Update app.py

app.py

@@ -8,56 +8,89 @@ except ImportError:
 
 import gradio as gr
 import torch
-from diffusers import StableDiffusionPipeline
+from diffusers import DiffusionPipeline, StableDiffusionXLPipeline
 from PIL import Image
 import datetime
 import io
 import json
 import os
-from typing import Optional
+import re
+from typing import Optional, List, Dict
+import numpy as np
 
 # ======================
-# 配置区（你只需修改这里即可扩展）
+# Configuration Section (Modify here to expand)
 # ======================
 
-# 1. 基础模型
-BASE_MODEL = "SG161222/RealisticVisionV6.0"
-
-# 2. 固定LoRA（不可选，自动加载）
-FIXED_LORAS = [
-    ("Lykon/epiCRealism_LoRA", 0.8),      # 质量增强
-    ("latent-consistency/lora-dreamshaper", 0.7),  # 姿势控制
-]
+# 1. Base Model - Illustrious XL v1.0
+BASE_MODEL = "OnomaAIResearch/Illustrious-XL-v1.0"
+
+# 2. Fixed LoRAs (Auto-loaded, not user-selectable)
+FIXED_LORAS = {
+    "quality_enhancer": {
+        "repo_id": "stabilityai/stable-diffusion-xl-base-1.0",
+        "filename": "sd_xl_base_1.0.safetensors",
+        "weight": 0.8,
+        "trigger_words": "high quality, detailed, sharp"
+    },
+    "pose_control": {
+        "repo_id": "latent-consistency/lcm-lora-sdxl",
+        "filename": None,
+        "weight": 0.7,
+        "trigger_words": "perfect anatomy, natural pose"
+    }
+}
 
-# 3. 风格模板（自动拼接到用户提示词前）
+# 3. Style Templates (Auto-prepended to user prompts)
 STYLE_PROMPTS = {
     "None": "",
-    "Realistic": "photorealistic, ultra-detailed skin, natural lighting, 8k, professional photography, f/1.8, shallow depth of field, Canon EOS R5, ",
-    "Anime": "anime style, cel shading, vibrant colors, detailed eyes, studio ghibli, trending on pixiv, ",
-    "Comic": "comic book style, bold outlines, dynamic angles, comic panel, Marvel style, inked lines, ",
-    "Watercolor": "watercolor painting, soft brush strokes, translucent layers, artistic, painterly, paper texture, ",
+    "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, ",
 }
 
-# 4. 可选LoRA下拉菜单（用户可选1个，None表示清除）
-OPTIONAL_LORAS = [
-    "None",
-    "Add Detail: https://huggingface.co/latent-consistency/lora-add-detail",
-    "Vintage Photo: https://huggingface.co/ckpt/LoRA-vintage-photo",
-    "Cinematic: https://huggingface.co/latent-consistency/lora-cinematic",
-    "Portrait Enhancer: https://huggingface.co/deforum/Portrait-Enhancer-LoRA",
-    "Soft Focus: https://huggingface.co/latent-consistency/lora-soft-focus",
-]
-
-# 解析可选LoRA的名称和ID
-OPTIONAL_LORA_MAP = {}
-for item in OPTIONAL_LORAS:
-    if item != "None":
-        name, url = item.split(": ", 1)
-        OPTIONAL_LORA_MAP[name] = url
-    else:
-        OPTIONAL_LORA_MAP["None"] = None
+# 4. Optional LoRAs (User-selectable via dropdown, can select multiple)
+OPTIONAL_LORAS = {
+    "None": {
+        "repo_id": None,
+        "weight": 0.0,
+        "trigger_words": "",
+        "description": "No additional LoRA"
+    },
+    "Detail Enhancement": {
+        "repo_id": "ByteDance/SDXL-Lightning",
+        "weight": 0.8,
+        "trigger_words": "extremely detailed, intricate details, hyperdetailed",
+        "description": "Enhances fine details and textures"
+    },
+    "Portrait Master": {
+        "repo_id": "ostris/face-helper-sdxl-lora",
+        "weight": 0.9,
+        "trigger_words": "perfect face, beautiful eyes, detailed skin texture",
+        "description": "Specializes in realistic portraits"
+    },
+    "Cinematic Style": {
+        "repo_id": "goofyai/cyborg_style_xl",
+        "weight": 0.7,
+        "trigger_words": "cinematic lighting, dramatic shadows, film noir",
+        "description": "Adds cinematic atmosphere"
+    },
+    "Vintage Photo": {
+        "repo_id": "artificialguybr/LogoRedmond-LogoLoraForSDXL-V2",
+        "weight": 0.6,
+        "trigger_words": "vintage photo, retro style, film photography",
+        "description": "Vintage photography effects"
+    },
+    "Art Nouveau": {
+        "repo_id": "ostris/super-cereal-sdxl-lora",
+        "weight": 0.8,
+        "trigger_words": "art nouveau style, ornate decorations, flowing lines",
+        "description": "Art Nouveau artistic style"
+    }
+}
 
-# 默认参数
+# Default Parameters
 DEFAULT_SEED = -1
 DEFAULT_WIDTH = 1024
 DEFAULT_HEIGHT = 1024
@@ -65,337 +98,542 @@ DEFAULT_LORA_SCALE = 0.8
 DEFAULT_STEPS = 30
 DEFAULT_CFG = 7.5
 
+# Supported Languages (for future expansion)
+SUPPORTED_LANGUAGES = {
+    "en": "English",
+    "zh": "中文",
+    "ja": "日本語",
+    "ko": "한국어"
+}
+
 # ======================
-# 全局变量：延迟加载模型
+# Global Variables: Lazy Loading
 # ======================
 pipe = None
+current_loras = {}
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 def load_pipeline():
+    """Load the base Illustrious XL pipeline"""
     global pipe
     if pipe is None:
-        print("🚀 Loading base model...")
-        pipe = StableDiffusionPipeline.from_pretrained(
+        print("🚀 Loading Illustrious XL base model...")
+        pipe = StableDiffusionXLPipeline.from_pretrained(
             BASE_MODEL,
             torch_dtype=torch.float16,
-            safety_checker=None,
-            requires_safety_checker=False,
+            use_safetensors=True,
+            variant="fp16"
         ).to(device)
+        
+        # Enable memory optimizations for ZeroGPU
         pipe.enable_attention_slicing()
         pipe.enable_vae_slicing()
-        pipe.enable_model_cpu_offload()  # 适配ZeroGPU
-        print("✅ Base model loaded.")
+        pipe.enable_model_cpu_offload()
+        pipe.enable_xformers_memory_efficient_attention()
+        
+        print("✅ Illustrious XL model loaded successfully.")
     return pipe
 
 def unload_pipeline():
-    global pipe
+    """Unload pipeline to free memory"""
+    global pipe, current_loras
     if pipe is not None:
+        # Clear any loaded LoRAs
+        try:
+            pipe.unload_lora_weights()
+        except:
+            pass
         del pipe
         torch.cuda.empty_cache()
         pipe = None
+        current_loras = {}
         print("🗑️ Pipeline unloaded.")
 
+def load_lora_weights(lora_configs: List[Dict]):
+    """Load multiple LoRA weights efficiently"""
+    global pipe, current_loras
+    
+    if not lora_configs:
+        return
+    
+    # Unload existing LoRAs if different
+    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:
+            pipe.unload_lora_weights()
+            current_loras = {}
+        except:
+            pass
+    
+    # Load new LoRAs
+    adapter_names = []
+    adapter_weights = []
+    
+    for config in lora_configs:
+        if config['repo_id'] and config['repo_id'] not in current_loras:
+            try:
+                pipe.load_lora_weights(
+                    config['repo_id'], 
+                    adapter_name=config['name']
+                )
+                current_loras[config['repo_id']] = config['name']
+                print(f"✅ Loaded LoRA: {config['name']}")
+            except Exception as e:
+                print(f"❌ Failed to load LoRA {config['name']}: {e}")
+                continue
+        
+        if config['repo_id']:
+            adapter_names.append(config['name'])
+            adapter_weights.append(config['weight'])
+    
+    # Set adapter weights
+    if adapter_names:
+        try:
+            pipe.set_adapters(adapter_names, adapter_weights=adapter_weights)
+        except Exception as e:
+            print(f"⚠️ Warning setting adapter weights: {e}")
+
+def process_long_prompt(prompt: str, max_length: int = 77) -> str:
+    """Process long prompts by intelligent truncation and optimization"""
+    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())
+        
+        for sentence in sentences[1:]:
+            words = sentence.split()
+            if len(words) <= remaining:
+                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)
+                break
+        
+        return result
+    
+    return " ".join(prompt.split()[:max_length])
+
 # ======================
-# 主生成函数
+# Main Generation Function
 # ======================
+@spaces.GPU(duration=60) if SPACES_AVAILABLE else lambda x: x
 def generate_image(
-    prompt, negative_prompt, style, seed, width, height, optional_lora_name, lora_scale,
-    steps, cfg_scale
+    prompt: str,
+    negative_prompt: str,
+    style: str,
+    seed: int,
+    width: int,
+    height: int,
+    selected_loras: List[str],
+    lora_scale: float,
+    steps: int,
+    cfg_scale: float,
+    language: str = "en"
 ):
+    """Main image generation function with ZeroGPU optimization"""
     global pipe
-
-    # 加载模型（懒加载）
-    pipe = load_pipeline()
-
-    # 处理种子
-    if seed == -1:
-        seed = torch.randint(0, 2**32, (1,)).item()
-    generator = torch.Generator(device=device).manual_seed(seed)
-
-    # 拼接风格提示词
-    full_prompt = STYLE_PROMPTS[style] + prompt
-    full_negative_prompt = negative_prompt
-
-    # 加载固定LoRA（每次生成前都加载，确保状态正确）
-    for lora_id, scale in FIXED_LORAS:
-        pipe.load_lora_weights(lora_id, adapter_name=lora_id)
-        pipe.set_adapters([lora_id], adapter_weights=[scale])
-
-    # 加载可选LoRA（如果非None）
-    if optional_lora_name != "None":
-        lora_url = OPTIONAL_LORA_MAP[optional_lora_name]
-        pipe.load_lora_weights(lora_url, adapter_name=optional_lora_name)
-        pipe.set_adapters([lora_id for lora_id, _ in FIXED_LORAS] + [optional_lora_name], 
-                          adapter_weights=[scale for _, scale in FIXED_LORAS] + [lora_scale])
-    else:
-        # 清除所有可选LoRA，只保留固定
-        pipe.set_adapters([lora_id for lora_id, _ in FIXED_LORAS], 
-                          adapter_weights=[scale for _, scale in FIXED_LORAS])
-
-    # 生成图像
-    image = pipe(
-        prompt=full_prompt,
-        negative_prompt=full_negative_prompt,
-        num_inference_steps=steps,
-        guidance_scale=cfg_scale,
-        width=width,
-        height=height,
-        generator=generator,
-    ).images[0]
-
-    # 生成元数据
-    metadata = {
-        "prompt": full_prompt,
-        "negative_prompt": full_negative_prompt,
-        "base_model": BASE_MODEL,
-        "fixed_loras": [lora_id for lora_id, _ in FIXED_LORAS],
-        "optional_lora": optional_lora_name if optional_lora_name != "None" else None,
-        "lora_scale": lora_scale,
-        "seed": seed,
-        "steps": steps,
-        "cfg_scale": cfg_scale,
-        "style": style,
-        "width": width,
-        "height": height,
-        "timestamp": datetime.datetime.now().isoformat()
-    }
-
-    # 生成文件名
-    timestamp = datetime.datetime.now().strftime("%y%m%d%H%M")
-    filename_base = f"{seed}-{timestamp}"
-
-    # 保存为WebP（高质量）
-    img_buffer = io.BytesIO()
-    image.save(img_buffer, format="WEBP", quality=95, method=6)
-    img_buffer.seek(0)
-
-    # 保存元数据为TXT
-    metadata_buffer = io.StringIO()
-    json.dump(metadata, metadata_buffer, indent=2, ensure_ascii=False)
-    metadata_buffer.seek(0)
-
-    # 返回：图像、元数据、文件名
-    return (
-        image,
-        json.dumps(metadata, indent=2, ensure_ascii=False),
-        f"{filename_base}.webp",
-        f"{filename_base}.txt",
-        img_buffer.getvalue(),
-        metadata_buffer.getvalue().encode('utf-8')
-    )
+    
+    try:
+        # Load pipeline
+        pipe = load_pipeline()
+        
+        # Handle seed
+        if seed == -1:
+            seed = torch.randint(0, 2**32, (1,)).item()
+        generator = torch.Generator(device=device).manual_seed(seed)
+        
+        # Process prompts
+        style_prefix = STYLE_PROMPTS.get(style, "")
+        processed_prompt = process_long_prompt(style_prefix + prompt, max_length=150)
+        processed_negative = process_long_prompt(negative_prompt, max_length=100)
+        
+        # Prepare LoRA configurations
+        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"])
+        
+        # Add selected optional LoRAs
+        for lora_name in selected_loras:
+            if lora_name != "None" and lora_name in OPTIONAL_LORAS:
+                config = OPTIONAL_LORAS[lora_name]
+                if config["repo_id"]:
+                    lora_configs.append({
+                        'name': lora_name,
+                        'repo_id': config["repo_id"],
+                        'weight': config["weight"] * lora_scale
+                    })
+                    if config["trigger_words"]:
+                        active_trigger_words.append(config["trigger_words"])
+        
+        # Load LoRAs
+        load_lora_weights(lora_configs)
+        
+        # Combine trigger words with prompt
+        if active_trigger_words:
+            trigger_text = ", ".join(active_trigger_words)
+            final_prompt = f"{processed_prompt}, {trigger_text}"
+        else:
+            final_prompt = processed_prompt
+        
+        # Generate image
+        with torch.autocast(device):
+            image = pipe(
+                prompt=final_prompt,
+                negative_prompt=processed_negative,
+                num_inference_steps=steps,
+                guidance_scale=cfg_scale,
+                width=width,
+                height=height,
+                generator=generator,
+            ).images[0]
+        
+        # Generate metadata
+        timestamp = datetime.datetime.now()
+        metadata = {
+            "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()],
+            "selected_loras": [name for name in selected_loras if name != "None"],
+            "lora_scale": lora_scale,
+            "seed": seed,
+            "steps": steps,
+            "cfg_scale": cfg_scale,
+            "width": width,
+            "height": height,
+            "language": language,
+            "timestamp": timestamp.isoformat(),
+            "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,
+            f"{filename_base}.webp",
+            f"{filename_base}.txt"
+        )
+        
+    except Exception as e:
+        error_msg = f"Generation failed: {str(e)}"
+        print(f"❌ {error_msg}")
+        return None, error_msg, "", ""
 
 # ======================
-# Gradio UI
+# Gradio Interface
 # ======================
-with gr.Blocks(
-    theme=gr.themes.Soft(
-        primary_hue="blue",
-        secondary_hue="green",
-        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)",
-    ),
-    css="""
-    body { font-family: 'Helvetica Neue', 'Segoe UI', 'Arial', sans-serif; }
-    .gr-button { font-family: 'Helvetica Neue', 'Arial', sans-serif; font-weight: 500; }
-    .gr-textarea { font-family: 'Consolas', 'Monaco', 'Courier New', monospace; }
-    """,
-) as demo:
-    gr.Markdown(
-        """
-        # 🎨 AI Photo Generator (RealisticVision + LoRA)
-        **PRO + ZeroGPU Optimized | Multi-LoRA | Style Templates | Metadata Export**
-        """
-    )
-
-    with gr.Row():
-        with gr.Column(scale=3):
-            # a. 提示词输入框
-            prompt_input = gr.Textbox(
-                label="Prompt (Positive)",
-                placeholder="A beautiful woman, golden hour, soft sunlight...",
-                lines=5,
-                max_lines=20,
-                elem_classes=["gr-textarea"]
-            )
-
-            # b. 负提示词输入框
-            negative_prompt_input = gr.Textbox(
-                label="Negative Prompt",
-                placeholder="blurry, low quality, deformed, cartoon, anime, text, watermark...",
-                lines=5,
-                max_lines=20,
-                elem_classes=["gr-textarea"]
-            )
-
-            # c. 风格选择（单选）
-            style_radio = gr.Radio(
-                choices=list(STYLE_PROMPTS.keys()),
-                label="Style",
-                value="Realistic",
-                elem_classes=["gr-radio"]
-            )
-
-            # d. 种子选择
-            with gr.Row():
-                seed_input = gr.Slider(
-                    minimum=-1,
-                    maximum=99999999,
-                    step=1,
-                    value=DEFAULT_SEED,
-                    label="Seed (-1 = Random)"
+def create_interface():
+    """Create the Gradio interface"""
+    
+    with gr.Blocks(
+        theme=gr.themes.Soft(
+            primary_hue="blue",
+            secondary_hue="green",
+            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;
+        }
+        .gr-form { 
+            background: rgba(255,255,255,0.05);
+            border-radius: 16px;
+            padding: 20px;
+            margin: 10px;
+        }
+        """,
+        title="AI Photo Generator - Illustrious XL"
+    ) as demo:
+        
+        gr.Markdown("""
+        # 🎨 AI Photo Generator (Illustrious XL + Multi-LoRA)
+        **PRO + ZeroGPU Optimized | Multi-LoRA Support | Style Templates | Metadata Export | 1536x1536 Native Resolution**
+        """)
+        
+        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"]
                 )
-                seed_reset = gr.Button("Reset Seed")
-
-            # e. 宽度选择
-            with gr.Row():
-                width_input = gr.Slider(
-                    minimum=512,
-                    maximum=1536,
-                    step=64,
-                    value=DEFAULT_WIDTH,
-                    label="Width"
+                
+                # 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"]
                 )
-                width_reset = gr.Button("Reset Width")
-
-            # f. 高度选择
-            with gr.Row():
-                height_input = gr.Slider(
-                    minimum=512,
-                    maximum=1536,
-                    step=64,
-                    value=DEFAULT_HEIGHT,
-                    label="Height"
+                
+                # c. Style Selection
+                style_radio = gr.Radio(
+                    choices=list(STYLE_PROMPTS.keys()),
+                    label="Style Template",
+                    value="Realistic",
+                    elem_classes=["gr-radio"]
                 )
-                height_reset = gr.Button("Reset Height")
-
-            # g. LoRA选择（下拉）
-            optional_lora_dropdown = gr.Dropdown(
-                choices=list(OPTIONAL_LORA_MAP.keys()),
-                label="Optional LoRA",
-                value="None",
-                elem_classes=["gr-dropdown"]
-            )
-
-            # h. LoRA控制
-            with gr.Row():
-                lora_scale_slider = gr.Slider(
-                    minimum=0.0,
-                    maximum=1.5,
-                    step=0.05,
-                    value=DEFAULT_LORA_SCALE,
-                    label="LoRA Scale"
+                
+                # Multi-row controls
+                with gr.Row():
+                    # d. Seed Control
+                    with gr.Column():
+                        seed_input = gr.Slider(
+                            minimum=-1,
+                            maximum=99999999,
+                            step=1,
+                            value=DEFAULT_SEED,
+                            label="Seed (-1 = Random)"
+                        )
+                        seed_reset = gr.Button("Reset Seed", size="sm")
+                
+                with gr.Row():
+                    # e. Width Control
+                    with gr.Column():
+                        width_input = gr.Slider(
+                            minimum=512,
+                            maximum=1536,
+                            step=64,
+                            value=DEFAULT_WIDTH,
+                            label="Width"
+                        )
+                        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"
+                        )
+                        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"]
                 )
-                lora_reset = gr.Button("Reset LoRA Scale")
-
-            # i. 功能控制（Steps & CFG）
-            with gr.Row():
-                steps_slider = gr.Slider(
-                    minimum=10,
-                    maximum=100,
-                    step=1,
-                    value=DEFAULT_STEPS,
-                    label="Steps"
+                
+                # h. LoRA Scale Control
+                with gr.Row():
+                    lora_scale_slider = gr.Slider(
+                        minimum=0.0,
+                        maximum=1.5,
+                        step=0.05,
+                        value=DEFAULT_LORA_SCALE,
+                        label="LoRA Scale"
+                    )
+                    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=0.5,
+                        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=False  # Hidden for now, can be enabled later
                 )
-                cfg_slider = gr.Slider(
-                    minimum=1.0,
-                    maximum=20.0,
-                    step=0.5,
-                    value=DEFAULT_CFG,
-                    label="CFG Scale"
+                
+                # m. Generate Button
+                generate_btn = gr.Button(
+                    "✨ Generate Image", 
+                    variant="primary", 
+                    size="lg",
+                    elem_classes=["gr-button"]
                 )
-                gen_reset = gr.Button("Reset Generation")
-
-            # m. 生成按钮
-            generate_btn = gr.Button("✨ Generate Image", variant="primary", size="lg")
-
-        with gr.Column(scale=2):
-            # j. 图片显示区
-            image_output = gr.Image(label="Generated Image", height=768, format="webp")
-
-            # k. 元数据显示区
-            metadata_output = gr.Textbox(
-                label="Metadata (JSON)",
-                lines=12,
-                max_lines=20,
-                elem_classes=["gr-textarea"]
-            )
-
-            # l. 下载按钮（并列）
-            with gr.Row():
-                download_img_btn = gr.Button("⬇️ Download Image (WebP)")
-                download_meta_btn = gr.Button("⬇️ Download Metadata (TXT)")
-
-            # 隐藏文件输出（用于下载）
-            hidden_img_file = gr.File(visible=False)
-            hidden_meta_file = gr.File(visible=False)
-
-    # ======================
-    # 事件绑定
-    # ======================
-
-    # 重置种子
-    seed_reset.click(fn=lambda: -1, outputs=seed_input)
-    # 重置宽度
-    width_reset.click(fn=lambda: DEFAULT_WIDTH, outputs=width_input)
-    # 重置高度
-    height_reset.click(fn=lambda: DEFAULT_HEIGHT, outputs=height_input)
-    # 重置LoRA缩放
-    lora_reset.click(fn=lambda: DEFAULT_LORA_SCALE, outputs=lora_scale_slider)
-    # 重置生成参数
-    gen_reset.click(
-        fn=lambda: (DEFAULT_STEPS, DEFAULT_CFG),
-        outputs=[steps_slider, cfg_slider]
-    )
-
-    # 生成
-    generate_btn.click(
-        fn=generate_image,
-        inputs=[
-            prompt_input, negative_prompt_input, style_radio,
-            seed_input, width_input, height_input,
-            optional_lora_dropdown, lora_scale_slider,
-            steps_slider, cfg_slider
-        ],
-        outputs=[
-            image_output, metadata_output,
-            hidden_img_file, hidden_meta_file,
-            hidden_img_file, hidden_meta_file
-        ]
-    )
-
-    # 下载图片
-    download_img_btn.click(
-        fn=None,
-        inputs=[hidden_img_file],
-        outputs=None,
-        js="(f) => { const a = document.createElement('a'); a.href = f; a.download = f.split('/').pop(); document.body.appendChild(a); a.click(); document.body.removeChild(a); }"
-    )
-
-    # 下载元数据
-    generate_btn.click(
-        fn=generate_image,
-        inputs=[
-            prompt_input, negative_prompt_input, style_radio,
-            seed_input, width_input, height_input,
-            optional_lora_dropdown, lora_scale_slider,
-            steps_slider, cfg_slider
-        ],
-        outputs=[
-            image_output,
-            metadata_output,
-            hidden_img_file,      # 👈 更新隐藏文件组件（Gradio 自动处理下载）
-            hidden_meta_file,     # 👈
-        ]
-    )
-
-    # 设置文件下载（通过返回值触发）
+            
+            # Right Column - Outputs
+            with gr.Column(scale=2):
+                # j. Image Display
+                image_output = gr.Image(
+                    label="Generated Image", 
+                    height=600, 
+                    format="webp"
+                )
+                
+                # l. Download Buttons (between image and metadata)
+                with gr.Row():
+                    download_img_btn = gr.DownloadButton(
+                        "⬇️ Download Image (WebP)",
+                        variant="secondary"
+                    )
+                    download_meta_btn = gr.DownloadButton(
+                        "⬇️ Download Metadata (TXT)",
+                        variant="secondary"
+                    )
+                
+                # k. Metadata Display
+                metadata_output = gr.Textbox(
+                    label="Generation Metadata (JSON)",
+                    lines=15,
+                    max_lines=25,
+                    elem_classes=["gr-textbox"]
+                )
+        
+        # ======================
+        # Event Handlers
+        # ======================
+        
+        # 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]
+        )
+        
+        # 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
+                
+                # Prepare download files
+                img_buffer = io.BytesIO()
+                image.save(img_buffer, format="WEBP", quality=95)
+                img_buffer.seek(0)
+                
+                meta_buffer = io.BytesIO()
+                meta_buffer.write(metadata.encode('utf-8'))
+                meta_buffer.seek(0)
+                
+                return (
+                    image,
+                    metadata,
+                    gr.DownloadButton.update(value=img_buffer.getvalue(), filename=img_filename),
+                    gr.DownloadButton.update(value=meta_buffer.getvalue(), filename=meta_filename)
+                )
+            else:  # Error
+                return result[0], result[1], None, None
+        
+        # Generate button click
+        generate_btn.click(
+            fn=generate_and_prepare_downloads,
+            inputs=[
+                prompt_input, negative_prompt_input, style_radio,
+                seed_input, width_input, height_input,
+                lora_dropdown, lora_scale_slider,
+                steps_slider, cfg_slider, language_dropdown
+            ],
+            outputs=[
+                image_output, metadata_output,
+                download_img_btn, download_meta_btn
+            ]
+        )
+        
+        # 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
+
 # ======================
-# 启动
+# Launch Application
 # ======================
 if __name__ == "__main__":
-    demo.launch()
+    demo = create_interface()
+    demo.queue(max_size=20)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        show_error=True
+    )