Update app.py

app.py

@@ -1,657 +1,35 @@
-# ===== 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/chocs"
-
-# 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
+import sys
+import streamlit as st
+from tempfile import NamedTemporaryFile
 
-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,
-):
+def main():
     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. cho 두 손으로 'Healing !' 현수막을 들고 있는 모습, 환경보호와 지속가능한 임업 발전에 대한 의지를 보여주고 있다.",
-    "Mr. cho 양팔을 들어 올리며 기쁜 표정으로 환호하는 모습, 조림 사업 성공과 미래 임업에 대한 희망을 보여주고 있다.",
-    "Mr. cho 운동복을 입고 산림 속에서 트레킹하는 모습, 건강한 생활습관과 활기찬 리더십을 보여주고 있다.",
-    "Mr. cho 산촌 마을에서 여성 임업인들과 따뜻하게 악수하는 모습, 여성 임업종사자들에 대한 진정한 관심과 소통을 보여주고 있다.",
-    "Mr. cho 임업박람회장에서 울창한 숲을 향해 손가락으로 가리키며 영감을 주는 제스처를 취하고 있고, 여성들과 아이들이 박수를 치고 있다.",
-    "Mr. cho 산림축제에 참여하여 열정적으로 응원하는 여성 임업인들에게 둘러싸여 있는 모습.",
-    "Mr. cho 목재시장을 방문하여 여성 목재상들과 목공예 장인들과 친근하게 대화하는 모습.",
-    "Mr. cho 산림과학원을 둘러보며 여성 연구원들과 교수들과 함께 임업 정책에 대해 토론하는 모습.",
-    "Mr. cho 대규모 임업인 대���에서 자신감 있는 제스처와 결연한 표정으로 역동적인 연설을 하는 모습.",
-    "Mr. cho 활기찬 인터뷰 현장에서 미래 임업 발전에 대한 비전을 열정적으로 설명하는 모습.",
-    "Mr. cho 중요한 임업정책 회의를 준비하며 서류들에 둘러싸여 집중하고 단호한 모습을 보이는 모습."
-]
-
-# ===== 커스텀 CSS (진한 붉은색 고급 디자인) =====
-custom_css = """
-:root {
-    --color-primary: #E91E63;
-    --color-secondary: #FCE4EC;
-    --color-accent: #F8BBD9;
-    --color-rose: #F06292;
-    --color-gold: #FFB74D;
-    --color-warm-gray: #F5F5F5;
-    --color-dark-gray: #424242;
-    --background-primary: linear-gradient(135deg, #FAFAFA 0%, #F5F5F5 50%, #EEEEEE 100%);
-    --background-accent: linear-gradient(135deg, #FCE4EC 0%, #F8BBD9 100%);
-    --text-primary: #212121;
-    --text-secondary: #757575;
-    --shadow-soft: 0 4px 20px rgba(0, 0, 0, 0.08);
-    --shadow-medium: 0 8px 30px rgba(0, 0, 0, 0.12);
-    --border-radius: 16px;
-}
-
-/* 전체 배경 */
-footer {visibility: hidden;}
-.gradio-container {
-    background: var(--background-primary) !important;
-    min-height: 100vh;
-    font-family: 'Inter', 'Noto Sans KR', sans-serif;
-}
-
-/* 타이틀 스타일 */
-.title {
-    color: var(--text-primary) !important;
-    font-size: 3rem !important;
-    font-weight: 700 !important;
-    text-align: center;
-    margin: 2rem 0;
-    background: linear-gradient(135deg, var(--color-primary) 0%, var(--color-rose) 50%, var(--color-gold) 100%);
-    -webkit-background-clip: text;
-    -webkit-text-fill-color: transparent;
-    background-clip: text;
-    letter-spacing: -0.02em;
-}
-
-.subtitle {
-    color: var(--text-secondary) !important;
-    font-size: 1.2rem !important;
-    text-align: center;
-    margin-bottom: 2rem;
-    font-weight: 400;
-}
-
-.collection-link {
-    text-align: center;
-    margin-bottom: 2rem;
-    font-size: 1rem;
-}
-
-.collection-link a {
-    color: var(--color-primary);
-    text-decoration: none;
-    transition: all 0.3s ease;
-    font-weight: 500;
-    border-bottom: 1px solid transparent;
-}
-
-.collection-link a:hover {
-    color: var(--color-rose);
-    border-bottom-color: var(--color-rose);
-}
-
-/* 심플한 카드 스타일 */
-.model-description {
-    background: rgba(255, 255, 255, 0.9);
-    border: 1px solid rgba(233, 30, 99, 0.1);
-    border-radius: var(--border-radius);
-    padding: 2rem;
-    margin: 1.5rem 0;
-    box-shadow: var(--shadow-soft);
-    backdrop-filter: blur(10px);
-    -webkit-backdrop-filter: blur(10px);
-}
-
-.model-description p {
-    color: var(--text-primary) !important;
-    font-size: 1rem;
-    line-height: 1.6;
-    margin: 0;
-}
-
-/* 버튼 스타일 */
-button.primary {
-    background: var(--background-accent) !important;
-    color: var(--color-primary) !important;
-    border: 1px solid var(--color-accent) !important;
-    border-radius: 12px !important;
-    box-shadow: var(--shadow-soft) !important;
-    transition: all 0.2s ease !important;
-    font-weight: 600 !important;
-    font-size: 0.95rem !important;
-}
-
-button.primary:hover {
-    background: linear-gradient(135deg, var(--color-accent) 0%, var(--color-secondary) 100%) !important;
-    transform: translateY(-1px) !important;
-    box-shadow: var(--shadow-medium) !important;
-}
-
-/* 입력 컨테이너 */
-.input-container {
-    background: rgba(255, 255, 255, 0.8);
-    border: 1px solid rgba(233, 30, 99, 0.15);
-    border-radius: var(--border-radius);
-    padding: 1.5rem;
-    margin-bottom: 1.5rem;
-    box-shadow: var(--shadow-soft);
-    backdrop-filter: blur(10px);
-    -webkit-backdrop-filter: blur(10px);
-}
-
-/* 고급 설정 */
-.advanced-settings {
-    background: rgba(255, 255, 255, 0.6);
-    border: 1px solid rgba(233, 30, 99, 0.1);
-    border-radius: var(--border-radius);
-    padding: 1.5rem;
-    margin-top: 1rem;
-    box-shadow: var(--shadow-soft);
-    backdrop-filter: blur(8px);
-    -webkit-backdrop-filter: blur(8px);
-}
-
-/* 예시 영역 */
-.example-region {
-    background: rgba(252, 228, 236, 0.3);
-    border: 1px solid rgba(233, 30, 99, 0.15);
-    border-radius: var(--border-radius);
-    padding: 1.5rem;
-    margin-top: 1rem;
-    box-shadow: var(--shadow-soft);
-}
-
-/* 프롬프트 입력칸 스타일 */
-.large-prompt textarea {
-    min-height: 120px !important;
-    font-size: 15px !important;
-    line-height: 1.5 !important;
-    background: rgba(255, 255, 255, 0.9) !important;
-    border: 2px solid rgba(233, 30, 99, 0.2) !important;
-    border-radius: 12px !important;
-    color: var(--text-primary) !important;
-    transition: all 0.3s ease !important;
-    padding: 1rem !important;
-}
-
-.large-prompt textarea:focus {
-    border-color: var(--color-primary) !important;
-    box-shadow: 0 0 0 3px rgba(233, 30, 99, 0.1) !important;
-    outline: none !important;
-}
-
-.large-prompt textarea::placeholder {
-    color: var(--text-secondary) !important;
-    font-style: italic;
-}
-
-/* 생성 버튼 */
-.small-generate-btn {
-    max-width: 140px !important;
-    height: 48px !important;
-    font-size: 15px !important;
-    padding: 12px 24px !important;
-    border-radius: 12px !important;
-    font-weight: 600 !important;
-}
-
-/* 프롬프트 증강 섹션 */
-.prompt-enhance-section {
-    background: linear-gradient(135deg, rgba(255, 183, 77, 0.1) 0%, rgba(252, 228, 236, 0.2) 100%);
-    border: 1px solid rgba(255, 183, 77, 0.3);
-    border-radius: var(--border-radius);
-    padding: 1.2rem;
-    margin-top: 1rem;
-    box-shadow: var(--shadow-soft);
-}
-
-/* 스타일 프리셋 섹션 */
-.style-preset-section {
-    background: linear-gradient(135deg, rgba(248, 187, 217, 0.15) 0%, rgba(252, 228, 236, 0.2) 100%);
-    border: 1px solid rgba(233, 30, 99, 0.2);
-    border-radius: var(--border-radius);
-    padding: 1.2rem;
-    margin-top: 1rem;
-    box-shadow: var(--shadow-soft);
-}
-
-/* 라벨 텍스트 */
-label {
-    color: var(--text-primary) !important;
-    font-weight: 600 !important;
-    font-size: 0.95rem !important;
-}
-
-/* 정보 텍스트 */
-.gr-info, .gr-textbox-info {
-    color: var(--text-secondary) !important;
-    font-size: 0.85rem !important;
-    line-height: 1.4 !important;
-}
-
-/* 예시 마크다운 */
-.example-region h3 {
-    color: var(--text-primary) !important;
-    font-weight: 600 !important;
-    margin-bottom: 1rem !important;
-}
-
-/* 폼 요소들 */
-input[type="radio"], input[type="checkbox"] {
-    accent-color: var(--color-primary) !important;
-}
-
-input[type="range"] {
-    accent-color: var(--color-primary) !important;
-}
-
-/* 결과 이미지 컨테이너 */
-.image-container {
-    border-radius: var(--border-radius) !important;
-    overflow: hidden !important;
-    box-shadow: var(--shadow-medium) !important;
-    background: rgba(255, 255, 255, 0.9) !important;
-    border: 1px solid rgba(233, 30, 99, 0.1) !important;
-}
-
-/* 슬라이더 컨테이너 스타일링 */
-.gr-slider {
-    margin: 0.5rem 0 !important;
-}
-
-/* 아코디언 스타일 */
-.gr-accordion {
-    border: 1px solid rgba(233, 30, 99, 0.15) !important;
-    border-radius: var(--border-radius) !important;
-    background: rgba(255, 255, 255, 0.7) !important;
-}
-
-.gr-accordion-header {
-    background: var(--background-accent) !important;
-    color: var(--color-primary) !important;
-    font-weight: 600 !important;
-    border-radius: var(--border-radius) var(--border-radius) 0 0 !important;
-}
-
-/* 부드러운 애니메이션 */
-.model-description, .input-container, .prompt-enhance-section, .style-preset-section {
-    animation: fadeInUp 0.4s ease-out;
-}
-
-@keyframes fadeInUp {
-    from {
-        opacity: 0;
-        transform: translateY(20px);
-    }
-    to {
-        opacity: 1;
-        transform: translateY(0);
-    }
-}
-
-/* 전체적인 텍스트 가독성 향상 */
-* {
-    -webkit-font-smoothing: antialiased;
-    -moz-osx-font-smoothing: grayscale;
-}
-
-/* 드롭다운 및 셀렉트 스타일 */
-select, .gr-dropdown {
-    background: rgba(255, 255, 255, 0.9) !important;
-    border: 1px solid rgba(233, 30, 99, 0.2) !important;
-    border-radius: 8px !important;
-    color: var(--text-primary) !important;
-}
-
-/* 체크박스와 라디오 버튼 개선 */
-.gr-checkbox, .gr-radio {
-    background: transparent !important;
-}
-
-/* 전체 컨테이너 여백 조정 */
-.gr-container {
-    max-width: 1200px !important;
-    margin: 0 auto !important;
-    padding: 2rem 1rem !important;
-}
-
-/* 모바일 반응형 */
-@media (max-width: 768px) {
-    .title {
-        font-size: 2.2rem !important;
-    }
-    
-    .model-description, .input-container, .advanced-settings, .example-region {
-        padding: 1rem !important;
-        margin: 1rem 0 !important;
-    }
-    
-    .large-prompt textarea {
-        min-height: 100px !important;
-        font-size: 14px !important;
-    }
-}
-"""
-
-# ===== Gradio UI =====
-def create_interface():
-    with gr.Blocks(css=custom_css, analytics_enabled=False) as demo:
-        with gr.Group(elem_classes="model-description"):
-            gr.HTML("""
-            <p>
-            <strong>Mr. CHO CS</strong><br>
-            <small style="opacity: 0.8;">본 모델은 연구 목적으로 특정인의 얼굴과 외모를 LoRA 기술로 학습한 모델입니다.목적 외의 용도로 무단 사용하지 않도록 유의해 주세요. 프롬프트에 'cho'을 포함하여 주세요.</small><br><br>
-            """)
-
-        # ===== 메인 입력 =====
-        with gr.Column():
-            with gr.Row(elem_classes="input-container"):
-                with gr.Column(scale=4):
-                    user_prompt = gr.Text(
-                        label="Prompt (프롬프트)", 
-                        max_lines=5, 
-                        value=examples[0],
-                        elem_classes="large-prompt",
-                        placeholder="Enter your image description here... (이미지 설명을 입력하세요...)"
-                    )
-                with gr.Column(scale=1):
-                    run_button = gr.Button(
-                        "Generate (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="🚀 Prompt Enhancement (프롬프트 증강)", 
-                    value=False,
-                    info="Automatically improve your prompt using OpenAI API for high-quality image generation (OpenAI API를 사용하여 고품질 이미지 생성을 위해 프롬프트를 자동으로 개선합니다)"
-                )
+        # Get the code from secrets
+        code = os.environ.get("MAIN_CODE")
+        
+        if not code:
+            st.error("⚠️ The application code wasn't found in secrets. Please add the MAIN_CODE secret.")
+            return
+        
+        # Create a temporary Python file
+        with NamedTemporaryFile(suffix='.py', delete=False, mode='w') as tmp:
+            tmp.write(code)
+            tmp_path = tmp.name
+        
+        # Execute the code
+        exec(compile(code, tmp_path, 'exec'), globals())
+        
+        # Clean up the temporary file
+        try:
+            os.unlink(tmp_path)
+        except:
+            pass
             
-            # 스타일 프리셋 섹션
-            with gr.Group(elem_classes="style-preset-section"):
-                style_select = gr.Radio(
-                    label="🎨 Style Preset (스타일 프리셋)", 
-                    choices=list(STYLE_PRESETS.keys()), 
-                    value="None", 
-                    interactive=True
-                )
-
-            result_image = gr.Image(label="Generated Image (생성된 이미지)")
-            seed_output = gr.Number(label="Seed (시드값)")
-
-            # ===== 고급 설정 =====
-            with gr.Accordion("Advanced Settings (고급 설정)", open=False, elem_classes="advanced-settings"):
-                seed = gr.Slider(label="Seed (시드값)", minimum=0, maximum=MAX_SEED, step=1, value=42)
-                randomize_seed = gr.Checkbox(label="Randomize seed (시드값 무작위)", value=True)
-                with gr.Row():
-                    width = gr.Slider(label="Width (가로)", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024)
-                    height = gr.Slider(label="Height (세로)", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=768)
-                with gr.Row():
-                    guidance_scale = gr.Slider(label="Guidance scale (가이던스 스케일)", minimum=0.0, maximum=10.0, step=0.1, value=3.5)
-                    num_inference_steps = gr.Slider(label="Inference steps (추론 단계)", minimum=1, maximum=50, step=1, value=30)
-                    lora_scale = gr.Slider(label="LoRA scale (LoRA 스케일)", minimum=0.0, maximum=1.0, step=0.1, value=1.0)
-
-            # ===== 예시 영역 =====
-            with gr.Group(elem_classes="example-region"):
-                gr.Markdown("### Examples (예시)")
-                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
+    except Exception as e:
+        st.error(f"⚠️ Error loading or executing the application: {str(e)}")
+        import traceback
+        st.code(traceback.format_exc())
 
-# ===== 애플리케이션 실행 =====
 if __name__ == "__main__":
-    demo = create_interface()
-    demo.queue()
-    demo.launch()
+    main()