#!/bin/bash
# 之之 v2.0 训练 · 一键部署脚本
# 由铸渊生成 · 2026-05-18
# 用法: bash setup_train.sh

set -e

echo "========================================"
 echo "  之之母模型 v2.0 · 训练部署"
 echo "  由铸渊配置 · 光湖 · 2026-05-18"
 echo "========================================"
 echo ""

# 检查路径
 DATA_PATH="/root/autodl-tmp/sft_v2_nosys.jsonl"
 if [ ! -f "$DATA_PATH" ]; then
   echo "❌ 数据文件不存在: $DATA_PATH"
   echo "   请确认语料已上传到 AutoDL"
   exit 1
 fi

data_lines=$(wc -l < "$DATA_PATH")
echo "✅ 数据文件: $DATA_PATH ($data_lines 条)"
echo ""

# 复制配置文件
 echo "  复制训练配置到 AutoDL..."
 cp dataset_info.json /root/autodl-tmp/dataset_info.json 2>/dev/null || true
 cp ds_config.json /root/autodl-tmp/ds_config.json 2>/dev/null || true

echo "✅ 配置文件已就绪"
echo ""

# 检查框架
 if python3 -c "import llamafactory; print(llamafactory.__version__)" 2>/dev/null; then
   echo "✅ LLaMA-Factory 已安装"
 else
   echo "⚠️  LLaMA-Factory 未安装，尝试安装稳定版..."
   pip install "llamafactory==0.8.3" -q
   echo "✅ 安装完成"
 fi

echo ""
echo "========================================"
echo "  全部就绪，执行以下命令启动训练:"
echo ""
echo "  cd /root/autodl-tmp"
echo "  CUDA_VISIBLE_DEVICES=0,1,2,3 llamafactory-cli train zhizhi_v2.yaml"
echo ""
echo "  或先试 dry_run 验证:"
echo "  llamafactory-cli train zhizhi_v2.yaml --dry_run"
echo "========================================"