Create app.py

app.py

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+# ===== CRITICAL: Import spaces FIRST before any CUDA operations =====
+try:
+    import spaces
+    HF_SPACES = True
+except ImportError:
+    # If running locally, create a dummy decorator
+    def spaces_gpu_decorator(duration=60):
+        def decorator(func):
+            return func
+        return decorator
+    spaces = type('spaces', (), {'GPU': spaces_gpu_decorator})()
+    HF_SPACES = False
+    print("Warning: Running without Hugging Face Spaces GPU allocation")
+
+# ===== Now import other libraries =====
+import random
+import os
+import uuid
+import re
+import time
+from datetime import datetime
+
+import gradio as gr
+import numpy as np
+import requests
+import torch
+from diffusers import DiffusionPipeline
+from PIL import Image
+
+# ===== OpenAI 설정 =====
+from openai import OpenAI
+
+# Add error handling for API key
+try:
+    client = OpenAI(api_key=os.getenv("LLM_API"))
+except Exception as e:
+    print(f"Warning: OpenAI client initialization failed: {e}")
+    client = None
+
+# ===== 프롬프트 증강용 스타일 프리셋 =====
+STYLE_PRESETS = {
+    "None": "",
+    "Realistic Photo": "photorealistic, 8k, ultra-detailed, cinematic lighting, realistic skin texture",
+    "Oil Painting": "oil painting, rich brush strokes, canvas texture, baroque lighting",
+    "Comic Book": "comic book style, bold ink outlines, cel shading, vibrant colors",
+    "Watercolor": "watercolor illustration, soft gradients, splatter effect, pastel palette",
+}
+
+# ===== 저장 폴더 =====
+SAVE_DIR = "saved_images"
+if not os.path.exists(SAVE_DIR):
+    os.makedirs(SAVE_DIR, exist_ok=True)
+
+# ===== 디바이스 & 모델 로드 =====
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"Using device: {device}")
+
+repo_id = "black-forest-labs/FLUX.1-dev"
+adapter_id = "seawolf2357/kim-korea"
+
+# Add error handling for model loading
+try:
+    pipeline = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
+    pipeline.load_lora_weights(adapter_id)
+    pipeline = pipeline.to(device)
+    print("Model loaded successfully")
+except Exception as e:
+    print(f"Error loading model: {e}")
+    pipeline = None
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 1024
+
+# ===== 한글 여부 판별 =====
+HANGUL_RE = re.compile(r"[\u3131-\u318E\uAC00-\uD7A3]+")
+
+def is_korean(text: str) -> bool:
+    return bool(HANGUL_RE.search(text))
+
+# ===== 번역 & 증강 함수 =====
+
+def openai_translate(text: str, retries: int = 3) -> str:
+    """한글을 영어로 번역 (OpenAI GPT-4o-mini 사용). 영어 입력이면 그대로 반환."""
+    if not is_korean(text):
+        return text
+    
+    if client is None:
+        print("Warning: OpenAI client not available, returning original text")
+        return text
+
+    for attempt in range(retries):
+        try:
+            res = client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": "Translate the following Korean prompt into concise, descriptive English suitable for an image generation model. Keep the meaning, do not add new concepts."
+                    },
+                    {"role": "user", "content": text}
+                ],
+                temperature=0.3,
+                max_tokens=256,
+            )
+            return res.choices[0].message.content.strip()
+        except Exception as e:
+            print(f"[translate] attempt {attempt + 1} failed: {e}")
+            time.sleep(2)
+    return text  # 번역 실패 시 원문 그대로
+
+def enhance_prompt(text: str, retries: int = 3) -> str:
+    """OpenAI를 통해 프롬프트를 증강하여 고품질 이미지 생성을 위한 상세한 설명으로 변환."""
+    if client is None:
+        print("Warning: OpenAI client not available, returning original text")
+        return text
+
+    for attempt in range(retries):
+        try:
+            res = client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": """You are an expert prompt engineer for image generation models. Enhance the given prompt to create high-quality, detailed images.
+
+Guidelines:
+- Add specific visual details (lighting, composition, colors, textures)
+- Include technical photography terms (depth of field, focal length, etc.)
+- Add atmosphere and mood descriptors
+- Specify image quality terms (4K, ultra-detailed, professional, etc.)
+- Keep the core subject and meaning intact
+- Make it comprehensive but not overly long
+- Focus on visual elements that will improve image generation quality
+
+Example:
+Input: "A man giving a speech"
+Output: "A professional man giving an inspiring speech at a podium, dramatic lighting with warm spotlights, confident posture and gestures, high-resolution 4K photography, sharp focus, cinematic composition, bokeh background with audience silhouettes, professional event setting, detailed facial expressions, realistic skin texture"
+"""
+                    },
+                    {"role": "user", "content": f"Enhance this prompt for high-quality image generation: {text}"}
+                ],
+                temperature=0.7,
+                max_tokens=512,
+            )
+            return res.choices[0].message.content.strip()
+        except Exception as e:
+            print(f"[enhance] attempt {attempt + 1} failed: {e}")
+            time.sleep(2)
+    return text  # 증강 실패 시 원문 그대로
+
+def prepare_prompt(user_prompt: str, style_key: str, enhance_prompt_enabled: bool = False) -> str:
+    """한글이면 번역하고, 프롬프트 증강 옵션이 활성화되면 증강하고, 선택한 스타일 프리셋을 붙여서 최종 프롬프트를 만든다."""
+    # 1. 번역 (한글인 경우)
+    prompt_en = openai_translate(user_prompt)
+    
+    # 2. 프롬프트 증강 (활성화된 경우)
+    if enhance_prompt_enabled:
+        prompt_en = enhance_prompt(prompt_en)
+        print(f"Enhanced prompt: {prompt_en}")
+    
+    # 3. 스타일 프리셋 적용
+    style_suffix = STYLE_PRESETS.get(style_key, "")
+    if style_suffix:
+        final_prompt = f"{prompt_en}, {style_suffix}"
+    else:
+        final_prompt = prompt_en
+    
+    return final_prompt
+
+# ===== 이미지 저장 =====
+
+def save_generated_image(image: Image.Image, prompt: str) -> str:
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    unique_id = str(uuid.uuid4())[:8]
+    filename = f"{timestamp}_{unique_id}.png"
+    filepath = os.path.join(SAVE_DIR, filename)
+    image.save(filepath)
+
+    # 메타데이터 저장
+    metadata_file = os.path.join(SAVE_DIR, "metadata.txt")
+    with open(metadata_file, "a", encoding="utf-8") as f:
+        f.write(f"{filename}|{prompt}|{timestamp}\n")
+    return filepath
+
+# ===== Diffusion 호출 =====
+
+def run_pipeline(prompt: str, seed: int, width: int, height: int, guidance_scale: float, num_steps: int, lora_scale: float):
+    if pipeline is None:
+        raise ValueError("Model pipeline not loaded")
+    
+    generator = torch.Generator(device=device).manual_seed(int(seed))
+    result = pipeline(
+        prompt=prompt,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_steps,
+        width=width,
+        height=height,
+        generator=generator,
+        joint_attention_kwargs={"scale": lora_scale},
+    ).images[0]
+    return result
+
+# ===== Gradio inference 래퍼 =====
+
+@spaces.GPU(duration=60)
+def generate_image(
+    user_prompt: str,
+    style_key: str,
+    enhance_prompt_enabled: bool = False,
+    seed: int = 42,
+    randomize_seed: bool = True,
+    width: int = 1024,
+    height: int = 768,
+    guidance_scale: float = 3.5,
+    num_inference_steps: int = 30,
+    lora_scale: float = 1.0,
+    progress=None,
+):
+    try:
+        if randomize_seed:
+            seed = random.randint(0, MAX_SEED)
+
+        # 1) 번역 + 증강
+        final_prompt = prepare_prompt(user_prompt, style_key, enhance_prompt_enabled)
+        print(f"Final prompt: {final_prompt}")
+
+        # 2) 파이프라인 호출
+        image = run_pipeline(final_prompt, seed, width, height, guidance_scale, num_inference_steps, lora_scale)
+
+        # 3) 저장
+        save_generated_image(image, final_prompt)
+
+        return image, seed
+    
+    except Exception as e:
+        print(f"Error generating image: {e}")
+        # Return a placeholder or error message
+        error_image = Image.new('RGB', (width, height), color='red')
+        return error_image, seed
+
+# ===== 예시 프롬프트 (한국어/영어 혼용 허용) =====
+
+examples = [
+    "Mr. KIM이 두 손으로 'Fighting!' 현수막을 들고 있는 모습, 애국심과 국가 발전에 대한 의지를 보여주고 있다.",   
+    "Mr. KIM이 양팔을 들어 올리며 승리의 표정으로 환호하는 모습, 승리와 미래에 대한 희망을 보여주고 있다.",
+    "Mr. KIM이 운동복을 입고 공원에서 조깅하는 모습, 건강한 생활습관과 활기찬 리더십을 보여주고 있다.",  
+    "Mr. KIM이 붐비는 거리에서 여성 시민들과 따뜻하게 악수하는 모습, 여성 유권자들에 대한 진정한 관심과 소통을 보여주고 있다.",
+    "Mr. KIM이 선거 유세장에서 지평선을 향해 손가락으로 가리키며 영감을 주는 제스처를 취하고 있고, 여성들과 아이들이 박수를 치고 있다.",
+    "Mr. KIM이 지역 행사에 참여하여 열정적으로 응원하는 여성 지지자들에게 둘러싸여 있는 모습.",
+    "Mr. KIM visiting a local market, engaging in friendly conversation with female vendors and shopkeepers.",
+    "Mr. KIM walking through a university campus, discussing education policies with female students and professors.",    
+    "Mr. KIM delivering a powerful speech in front of a large crowd with confident gestures and determined expression.",
+    "Mr. KIM in a dynamic interview setting, passionately outlining his visions for the future.",
+    "Mr. KIM preparing for an important debate, surrounded by paperwork, looking focused and resolute.",
+]
+
+# ===== 커스텀 CSS (진한 붉은색 고급 디자인) =====
+custom_css = """
+:root {
+    --color-primary: #8F1A3A;
+    --color-secondary: #FF4B4B;
+    --color-accent: #B91C3C;
+    --color-dark-red: #7F1D1D;
+    --color-gold: #D4AF37;
+    --background-fill-primary: linear-gradient(135deg, #450A0A 0%, #7F1D1D 25%, #991B1B 50%, #B91C3C 75%, #DC2626 100%);
+    --glass-bg: rgba(255, 255, 255, 0.1);
+    --glass-border: rgba(255, 255, 255, 0.2);
+    --shadow-primary: 0 25px 50px -12px rgba(0, 0, 0, 0.5);
+    --shadow-secondary: 0 10px 25px -3px rgba(0, 0, 0, 0.3);
+    --shadow-accent: 0 4px 15px rgba(185, 28, 60, 0.4);
+}
+
+/* 전체 배경 */
+footer {visibility: hidden;}
+.gradio-container {
+    background: var(--background-fill-primary) !important;
+    min-height: 100vh;
+    position: relative;
+}
+
+/* 배경에 패턴 추가 */
+.gradio-container::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: 0;
+    right: 0;
+    bottom: 0;
+    background-image: 
+        radial-gradient(circle at 25% 25%, rgba(255, 255, 255, 0.1) 0%, transparent 50%),
+        radial-gradient(circle at 75% 75%, rgba(212, 175, 55, 0.1) 0%, transparent 50%);
+    pointer-events: none;
+    z-index: 1;
+}
+
+/* 메인 콘텐츠 z-index */
+.gradio-container > * {
+    position: relative;
+    z-index: 2;
+}
+
+/* 타이틀 스타일 */
+.title {
+    color: #FFFFFF !important;
+    font-size: 3.5rem !important;
+    font-weight: 800 !important;
+    text-align: center;
+    margin: 2rem 0;
+    font-family: 'Playfair Display', serif;
+    text-shadow: 0 4px 8px rgba(0, 0, 0, 0.5);
+    background: linear-gradient(135deg, #FFFFFF 0%, var(--color-gold) 50%, #FFFFFF 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
+}
+
+.subtitle {
+    color: #F3F4F6 !important;
+    font-size: 1.3rem !important;
+    text-align: center;
+    margin-bottom: 2rem;
+    font-style: italic;
+    text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
+}
+
+.collection-link {
+    text-align: center;
+    margin-bottom: 2rem;
+    font-size: 1.1rem;
+}
+
+.collection-link a {
+    color: var(--color-gold);
+    text-decoration: none;
+    transition: all 0.3s ease;
+    font-weight: 600;
+    text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
+}
+
+.collection-link a:hover {
+    color: #F59E0B;
+    text-shadow: 0 4px 8px rgba(245, 158, 11, 0.5);
+}
+
+/* 고급스러운 3D 박스 스타일 */
+.model-description {
+    background: linear-gradient(135deg, var(--glass-bg) 0%, rgba(255, 255, 255, 0.05) 100%);
+    backdrop-filter: blur(20px);
+    -webkit-backdrop-filter: blur(20px);
+    border: 1px solid var(--glass-border);
+    border-radius: 20px;
+    padding: 30px;
+    margin: 25px 0;
+    box-shadow: 
+        var(--shadow-primary),
+        inset 0 1px 0 rgba(255, 255, 255, 0.2),
+        0 0 30px rgba(185, 28, 60, 0.2);
+    position: relative;
+    overflow: hidden;
+    transform: translateZ(0);
+}
+
+.model-description::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: 0;
+    right: 0;
+    height: 1px;
+    background: linear-gradient(90deg, transparent, var(--color-gold), transparent);
+}
+
+.model-description p {
+    color: #F9FAFB !important;
+    font-size: 1.1rem;
+    line-height: 1.6;
+    text-shadow: 0 1px 2px rgba(0, 0, 0, 0.5);
+}
+
+/* 버튼 스타일 */
+button.primary {
+    background: linear-gradient(135deg, var(--color-primary) 0%, var(--color-accent) 100%) !important;
+    color: #FFFFFF !important;
+    border: none !important;
+    box-shadow: 
+        var(--shadow-accent),
+        inset 0 1px 0 rgba(255, 255, 255, 0.2) !important;
+    transition: all 0.3s ease !important;
+    font-weight: 600 !important;
+    text-transform: uppercase !important;
+    letter-spacing: 0.5px !important;
+}
+
+button.primary:hover {
+    transform: translateY(-3px) !important;
+    box-shadow: 
+        0 20px 40px rgba(185, 28, 60, 0.4),
+        inset 0 1px 0 rgba(255, 255, 255, 0.2) !important;
+    background: linear-gradient(135deg, var(--color-accent) 0%, #DC2626 100%) !important;
+}
+
+/* 입력 컨테이너 */
+.input-container {
+    background: linear-gradient(135deg, var(--glass-bg) 0%, rgba(255, 255, 255, 0.08) 100%);
+    backdrop-filter: blur(25px);
+    -webkit-backdrop-filter: blur(25px);
+    border: 1px solid var(--glass-border);
+    border-radius: 20px;
+    padding: 25px;
+    margin-bottom: 2rem;
+    box-shadow: var(--shadow-secondary);
+    position: relative;
+    overflow: hidden;
+}
+
+.input-container::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: 0;
+    right: 0;
+    height: 2px;
+    background: linear-gradient(90deg, var(--color-primary), var(--color-gold), var(--color-primary));
+}
+
+/* 고급 설정 */
+.advanced-settings {
+    background: linear-gradient(135deg, rgba(0, 0, 0, 0.3) 0%, rgba(0, 0, 0, 0.1) 100%);
+    backdrop-filter: blur(15px);
+    -webkit-backdrop-filter: blur(15px);
+    border: 1px solid rgba(255, 255, 255, 0.1);
+    border-radius: 16px;
+    padding: 20px;
+    margin-top: 1.5rem;
+    box-shadow: var(--shadow-secondary);
+}
+
+/* 예시 영역 */
+.example-region {
+    background: linear-gradient(135deg, rgba(0, 0, 0, 0.2) 0%, rgba(0, 0, 0, 0.05) 100%);
+    backdrop-filter: blur(20px);
+    -webkit-backdrop-filter: blur(20px);
+    border: 1px solid rgba(255, 255, 255, 0.15);
+    border-radius: 16px;
+    padding: 20px;
+    margin-top: 1.5rem;
+    box-shadow: var(--shadow-secondary);
+}
+
+/* 프롬프트 입력칸 크기 2배 증가 + 스타일 */
+.large-prompt textarea {
+    min-height: 120px !important;
+    font-size: 16px !important;
+    line-height: 1.5 !important;
+    background: rgba(0, 0, 0, 0.3) !important;
+    border: 2px solid rgba(255, 255, 255, 0.2) !important;
+    border-radius: 12px !important;
+    color: #FFFFFF !important;
+    backdrop-filter: blur(10px) !important;
+    transition: all 0.3s ease !important;
+}
+
+.large-prompt textarea:focus {
+    border-color: var(--color-gold) !important;
+    box-shadow: 0 0 20px rgba(212, 175, 55, 0.3) !important;
+}
+
+.large-prompt textarea::placeholder {
+    color: rgba(255, 255, 255, 0.6) !important;
+}
+
+/* 생성 버튼 작게 만들기 + 3D 효과 */
+.small-generate-btn {
+    max-width: 120px !important;
+    height: 45px !important;
+    font-size: 14px !important;
+    padding: 10px 20px !important;
+    border-radius: 12px !important;
+    position: relative !important;
+    overflow: hidden !important;
+}
+
+.small-generate-btn::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: -100%;
+    width: 100%;
+    height: 100%;
+    background: linear-gradient(90deg, transparent, rgba(255, 255, 255, 0.2), transparent);
+    transition: left 0.5s ease;
+}
+
+.small-generate-btn:hover::before {
+    left: 100%;
+}
+
+/* 프롬프트 증강 섹션 스타일 */
+.prompt-enhance-section {
+    background: linear-gradient(135deg, rgba(212, 175, 55, 0.15) 0%, rgba(212, 175, 55, 0.05) 100%);
+    backdrop-filter: blur(15px);
+    -webkit-backdrop-filter: blur(15px);
+    border: 1px solid rgba(212, 175, 55, 0.3);
+    border-radius: 15px;
+    padding: 20px;
+    margin-top: 15px;
+    box-shadow: 
+        0 8px 25px rgba(0, 0, 0, 0.2),
+        inset 0 1px 0 rgba(255, 255, 255, 0.1);
+    position: relative;
+}
+
+.prompt-enhance-section::before {
+    content: '';
+    position: absolute;
+    top: 0;
+    left: 20px;
+    right: 20px;
+    height: 1px;
+    background: linear-gradient(90deg, transparent, var(--color-gold), transparent);
+}
+
+/* 스타일 프리셋 섹션 */
+.style-preset-section {
+    background: linear-gradient(135deg, rgba(255, 255, 255, 0.1) 0%, rgba(255, 255, 255, 0.05) 100%);
+    backdrop-filter: blur(15px);
+    -webkit-backdrop-filter: blur(15px);
+    border: 1px solid rgba(255, 255, 255, 0.2);
+    border-radius: 15px;
+    padding: 20px;
+    margin-top: 15px;
+    box-shadow: var(--shadow-secondary);
+}
+
+/* 라벨 텍스트 색상 */
+label {
+    color: #F9FAFB !important;
+    font-weight: 600 !important;
+    text-shadow: 0 1px 2px rgba(0, 0, 0, 0.5) !important;
+}
+
+/* 라디오 버튼 및 체크박스 스타일 */
+input[type="radio"], input[type="checkbox"] {
+    accent-color: var(--color-gold) !important;
+}
+
+/* 슬라이더 스타일 */
+input[type="range"] {
+    accent-color: var(--color-gold) !important;
+}
+
+/* 결과 이미지 컨테이너 */
+.image-container {
+    border-radius: 16px !important;
+    overflow: hidden !important;
+    box-shadow: var(--shadow-primary) !important;
+    background: rgba(0, 0, 0, 0.3) !important;
+    backdrop-filter: blur(10px) !important;
+}
+
+/* 애니메이션 추가 */
+@keyframes shimmer {
+    0% { transform: translateX(-100%); }
+    100% { transform: translateX(100%); }
+}
+
+.model-description, .input-container, .prompt-enhance-section, .style-preset-section {
+    animation: fadeInUp 0.6s ease-out;
+}
+
+@keyframes fadeInUp {
+    from {
+        opacity: 0;
+        transform: translateY(30px);
+    }
+    to {
+        opacity: 1;
+        transform: translateY(0);
+    }
+}
+"""
+
+# ===== Gradio UI =====
+def create_interface():
+    with gr.Blocks(css=custom_css, analytics_enabled=False) as demo:
+        gr.HTML('<div class="title">Mr. KIM in KOREA</div>')
+        gr.HTML('<div class="collection-link"><a href="https://huggingface.co/collections/openfree/painting-art-ai-681453484ec15ef5978bbeb1" target="_blank">Visit the LoRA Model Collection</a></div>')
+
+        with gr.Group(elem_classes="model-description"):
+            gr.HTML("""
+            <p>
+            본 모델은 연구 목적으로 특정인의 얼굴과 외모를 학습한 LoRA 모델입니다.<br>
+            목적외의 용도로 무단 사용 않도록 유의해 주세요.<br>
+            (예시 prompt 사용 시 반드시 'kim'을 포함하여야 최적의 결과를 얻을 수 있습니다.)
+            </p>
+            """)
+
+        # ===== 메인 입력 =====
+        with gr.Column():
+            with gr.Row(elem_classes="input-container"):
+                with gr.Column(scale=4):
+                    user_prompt = gr.Text(
+                        label="Prompt", 
+                        max_lines=5, 
+                        value=examples[0],
+                        elem_classes="large-prompt"
+                    )
+                with gr.Column(scale=1):
+                    run_button = gr.Button(
+                        "생성", 
+                        variant="primary",
+                        elem_classes="small-generate-btn"
+                    )
+            
+            # 프롬프트 증강 옵션 (생성 버튼 아래)
+            with gr.Group(elem_classes="prompt-enhance-section"):
+                enhance_prompt_checkbox = gr.Checkbox(
+                    label="🚀 프롬프트 증강 (AI로 프롬프트를 자동으로 개선하여 고품질 이미지 생성)", 
+                    value=False,
+                    info="OpenAI API를 사용하여 입력한 프롬프트를 더욱 상세하고 고품질의 이미지를 생성할 수 있도록 자동으로 증강합니다."
+                )
+            
+            # 스타일 프리셋 섹션
+            with gr.Group(elem_classes="style-preset-section"):
+                style_select = gr.Radio(
+                    label="🎨 Style Preset", 
+                    choices=list(STYLE_PRESETS.keys()), 
+                    value="None", 
+                    interactive=True
+                )
+
+            result_image = gr.Image(label="Generated Image")
+            seed_output = gr.Number(label="Seed")
+
+            # ===== 고급 설정 =====
+            with gr.Accordion("Advanced Settings", open=False, elem_classes="advanced-settings"):
+                seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=42)
+                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                with gr.Row():
+                    width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024)
+                    height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=768)
+                with gr.Row():
+                    guidance_scale = gr.Slider(label="Guidance scale", minimum=0.0, maximum=10.0, step=0.1, value=3.5)
+                    num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=50, step=1, value=30)
+                    lora_scale = gr.Slider(label="LoRA scale", minimum=0.0, maximum=1.0, step=0.1, value=1.0)
+
+            # ===== 예시 영역 =====
+            with gr.Group(elem_classes="example-region"):
+                gr.Markdown("### Examples")
+                gr.Examples(examples=examples, inputs=user_prompt, cache_examples=False)
+
+        # ===== 이벤트 =====
+        run_button.click(
+            fn=generate_image,
+            inputs=[
+                user_prompt,
+                style_select,
+                enhance_prompt_checkbox,
+                seed,
+                randomize_seed,
+                width,
+                height,
+                guidance_scale,
+                num_inference_steps,
+                lora_scale,
+            ],
+            outputs=[result_image, seed_output],
+        )
+    
+    return demo
+
+# ===== 애플리케이션 실행 =====
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.queue()
+    demo.launch()