# ===== 必须首先导入spaces =====
try:
    import spaces
    SPACES_AVAILABLE = True
    print("✅ Spaces available - ZeroGPU mode")
except ImportError:
    SPACES_AVAILABLE = False
    print("⚠️ Spaces not available - running in regular mode")

# ===== 其他导入 =====
import os
import uuid
from datetime import datetime
import random
import torch
import gradio as gr
from diffusers import DiffusionPipeline
from PIL import Image
import traceback
import numpy as np
import cv2
import imageio
from pathlib import Path
import tempfile
import shutil

# ===== 长提示词处理 =====
try:
    from compel import Compel, ReturnedEmbeddingsType
    COMPEL_AVAILABLE = True
    print("✅ Compel available for long prompt processing")
except ImportError:
    COMPEL_AVAILABLE = False
    print("⚠️ Compel not available - using standard prompt processing")

# ===== 修复后的配置 =====
STYLE_PRESETS = {
    "None": "",
    "Cinematic": "cinematic lighting, dramatic composition, film grain, professional cinematography, movie scene, high production value",
    "Anime": "anime style, detailed animation, high quality anime, cel animation, vibrant anime colors, smooth animation",
    "Realistic": "photorealistic, ultra-detailed, natural lighting, realistic motion, lifelike animation, high fidelity",
    "Fantasy": "fantasy style, magical atmosphere, ethereal lighting, mystical effects, enchanted scene",
    "Artistic": "artistic style, creative composition, unique visual style, expressive animation, stylized rendering"
}

# 固定模型配置 - 使用CogVideoX + LoRA架构
BASE_MODEL = "THUDM/CogVideoX-5b"  # 稳定的官方base model
# 实际可用的LoRA适配器列表
LORA_CONFIGS = [
    {
        "repo_id": "hashu786/CogVideoX-LoRA-CineCam",
        "filename": "pytorch_lora_weights.safetensors", 
        "adapter_name": "cinematic_camera",
        "scale": 0.6
    },
    {
        "repo_id": "alibaba-pai/CogVideoX-Fun-V1.1-Reward-LoRAs",
        "filename": "pytorch_lora_weights.safetensors",
        "adapter_name": "quality_reward", 
        "scale": 0.8
    }
    # 注意：由于是NSFW内容，暂时使用增强质量的LoRA
    # 您可以later添加专门的NSFW LoRA
]

# 质量增强提示词 - 适配视频
QUALITY_ENHANCERS = [
    "high quality video", "(masterpiece:1.3)", "(best quality:1.2)", "smooth animation",
    "detailed motion", "fluid movement", "professional video quality", "high resolution",
    "consistent lighting", "stable composition", "(perfect anatomy:1.1)", "natural motion",
    "cinematic quality", "detailed textures", "smooth transitions"
]

# 修复后的风格专用增强词 - 视频优化
STYLE_ENHANCERS = {
    "Cinematic": [
        "cinematic shot", "(cinematic quality:1.3)", "movie scene", "film lighting", 
        "dramatic composition", "professional cinematography", "cinematic motion", "film grain",
        "dynamic camera work", "cinematic storytelling"
    ],
    "Anime": [
        "anime animation", "(high quality anime:1.3)", "detailed anime", "smooth anime motion", 
        "cel animation style", "(anime video:1.2)", "vibrant anime colors", "anime cinematics",
        "japanese animation", "fluid anime movement"
    ],
    "Realistic": [
        "realistic video", "(photorealistic animation:1.3)", "natural motion", "lifelike movement", 
        "realistic lighting", "(realistic video:1.2)", "natural dynamics", "authentic motion",
        "real-world physics", "documentary style"
    ],
    "Fantasy": [
        "fantasy animation", "(magical video:1.3)", "mystical motion", "ethereal effects", 
        "enchanted scene", "magical atmosphere", "fantasy cinematics", "surreal animation",
        "otherworldly movement", "magical realism"
    ],
    "Artistic": [
        "artistic video", "(creative animation:1.3)", "stylized motion", "artistic composition", 
        "unique visual style", "expressive animation", "creative cinematics", "artistic movement",
        "stylized rendering", "avant-garde video"
    ]
}

# 视频参数配置 - 优化帧率和时长
VIDEO_CONFIG = {
    "default_duration": 2.0,  # 降低到2秒，更稳定
    "max_duration": 4.0,      # 最大4秒
    "default_fps": 12,        # 降低到12fps，减少GPU占用和动画速度
    "max_fps": 24,            # 最大24fps
    "default_width": 512,
    "default_height": 512,
    "max_resolution": 768
}

SAVE_DIR = "generated_videos"
os.makedirs(SAVE_DIR, exist_ok=True)

# ===== 模型相关变量 =====
pipeline = None
compel_processor = None
device = None
model_loaded = False

def initialize_model():
    """优化的模型初始化函数"""
    global pipeline, compel_processor, device, model_loaded
    
    if model_loaded and pipeline is not None:
        return True
    
    try:
        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
        print(f"🖥️ Using device: {device}")
        
        print(f"Loading CogVideoX base model: {BASE_MODEL}")
        print(f"LoRA configurations: {len(LORA_CONFIGS)} adapters")
        
        # 加载基础CogVideoX模型
        try:
            from diffusers import CogVideoXPipeline
            pipeline = CogVideoXPipeline.from_pretrained(
                BASE_MODEL,
                torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
                use_safetensors=True
            )
            print("Successfully loaded CogVideoX base model!")
            
            # 加载LoRA适配器
            for lora_config in LORA_CONFIGS:
                try:
                    pipeline.load_lora_weights(
                        lora_config["repo_id"],
                        weight_name=lora_config["filename"],
                        adapter_name=lora_config["adapter_name"]
                    )
                    print(f"✓ Loaded LoRA: {lora_config['adapter_name']}")
                except Exception as lora_error:
                    print(f"⚠ LoRA loading failed ({lora_config['adapter_name']}): {lora_error}")
            
            # 设置LoRA权重
            adapter_names = [config["adapter_name"] for config in LORA_CONFIGS]
            adapter_weights = [config["scale"] for config in LORA_CONFIGS]
            if adapter_names:
                pipeline.set_adapters(adapter_names, adapter_weights)
                print(f"✓ Applied LoRA adapters with weights: {adapter_weights}")
            
        except Exception as base_error:
            print(f"Base model loading failed: {base_error}")
            print("This should not happen with official CogVideoX model")
            return False
        
        pipeline = pipeline.to(device)
        
        # GPU优化 - CogVideoX优化（更简单可靠）
        if torch.cuda.is_available():
            try:
                if hasattr(pipeline, 'enable_model_cpu_offload'):
                    pipeline.enable_model_cpu_offload()
                if hasattr(pipeline, 'enable_vae_tiling'):
                    pipeline.enable_vae_tiling()
                try:
                    pipeline.enable_xformers_memory_efficient_attention()
                except:
                    pass
                print("CogVideoX memory optimizations applied")
            except Exception as mem_error:
                print(f"Memory optimization warning: {mem_error}")
        
        # 初始化Compel
        if COMPEL_AVAILABLE and hasattr(pipeline, 'tokenizer'):
            try:
                compel_processor = Compel(
                    tokenizer=pipeline.tokenizer,
                    text_encoder=pipeline.text_encoder,
                    returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED,
                    truncate_long_prompts=False
                )
                print("✅ Long prompt processor (Compel) initialized successfully")
            except Exception as compel_error:
                print(f"⚠️ Compel initialization failed: {compel_error}")
                compel_processor = None
        
        model_loaded = True
        print("✅ T2V Model initialization complete")
        return True
        
    except Exception as e:
        print(f"❌ Critical model loading error: {e}")
        print(traceback.format_exc())
        model_loaded = False
        return False

def enhance_prompt(prompt: str, style: str) -> str:
    """修复后的增强提示词函数 - 视频优化"""
    if not prompt or prompt.strip() == "":
        return ""
    
    enhanced_parts = [prompt.strip()]
    
    # 添加风格前缀
    style_prefix = STYLE_PRESETS.get(style, "")
    if style_prefix and style != "None":
        enhanced_parts.insert(0, style_prefix)
    
    # 添加风格特定增强词
    if style in STYLE_ENHANCERS and style != "None":
        style_terms = ", ".join(STYLE_ENHANCERS[style])
        enhanced_parts.append(style_terms)
    
    # 添加质量增强词
    quality_terms = ", ".join(QUALITY_ENHANCERS)
    enhanced_parts.append(quality_terms)
    
    enhanced_prompt = ", ".join(filter(None, enhanced_parts))
    
    print(f"🎨 Style: {style}")
    print(f"📝 Original prompt: {prompt[:100]}...")
    print(f"✨ Enhanced prompt: {enhanced_prompt[:150]}...")
    
    return enhanced_prompt

def process_long_prompt(prompt, negative_prompt=""):
    """处理长提示词"""
    if not compel_processor:
        return None, None
    
    try:
        conditioning = compel_processor([prompt, negative_prompt])
        return conditioning, None
    except Exception as e:
        print(f"Long prompt processing failed: {e}")
        return None, None

def apply_spaces_decorator(func):
    """应用spaces装饰器 - 增加超时时间"""
    if SPACES_AVAILABLE:
        return spaces.GPU(duration=120)(func)  # 2分钟超时
    return func

def create_metadata_content(prompt, enhanced_prompt, seed, steps, cfg_scale, width, height, duration, fps, style):
    """创建元数据内容 - 视频版本"""
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    return f"""Generated Video Metadata
======================
Timestamp: {timestamp}
Original Prompt: {prompt}
Enhanced Prompt: {enhanced_prompt}
Seed: {seed}
Steps: {steps}
CFG Scale: {cfg_scale}
Dimensions: {width}×{height}
Duration: {duration}s
FPS: {fps}
Style: {style}
Model: NSFW_Wan_14b
Total Frames: {int(duration * fps)}
"""

def frames_to_video(frames, output_path, fps=24, format="mp4"):
    """将帧序列转换为视频文件"""
    try:
        if format.lower() == "gif":
            # 生成GIF
            imageio.mimsave(output_path, frames, fps=fps, loop=0)
        else:
            # 生成MP4
            writer = imageio.get_writer(output_path, fps=fps, codec='libx264', quality=8)
            for frame in frames:
                if isinstance(frame, Image.Image):
                    frame = np.array(frame)
                writer.append_data(frame)
            writer.close()
        
        return True
    except Exception as e:
        print(f"Video creation error: {e}")
        return False

@apply_spaces_decorator
def generate_video(prompt: str, style: str, negative_prompt: str = "", steps: int = 20, cfg_scale: float = 7.0, 
                  seed: int = -1, width: int = 512, height: int = 512, duration: float = 4.0, fps: int = 24,
                  progress=gr.Progress()):
    """视频生成函数"""
    if not prompt or prompt.strip() == "":
        return None, None, "", ""
    
    # 初始化模型
    progress(0.1, desc="Loading T2V model...")
    if not initialize_model():
        return None, None, "", "❌ Failed to load T2V model"
    
    progress(0.2, desc="Processing prompt...")
    
    try:
        # 处理seed
        if seed == -1:
            seed = random.randint(0, np.iinfo(np.int32).max)
        
        # 增强提示词
        enhanced_prompt = enhance_prompt(prompt.strip(), style)
        
        # 增强负面提示词
        if not negative_prompt.strip():
            negative_prompt = "(low quality, worst quality:1.4), (bad anatomy:1.2), blurry, watermark, signature, text, error, distorted motion, choppy animation, inconsistent lighting, frame drops, stuttering"
        
        # 计算帧数
        num_frames = int(duration * fps)
        print(f"🎬 Generating {num_frames} frames at {fps} FPS for {duration}s video")
        
        # 生成参数
        generator = torch.Generator(device).manual_seed(seed)
        
        progress(0.3, desc=f"Generating {duration}s video...")
        
        # 长提示词处理
        use_long_prompt = len(enhanced_prompt.split()) > 60 or len(enhanced_prompt) > 300
        
        generation_kwargs = {
            "num_inference_steps": steps,
            "guidance_scale": cfg_scale,
            "width": width,
            "height": height,
            "num_frames": num_frames,
            "generator": generator
        }
        
        if use_long_prompt and compel_processor:
            conditioning, _ = process_long_prompt(enhanced_prompt, negative_prompt)
            if conditioning is not None:
                result = pipeline(
                    prompt_embeds=conditioning[0:1],
                    negative_prompt_embeds=conditioning[1:2],
                    **generation_kwargs
                )
            else:
                result = pipeline(
                    prompt=enhanced_prompt,
                    negative_prompt=negative_prompt,
                    **generation_kwargs
                )
        else:
            result = pipeline(
                prompt=enhanced_prompt,
                negative_prompt=negative_prompt,
                **generation_kwargs
            )
        
        progress(0.8, desc="Processing video output...")
        
        # 获取视频帧
        if hasattr(result, 'frames') and result.frames is not None:
            frames = result.frames[0]  # 取第一个批次
        elif hasattr(result, 'images') and result.images is not None:
            frames = result.images
        else:
            return None, None, "", "❌ No frames generated from model"
        
        print(f"📹 Generated {len(frames)} frames")
        
        # 创建临时文件
        with tempfile.TemporaryDirectory() as temp_dir:
            # 生成MP4
            mp4_path = os.path.join(temp_dir, f"video_{seed}.mp4")
            mp4_success = frames_to_video(frames, mp4_path, fps=fps, format="mp4")
            
            # 生成GIF
            gif_path = os.path.join(temp_dir, f"video_{seed}.gif")
            gif_success = frames_to_video(frames, gif_path, fps=fps, format="gif")
            
            if not mp4_success and not gif_success:
                return None, None, "", "❌ Failed to create video files"
            
            # 复制到永久目录
            final_mp4_path = None
            final_gif_path = None
            
            if mp4_success:
                final_mp4_path = os.path.join(SAVE_DIR, f"video_{seed}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.mp4")
                shutil.copy2(mp4_path, final_mp4_path)
            
            if gif_success:
                final_gif_path = os.path.join(SAVE_DIR, f"video_{seed}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.gif")
                shutil.copy2(gif_path, final_gif_path)
        
        progress(0.95, desc="Creating metadata...")
        
        # 创建元数据内容
        metadata_content = create_metadata_content(
            prompt, enhanced_prompt, seed, steps, cfg_scale, width, height, duration, fps, style
        )
        
        progress(1.0, desc="Complete!")
        
        # 生成信息显示
        generation_info = f"Style: {style} | Seed: {seed} | Size: {width}×{height} | Duration: {duration}s | FPS: {fps} | Frames: {num_frames}"
        
        # 返回MP4路径用于显示，同时提供两种格式的下载
        return final_mp4_path, final_gif_path, generation_info, metadata_content
        
    except Exception as e:
        error_msg = str(e)
        print(f"Generation error: {error_msg}")
        print(traceback.format_exc())
        return None, None, "", f"❌ Generation failed: {error_msg}"

# ===== CSS样式 - 视频版本 =====
css = """
/* 全局容器 */
.gradio-container {
    max-width: 100% !important;
    margin: 0 !important;
    padding: 0 !important;
    background: linear-gradient(135deg, #e6a4f2 0%, #1197e4 100%) !important;
    min-height: 100vh !important;
    font-family: 'Segoe UI', Arial, sans-serif !important;
}

/* 主要内容区域 */
.main-content {
    background: rgba(255, 255, 255, 0.9) !important;
    border-radius: 20px !important;
    padding: 20px !important;
    margin: 15px !important;
    box-shadow: 0 10px 25px rgba(255, 255, 255, 0.2) !important;
    min-height: calc(100vh - 30px) !important;
    color: #3e3e3e !important;
    backdrop-filter: blur(10px) !important;
}

/* 简化标题 */
.title {
    text-align: center !important;
    background: linear-gradient(45deg, #bb6ded, #08676b) !important;
    -webkit-background-clip: text !important;
    -webkit-text-fill-color: transparent !important;
    background-clip: text !important;
    font-size: 2rem !important;
    margin-bottom: 15px !important;
    font-weight: bold !important;
}

/* 简化警告信息 */
.warning-box {
    background: linear-gradient(45deg, #bb6ded, #08676b) !important;
    color: white !important;
    padding: 8px !important;
    border-radius: 8px !important;
    margin-bottom: 15px !important;
    text-align: center !important;
    font-weight: bold !important;
    font-size: 14px !important;
}

/* 输入框样式 - 修复背景色 */
.prompt-box textarea, .prompt-box input {
    border-radius: 10px !important;
    border: 2px solid #bb6ded !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;
    color: #2d2d2d !important;
}

.prompt-box textarea:focus, .prompt-box input:focus {
    border-color: #08676b !important;
    box-shadow: 0 0 15px rgba(77, 8, 161, 0.3) !important;
    background: linear-gradient(135deg, rgba(255, 255, 255, 0.95), rgba(248, 249, 250, 0.95)) !important;
}

/* 右侧控制区域 - 修复背景色 */
.controls-section {
    background: linear-gradient(135deg, rgba(224, 218, 255, 0.8), rgba(196, 181, 253, 0.8)) !important;
    border-radius: 12px !important;
    padding: 15px !important;
    margin-bottom: 8px !important;
    border: 2px solid rgba(187, 109, 237, 0.3) !important;
    backdrop-filter: blur(5px) !important;
}

.controls-section label {
    font-weight: 600 !important;
    color: #2d2d2d !important;
    margin-bottom: 8px !important;
}

/* 修复单选按钮和输入框背景 */
.controls-section input[type="radio"] {
    accent-color: #bb6ded !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-radius: 6px !important;
    padding: 8px !important;
    color: #2d2d2d !important;
}

.controls-section select {
    background: rgba(255, 255, 255, 0.9) !important;
    border: 1px solid #bb6ded !important;
    border-radius: 6px !important;
    padding: 8px !important;
    color: #2d2d2d !important;
}

/* 生成按钮 */
.generate-btn {
    background: linear-gradient(45deg, #bb6ded, #08676b) !important;
    color: white !important;
    border: none !important;
    padding: 15px 25px !important;
    border-radius: 25px !important;
    font-size: 16px !important;
    font-weight: bold !important;
    width: 100% !important;
    cursor: pointer !important;
    transition: all 0.3s ease !important;
    text-transform: uppercase !important;
    letter-spacing: 1px !important;
}

.generate-btn:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 8px 25px rgba(187, 109, 237, 0.5) !important;
}

/* 视频输出区域 */
.video-output {
    border-radius: 15px !important;
    overflow: hidden !important;
    max-width: 100% !important;
    max-height: 70vh !important;
    border: 3px solid #08676b !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;
}

/* 下载按钮样式 */
.download-btn {
    background: linear-gradient(45deg, #28a745, #20c997) !important;
    color: white !important;
    border: none !important;
    padding: 10px 20px !important;
    border-radius: 20px !important;
    font-size: 14px !important;
    font-weight: bold !important;
    margin: 5px !important;
    cursor: pointer !important;
    transition: all 0.3s ease !important;
}

.download-btn:hover {
    transform: translateY(-1px) !important;
    box-shadow: 0 5px 15px rgba(40, 167, 69, 0.4) !important;
}

/* 视频信息区域 */
.video-info {
    background: linear-gradient(135deg, rgba(248, 249, 250, 0.2), 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;
    backdrop-filter: blur(5px) !important;
}

/* 元数据区域样式 */
.metadata-box {
    background: linear-gradient(135deg, rgba(248, 249, 250, 0.2), 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;
    backdrop-filter: blur(5px) !important;
    white-space: pre-wrap !important;
    overflow-y: auto !important;
    max-height: 300px !important;
}

/* 滑块样式 */
.slider-container input[type="range"] {
    accent-color: #bb6ded !important;
}

/* 响应式设计 */
@media (max-width: 768px) {
    .main-content {
        margin: 10px !important;
        padding: 15px !important;
    }
    
    .title {
        font-size: 1.5rem !important;
    }
}

/* 强制覆盖Gradio默认样式 */
.gradio-container .gr-textbox, 
.gradio-container .gr-radio-group,
.gradio-container .gr-slider,
.gradio-container .gr-number {
    background: rgba(255, 255, 255, 0.95) !important;
    border: 1px solid rgba(187, 109, 237, 0.5) !important;
    border-radius: 8px !important;
}

.gradio-container .gr-radio-group label {
    color: #2d2d2d !important;
    background: transparent !important;
}
"""

# ===== 创建UI =====
def create_interface():
    with gr.Blocks(css=css, title="Adult NSFW AI Video Generator") as interface:
        with gr.Column(elem_classes=["main-content"]):
            # 简化标题
            gr.HTML('<div class="title">🎬 Adult NSFW AI Video Generator</div>')
            
            # 简化警告信息
            gr.HTML('''
                <div class="warning-box">
                    ⚠️ 18+ CONTENT WARNING ⚠️ | Model: NSFW_Wan_14b → CogVideoX Architecture
                </div>
            ''')
            
            # 主要输入区域
            with gr.Row():
                # 左侧：提示词输入
                with gr.Column(scale=2):
                    prompt_input = gr.Textbox(
                        label="Detailed Video Prompt",
                        placeholder="Describe the video scene you want to generate...",
                        lines=12,
                        elem_classes=["prompt-box"]
                    )
                    
                    negative_prompt_input = gr.Textbox(
                        label="Negative Prompt (Optional)",
                        placeholder="Things you don't want in the video...",
                        lines=4,
                        elem_classes=["prompt-box"]
                    )
                
                # 右侧：控制选项
                with gr.Column(scale=1):
                    # Style选项
                    with gr.Group(elem_classes=["controls-section"]):
                        style_input = gr.Radio(
                            label="Style Preset",
                            choices=list(STYLE_PRESETS.keys()),
                            value="Cinematic"
                        )
                    
                    # 视频参数
                    with gr.Group(elem_classes=["controls-section"]):
                        gr.HTML("<b>📹 Video Settings</b>")
                        duration_input = gr.Slider(
                            label=f"Duration (seconds)",
                            minimum=1.0,
                            maximum=VIDEO_CONFIG["max_duration"],
                            value=VIDEO_CONFIG["default_duration"],
                            step=0.5
                        )
                        
                        fps_input = gr.Slider(
                            label="FPS (Frames per Second)",
                            minimum=12,
                            maximum=VIDEO_CONFIG["max_fps"],
                            value=VIDEO_CONFIG["default_fps"],
                            step=6
                        )
                    
                    # 分辨率设置
                    with gr.Group(elem_classes=["controls-section"]):
                        gr.HTML("<b>📐 Resolution</b>")
                        width_input = gr.Slider(
                            label="Width",
                            minimum=256,
                            maximum=VIDEO_CONFIG["max_resolution"],
                            value=VIDEO_CONFIG["default_width"],
                            step=64
                        )
                        
                        height_input = gr.Slider(
                            label="Height",
                            minimum=256,
                            maximum=VIDEO_CONFIG["max_resolution"],
                            value=VIDEO_CONFIG["default_height"],
                            step=64
                        )
                    
                    # Seed选项
                    with gr.Group(elem_classes=["controls-section"]):
                        seed_input = gr.Number(
                            label="Seed (-1 for random)",
                            value=-1,
                            precision=0
                        )
                    
                    # 高级参数
                    with gr.Group(elem_classes=["controls-section"]):
                        gr.HTML("<b>⚙️ Advanced</b>")
                        steps_input = gr.Slider(
                            label="Steps",
                            minimum=10,
                            maximum=30,
                            value=20,
                            step=1
                        )
                        
                        cfg_input = gr.Slider(
                            label="CFG Scale",
                            minimum=1.0,
                            maximum=15.0,
                            value=7.0,
                            step=0.1
                        )
                    
                    # 生成按钮
                    generate_button = gr.Button(
                        "🎬 GENERATE VIDEO",
                        elem_classes=["generate-btn"],
                        variant="primary"
                    )
            
            # 视频输出区域
            with gr.Row():
                video_output = gr.Video(
                    label="Generated Video (MP4)",
                    elem_classes=["video-output"],
                    show_label=True,
                    height=400
                )
            
            # 下载区域和信息显示
            with gr.Row():
                with gr.Column(scale=1):
                    mp4_download = gr.File(
                        label="📱 Download MP4",
                        visible=False
                    )
                with gr.Column(scale=1):
                    gif_download = gr.File(
                        label="🎞️ Download GIF",
                        visible=False
                    )
            
            # 视频信息显示
            with gr.Row():
                generation_info = gr.Textbox(
                    label="Generation Info",
                    interactive=False,
                    elem_classes=["video-info"],
                    show_label=True,
                    visible=False
                )
            
            # 元数据显示区域
            with gr.Row():
                metadata_display = gr.Textbox(
                    label="Video Metadata (Copy to save)",
                    interactive=True,
                    elem_classes=["metadata-box"],
                    show_label=True,
                    lines=15,
                    visible=False,
                    placeholder="Generated video metadata will appear here..."
                )
        
        # 生成视频的主要函数
        def on_generate(prompt, style, neg_prompt, steps, cfg, seed, width, height, duration, fps):
            mp4_path, gif_path, info, metadata = generate_video(
                prompt, style, neg_prompt, steps, cfg, seed, width, height, duration, fps
            )
            
            if mp4_path is not None:
                return (
                    mp4_path,  # 视频输出
                    mp4_path if mp4_path and os.path.exists(mp4_path) else None,  # MP4下载
                    gif_path if gif_path and os.path.exists(gif_path) else None,  # GIF下载
                    gr.update(visible=True, value=info),  # 显示生成信息
                    gr.update(visible=True, value=metadata),  # 显示元数据
                    gr.update(visible=True),  # 显示MP4下载
                    gr.update(visible=True)   # 显示GIF下载
                )
            else:
                return (
                    None, 
                    None,
                    None,
                    gr.update(visible=True, value=info if info else "Generation failed"),
                    gr.update(visible=False),
                    gr.update(visible=False),
                    gr.update(visible=False)
                )
        
        # 绑定生成事件
        generate_button.click(
            fn=on_generate,
            inputs=[
                prompt_input, style_input, negative_prompt_input, 
                steps_input, cfg_input, seed_input, width_input, height_input,
                duration_input, fps_input
            ],
            outputs=[
                video_output, mp4_download, gif_download,
                generation_info, metadata_display,
                mp4_download, gif_download
            ],
            show_progress=True
        )
        
        # 支持Enter键触发
        prompt_input.submit(
            fn=on_generate,
            inputs=[
                prompt_input, style_input, negative_prompt_input, 
                steps_input, cfg_input, seed_input, width_input, height_input,
                duration_input, fps_input
            ],
            outputs=[
                video_output, mp4_download, gif_download,
                generation_info, metadata_display,
                mp4_download, gif_download
            ],
            show_progress=True
        )
        
        # 启动时显示欢迎信息
        interface.load(
            fn=lambda: (
                None, None, None,
                gr.update(visible=False), 
                gr.update(visible=False),
                gr.update(visible=False),
                gr.update(visible=False)
            ),
            outputs=[
                video_output, mp4_download, gif_download,
                generation_info, metadata_display,
                mp4_download, gif_download
            ]
        )
    
    return interface

# ===== 启动应用 =====
if __name__ == "__main__":
    print("🎬 Starting NSFW Video Generator...")
    print("Using complete repository structure for proper loading")
    print(f"🔧 Default Duration: {VIDEO_CONFIG['default_duration']}s")
    print(f"🔧 Default Resolution: {VIDEO_CONFIG['default_width']}×{VIDEO_CONFIG['default_height']}")
    print(f"🔧 Spaces GPU: {'✅ Available' if SPACES_AVAILABLE else '❌ Not Available'}")
    print(f"🔧 Compel Library: {'✅ Available' if COMPEL_AVAILABLE else '❌ Not Available'}")
    print(f"🔧 CUDA: {'✅ Available' if torch.cuda.is_available() else '❌ Not Available'}")
    
    app = create_interface()
    app.queue(max_size=5, default_concurrency_limit=1)  # 降低并发以节省GPU
    
    app.launch(
        server_name="0.0.0.0",
        server_port=7860,
        show_error=True,
        share=False
    )