import asyncio
import logging
import time

from utils.Database import *
from utils.DocxUtil import get_docx_content_by_pandoc
from utils.LightRagUtil import initialize_pg_rag

# 使用PG库后，这个是没有用的,但目前的项目代码要求必传，就写一个吧。
WORKING_DIR = f"./output"

# 后台任务，监控是否有新的未训练的文档进行训练
async def train_document_task():
    print("线程5秒后开始运行【监控是否有新的未训练的文档进行训练】")
    await asyncio.sleep(5)  # 使用 asyncio.sleep 而不是 time.sleep
    # 这里放置你的线程逻辑
    while True:
        # 这里可以放置你的线程要执行的代码
        logging.info("开始查询是否有未训练的文档")
        no_train_document_sql: str = " SELECT * FROM t_ai_teaching_model_document WHERE is_deleted = 0 and train_flag = 0 ORDER BY create_time DESC"
        no_train_document_result = await find_by_sql(no_train_document_sql, ())
        if not no_train_document_result:
            logging.info("没有未训练的文档")
        else:
            logging.info("存在未训练的文档" + str(len(no_train_document_result))+"个")
            # document = no_train_document_result[0]
            # print("开始训练文档：" + document["document_name"])
            # theme = await find_by_id("t_ai_teaching_model_theme", "id", document["theme_id"])
            # # 训练开始前，更新训练状态
            # update_sql: str = " UPDATE t_ai_teaching_model_document SET train_flag = 1 WHERE id = " + str(document["id"])
            # execute_sql(update_sql)
            # document_name = document["document_name"] + "." + document["document_suffix"]
            # logging.info("开始训练文档：" + document_name)
            # workspace = theme["short_name"]
            # docx_name = document_name
            # docx_path = document["document_path"]
            # logging.info(f"开始处理文档：{docx_name}, 还有%s个文档需要处理！", len(no_train_document_result) - 1)
            # # 训练代码开始
            # try:
            #     rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace=workspace)
            #     # 获取docx文件的内容
            #     content = get_docx_content_by_pandoc(docx_path)
            #     await rag.insert(input=content, file_paths=[docx_name])
            # finally:
            #     if rag:
            #         await rag.finalize_storages()
            # # 训练结束，更新训练状态
            # update_sql: str = " UPDATE t_ai_teaching_model_document SET train_flag = 2 WHERE id = " + str(document["id"])
            # execute_sql(update_sql)

            # 添加适当的等待时间，避免频繁查询
            await asyncio.sleep(60)  # 每分钟查询一次