data3/quick_batch_start.sh

#!/bin/bash
# 快速启动批处理（仅准备和提交，不等待完成）

set -e

echo "🚀 快速启动 Batch API 任务"
echo "========================================"

# 配置
MIN_SCORE=60
MODEL="gpt-4o-mini"
INPUT_FILE="function_dataset_v2.csv"
BATCH_REQUESTS_FILE="batch_requests_full.jsonl"

# 步骤1: 准备批量请求
echo "📋 准备批量请求..."
python3 generate_problems_batch.py prepare \
    --input $INPUT_FILE \
    --output $BATCH_REQUESTS_FILE \
    --min-score $MIN_SCORE \
    --model $MODEL

REQUEST_COUNT=$(wc -l < $BATCH_REQUESTS_FILE)
echo ""
echo "✅ 已准备 $REQUEST_COUNT 个请求"

# 步骤2: 提交
echo ""
echo "🚀 提交批处理任务..."
python3 generate_problems_batch.py submit \
    --input $BATCH_REQUESTS_FILE \
    --model $MODEL \
    --description "Scientific computing problems - $REQUEST_COUNT samples" \
    | tee batch_submit_output.txt

# 提取 Batch ID
BATCH_ID=$(grep -oP 'batch_[a-zA-Z0-9_]+' batch_submit_output.txt | head -1)

if [ -n "$BATCH_ID" ]; then
    echo "$BATCH_ID" > batch_id.txt
    echo ""
    echo "✅ 批处理已提交！"
    echo "📝 Batch ID: $BATCH_ID (已保存到 batch_id.txt)"
    echo ""
    echo "监控命令:"
    echo "  python3 generate_problems_batch.py status $BATCH_ID"
    echo ""
    echo "或运行监控脚本:"
    echo "  ./monitor_batch.sh"
fi