# 更新系统
sudo apt update && sudo apt upgrade -y

# 安装基础工具
sudo apt install -y git curl wget unzip rsync ca-certificates

# 安装 Docker（推荐方式）
curl -fsSL https://get.docker.com | sudo sh
sudo usermod -aG docker $USER
newgrp docker

# 安装 NVIDIA Container Toolkit（GPU 模式必需）
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/stable/deb/$(. /etc/os-release && echo $UBUNTU_CODENAME) main" | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt update
sudo apt install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

# 检查 NVIDIA 驱动
nvidia-smi

# 验证 Docker GPU 支持
docker run --rm --gpus all nvidia/cuda:12.4.1-base-ubuntu22.04 nvidia-smi

mkdir -p ~/stable-diffusion/{models,outputs,data}
cd ~/stable-diffusion

version: "3.8"

services:
  sd-webui:
    image: ghcr.io/fofr/stable-diffusion-webui:latest
    container_name: sd-webui
    restart: unless-stopped
    ports:
      - "7860:7860"
    environment:
      - WEBUI_PORT=7860
      - WEBUI_ARGS=--api --enable-insecure-extension-access --no-half --precision full
    volumes:
      - ./outputs:/backend/outputs
      - ./data:/backend/data
    devices:
      - /dev/null
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]

docker compose up -d

# 从 HuggingFace 下载 SDXL
cd ~/stable-diffusion/models/Stable-diffusion
wget https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors

# 在 docker-compose.yml 中添加 ControlNet 支持
volumes:
  - ./outputs:/backend/outputs
  - ./data:/backend/data
  - ./models/ControlNet:/backend/models/ControlNet

cd ~/stable-diffusion/models/LoRA
wget https://civitai.com/api/download/models/XXXXX -O your-lora.safetensors

#!/bin/bash
export COMMANDLINE_ARGS="--xformers --opt-split-attention --enable-unsafe-sdwebui_args"
export PYTHONFAULTHANDLER=1
export HF_HUB_ENABLE_HF_TRANSFER=1

# Nginx 反向代理配置
server {
    listen 80;
    server_name sd.yourdomain.com;
    
    location / {
        proxy_pass http://127.0.0.1:7860;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
        
        # WebSocket 支持
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
    }
}

export WEBUI_ARGS="--api --api-auth your-secret-api-key"

# 安装 cloudflared
wget https://github.com/cloudflare/cloudflared/releases/latest/download/cloudflared-linux-amd64.deb
sudo dpkg -i cloudflared-linux-amd64.deb

# 启动 Tunnel
cloudflared tunnel --url http://localhost:7860

#!/bin/bash
case "$1" in
  start)
    docker compose up -d
    echo "✅ SD WebUI 已启动，访问 http://$(curl -s ifconfig.me):7860"
    ;;
  stop)
    docker compose stop
    echo "⏹️ SD WebUI 已停止"
    ;;
  restart)
    docker compose restart
    echo "🔄 SD WebUI 已重启"
    ;;
  update)
    docker compose pull
    docker compose up -d
    echo "📦 SD WebUI 已更新到最新版本"
    ;;
  status)
    docker compose ps
    ;;
  logs)
    docker compose logs -f
    ;;
  *)
    echo "用法: $0 {start|stop|restart|update|status|logs}"
    exit 1
    ;;
esac

# 方案1：使用 --medvram 参数
export WEBUI_ARGS="--xformers --medvram"

# 方案2：切换到 SD 1.5 模型（比 SDXL 更省显存）
# 方案3：使用 SD WebUI Forge 版本（更低的显存占用）

# 自动备份脚本
#!/bin/bash
BACKUP_DIR="/backup/sd-outputs-$(date +%Y%m%d)"
mkdir -p $BACKUP_DIR
cp -r ~/stable-diffusion/outputs/* $BACKUP_DIR/
# 可选：上传到 S3/R2
aws s3 sync $BACKUP_DIR s3://your-bucket/sd-backups/

# 启用 Basic Auth
export WEBUI_ARGS="--api --api-auth user:password"

# 或使用 Nginx 基本认证
# 或配置 Cloudflare Access 策略

import requests

API_URL = "http://your-vps:7860/sdapi/v1/txt2img"

payload = {
    "prompt": "a beautiful sunset over the ocean, photorealistic, 8k",
    "negative_prompt": "blurry, low quality",
    "steps": 25,
    "cfg_scale": 7,
    "width": 1024,
    "height": 1024,
    "sampler_name": "Euler a"
}

response = requests.post(API_URL, json=payload)
images = response.json()["images"]

# 保存图片
for i, img in enumerate(images):
    with open(f"output_{i}.png", "wb") as f:
        f.write(requests.get(f"data:image/png;base64,{img}").content)

# crontab 示例：每天早上 9 点生成一张随机创意图
0 9 * * * cd ~/stable-diffusion && python3 auto_generate.py >> logs/auto.log 2>&1