Update app.py

app.py

@@ -19,103 +19,184 @@ from typing import Optional, List, Dict
 import numpy as np
 
 # ======================
-# Configuration Section (Modify here to expand)
+# Configuration Section - 灵活模型配置
 # ======================
 
-# 1. Base Model - Using reliable SDXL models (avoiding incomplete "bait" models)
-BASE_MODELS = {
-    "realistic":"John6666/wai-nsfw-illustrious-v80-sdxl",
-    "sdxl_base": "stabilityai/stable-diffusion-xl-base-1.0",  # Most reliable choice
-    "realistic_vision": "SG161222/RealVisXL_V4.0",  # High-quality realistic model
-    "anime_xl": "Linaqruf/animagine-xl-3.1",  # Popular anime-style SDXL
-    "juggernaut_xl": "RunDiffusion/Juggernaut-XL-v9",  # High-quality general purpose
-    "playground_v2": "playgroundai/playground-v2.5-1024px-aesthetic"  # Aesthetic focused
+# 1. 模型配置字典 - 支持多种模型类型
+MODEL_CONFIGS = {
+    "wai_nsfw_illustrious_v80": {
+        "repo_id": "John6666/wai-nsfw-illustrious-v80-sdxl",
+        "type": "sdxl",  # SDXL架构
+        "requires_safety_checker": False,
+        "default_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",
+        "optimal_settings": {
+            "steps": 28,
+            "cfg": 7.0,
+            "sampler": "DPM++ 2M Karras"
+        },
+        "description": "WAI NSFW Illustrious v8.0 - 高质量插画风格模型"
+    },
+    "wai_nsfw_illustrious_v90": {
+        "repo_id": "John6666/wai-nsfw-illustrious-v90-sdxl",
+        "type": "sdxl",
+        "requires_safety_checker": False,
+        "default_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",
+        "optimal_settings": {
+            "steps": 28,
+            "cfg": 7.0,
+            "sampler": "DPM++ 2M Karras"
+        },
+        "description": "WAI NSFW Illustrious v9.0 - 最新版本"
+    },
+    "wai_nsfw_illustrious_v110": {
+        "repo_id": "John6666/wai-nsfw-illustrious-v110-sdxl",
+        "type": "sdxl",
+        "requires_safety_checker": False,
+        "default_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",
+        "optimal_settings": {
+            "steps": 30,
+            "cfg": 7.5,
+            "sampler": "DPM++ 2M Karras"
+        },
+        "description": "WAI NSFW Illustrious v11.0 - 增强版本"
+    },
+    "sdxl_base": {
+        "repo_id": "stabilityai/stable-diffusion-xl-base-1.0",
+        "type": "sdxl",
+        "requires_safety_checker": True,
+        "default_negative": "blurry, low quality, deformed, cartoon, anime, text, watermark, signature, username, worst quality, low res, bad anatomy, bad hands",
+        "optimal_settings": {
+            "steps": 30,
+            "cfg": 7.5,
+            "sampler": "Default"
+        },
+        "description": "Stable Diffusion XL Base 1.0 - 官方基础模型"
+    },
+    "realistic_vision": {
+        "repo_id": "SG161222/RealVisXL_V4.0",
+        "type": "sdxl",
+        "requires_safety_checker": False,
+        "default_negative": "blurry, low quality, deformed, text, watermark, signature, worst quality, bad anatomy",
+        "optimal_settings": {
+            "steps": 30,
+            "cfg": 7.5,
+            "sampler": "Default"
+        },
+        "description": "RealVisXL V4.0 - 高质量写实风格"
+    },
+    "anime_xl": {
+        "repo_id": "Linaqruf/animagine-xl-3.1",
+        "type": "sdxl",
+        "requires_safety_checker": False,
+        "default_negative": "lowres, bad anatomy, text, error, cropped, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated",
+        "optimal_settings": {
+            "steps": 28,
+            "cfg": 7.0,
+            "sampler": "Default"
+        },
+        "description": "Animagine XL 3.1 - 动漫风格"
+    },
+    "juggernaut_xl": {
+        "repo_id": "RunDiffusion/Juggernaut-XL-v9",
+        "type": "sdxl",
+        "requires_safety_checker": False,
+        "default_negative": "blurry, low quality, text, watermark, signature, worst quality",
+        "optimal_settings": {
+            "steps": 30,
+            "cfg": 7.5,
+            "sampler": "Default"
+        },
+        "description": "Juggernaut XL v9 - 通用高质量模型"
+    }
 }
 
-# Current model selection (change this to switch models)
-CURRENT_MODEL_KEY = "realistic"  # Changed to working model
-BASE_MODEL = BASE_MODELS[CURRENT_MODEL_KEY]
+# 默认使用的模型 - 可以通过UI切换
+DEFAULT_MODEL_KEY = "wai_nsfw_illustrious_v80"
 
-# 2. Fixed LoRAs (Auto-loaded, not user-selectable) - Using actual LoRA models
+# 2. 固定LoRA配置 - 自动加载
 FIXED_LORAS = {
     "detail_enhancer": {
-        "repo_id": "ostris/ikea-instructions-lora-sdxl",  # Real LoRA for details
+        "repo_id": "ostris/ikea-instructions-lora-sdxl",
         "filename": None,
-        "weight": 0.6,
-        "trigger_words": "high quality, detailed, sharp focus"
+        "weight": 0.5,  # 降低权重避免过度影响
+        "trigger_words": "high quality, detailed",
+        "enabled": True  # 可以禁用
     },
     "quality_boost": {
-        "repo_id": "stabilityai/stable-diffusion-xl-offset-example-lora",  # Official SDXL LoRA
+        "repo_id": "stabilityai/stable-diffusion-xl-offset-example-lora",
         "filename": None,
-        "weight": 0.5,
-        "trigger_words": "masterpiece, best quality"
+        "weight": 0.4,
+        "trigger_words": "masterpiece, best quality",
+        "enabled": True
     }
 }
 
-# 3. Style Templates (Auto-prepended to user prompts)
+# 3. 风格模板 - 根据不同模型优化
 STYLE_PROMPTS = {
     "None": "",
-    "Realistic": "photorealistic, ultra-detailed skin, natural lighting, 8k uhd, professional photography, DSLR, soft lighting, high quality, film grain, Fujifilm XT3, masterpiece, ",
-    "Anime": "anime style, cel shading, vibrant colors, detailed eyes, studio ghibli style, manga style, trending on pixiv, masterpiece, ",
-    "Comic": "comic book style, bold outlines, dynamic angles, comic panel, Marvel DC style, inked lines, pop art, masterpiece, ",
-    "Watercolor": "watercolor painting, soft brush strokes, translucent layers, artistic, painterly, paper texture, traditional art, masterpiece, ",
+    "Realistic Photo": "photorealistic, ultra-detailed, natural lighting, 8k uhd, professional photography, DSLR, high quality, masterpiece, ",
+    "Anime/Illustration": "anime style, high quality illustration, vibrant colors, detailed, masterpiece, best quality, ",
+    "Artistic Illustration": "artistic illustration, painterly, detailed artwork, high quality, professional illustration, ",
+    "Comic Book": "comic book style, bold lines, dynamic composition, pop art, high quality, ",
+    "Watercolor": "watercolor painting, soft brush strokes, artistic, traditional art, masterpiece, ",
+    "Cinematic": "cinematic lighting, dramatic atmosphere, film grain, professional color grading, high quality, ",
 }
 
-# 4. Optional LoRAs (User-selectable via dropdown, can select multiple) - Using real, verified LoRAs
+# 4. 可选LoRA配置 - 用户可选择
 OPTIONAL_LORAS = {
     "None": {
         "repo_id": None,
         "weight": 0.0,
         "trigger_words": "",
-        "description": "No additional LoRA"
+        "description": "不使用额外LoRA"
     },
-    "Offset Noise LoRA": {
+    "Offset Noise": {
         "repo_id": "stabilityai/stable-diffusion-xl-offset-example-lora",
         "weight": 0.7,
         "trigger_words": "high contrast, dramatic lighting",
-        "description": "Enhanced contrast and lighting (Official Stability AI)"
+        "description": "增强对比度和光照效果"
     },
     "LCM LoRA": {
         "repo_id": "latent-consistency/lcm-lora-sdxl",
         "weight": 0.8,
-        "trigger_words": "lcm style, high quality",
-        "description": "Latent Consistency Model for faster generation"
+        "trigger_words": "high quality",
+        "description": "快速生成模式"
     },
-    "Pixel Art LoRA": {
+    "Pixel Art": {
         "repo_id": "nerijs/pixel-art-xl",
         "weight": 0.9,
-        "trigger_words": "pixel art style, 8bit, retro game",
-        "description": "Pixel art style transformation"
+        "trigger_words": "pixel art style, 8bit, retro",
+        "description": "像素艺术风格"
     },
-    "Watercolor LoRA": {
+    "Watercolor": {
         "repo_id": "ostris/watercolor-style-lora-sdxl",
         "weight": 0.8,
-        "trigger_words": "watercolor painting, soft colors, artistic",
-        "description": "Watercolor painting style"
+        "trigger_words": "watercolor painting, soft colors",
+        "description": "水彩画风格"
     },
-    "Sketch LoRA": {
+    "Sketch": {
         "repo_id": "ostris/crayon-style-lora-sdxl",
         "weight": 0.7,
-        "trigger_words": "sketch style, pencil drawing, artistic",
-        "description": "Hand-drawn sketch style"
+        "trigger_words": "sketch style, pencil drawing",
+        "description": "素描风格"
     },
-    "Portrait LoRA": {
+    "Portrait": {
         "repo_id": "ostris/face-helper-sdxl-lora",
         "weight": 0.8,
         "trigger_words": "portrait, beautiful face, detailed eyes",
-        "description": "Portrait and face enhancement"
+        "description": "肖像和面部增强"
     }
 }
 
-# Default Parameters
+# 默认参数
 DEFAULT_SEED = -1
 DEFAULT_WIDTH = 1024
 DEFAULT_HEIGHT = 1024
 DEFAULT_LORA_SCALE = 0.8
-DEFAULT_STEPS = 30
-DEFAULT_CFG = 7.5
+DEFAULT_STEPS = 28
+DEFAULT_CFG = 7.0
 
-# Supported Languages (for future expansion)
+# 支持的语言
 SUPPORTED_LANGUAGES = {
     "en": "English",
     "zh": "中文",
@@ -124,64 +205,75 @@ SUPPORTED_LANGUAGES = {
 }
 
 # ======================
-# Global Variables: Lazy Loading
+# 全局变量: 懒加载
 # ======================
 pipe = None
+current_model_key = None
 current_loras = {}
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-def load_pipeline():
-    """Load the base Illustrious XL pipeline with fallback options"""
-    global pipe
-    if pipe is None:
-        print(f"🚀 Loading base model: {BASE_MODEL}...")
-        
-        # Try to load the selected model with fallback options
-        model_loaded = False
-        models_to_try = [BASE_MODEL]
-        
-        # Add fallback models if primary fails
-        if CURRENT_MODEL_KEY != "sdxl_base":
-            models_to_try.append(BASE_MODELS["sdxl_base"])
-        if CURRENT_MODEL_KEY != "realistic_vision":
-            models_to_try.append(BASE_MODELS["realistic_vision"])
+def load_pipeline(model_key: str = None):
+    """灵活加载pipeline,支持不同模型"""
+    global pipe, current_model_key
+    
+    if model_key is None:
+        model_key = DEFAULT_MODEL_KEY
+    
+    # 如果模型已加载且是同一个,直接返回
+    if pipe is not None and current_model_key == model_key:
+        return pipe
+    
+    # 卸载旧模型
+    if pipe is not None:
+        unload_pipeline()
+    
+    model_config = MODEL_CONFIGS.get(model_key)
+    if not model_config:
+        raise ValueError(f"未知的模型配置: {model_key}")
+    
+    print(f"🚀 加载模型: {model_config['description']} ({model_config['repo_id']})")
+    
+    try:
+        # 加载SDXL类型的模型
+        if model_config["type"] == "sdxl":
+            pipe = StableDiffusionXLPipeline.from_pretrained(
+                model_config["repo_id"],
+                torch_dtype=torch.float16,
+                use_safetensors=True,
+                variant="fp16",
+                safety_checker=None if not model_config["requires_safety_checker"] else "default"
+            ).to(device)
             
-        for model_id in models_to_try:
-            try:
-                print(f"Attempting to load: {model_id}")
-                pipe = StableDiffusionXLPipeline.from_pretrained(
-                    model_id,
-                    torch_dtype=torch.float16,
-                    use_safetensors=True,
-                    variant="fp16"
-                ).to(device)
-                
-                # Enable memory optimizations for ZeroGPU
-                pipe.enable_attention_slicing()
-                pipe.enable_vae_slicing()
-                if hasattr(pipe, 'enable_model_cpu_offload'):
-                    pipe.enable_model_cpu_offload()
-                if hasattr(pipe, 'enable_xformers_memory_efficient_attention'):
+            # 内存优化
+            pipe.enable_attention_slicing()
+            pipe.enable_vae_slicing()
+            if hasattr(pipe, 'enable_model_cpu_offload'):
+                pipe.enable_model_cpu_offload()
+            if hasattr(pipe, 'enable_xformers_memory_efficient_attention'):
+                try:
                     pipe.enable_xformers_memory_efficient_attention()
-                
-                print(f"✅ Successfully loaded: {model_id}")
-                model_loaded = True
-                break
-                
-            except Exception as e:
-                print(f"❌ Failed to load {model_id}: {e}")
-                continue
-        
-        if not model_loaded:
-            raise Exception("Failed to load any model. Please check your configuration.")
+                except:
+                    print("⚠️ xformers不可用,跳过")
+            
+            current_model_key = model_key
+            print(f"✅ 成功加载模型: {model_config['description']}")
+            return pipe
+        else:
+            raise ValueError(f"不支持的模型类型: {model_config['type']}")
             
-    return pipe
+    except Exception as e:
+        print(f"❌ 加载模型失败: {e}")
+        # 尝试加载备用模型
+        if model_key != "sdxl_base":
+            print("🔄 尝试加载备用模型...")
+            return load_pipeline("sdxl_base")
+        else:
+            raise Exception("无法加载任何模型")
 
 def unload_pipeline():
-    """Unload pipeline to free memory"""
-    global pipe, current_loras
+    """卸载pipeline释放内存"""
+    global pipe, current_loras, current_model_key
     if pipe is not None:
-        # Clear any loaded LoRAs
         try:
             pipe.unload_lora_weights()
         except:
@@ -190,16 +282,17 @@ def unload_pipeline():
         torch.cuda.empty_cache()
         pipe = None
         current_loras = {}
-        print("🗑️ Pipeline unloaded.")
+        current_model_key = None
+        print("🗑️ Pipeline已卸载")
 
 def load_lora_weights(lora_configs: List[Dict]):
-    """Load multiple LoRA weights efficiently with error handling"""
+    """加载多个LoRA权重,带错误处理"""
     global pipe, current_loras
     
     if not lora_configs:
         return
     
-    # Unload existing LoRAs if different
+    # 卸载现有LoRA
     new_lora_ids = [config['repo_id'] for config in lora_configs if config['repo_id']]
     if set(current_loras.keys()) != set(new_lora_ids):
         try:
@@ -208,57 +301,48 @@ def load_lora_weights(lora_configs: List[Dict]):
         except:
             pass
     
-    # Load new LoRAs with better error handling
+    # 加载新LoRA
     adapter_names = []
     adapter_weights = []
     
     for config in lora_configs:
         if config['repo_id'] and config['repo_id'] not in current_loras:
             try:
-                # Try different loading methods
                 adapter_name = config['name'].replace(' ', '_').lower()
-                
-                # Method 1: Direct loading
                 pipe.load_lora_weights(
                     config['repo_id'], 
                     adapter_name=adapter_name
                 )
                 current_loras[config['repo_id']] = adapter_name
-                print(f"✅ Loaded LoRA: {config['name']}")
-                
+                print(f"✅ 加载LoRA: {config['name']}")
             except Exception as e:
-                print(f"⚠️ Failed to load LoRA {config['name']}: {e}")
-                # Skip this LoRA and continue with others
+                print(f"⚠️ LoRA加载失败 {config['name']}: {e}")
                 continue
         
-        # Add to active adapters if successfully loaded
         if config['repo_id'] in current_loras:
             adapter_names.append(current_loras[config['repo_id']])
             adapter_weights.append(config['weight'])
     
-    # Set adapter weights if any adapters loaded
+    # 设置adapter权重
     if adapter_names:
         try:
             pipe.set_adapters(adapter_names, adapter_weights=adapter_weights)
-            print(f"✅ Activated {len(adapter_names)} LoRA adapters")
+            print(f"✅ 激活了 {len(adapter_names)} 个LoRA")
         except Exception as e:
-            print(f"⚠️ Warning setting adapter weights: {e}")
-            # Try without weights
+            print(f"⚠️ 设置adapter权重警告: {e}")
             try:
                 pipe.set_adapters(adapter_names)
             except:
-                print("❌ Failed to set any adapters")
+                print("❌ 无法设置任何adapter")
 
 def process_long_prompt(prompt: str, max_length: int = 77) -> str:
-    """Process long prompts by intelligent truncation and optimization"""
+    """处理长提示词"""
     if len(prompt.split()) <= max_length:
         return prompt
     
-    # Split into sentences and prioritize
     sentences = re.split(r'[.!?]+', prompt)
     sentences = [s.strip() for s in sentences if s.strip()]
     
-    # Keep most important parts (first sentence + key descriptors)
     if sentences:
         result = sentences[0]
         remaining = max_length - len(result.split())
@@ -269,7 +353,6 @@ def process_long_prompt(prompt: str, max_length: int = 77) -> str:
                 result += ". " + sentence
                 remaining -= len(words)
             else:
-                # Add partial sentence with most important words
                 important_words = [w for w in words if len(w) > 3][:remaining]
                 if important_words:
                     result += ". " + " ".join(important_words)
@@ -280,10 +363,11 @@ def process_long_prompt(prompt: str, max_length: int = 77) -> str:
     return " ".join(prompt.split()[:max_length])
 
 # ======================
-# Main Generation Function
+# 主生成函数
 # ======================
 @spaces.GPU(duration=60) if SPACES_AVAILABLE else lambda x: x
 def generate_image(
+    model_key: str,
     prompt: str,
     negative_prompt: str,
     style: str,
@@ -294,41 +378,48 @@ def generate_image(
     lora_scale: float,
     steps: int,
     cfg_scale: float,
+    use_fixed_loras: bool,
     language: str = "en"
 ):
-    """Main image generation function with ZeroGPU optimization"""
+    """主图像生成函数,支持ZeroGPU优化"""
     global pipe
     
     try:
-        # Load pipeline
-        pipe = load_pipeline()
+        # 加载指定模型
+        pipe = load_pipeline(model_key)
+        model_config = MODEL_CONFIGS[model_key]
         
-        # Handle seed
+        # 处理种子
         if seed == -1:
             seed = torch.randint(0, 2**32, (1,)).item()
         generator = torch.Generator(device=device).manual_seed(seed)
         
-        # Process prompts
+        # 处理提示词
         style_prefix = STYLE_PROMPTS.get(style, "")
         processed_prompt = process_long_prompt(style_prefix + prompt, max_length=150)
+        
+        # 使用模型默认负面提示词(如果用户未提供)
+        if not negative_prompt.strip():
+            negative_prompt = model_config["default_negative"]
         processed_negative = process_long_prompt(negative_prompt, max_length=100)
         
-        # Prepare LoRA configurations
+        # 准备LoRA配置
         lora_configs = []
         active_trigger_words = []
         
-        # Add fixed LoRAs
-        for name, config in FIXED_LORAS.items():
-            if config["repo_id"]:
-                lora_configs.append({
-                    'name': name,
-                    'repo_id': config["repo_id"],
-                    'weight': config["weight"]
-                })
-                if config["trigger_words"]:
-                    active_trigger_words.append(config["trigger_words"])
+        # 添加固定LoRA(如果启用)
+        if use_fixed_loras:
+            for name, config in FIXED_LORAS.items():
+                if config["repo_id"] and config["enabled"]:
+                    lora_configs.append({
+                        'name': name,
+                        'repo_id': config["repo_id"],
+                        'weight': config["weight"]
+                    })
+                    if config["trigger_words"]:
+                        active_trigger_words.append(config["trigger_words"])
         
-        # Add selected optional LoRAs
+        # 添加用户选择的LoRA
         for lora_name in selected_loras:
             if lora_name != "None" and lora_name in OPTIONAL_LORAS:
                 config = OPTIONAL_LORAS[lora_name]
@@ -341,17 +432,17 @@ def generate_image(
                     if config["trigger_words"]:
                         active_trigger_words.append(config["trigger_words"])
         
-        # Load LoRAs
+        # 加载LoRA
         load_lora_weights(lora_configs)
         
-        # Combine trigger words with prompt
+        # 组合触发词
         if active_trigger_words:
             trigger_text = ", ".join(active_trigger_words)
             final_prompt = f"{processed_prompt}, {trigger_text}"
         else:
             final_prompt = processed_prompt
         
-        # Generate image
+        # 生成图像
         with torch.autocast(device):
             image = pipe(
                 prompt=final_prompt,
@@ -363,15 +454,17 @@ def generate_image(
                 generator=generator,
             ).images[0]
         
-        # Generate metadata
+        # 生成元数据
         timestamp = datetime.datetime.now()
         metadata = {
+            "model": model_config["description"],
+            "model_repo": model_config["repo_id"],
             "prompt": final_prompt,
             "original_prompt": prompt,
             "negative_prompt": processed_negative,
-            "base_model": BASE_MODEL,
             "style": style,
-            "fixed_loras": [name for name in FIXED_LORAS.keys()],
+            "fixed_loras_enabled": use_fixed_loras,
+            "fixed_loras": [name for name, config in FIXED_LORAS.items() if config["enabled"]] if use_fixed_loras else [],
             "selected_loras": [name for name in selected_loras if name != "None"],
             "lora_scale": lora_scale,
             "seed": seed,
@@ -384,301 +477,237 @@ def generate_image(
             "trigger_words": active_trigger_words
         }
         
-        # Generate filenames
-        timestamp_str = timestamp.strftime("%y%m%d%H%M")
-        filename_base = f"{seed}-{timestamp_str}"
-        
-        # Save image as WebP
-        img_buffer = io.BytesIO()
-        image.save(img_buffer, format="WEBP", quality=95, method=6)
-        img_buffer.seek(0)
-        
-        # Save metadata as JSON
         metadata_str = json.dumps(metadata, indent=2, ensure_ascii=False)
         
         return (
             image,
-            metadata_str
+            metadata_str,
+            f"✅ 生成成功! 种子: {seed}"
         )
         
     except Exception as e:
-        error_msg = f"Generation failed: {str(e)}"
+        error_msg = f"生成失败: {str(e)}"
         print(f"❌ {error_msg}")
-        return None, error_msg
+        return None, error_msg, error_msg
 
 # ======================
-# Gradio Interface
+# Gradio界面
 # ======================
 def create_interface():
-    """Create the Gradio interface"""
+    """创建Gradio界面"""
     
     with gr.Blocks(
         theme=gr.themes.Soft(
-            primary_hue="indigo",
-            secondary_hue="green",
+            primary_hue="blue",
+            secondary_hue="purple",
             neutral_hue="slate",
-        ).set(
-            body_background_fill="linear-gradient(135deg, #1e40af, #059669)",
-            button_primary_background_fill="white",
-            button_primary_text_color="#1e40af",
-            input_background_fill="rgba(255,255,255,0.9)",
-            block_background_fill="rgba(255,255,255,0.1)",
         ),
         css="""
-        body { 
-            font-family: 'Segoe UI', 'Arial', sans-serif; 
-            background: linear-gradient(135deg, #1e40af, #059669);
-        }
-        .gr-button { 
-            font-family: 'Segoe UI', 'Arial', sans-serif; 
-            font-weight: 600;
-            border-radius: 8px;
-        }
-        .gr-textbox { 
-            font-family: 'Consolas', 'Monaco', 'Courier New', monospace; 
-            border-radius: 8px;
-        }
-        .gr-dropdown, .gr-slider, .gr-radio { 
-            border-radius: 8px;
+        .model-card { 
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            padding: 20px;
+            border-radius: 12px;
+            color: white;
+            margin-bottom: 20px;
         }
-        .gr-form { 
+        .control-section {
             background: rgba(255,255,255,0.05);
-            border-radius: 16px;
-            padding: 20px;
-            margin: 10px;
+            border-radius: 12px;
+            padding: 15px;
+            margin: 10px 0;
         }
         """,
-        title="AI Photo Generator - Illustrious XL"
+        title="AI图像生成器 - Illustrious XL多模型版"
     ) as demo:
         
         gr.Markdown("""
-        # 🎨 AI Photo Generator (Illustrious XL + Multi-LoRA)
-        """)
+        # 🎨 AI图像生成器 - Illustrious XL多模型版
+        ### 支持多种SDXL模型自由切换 | 灵活的LoRA组合 | 优化的参数配置
+        """, elem_classes=["model-card"])
         
         with gr.Row():
-            # Left Column - Controls
-            with gr.Column(scale=3, elem_classes=["gr-form"]):
-                
-                # a. Prompt Input
-                prompt_input = gr.Textbox(
-                    label="Prompt (Positive)",
-                    placeholder="A beautiful woman with flowing hair, golden hour lighting, cinematic composition, high detail...",
-                    lines=6,
-                    max_lines=20,
-                    elem_classes=["gr-textbox"]
-                )
+            # 左侧 - 控制面板
+            with gr.Column(scale=3):
                 
-                # b. Negative Prompt Input
-                negative_prompt_input = gr.Textbox(
-                    label="Negative Prompt",
-                    value="blurry, low quality, deformed, cartoon, anime, text, watermark, signature, username, worst quality, low res, bad anatomy, bad hands, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, bad feet, extra fingers, mutated hands, poorly drawn hands, bad proportions, extra limbs, disfigured, ugly, gross proportions, malformed limbs",
-                    lines=4,
-                    max_lines=15,
-                    elem_classes=["gr-textbox"]
-                )
+                # 模型选择
+                with gr.Group(elem_classes=["control-section"]):
+                    gr.Markdown("### 📦 模型选择")
+                    model_dropdown = gr.Dropdown(
+                        choices=[(config["description"], key) for key, config in MODEL_CONFIGS.items()],
+                        value=DEFAULT_MODEL_KEY,
+                        label="基础模型",
+                        info="选择不同的模型以获得不同的风格"
+                    )
+                    model_info = gr.Markdown(MODEL_CONFIGS[DEFAULT_MODEL_KEY]["description"])
                 
-                # c. Style Selection
-                style_radio = gr.Radio(
-                    choices=list(STYLE_PROMPTS.keys()),
-                    label="Style Template",
-                    value="Realistic",
-                    elem_classes=["gr-radio"]
-                )
+                # 提示词输入
+                with gr.Group(elem_classes=["control-section"]):
+                    gr.Markdown("### ✍️ 提示词")
+                    prompt_input = gr.Textbox(
+                        label="正面提示词",
+                        placeholder="描述你想要生成的图像...",
+                        lines=4,
+                        max_lines=20
+                    )
+                    
+                    negative_prompt_input = gr.Textbox(
+                        label="负面提示词(留空使用模型默认)",
+                        placeholder="将自动使用所选模型的推荐负面提示词...",
+                        lines=3,
+                        max_lines=15
+                    )
+                    
+                    style_radio = gr.Radio(
+                        choices=list(STYLE_PROMPTS.keys()),
+                        label="风格模板",
+                        value="None",
+                        info="将自动添加到提示词前"
+                    )
                 
-                # Multi-row controls
-                with gr.Row():
-                    # d. Seed Control
-                    with gr.Column():
+                # 基础参数
+                with gr.Group(elem_classes=["control-section"]):
+                    gr.Markdown("### ⚙️ 基础参数")
+                    
+                    with gr.Row():
                         seed_input = gr.Slider(
                             minimum=-1,
                             maximum=99999999,
                             step=1,
                             value=DEFAULT_SEED,
-                            label="Seed (-1 = Random)"
+                            label="种子 (-1=随机)"
                         )
-                    #    seed_reset = gr.Button("Reset Seed", size="sm")
-                
-                with gr.Row():
-                    # e. Width Control
-                    with gr.Column():
+                    
+                    with gr.Row():
                         width_input = gr.Slider(
                             minimum=512,
                             maximum=1536,
                             step=64,
                             value=DEFAULT_WIDTH,
-                            label="Width"
+                            label="宽度"
                         )
-                    #    width_reset = gr.Button("Reset Width", size="sm")
-                    
-                    # f. Height Control
-                    with gr.Column():
                         height_input = gr.Slider(
                             minimum=512,
                             maximum=1536,
                             step=64,
                             value=DEFAULT_HEIGHT,
-                            label="Height"
+                            label="高度"
+                        )
+                    
+                    with gr.Row():
+                        steps_slider = gr.Slider(
+                            minimum=10,
+                            maximum=100,
+                            step=1,
+                            value=DEFAULT_STEPS,
+                            label="采样步数"
+                        )
+                        cfg_slider = gr.Slider(
+                            minimum=1.0,
+                            maximum=20.0,
+                            step=0.5,
+                            value=DEFAULT_CFG,
+                            label="CFG Scale"
                         )
-                    #    height_reset = gr.Button("Reset Height", size="sm")
-                
-                # g. LoRA Selection (Multi-select)
-                lora_dropdown = gr.Dropdown(
-                    choices=list(OPTIONAL_LORAS.keys()),
-                    label="Optional LoRAs (Multi-select)",
-                    value=["None"],
-                    multiselect=True,
-                    elem_classes=["gr-dropdown"]
-                )
                 
-                # h. LoRA Scale Control
-                with gr.Row():
+                # LoRA配置
+                with gr.Group(elem_classes=["control-section"]):
+                    gr.Markdown("### 🎭 LoRA配置")
+                    
+                    use_fixed_loras = gr.Checkbox(
+                        label="启用固定LoRA增强(质量+细节)",
+                        value=True,
+                        info="自动加载质量和细节增强LoRA"
+                    )
+                    
+                    lora_dropdown = gr.Dropdown(
+                        choices=list(OPTIONAL_LORAS.keys()),
+                        label="额外LoRA(可多选)",
+                        value=["None"],
+                        multiselect=True,
+                        info="选择额外的风格LoRA"
+                    )
+                    
                     lora_scale_slider = gr.Slider(
                         minimum=0.0,
                         maximum=1.5,
                         step=0.05,
                         value=DEFAULT_LORA_SCALE,
-                        label="LoRA Scale"
+                        label="LoRA强度"
                     )
-                #    lora_reset = gr.Button("Reset LoRA", size="sm")
                 
-                # i. Generation Controls
-                with gr.Row():
-                    steps_slider = gr.Slider(
-                        minimum=10,
-                        maximum=100,
-                        step=1,
-                        value=DEFAULT_STEPS,
-                        label="Steps"
-                    )
-                    cfg_slider = gr.Slider(
-                        minimum=1.0,
-                        maximum=20.0,
-                        step=0.1,
-                        value=DEFAULT_CFG,
-                        label="CFG Scale"
-                    )
-                #    gen_reset = gr.Button("Reset Generation", size="sm")
-                
-                # Language Selection (Optional)
-                language_dropdown = gr.Dropdown(
-                    choices=list(SUPPORTED_LANGUAGES.keys()),
-                    label="Language (Optional)",
-                    value="en",
-                    visible=True  # Hidden for now, can be enabled later
-                )
-                
-                # m. Generate Button
+                # 生成按钮
                 generate_btn = gr.Button(
-                    "✨ Generate Image", 
+                    "✨ 生成图像", 
                     variant="primary", 
-                    size="lg",
-                    elem_classes=["gr-button"]
+                    size="lg"
+                )
+                
+                status_text = gr.Textbox(
+                    label="状态",
+                    value="准备就绪",
+                    interactive=False
                 )
             
-            # Right Column - Outputs
+            # 右侧 - 输出
             with gr.Column(scale=2):
-                # j. Image Display
                 image_output = gr.Image(
-                    label="Generated Image", 
-                    height=600, 
+                    label="生成的图像", 
+                    height=600,
                     format="webp"
                 )
                 
-                # Simplified UI without complex download buttons
-                with gr.Row():
-                    gr.Markdown("**Right-click the image above to download**")
+                gr.Markdown("**右键点击图像下载**")
                 
-                # k. Metadata Display
                 metadata_output = gr.Textbox(
-                    label="Generation Metadata (JSON)",
+                    label="生成元数据 (JSON)",
                     lines=15,
-                    max_lines=25,
-                    elem_classes=["gr-textbox"]
+                    max_lines=25
                 )
         
         # ======================
-        # Event Handlers
+        # 事件处理
         # ======================
         
-        # Reset buttons
-        # seed_reset.click(fn=lambda: -1, outputs=seed_input)
-        # width_reset.click(fn=lambda: DEFAULT_WIDTH, outputs=width_input)
-        # height_reset.click(fn=lambda: DEFAULT_HEIGHT, outputs=height_input)
-        # lora_reset.click(fn=lambda: DEFAULT_LORA_SCALE, outputs=lora_scale_slider)
-        # gen_reset.click(
-        #     fn=lambda: (DEFAULT_STEPS, DEFAULT_CFG),
-        #     outputs=[steps_slider, cfg_slider]
-        # )
+        # 模型切换时更新信息
+        def update_model_info(model_key):
+            config = MODEL_CONFIGS[model_key]
+            info = f"""
+**模型:** {config['description']}  
+**仓库:** `{config['repo_id']}`  
+**推荐设置:** 步数={config['optimal_settings']['steps']}, CFG={config['optimal_settings']['cfg']}
+            """
+            return (
+                info,
+                config['optimal_settings']['steps'],
+                config['optimal_settings']['cfg'],
+                config['default_negative']
+            )
         
-        # Main generation function
-        def generate_and_prepare_downloads(*args):
-            result = generate_image(*args)
-            if result[0] is not None:  # Success
-                image, metadata, img_filename, meta_filename = result
-                
-                # Save files temporarily for download
-                import tempfile
-                import os
-                
-                # Create temporary files
-                temp_dir = tempfile.mkdtemp()
-                img_path = os.path.join(temp_dir, img_filename)
-                meta_path = os.path.join(temp_dir, meta_filename)
-                
-                # Save image
-                image.save(img_path, format="WEBP", quality=95)
-                
-                # Save metadata
-                with open(meta_path, 'w', encoding='utf-8') as f:
-                    f.write(metadata)
-                
-                return (
-                    image,
-                    metadata,
-                    img_path,   # File path for download
-                    meta_path   # File path for download
-                )
-            else:  # Error
-                return result[0], result[1], None, None
+        model_dropdown.change(
+            fn=update_model_info,
+            inputs=[model_dropdown],
+            outputs=[model_info, steps_slider, cfg_slider, negative_prompt_input]
+        )
         
-        # Generate button click - Simplified without complex downloads
+        # 生成按钮
         generate_btn.click(
             fn=generate_image,
             inputs=[
-                prompt_input, negative_prompt_input, style_radio,
+                model_dropdown, prompt_input, negative_prompt_input, style_radio,
                 seed_input, width_input, height_input,
                 lora_dropdown, lora_scale_slider,
-                steps_slider, cfg_slider, language_dropdown
+                steps_slider, cfg_slider, use_fixed_loras,
+                gr.Textbox(value="zh", visible=False)
             ],
             outputs=[
-                image_output, metadata_output
+                image_output, metadata_output, status_text
             ]
         )
-        
-        # Show LoRA descriptions
-        def show_lora_info(selected_loras):
-            if not selected_loras or selected_loras == ["None"]:
-                return "No LoRAs selected"
-            
-            info = "Selected LoRAs:\n"
-            for lora_name in selected_loras:
-                if lora_name in OPTIONAL_LORAS:
-                    config = OPTIONAL_LORAS[lora_name]
-                    info += f"• {lora_name}: {config['description']}\n"
-                    if config['trigger_words']:
-                        info += f"  Triggers: {config['trigger_words']}\n"
-            return info
-        
-        lora_dropdown.change(
-            fn=show_lora_info,
-            inputs=[lora_dropdown],
-            outputs=[gr.Textbox(label="LoRA Information", visible=False)]
-        )
     
     return demo
 
 # ======================
-# Launch Application
+# 启动应用
 # ======================
 if __name__ == "__main__":
     demo = create_interface()