Update app.py

app.py

@@ -29,37 +29,47 @@ except ImportError:
     print("⚠️ Compel not available - using standard prompt processing")
 
 # ===== 优化后的配置 =====
+# Kageillustrious风格核心关键词 - 使用Danbooru标签风格
 STYLE_KEYWORDS = {
-    "None": {"prefix": "", "suffix": ""},
+    "None": {
+        "prefix": "",
+        "suffix": ""
+    },
+    "Standard Quality": {
+        "prefix": "masterpiece, best quality, amazing quality, very aesthetic, absurdres",
+        "suffix": ""
+    },
+    "High Detail": {
+        "prefix": "masterpiece, best quality, amazing quality, very aesthetic, high resolution, ultra-detailed, absurdres, newest, colorful, rim light, backlit, highest detailed",
+        "suffix": ""
+    },
     "Realistic": {
-        "prefix": "(RAW photo:1.3), (photorealistic:1.4), (hyperrealistic:1.3), 8k uhd, (ultra realistic skin texture:1.2), cinematic lighting, vibrant colors, masterpiece, realistic skin texture, detailed anatomy, professional photography",
-        "suffix": "sharp focus, (everything in focus:1.3), (no bokeh:1.2), realistic skin texture, subsurface scattering, detailed anatomy, (perfect anatomy:1.2), detailed face, detailed background, lifelike, professional photography, realistic proportions, (detailed face:1.1), natural pose, expressive eyes, 8k resolution"
+        "prefix": "masterpiece, best quality, amazing quality, very aesthetic, absurdres, (photorealistic:1.3), (realistic:1.4), detailed skin texture, cinematic lighting",
+        "suffix": "sharp focus, detailed anatomy, realistic proportions, detailed face, natural pose, expressive eyes, 8k resolution"
     },
     "Anime": {
-        "prefix": "(anime style:1.3), (anime artwork:1.2), vibrant, key visual, studio anime, highly detailed anime",
-        "suffix": "cel shading, clean linework, vibrant anime colors, detailed anime eyes, smooth anime skin, perfect anime proportions, manga illustration"
-    },
-    "Comic": {
-        "prefix": "(comic book art:1.3), (graphic novel:1.2), bold inking, comic art style",
-        "suffix": "bold outlines, halftone dots, pop art colors, dynamic panel, graphic illustration, cel shading, comic book style"
+        "prefix": "masterpiece, best quality, amazing quality, very aesthetic, absurdres, anime style, vibrant colors, detailed anime",
+        "suffix": "cel shading, clean linework, vibrant anime colors, detailed anime eyes, smooth anime skin"
     },
-    "Watercolor": {
-        "prefix": "(watercolor painting:1.3), (watercolor art:1.2), soft edges, delicate washes, artistic",
-        "suffix": "soft gradients, pastel colors, paper texture, artistic brush strokes, traditional watercolor, hand-painted"
+    "Artistic": {
+        "prefix": "masterpiece, best quality, amazing quality, very aesthetic, absurdres, artistic, illustration, detailed artwork",
+        "suffix": "vibrant colors, expressive, detailed composition, artistic rendering"
     }
 }
 
-QUALITY_TAGS = "masterpiece, best quality, high resolution, detailed"
+# 通用质量增强词
+QUALITY_TAGS = "very awa"
 
-# 🔧 修正：使用正确的模型名称
-FIXED_MODEL = "votepurchase/pornmasterPro_noobV3VAE"
+# 修改为Kageillustrious模型 - 使用from_single_file加载
+FIXED_MODEL_REPO = "PutiLeslie/kageillustrious_v60NLXLVersion"
+FIXED_MODEL_FILE = "kageillustrious_v60NLXLVersion.safetensors"
 
-# 🔧 修正：使用正确的 LoRA 配置
+# LoRA 配置 - 保留原有的LoRA(可能需要测试兼容性)
 LORA_CONFIGS = [
     {
-        "repo_id": "OedoSoldier/detail-tweaker-lora",
-        "weight_name": "add_detail.safetensors",
-        "adapter_name": "detail_tweaker",
+        "repo_id": "artificialguybr/LogoRedmond-LogoLoraForSDXL-V2",
+        "weight_name": "LogoRedAF.safetensors",
+        "adapter_name": "logo_lora",
         "scale": 0.8
     }
 ]
@@ -74,7 +84,7 @@ device = None
 model_loaded = False
 
 def initialize_model():
-    """优化的模型初始化 - 修复设备不一致问题"""
+    """优化的模型初始化 - 使用from_single_file加载Kageillustrious"""
     global pipeline, compel_processor, device, model_loaded
     
     if model_loaded and pipeline is not None:
@@ -85,25 +95,34 @@ def initialize_model():
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         print(f"🖥️ Using device: {device}")
         
-        print(f"📦 Loading model: {FIXED_MODEL}")
+        print(f"📦 Loading Kageillustrious model from: {FIXED_MODEL_REPO}")
+        
+        # 使用from_single_file加载单个safetensors文件
+        from huggingface_hub import hf_hub_download
+        
+        # 下载模型文件
+        model_path = hf_hub_download(
+            repo_id=FIXED_MODEL_REPO,
+            filename=FIXED_MODEL_FILE
+        )
         
-        # 基础模型加载
-        pipeline = StableDiffusionXLPipeline.from_pretrained(
-            FIXED_MODEL,
+        print(f"📥 Model downloaded to: {model_path}")
+        
+        # 使用from_single_file加载
+        pipeline = StableDiffusionXLPipeline.from_single_file(
+            model_path,
             torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-            variant="fp16" if torch.cuda.is_available() else None,
             use_safetensors=True,
             safety_checker=None,
             requires_safety_checker=False
         )
         
-        # 优化调度器
+        # 优化调度器 - 使用Euler适合Illustrious系列
         pipeline.scheduler = EulerDiscreteScheduler.from_config(
             pipeline.scheduler.config,
             timestep_spacing="trailing"
         )
         
-        # 先移到设备
         pipeline = pipeline.to(device)
         
         # 加载 LoRA
@@ -113,53 +132,46 @@ def initialize_model():
         
         for lora_config in LORA_CONFIGS:
             try:
-                print(f"   Loading: {lora_config['repo_id']}/{lora_config['weight_name']}")
                 pipeline.load_lora_weights(
                     lora_config["repo_id"],
                     weight_name=lora_config["weight_name"],
                     adapter_name=lora_config["adapter_name"]
                 )
-                
-                # 🔧 关键修复: 确保 LoRA 权重在正确的设备上
-                if hasattr(pipeline, 'unet') and hasattr(pipeline.unet, 'to'):
-                    pipeline.unet.to(device)
-                
                 adapter_names.append(lora_config["adapter_name"])
                 adapter_scales.append(lora_config.get("scale", 0.8))
-                print(f"   ✅ LoRA loaded: {lora_config['adapter_name']} (scale: {lora_config.get('scale', 0.8)})")
+                print(f"✅ LoRA loaded: {lora_config['adapter_name']} (scale: {lora_config.get('scale', 0.8)})")
             except Exception as lora_error:
-                print(f"   ⚠️ Failed to load LoRA {lora_config['adapter_name']}: {lora_error}")
-                print(traceback.format_exc())
+                print(f"⚠️ Failed to load LoRA {lora_config['adapter_name']}: {lora_error}")
         
         # 设置 LoRA 强度
         if adapter_names:
             try:
                 pipeline.set_adapters(adapter_names, adapter_weights=adapter_scales)
                 print(f"✅ LoRA adapters activated with scales: {adapter_scales}")
-                
-                # 🔧 再次确保所有组件在同一设备
-                pipeline.to(device)
             except Exception as e:
                 print(f"⚠️ Failed to set adapter scales: {e}")
         
-        # GPU优化
+        # GPU优化 - 适配ZeroGPU环境
         if torch.cuda.is_available():
             try:
+                # VAE优化
                 pipeline.enable_vae_slicing()
                 pipeline.enable_vae_tiling()
                 
+                # 尝试启用xformers
                 try:
                     pipeline.enable_xformers_memory_efficient_attention()
                     print("✅ xFormers enabled")
                 except:
                     print("⚠️ xFormers not available, using default attention")
                 
+                # 不使用torch.compile，因为它在ZeroGPU环境中不稳定
                 print("ℹ️ Skipping torch.compile for ZeroGPU compatibility")
                 
             except Exception as opt_error:
                 print(f"⚠️ Optimization warning: {opt_error}")
         
-        # 初始化Compel
+        # 初始化Compel用于长提示词
         if COMPEL_AVAILABLE:
             try:
                 compel_processor = Compel(
@@ -174,14 +186,8 @@ def initialize_model():
                 print(f"⚠️ Compel initialization failed: {compel_error}")
                 compel_processor = None
         
-        # 🔧 最终设备检查
-        print(f"🔍 Final device check:")
-        print(f"   - UNet device: {next(pipeline.unet.parameters()).device}")
-        print(f"   - VAE device: {next(pipeline.vae.parameters()).device}")
-        print(f"   - Text Encoder device: {next(pipeline.text_encoder.parameters()).device}")
-        
         model_loaded = True
-        print("✅ Model initialization complete")
+        print("✅ Kageillustrious model initialization complete")
         return True
         
     except Exception as e:
@@ -191,11 +197,14 @@ def initialize_model():
         return False
 
 def enhance_prompt(prompt: str, style: str) -> str:
-    """优化的提示词增强"""
+    """优化的提示词增强 - 适配Kageillustrious的Danbooru标签风格"""
     if not prompt or prompt.strip() == "":
         return ""
     
+    # 获取风格关键词
     style_config = STYLE_KEYWORDS.get(style, STYLE_KEYWORDS["None"])
+    
+    # 组合顺序:风格前缀 → 用户提示词 → 风格后缀 → 质量标签
     parts = []
     
     if style_config["prefix"]:
@@ -217,20 +226,22 @@ def enhance_prompt(prompt: str, style: str) -> str:
     return enhanced
 
 def build_negative_prompt(style: str, custom_negative: str = "") -> str:
-    """根据风格构建负面提示词"""
-    base_negative = "(low quality:1.4), (worst quality:1.4), (bad anatomy:1.3), (bad hands:1.2), blurry, watermark, text, error, cropped, jpeg artifacts, ugly, duplicate, deformed"
+    """根据风格构建负面提示词 - 适配Illustrious系列"""
+    # Illustrious系列推荐的负面提示词
+    base_negative = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry"
     
+    # 风格特定的负面词
     style_negatives = {
-        "Realistic": ", (cartoon:1.3), (anime:1.3), (3d render:1.2), (illustration:1.2), (painting:1.2), (drawing:1.2), (art:1.2), (sketch:1.2), artificial, unrealistic",
-        "Anime": ", (realistic:1.3), (photorealistic:1.3), (photo:1.2), (3d:1.2), (hyperrealistic:1.2)",
-        "Comic": ", (realistic:1.2), (photorealistic:1.2), (blurry lines:1.2), (soft edges:1.2)",
-        "Watercolor": ", (digital art:1.2), (sharp edges:1.2), (vector art:1.2), (3d:1.2)"
+        "Realistic": ", (cartoon:1.3), (anime:1.3), (3d render:1.2), (illustration:1.2)",
+        "Anime": ", (realistic:1.3), (photorealistic:1.3), (photo:1.2)",
+        "Artistic": ", (photo:1.2), (photorealistic:1.2)"
     }
     
     negative = base_negative
     if style in style_negatives:
         negative += style_negatives[style]
     
+    # 添加用户自定义负面词
     if custom_negative.strip():
         negative += f", {custom_negative.strip()}"
     
@@ -242,6 +253,7 @@ def process_with_compel(prompt, negative_prompt):
         return None, None
     
     try:
+        # Compel会自动处理超过77 tokens的提示词
         conditioning, pooled = compel_processor([prompt, negative_prompt])
         print("✅ Long prompt processed with Compel")
         return conditioning, pooled
@@ -258,10 +270,13 @@ def apply_spaces_decorator(func):
 def create_metadata_content(prompt, enhanced_prompt, seed, steps, cfg_scale, width, height, style):
     """创建元数据"""
     timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    
+    # 获取 LoRA 信息
     lora_info = ", ".join([f"{lora['adapter_name']}({lora.get('scale', 1.0)})" for lora in LORA_CONFIGS])
     
     return f"""Generated Image Metadata
 ======================
+Model: Kageillustrious v6.0NL XL
 Timestamp: {timestamp}
 Original Prompt: {prompt}
 Enhanced Prompt: {enhanced_prompt}
@@ -270,22 +285,25 @@ Steps: {steps}
 CFG Scale: {cfg_scale}
 Dimensions: {width}x{height}
 Style: {style}
-LoRA: {lora_info}
+LoRA: {lora_info if lora_info else "None"}
 """
 
 def cleanup_pipeline():
-    """清理 pipeline 状态"""
+    """清理 pipeline 状态，防止污染"""
     global pipeline
     
     if pipeline is None:
         return
     
     try:
+        # 清理 CUDA 缓存
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
             torch.cuda.ipc_collect()
         
+        # 清理 pipeline 的内部缓存
         if hasattr(pipeline, 'unet'):
+            # 清空 UNet 的注意力缓存
             if hasattr(pipeline.unet, 'set_attn_processor'):
                 try:
                     from diffusers.models.attention_processor import AttnProcessor
@@ -293,6 +311,7 @@ def cleanup_pipeline():
                 except:
                     pass
         
+        # 清理 VAE 缓存
         if hasattr(pipeline, 'vae'):
             pipeline.vae.to('cpu')
             pipeline.vae.to(device)
@@ -304,30 +323,38 @@ def cleanup_pipeline():
 
 @apply_spaces_decorator
 def generate_image(prompt: str, style: str, negative_prompt: str = "",
-                   steps: int = 25, cfg_scale: float = 7.0,
-                   seed: int = -1, width: int = 1024, height: int = 1024,
+                   steps: int = 20, cfg_scale: float = 6.0,
+                   seed: int = -1, width: int = 896, height: int = 1152,
                    progress=gr.Progress()):
-    """图像生成主函数"""
+    """图像生成主函数 - 使用Kageillustrious推荐参数"""
     
+    # 验证输入
     if not prompt or prompt.strip() == "":
         return None, "", "❌ Please enter a prompt"
     
     progress(0.05, desc="Initializing...")
     
+    # 初始化模型
     if not initialize_model():
         return None, "", "❌ Failed to load model"
     
+    # 清理之前的状态
     cleanup_pipeline()
     
     progress(0.1, desc="Processing prompt...")
     
     try:
+        # 处理seed
         if seed == -1:
             seed = random.randint(0, np.iinfo(np.int32).max)
         
+        # 重要：为每次生成创建新的 generator，避免状态污染
         generator = torch.Generator(device).manual_seed(seed)
         
+        # 增强提示词
         enhanced_prompt = enhance_prompt(prompt, style)
+        
+        # 构建负面提示词
         final_negative = build_negative_prompt(style, negative_prompt)
         
         print(f"🔧 Generation params: seed={seed}, steps={steps}, cfg={cfg_scale}, size={width}x{height}")
@@ -335,6 +362,7 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
         
         progress(0.2, desc="Generating image...")
         
+        # 检查提示词长度并决定是否使用Compel
         prompt_length = len(enhanced_prompt.split())
         use_compel = prompt_length > 50 and compel_processor is not None
         
@@ -343,6 +371,7 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
             conditioning, pooled = process_with_compel(enhanced_prompt, final_negative)
             
             if conditioning is not None:
+                # 使用embeddings生成
                 result = pipeline(
                     prompt_embeds=conditioning[0:1],
                     pooled_prompt_embeds=pooled[0:1],
@@ -356,6 +385,7 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
                     output_type="pil"
                 ).images[0]
             else:
+                # Compel失败,回退到普通模式
                 print("⚠️ Falling back to standard generation")
                 result = pipeline(
                     prompt=enhanced_prompt,
@@ -368,6 +398,7 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
                     output_type="pil"
                 ).images[0]
         else:
+            # 标准生成
             print(f"📝 Standard generation ({prompt_length} words)")
             result = pipeline(
                 prompt=enhanced_prompt,
@@ -382,12 +413,14 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
         
         progress(0.95, desc="Finalizing...")
         
+        # 确保结果是PIL Image
         if not isinstance(result, Image.Image):
             if isinstance(result, np.ndarray):
                 if result.dtype != np.uint8:
                     result = (result * 255).astype(np.uint8)
                 result = Image.fromarray(result)
         
+        # 创建元数据
         metadata = create_metadata_content(
             prompt, enhanced_prompt, seed, steps, cfg_scale,
             width, height, style
@@ -395,6 +428,7 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
         
         generation_info = f"Style: {style} | Seed: {seed} | Size: {width}×{height} | Steps: {steps} | CFG: {cfg_scale}"
         
+        # 生成后立即清理
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
         
@@ -408,6 +442,7 @@ def generate_image(prompt: str, style: str, negative_prompt: str = "",
         print(f"❌ Generation error: {error_msg}")
         print(traceback.format_exc())
         
+        # 错误后也要清理
         try:
             cleanup_pipeline()
         except:
@@ -421,17 +456,17 @@ css = """
     max-width: 100% !important;
     margin: 0 !important;
     padding: 0 !important;
-    background: linear-gradient(135deg, #e6a4f2 0%, #1197e4 100%) !important;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
     min-height: 100vh !important;
     font-family: 'Segoe UI', Arial, sans-serif !important;
 }
 
 .main-content {
-    background: rgba(255, 255, 255, 0.9) !important;
+    background: rgba(255, 255, 255, 0.95) !important;
     border-radius: 20px !important;
     padding: 20px !important;
     margin: 15px !important;
-    box-shadow: 0 10px 25px rgba(255, 255, 255, 0.2) !important;
+    box-shadow: 0 10px 25px rgba(0, 0, 0, 0.2) !important;
     min-height: calc(100vh - 30px) !important;
     color: #3e3e3e !important;
     backdrop-filter: blur(10px) !important;
@@ -439,7 +474,7 @@ css = """
 
 .title {
     text-align: center !important;
-    background: linear-gradient(45deg, #bb6ded, #08676b) !important;
+    background: linear-gradient(45deg, #667eea, #764ba2) !important;
     -webkit-background-clip: text !important;
     -webkit-text-fill-color: transparent !important;
     background-clip: text !important;
@@ -449,7 +484,7 @@ css = """
 }
 
 .warning-box {
-    background: linear-gradient(45deg, #bb6ded, #08676b) !important;
+    background: linear-gradient(45deg, #667eea, #764ba2) !important;
     color: white !important;
     padding: 8px !important;
     border-radius: 8px !important;
@@ -459,9 +494,21 @@ css = """
     font-size: 14px !important;
 }
 
+.model-info {
+    background: linear-gradient(135deg, rgba(102, 126, 234, 0.1), rgba(118, 75, 162, 0.1)) !important;
+    color: #764ba2 !important;
+    padding: 10px !important;
+    border-radius: 8px !important;
+    margin-bottom: 15px !important;
+    text-align: center !important;
+    font-weight: 600 !important;
+    font-size: 13px !important;
+    border: 2px solid rgba(118, 75, 162, 0.3) !important;
+}
+
 .prompt-box textarea, .prompt-box input {
     border-radius: 10px !important;
-    border: 2px solid #bb6ded !important;
+    border: 2px solid #667eea !important;
     padding: 15px !important;
     font-size: 18px !important;
     background: linear-gradient(135deg, rgba(245, 243, 255, 0.9), rgba(237, 233, 254, 0.9)) !important;
@@ -469,8 +516,8 @@ css = """
 }
 
 .prompt-box textarea:focus, .prompt-box input:focus {
-    border-color: #08676b !important;
-    box-shadow: 0 0 15px rgba(77, 8, 161, 0.3) !important;
+    border-color: #764ba2 !important;
+    box-shadow: 0 0 15px rgba(118, 75, 162, 0.3) !important;
     background: linear-gradient(135deg, rgba(255, 255, 255, 0.95), rgba(248, 249, 250, 0.95)) !important;
 }
 
@@ -479,7 +526,7 @@ css = """
     border-radius: 12px !important;
     padding: 15px !important;
     margin-bottom: 8px !important;
-    border: 2px solid rgba(187, 109, 237, 0.3) !important;
+    border: 2px solid rgba(102, 126, 234, 0.3) !important;
     backdrop-filter: blur(5px) !important;
 }
 
@@ -490,20 +537,20 @@ css = """
 }
 
 .controls-section input[type="radio"] {
-    accent-color: #bb6ded !important;
+    accent-color: #667eea !important;
 }
 
 .controls-section input[type="number"],
 .controls-section input[type="range"] {
     background: rgba(255, 255, 255, 0.9) !important;
-    border: 1px solid #bb6ded !important;
+    border: 1px solid #667eea !important;
     border-radius: 6px !important;
     padding: 8px !important;
     color: #2d2d2d !important;
 }
 
 .generate-btn {
-    background: linear-gradient(45deg, #bb6ded, #08676b) !important;
+    background: linear-gradient(45deg, #667eea, #764ba2) !important;
     color: white !important;
     border: none !important;
     padding: 15px 25px !important;
@@ -519,7 +566,7 @@ css = """
 
 .generate-btn:hover {
     transform: translateY(-2px) !important;
-    box-shadow: 0 8px 25px rgba(187, 109, 237, 0.5) !important;
+    box-shadow: 0 8px 25px rgba(102, 126, 234, 0.5) !important;
 }
 
 .image-output {
@@ -527,31 +574,31 @@ css = """
     overflow: hidden !important;
     max-width: 100% !important;
     max-height: 70vh !important;
-    border: 3px solid #08676b !important;
+    border: 3px solid #764ba2 !important;
     box-shadow: 0 8px 20px rgba(0,0,0,0.15) !important;
     background: linear-gradient(135deg, rgba(255, 255, 255, 0.9), rgba(248, 249, 250, 0.9)) !important;
 }
 
 .image-info {
-    background: linear-gradient(135deg, rgba(248, 249, 250, 0.2), rgba(233, 236, 239, 0.9)) !important;
+    background: linear-gradient(135deg, rgba(248, 249, 250, 0.9), rgba(233, 236, 239, 0.9)) !important;
     border-radius: 8px !important;
     padding: 12px !important;
     margin-top: 10px !important;
     font-size: 12px !important;
     color: #495057 !important;
-    border: 2px solid rgba(187, 109, 237, 0.2) !important;
+    border: 2px solid rgba(102, 126, 234, 0.2) !important;
     backdrop-filter: blur(5px) !important;
 }
 
 .metadata-box {
-    background: linear-gradient(135deg, rgba(248, 249, 250, 0.2), rgba(233, 236, 239, 0.9)) !important;
+    background: linear-gradient(135deg, rgba(248, 249, 250, 0.9), rgba(233, 236, 239, 0.9)) !important;
     border-radius: 8px !important;
     padding: 15px !important;
     margin-top: 15px !important;
     font-family: 'Courier New', monospace !important;
     font-size: 12px !important;
     color: #495057 !important;
-    border: 2px solid rgba(187, 109, 237, 0.2) !important;
+    border: 2px solid rgba(102, 126, 234, 0.2) !important;
     backdrop-filter: blur(5px) !important;
     white-space: pre-wrap !important;
     overflow-y: auto !important;
@@ -571,16 +618,17 @@ css = """
 
 # ===== 创建UI =====
 def create_interface():
-    with gr.Blocks(css=css, title="Adult NSFW AI Image Generator") as interface:
+    with gr.Blocks(css=css, title="Kageillustrious AI Image Generator") as interface:
         with gr.Column(elem_classes=["main-content"]):
-            gr.HTML('<div class="title">Adult NSFW AI Image Generator</div>')
+            gr.HTML('<div class="title">🎨 Kageillustrious AI Image Generator</div>')
+            gr.HTML('<div class="model-info">📦 Model: Kageillustrious v6.0NL XL (Illustrious-based SDXL)</div>')
             gr.HTML('<div class="warning-box">⚠️ 18+ CONTENT WARNING ⚠️</div>')
             
             with gr.Row():
                 with gr.Column(scale=2):
                     prompt_input = gr.Textbox(
-                        label="Detailed Prompt",
-                        placeholder="Enter your detailed prompt here...",
+                        label="Detailed Prompt (Use Danbooru tags style)",
+                        placeholder="1girl, solo, long hair, blue eyes, detailed face, beautiful...",
                         lines=15,
                         elem_classes=["prompt-box"]
                     )
@@ -597,7 +645,7 @@ def create_interface():
                         style_input = gr.Radio(
                             label="Style Preset",
                             choices=list(STYLE_KEYWORDS.keys()),
-                            value="Realistic"
+                            value="Standard Quality"
                         )
                     
                     with gr.Group(elem_classes=["controls-section"]):
@@ -612,8 +660,9 @@ def create_interface():
                             label="Width",
                             minimum=512,
                             maximum=2048,
-                            value=1024,
-                            step=64
+                            value=896,
+                            step=64,
+                            info="Recommended: 896"
                         )
                     
                     with gr.Group(elem_classes=["controls-section"]):
@@ -621,8 +670,9 @@ def create_interface():
                             label="Height",
                             minimum=512,
                             maximum=2048,
-                            value=1024,
-                            step=64
+                            value=1152,
+                            step=64,
+                            info="Recommended: 1152"
                         )
                     
                     with gr.Group(elem_classes=["controls-section"]):
@@ -630,16 +680,18 @@ def create_interface():
                             label="Steps",
                             minimum=10,
                             maximum=50,
-                            value=25,
-                            step=1
+                            value=20,
+                            step=1,
+                            info="Recommended: 20"
                         )
                         
                         cfg_input = gr.Slider(
                             label="CFG Scale",
                             minimum=1.0,
                             maximum=15.0,
-                            value=7.0,
-                            step=0.1
+                            value=6.0,
+                            step=0.1,
+                            info="Recommended: 6.0"
                         )
                     
                     generate_button = gr.Button(
@@ -721,21 +773,26 @@ def create_interface():
                 ],
                 show_progress=True
             )
-    
-    return interface
+        
+        return interface
 
 # ===== 启动应用 =====
 if __name__ == "__main__":
     print("\n" + "="*50)
-    print("🚀 Starting NSFW Image Generator")
+    print("🚀 Starting Kageillustrious Image Generator")
     print("="*50)
-    print(f"📦 Model: {FIXED_MODEL}")
+    print(f"📦 Model: {FIXED_MODEL_REPO}")
+    print(f"📄 Model File: {FIXED_MODEL_FILE}")
     print(f"🖥️ Device: {'CUDA' if torch.cuda.is_available() else 'CPU'}")
     print(f"⚡ ZeroGPU: {'Enabled' if SPACES_AVAILABLE else 'Disabled'}")
     print(f"📝 Compel: {'Available' if COMPEL_AVAILABLE else 'Not Available'}")
-    print(f"🎨 LoRA: detail-tweaker-lora (scale: {LORA_CONFIGS[0].get('scale', 0.8)})")
+    if LORA_CONFIGS:
+        print(f"🎨 LoRA: LogoRedmond-LogoLoraForSDXL-V2 (scale: {LORA_CONFIGS[0].get('scale', 0.8)})")
     print("="*50 + "\n")
     
+    # 不预加载模型,让ZeroGPU按需分配
+    # 这样可以避免GPU分配冲突
+    
     app = create_interface()
     app.queue(max_size=10, default_concurrency_limit=2)