#!/bin/bash
set -e

BASE_DIR="$(cd "$(dirname "$0")" && pwd)"
CONDA_BASE="${CONDA_BASE:-/home/szlc/miniconda3}"

# 初始化 conda（脚本中需要 source 才能用 conda activate）
if [ -f "$CONDA_BASE/etc/profile.d/conda.sh" ]; then
    source "$CONDA_BASE/etc/profile.d/conda.sh"
else
    echo "WARNING: 未找到 conda.sh，请确认 CONDA_BASE=$CONDA_BASE 正确"
fi

echo "=== 换发型项目部署脚本 ==="
echo "BASE_DIR: $BASE_DIR"

# 1. 检查前提条件
echo "[1/7] 检查前提条件..."
command -v git >/dev/null || { echo "ERROR: git 未安装"; exit 1; }
command -v conda >/dev/null || { echo "ERROR: conda 未安装"; exit 1; }
nvidia-smi >/dev/null 2>&1 || { echo "ERROR: NVIDIA 驱动未安装"; exit 1; }

# 2. 生成 configure.ini
echo "[2/7] 生成 configure.ini..."
sed "s|__BASE_DIR__|$BASE_DIR|g" "$BASE_DIR/hair_service_sd/config/configure.ini.template" > "$BASE_DIR/hair_service_sd/config/configure.ini"
echo "  configure.ini 已生成"

# 3. 恢复 conda 环境（conda-pack）
echo "[3/7] 恢复 conda 环境..."
for env_name in my_hair sdwebui kohya; do
    if [ -f "$BASE_DIR/conda_envs/${env_name}.tar.gz" ]; then
        echo "  恢复 $env_name ..."
        rm -rf "$CONDA_BASE/envs/$env_name"
        mkdir -p "$CONDA_BASE/envs/$env_name"
        tar -xzf "$BASE_DIR/conda_envs/${env_name}.tar.gz" -C "$CONDA_BASE/envs/$env_name"
        conda activate "$env_name"
        conda-unpack  # 修复打包后的硬编码路径
        conda deactivate
        echo "  ✓ $env_name 已恢复"
    else
        echo "  ✗ conda_envs/${env_name}.tar.gz 不存在，请从网盘下载"
    fi
done

# 4. 创建 py310 环境（从 yml）
echo "[4/7] 创建 py310 环境..."
if [ -f "$BASE_DIR/conda_envs/py310.yml" ]; then
    conda env create -f "$BASE_DIR/conda_envs/py310.yml" -n py310 2>/dev/null || echo "  py310 环境已存在，跳过"
    echo "  ✓ py310 已就绪"
else
    echo "  ✗ conda_envs/py310.yml 不存在"
fi

# 5. 检查模型/数据目录
echo "[5/7] 检查模型和数据目录..."
for dir in hair_service_sd/weights stable-diffusion-webui/models/Lora stable-diffusion-webui/models/Stable-diffusion stable-diffusion-webui/extensions/sd-webui-controlnet stable-diffusion-webui/repositories kohya_ss_home/.local kohya_ss_home/kohya_ss data/ref_hairstyle; do
    if [ -d "$BASE_DIR/$dir" ]; then
        echo "  ✓ $dir"
    else
        echo "  ✗ $dir 缺失，请从网盘下载"
    fi
done

# 6. 检查训练底模
echo "[6/7] 检查训练底模 v1-5-pruned-emaonly..."
if [ -f "$BASE_DIR/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.safetensors" ]; then
    echo "  ✓ v1-5-pruned-emaonly.safetensors 已存在"
else
    echo "  ✗ v1-5-pruned-emaonly.safetensors 缺失，请从网盘下载 models/ 目录"
fi

# 7. 创建运行时目录
echo "[7/7] 创建运行时目录..."
mkdir -p "$BASE_DIR/logs"
mkdir -p "$BASE_DIR/data/tmp" "$BASE_DIR/data/res_dir" "$BASE_DIR/data/userImage" "$BASE_DIR/data/user_info"
mkdir -p "$BASE_DIR/kohya_ss_home/train_material"

echo ""
echo "=== 部署完成 ==="
echo "启动服务: ./start_all_services.sh"