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import spaces
import gradio as gr
import torch
from PIL import Image
from diffusers import DiffusionPipeline
import random
from transformers import pipeline

torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
torch.backends.cuda.matmul.allow_tf32 = True

# λ²ˆμ—­ λͺ¨λΈ μ΄ˆκΈ°ν™”
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")

# κΈ°λ³Έ λͺ¨λΈ 및 LoRA μ„€μ •
base_model = "black-forest-labs/FLUX.1-dev"
model_lora_repo = "Motas/Flux_Fashion_Photography_Style"
clothes_lora_repo = "prithivMLmods/Canopus-Clothing-Flux-LoRA"

pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
pipe.to("cuda")

MAX_SEED = 2**32-1

# μ˜ˆμ‹œ ν”„λ‘¬ν”„νŠΈ μ •μ˜
model_examples = [
    "professional fashion model wearing elegant black dress in studio lighting",
    "fashion model in casual street wear, urban background",
    "high fashion model in avant-garde outfit on runway"
]

clothes_examples = [
    "luxurious red evening gown with detailed embroidery",
    "casual denim jacket with vintage wash",
    "modern minimalist white blazer with clean lines"
]

@spaces.GPU()
def generate_fashion(prompt, mode, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
    if not prompt:
        return None, seed
    
    def contains_korean(text):
        return any(ord('κ°€') <= ord(char) <= ord('힣') for char in text)
    
    if contains_korean(prompt):
        translated = translator(prompt)[0]['translation_text']
        actual_prompt = translated
    else:
        actual_prompt = prompt

    if mode == "νŒ¨μ…˜ λͺ¨λΈ 생성":
        pipe.load_lora_weights(model_lora_repo)
        trigger_word = "fashion photography, professional model"
    else:
        pipe.load_lora_weights(clothes_lora_repo)
        trigger_word = "upper clothing, fashion item"

    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    generator = torch.Generator(device="cuda").manual_seed(seed)

    image = pipe(
        prompt=f"{actual_prompt} {trigger_word}",
        num_inference_steps=steps,
        guidance_scale=cfg_scale,
        width=width,
        height=height,
        generator=generator,
        joint_attention_kwargs={"scale": lora_scale},
    ).images[0]

    return image, seed

with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange") as app:
    gr.Markdown("# 🎭 Fashion AI Studio")
    
    with gr.Column():
        mode = gr.Radio(
            choices=["Person", "Clothes"],
            label="Generation",
            value="Fashion Model"
        )
        
        prompt = gr.TextArea(
            label="✍️ Prompt (ν•œκΈ€ 지원)",
            placeholder="Text Input Prompt",
            lines=3
        )
        
        # μ˜ˆμ‹œ μ„Ήμ…˜μ„ λͺ¨λ“œλ³„λ‘œ 뢄리
        with gr.Column(visible=True) as model_examples_container:
            gr.Examples(
                examples=model_examples,
                inputs=prompt,
                label="Examples(person)"
            )
            
        with gr.Column(visible=False) as clothes_examples_container:
            gr.Examples(
                examples=clothes_examples,
                inputs=prompt,
                label="Examples(clothes)"
            )
        
        result = gr.Image(label="Generated Image")
        generate_button = gr.Button("πŸš€ START")
        
        with gr.Accordion("🎨 OPTION", open=False):
            with gr.Row():
                cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7.0)
                steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=30)
                lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=1, value=0.85)
            
            with gr.Row():
                width = gr.Slider(label="Width", minimum=256, maximum=1536, value=512)
                height = gr.Slider(label="Height", minimum=256, maximum=1536, value=768)
            
            with gr.Row():
                randomize_seed = gr.Checkbox(True, label="μ‹œλ“œ λžœλ€ν™”")
                seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, value=42)

    def update_visibility(mode):
        return (
            gr.update(visible=(mode == "Person")),
            gr.update(visible=(mode == "Clothes"))
        )

    mode.change(
        fn=update_visibility,
        inputs=[mode],
        outputs=[model_examples_container, clothes_examples_container]
    )
    
    generate_button.click(
        generate_fashion,
        inputs=[prompt, mode, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale],
        outputs=[result, seed]
    )

if __name__ == "__main__":
    app.launch(share=True)