#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
将智能制造问答内容转换为专家支持中心数据格式
"""

import json
from datetime import datetime

# 导师头像映射
mentor_avatars = {
    "顾华": "https://ddcz-1315997005.cos.ap-nanjing.myqcloud.com/static/img/teach_sys_teacher-avatar/recuW7cCvScko4.png",
    "王军": "https://ddcz-1315997005.cos.ap-nanjing.myqcloud.com/static/img/teach_sys_teacher-avatar/recuW7c44HkjqO.png",
    "杨文琦": "https://ddcz-1315997005.cos.ap-nanjing.myqcloud.com/static/img/teach_sys_teacher-avatar/recuW7dxJ5Av9E.png",
    "李奇": "https://ddcz-1315997005.cos.ap-nanjing.myqcloud.com/static/img/teach_sys_teacher-avatar/recuW7dDIg60Tg.png"
}

# 读取原始数据
with open('网页未导入数据/智能制造产业/智能制造问答内容.json', 'r', encoding='utf-8') as f:
    data = json.load(f)

conversations = []
for idx, item in enumerate(data, 1):
    # 解析日期获取月份
    first_time = item.get('流程1_时间', '')
    if first_time:
        try:
            date_obj = datetime.strptime(first_time.split(' ')[0], '%Y/%m/%d')
            date_str = f"{date_obj.year}年{date_obj.month}月"
        except:
            date_str = "2024年10月"  # 默认日期
    else:
        date_str = "2024年10月"

    # 构建对话消息
    messages = []

    # 流程1和2
    if item.get('问题_流程1'):
        messages.append({
            "type": "user",
            "content": item['问题_流程1'],
            "time": item.get('流程1_时间', '')
        })

    if item.get('回答_流程2'):
        mentor_name = item.get('查询导师名称', '')
        if item['问答类型'] == '智能客服':
            mentor = "多多畅职机器人"
            avatar = "https://ddcz-1315997005.cos.ap-nanjing.myqcloud.com/static/img/teach_sys_icon/recuWmDuekBTlr.png"
        else:
            mentor = f"{mentor_name}老师" if mentor_name else "顾华老师"
            avatar = mentor_avatars.get(mentor_name, mentor_avatars['顾华'])

        messages.append({
            "type": "assistant",
            "content": item['回答_流程2'],
            "mentor": mentor,
            "time": item.get('流程2_时间', ''),
            "mentorAvatar": avatar
        })

    # 流程3和4
    if item.get('问题_流程3'):
        messages.append({
            "type": "user",
            "content": item['问题_流程3'],
            "time": item.get('流程3_时间', '')
        })

    if item.get('回答_流程4'):
        messages.append({
            "type": "assistant",
            "content": item['回答_流程4'],
            "mentor": mentor,
            "time": item.get('流程4_时间', ''),
            "mentorAvatar": avatar
        })

    # 流程5和6
    if item.get('问题_流程5'):
        messages.append({
            "type": "user",
            "content": item['问题_流程5'],
            "time": item.get('流程5_时间', '')
        })

    if item.get('回答_流程6'):
        messages.append({
            "type": "assistant",
            "content": item['回答_流程6'],
            "mentor": mentor,
            "time": item.get('流程6_时间', ''),
            "mentorAvatar": avatar
        })

    # 创建对话对象
    conversation = {
        "id": idx,
        "title": item['问题标题'],
        "status": "finish",
        "date": date_str,
        "type": item['问题类型'],
        "messages": messages
    }

    conversations.append(conversation)

# 生成最终的JavaScript文件
js_content = """// 从智能制造问答内容.json转换的专家支持中心数据
const expertSupportData = {
  "conversations": %s
};

export default expertSupportData;
""" % json.dumps(conversations, ensure_ascii=False, indent=2)

# 写入文件
with open('src/data/expertSupportData.js', 'w', encoding='utf-8') as f:
    f.write(js_content)

print(f"成功转换 {len(conversations)} 个对话")