes=["output-image"]
)
gr.HTML("<div style='margin: 30px 0 20px 0;'></div>")
gr.Examples(
examples=edit_example_data,
inputs=[input_image, prompt, seed],
outputs=output_image,
fn=edit_image,
cache_examples=False,
label="Try an example",
examples_per_page=3
)
# Text-to-Image Tab (Responsive Layout: Row on Desktop, Column on Mobile)
with gr.TabItem("Generate Image", id=1):
with gr.Row():
# Left Column (Inputs)
with gr.Column(scale=1, min_width=0, variant="panel"):
gr.Markdown("### 🎨 Generation Controls")
t2i_prompt = gr.Textbox(
label="Describe your image",
placeholder="e.g., A serene mountain landscape at sunset...",
lines=4,
max_lines=6
)
t2i_width = gr.Slider(
minimum=512,
maximum=2048,
value=1344,
step=64,
label="Width",
)
t2i_height = gr.Slider(
minimum=512,
maximum=2048,
value=768,
step=64,
label="Height",
)
t2i_seed = gr.Slider(
minimum=0,
maximum=999999,
value=42,
step=1,
label="Seed",
visible=False
)
generate_btn = gr.Button("Generate Image", variant="primary", size="lg", elem_classes=["primary-btn"])
# Right Column (Output)
with gr.Column(scale=1, min_width=0, variant="panel"):
gr.Markdown("### ✨ Result")
t2i_output = gr.Image(
label="Result",
type="pil",
height=550,
elem_classes=["output-image"]
)
gr.HTML("<div style='margin: 30px 0 20px 0;'></div>")
gr.Examples(
examples=t2i_example_prompts,
inputs=[t2i_prompt, t2i_width, t2i_height, t2i_seed],
outputs=t2i_output,
fn=generate_image,
cache_examples=False,
label="Try an example",
examples_per_page=3
)
# Event handlers
generate_btn.click(
fn=generate_image,
inputs=[t2i_prompt, t2i_width, t2i_height, t2i_seed],
outputs=t2i_output,
)
edit_btn.click(
fn=edit_image,
inputs=[input_image, prompt, seed],
outputs=output_image,
)
# Footer
gr.HTML("""
<div style="text-align: center; margin-top: 60px; padding: 30px 20px; border-top: 1px solid #d2d2d7;">
<p style="color: #86868b; font-size: 13px; margin: 0;">
Powered by LongCat • Built with
<a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color: #007aff; text-decoration: none;">anycoder</a>
</p>
</div>
""")
# Launch the app with theme and custom CSS
if __name__ == "__main__":
demo.launch(
mcp_server=True,
theme=gr.themes.Soft(),
css=custom_css
)