Create app.py

app.py

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+import gradio as gr
+from google import genai 
+from google.genai import types 
+import os
+from typing import Optional, List
+from huggingface_hub import whoami
+from PIL import Image
+from io import BytesIO
+import tempfile
+
+# --- Google Gemini API Configuration ---
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY", "")
+if not GOOGLE_API_KEY:
+    raise ValueError("GOOGLE_API_KEY environment variable not set.")
+
+client = genai.Client(
+    api_key=os.environ.get("GEMINI_API_KEY"),
+)
+
+GEMINI_MODEL_NAME = 'gemini-2.5-flash-image-preview'
+
+def verify_pro_status(token: Optional[gr.OAuthToken]) -> bool:
+    """Verifies if the user is a Hugging Face PRO user or part of an enterprise org."""
+    if not token:
+        return False
+    try:
+        user_info = whoami(token=token.token)
+        if user_info.get("isPro", False):
+            return True
+        orgs = user_info.get("orgs", [])
+        if any(org.get("isEnterprise", False) for org in orgs):
+            return True
+        return False
+    except Exception as e:
+        print(f"Could not verify user's PRO/Enterprise status: {e}")
+        return False
+
+def _extract_image_data_from_response(response) -> Optional[bytes]:
+    """Helper to extract image data from the model's response."""
+    if hasattr(response, 'candidates') and response.candidates:
+        for candidate in response.candidates:
+            if hasattr(candidate, 'content') and hasattr(candidate.content, 'parts') and candidate.content.parts:
+                for part in candidate.content.parts:
+                    if hasattr(part, 'inline_data') and hasattr(part.inline_data, 'data'):
+                        return part.inline_data.data
+    return None
+
+def run_single_image_logic(prompt: str, image_path: Optional[str] = None, progress=gr.Progress()) -> str:
+    """Handles text-to-image or single image-to-image using Google Gemini."""
+    try:
+        progress(0.2, desc="🎨 준비 중...")
+        contents = [prompt]
+        if image_path:
+            input_image = Image.open(image_path)
+            contents.append(input_image)
+
+        progress(0.5, desc="✨ 생성 중...")
+        response = client.models.generate_content( 
+            model=GEMINI_MODEL_NAME,
+            contents=contents,
+        )
+        
+        progress(0.8, desc="🖼️ 마무리 중...")
+        image_data = _extract_image_data_from_response(response)
+        
+        if not image_data:
+            raise ValueError("No image data found in the model response.")
+
+        # Save the generated image to a temporary file to return its path
+        pil_image = Image.open(BytesIO(image_data))
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as tmpfile:
+            pil_image.save(tmpfile.name)
+            progress(1.0, desc="✅ 완료!")
+            return tmpfile.name
+
+    except Exception as e:
+        raise gr.Error(f"이미지 생성 실패: {e}")
+
+
+def run_multi_image_logic(prompt: str, images: List[str], progress=gr.Progress()) -> str:
+    """
+    Handles multi-image editing by sending a list of images and a prompt.
+    """
+    if not images:
+        raise gr.Error("'여러 이미지' 탭에서 최소 한 개의 이미지를 업로드해주세요.")
+    
+    try:
+        progress(0.2, desc="🎨 이미지 준비 중...")
+        contents = [Image.open(image_path[0]) for image_path in images]
+        contents.append(prompt)
+
+        progress(0.5, desc="✨ 생성 중...")
+        response = client.models.generate_content( 
+            model=GEMINI_MODEL_NAME,
+            contents=contents,
+        )
+        
+        progress(0.8, desc="🖼️ 마무리 중...")
+        image_data = _extract_image_data_from_response(response)
+
+        if not image_data:
+            raise ValueError("No image data found in the model response.")
+            
+        pil_image = Image.open(BytesIO(image_data))
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as tmpfile:
+            pil_image.save(tmpfile.name)
+            progress(1.0, desc="✅ 완료!")
+            return tmpfile.name
+            
+    except Exception as e:
+        raise gr.Error(f"이미지 생성 실패: {e}")
+
+
+# --- Gradio App UI ---
+css = '''
+/* Header Styling */
+.main-header {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    padding: 2rem;
+    border-radius: 1rem;
+    margin-bottom: 2rem;
+    box-shadow: 0 10px 30px rgba(0,0,0,0.1);
+}
+
+.header-title {
+    font-size: 2.5rem !important;
+    font-weight: bold;
+    color: white;
+    text-align: center;
+    margin: 0 !important;
+    text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
+}
+
+.header-subtitle {
+    color: rgba(255,255,255,0.9);
+    text-align: center;
+    margin-top: 0.5rem !important;
+    font-size: 1.1rem;
+}
+
+/* Card Styling */
+.card {
+    background: white;
+    border-radius: 1rem;
+    padding: 1.5rem;
+    box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+    border: 1px solid rgba(0,0,0,0.05);
+}
+
+.dark .card {
+    background: #1f2937;
+    border: 1px solid #374151;
+}
+
+/* Tab Styling */
+.tabs {
+    border-radius: 0.5rem;
+    overflow: hidden;
+    margin-bottom: 1rem;
+}
+
+.tabitem {
+    padding: 1rem !important;
+}
+
+button.selected {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    color: white !important;
+}
+
+/* Button Styling */
+.generate-btn {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    border: none !important;
+    color: white !important;
+    font-size: 1.1rem !important;
+    font-weight: 600 !important;
+    padding: 0.8rem 2rem !important;
+    border-radius: 0.5rem !important;
+    cursor: pointer !important;
+    transition: all 0.3s ease !important;
+    width: 100% !important;
+    margin-top: 1rem !important;
+}
+
+.generate-btn:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 10px 20px rgba(102, 126, 234, 0.4) !important;
+}
+
+.use-btn {
+    background: linear-gradient(135deg, #10b981 0%, #059669 100%) !important;
+    border: none !important;
+    color: white !important;
+    font-weight: 600 !important;
+    padding: 0.6rem 1.5rem !important;
+    border-radius: 0.5rem !important;
+    cursor: pointer !important;
+    transition: all 0.3s ease !important;
+    width: 100% !important;
+}
+
+.use-btn:hover {
+    transform: translateY(-1px) !important;
+    box-shadow: 0 5px 15px rgba(16, 185, 129, 0.4) !important;
+}
+
+/* Input Styling */
+.prompt-input textarea {
+    border-radius: 0.5rem !important;
+    border: 2px solid #e5e7eb !important;
+    padding: 0.8rem !important;
+    font-size: 1rem !important;
+    transition: border-color 0.3s ease !important;
+}
+
+.prompt-input textarea:focus {
+    border-color: #667eea !important;
+    outline: none !important;
+}
+
+.dark .prompt-input textarea {
+    border-color: #374151 !important;
+    background: #1f2937 !important;
+}
+
+/* Image Output Styling */
+#output {
+    border-radius: 0.5rem !important;
+    overflow: hidden !important;
+    box-shadow: 0 4px 6px rgba(0,0,0,0.1) !important;
+}
+
+/* Progress Bar Styling */
+.progress-bar {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+}
+
+/* Examples Styling */
+.examples-container {
+    background: #f9fafb;
+    border-radius: 0.5rem;
+    padding: 1rem;
+    margin-top: 1rem;
+}
+
+.dark .examples-container {
+    background: #1f2937;
+}
+
+/* Pro Message Styling */
+.pro-message {
+    background: linear-gradient(135deg, #fef3c7 0%, #fde68a 100%);
+    border-radius: 1rem;
+    padding: 2rem;
+    text-align: center;
+    border: 2px solid #f59e0b;
+}
+
+.dark .pro-message {
+    background: linear-gradient(135deg, #7c2d12 0%, #92400e 100%);
+    border-color: #f59e0b;
+}
+
+/* Emoji Animations */
+@keyframes bounce {
+    0%, 100% { transform: translateY(0); }
+    50% { transform: translateY(-10px); }
+}
+
+.emoji-icon {
+    display: inline-block;
+    animation: bounce 2s infinite;
+}
+
+/* Responsive Design */
+@media (max-width: 768px) {
+    .header-title {
+        font-size: 2rem !important;
+    }
+    
+    .main-container {
+        padding: 1rem !important;
+    }
+}
+'''
+
+with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
+    # Header
+    gr.HTML('''
+    <div class="main-header">
+        <h1 class="header-title">
+            🍌 Real Nano Banana
+        </h1>
+        <p class="header-subtitle">
+            Google Gemini 2.5 Flash Image Preview로 구동되는 AI 이미지 생성기
+        </p>
+    </div>
+    ''')
+    
+    # Pro User Notice
+    gr.HTML('''
+    <div style="background: linear-gradient(135deg, #fef3c7 0%, #fde68a 100%); 
+                border-radius: 0.5rem; padding: 1rem; margin-bottom: 1.5rem; 
+                border-left: 4px solid #f59e0b;">
+        <p style="margin: 0; color: #92400e; font-weight: 600;">
+            🌟 이 스페이스는 Hugging Face PRO 사용자 전용입니다. 
+            <a href="https://huggingface.co/pro" target="_blank" 
+               style="color: #dc2626; text-decoration: underline;">
+               PRO 구독하기
+            </a>
+        </p>
+    </div>
+    ''')
+
+    pro_message = gr.Markdown(visible=False)
+    main_interface = gr.Column(visible=False, elem_classes="main-container")
+
+    with main_interface:
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.HTML('<div class="card">')
+                
+                # Mode Selection
+                gr.HTML('<h3 style="margin-top: 0;">📸 모드 선택</h3>')
+                active_tab_state = gr.State(value="single")
+                
+                with gr.Tabs(elem_classes="tabs") as tabs:
+                    with gr.TabItem("🖼️ 단일 이미지", id="single") as single_tab:
+                        image_input = gr.Image(
+                            type="filepath",
+                            label="입력 이미지",
+                            elem_classes="image-input"
+                        )
+                        gr.HTML('''
+                        <p style="text-align: center; color: #6b7280; font-size: 0.9rem; margin-top: 0.5rem;">
+                            💡 텍스트→이미지 생성은 비워두세요
+                        </p>
+                        ''')
+                        
+                    with gr.TabItem("🎨 다중 이미지", id="multiple") as multi_tab:
+                        gallery_input = gr.Gallery(
+                            label="입력 이미지들", 
+                            file_types=["image"],
+                            elem_classes="gallery-input"
+                        )
+                        gr.HTML('''
+                        <p style="text-align: center; color: #6b7280; font-size: 0.9rem; margin-top: 0.5rem;">
+                            💡 여러 이미지를 드래그 앤 드롭하세요
+                        </p>
+                        ''')
+                
+                # Prompt Input
+                gr.HTML('<h3>✍️ 프롬프트</h3>')
+                prompt_input = gr.Textbox(
+                    label="",
+                    info="AI에게 원하는 것을 설명하세요",
+                    placeholder="예: 맛있어 보이는 피자, 우주를 배경으로 한 고양이, 미래적인 도시 풍경...",
+                    lines=3,
+                    elem_classes="prompt-input"
+                )
+                
+                # Generate Button
+                generate_button = gr.Button(
+                    "🚀 생성하기", 
+                    variant="primary",
+                    elem_classes="generate-btn"
+                )
+                
+                # Examples
+                with gr.Accordion("💡 예제 프롬프트", open=False):
+                    gr.Examples(
+                        examples=[
+                            ["치즈가 늘어나는 맛있어 보이는 피자"],
+                            ["우주복을 입은 고양이가 달 표면을 걷고 있는 모습"],
+                            ["네온 불빛이 빛나는 사이버펑크 도시의 야경"],
+                            ["봄날 벚꽃이 만개한 일본 정원"],
+                            ["판타지 세계의 마법사 탑"],
+                        ],
+                        inputs=prompt_input,
+                        elem_classes="examples-container"
+                    )
+                
+                gr.HTML('</div>')
+
+            with gr.Column(scale=1):
+                gr.HTML('<div class="card">')
+                gr.HTML('<h3 style="margin-top: 0;">🎨 생성 결과</h3>')
+                
+                output_image = gr.Image(
+                    label="", 
+                    interactive=False, 
+                    elem_id="output"
+                )
+                
+                use_image_button = gr.Button(
+                    "♻️ 이 이미지를 다음 편집에 사용", 
+                    elem_classes="use-btn",
+                    visible=False
+                )
+                
+                # Tips
+                gr.HTML('''
+                <div style="background: #f0f9ff; border-radius: 0.5rem; padding: 1rem; margin-top: 1rem;">
+                    <h4 style="margin-top: 0; color: #0369a1;">💡 팁</h4>
+                    <ul style="margin: 0; padding-left: 1.5rem; color: #0c4a6e;">
+                        <li>구체적이고 상세한 프롬프트를 사용하세요</li>
+                        <li>생성된 이미지를 재사용하여 반복적으로 개선할 수 있습니다</li>
+                        <li>다중 이미지 모드로 여러 참조 이미지를 결합할 수 있습니다</li>
+                    </ul>
+                </div>
+                ''')
+                
+                gr.HTML('</div>')
+        
+        # Footer
+        gr.HTML('''
+        <div style="text-align: center; margin-top: 2rem; padding: 1rem; 
+                    border-top: 1px solid #e5e7eb;">
+            <p style="color: #6b7280;">
+                Made with 💜 by Hugging Face PRO | Powered by Google Gemini 2.5 Flash
+            </p>
+        </div>
+        ''')
+    
+    login_button = gr.LoginButton()
+    
+    # --- Event Handlers ---
+    def unified_generator(
+        prompt: str,
+        single_image: Optional[str],
+        multi_images: Optional[List[str]],
+        active_tab: str,
+        oauth_token: Optional[gr.OAuthToken] = None,
+    ):
+        if not verify_pro_status(oauth_token):
+            raise gr.Error("액세스 거부: 이 서비스는 PRO 사용자 전용입니다.")
+        if not prompt:
+            raise gr.Error("프롬프트를 입력해주세요.")
+        if active_tab == "multiple" and multi_images:
+            result = run_multi_image_logic(prompt, multi_images)
+        else:
+            result = run_single_image_logic(prompt, single_image)
+        return result, gr.update(visible=True)
+
+    single_tab.select(lambda: "single", None, active_tab_state)
+    multi_tab.select(lambda: "multiple", None, active_tab_state)
+
+    generate_button.click(
+        unified_generator,
+        inputs=[prompt_input, image_input, gallery_input, active_tab_state],
+        outputs=[output_image, use_image_button],
+    )
+
+    use_image_button.click(
+        lambda img: (img, gr.update(visible=False)), 
+        inputs=[output_image],
+        outputs=[image_input, use_image_button]
+    )
+
+    # --- Access Control Logic ---
+    def control_access(
+        profile: Optional[gr.OAuthProfile] = None,
+        oauth_token: Optional[gr.OAuthToken] = None
+    ):
+        if not profile:
+            return gr.update(visible=False), gr.update(visible=False)
+        if verify_pro_status(oauth_token):
+            return gr.update(visible=True), gr.update(visible=False)
+        else:
+            message = '''
+            <div class="pro-message">
+                <h2>✨ PRO 사용자 전용 기능</h2>
+                <p style="font-size: 1.1rem; margin: 1rem 0;">
+                    이 강력한 AI 이미지 생성 도구는 Hugging Face <strong>PRO</strong> 멤버 전용입니다.
+                </p>
+                <p style="margin: 1rem 0;">
+                    PRO 구독으로 다음을 누리세요:
+                </p>
+                <ul style="text-align: left; display: inline-block; margin: 1rem 0;">
+                    <li>🚀 Google Gemini 2.5 Flash 무제한 액세스</li>
+                    <li>⚡ 빠른 이미지 생성</li>
+                    <li>🎨 고품질 결과물</li>
+                    <li>🔧 다중 이미지 편집 기능</li>
+                </ul>
+                <a href="https://huggingface.co/pro" target="_blank" 
+                   style="display: inline-block; margin-top: 1rem; padding: 1rem 2rem;
+                          background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+                          color: white; text-decoration: none; border-radius: 0.5rem;
+                          font-weight: bold; font-size: 1.1rem;">
+                    🌟 지금 PRO 멤버 되기
+                </a>
+            </div>
+            '''
+            return gr.update(visible=False), gr.update(visible=True, value=message)
+
+    demo.load(control_access, inputs=None, outputs=[main_interface, pro_message])
+
+if __name__ == "__main__":
+    demo.queue(max_size=None, default_concurrency_limit=None)
+    demo.launch()