import time
import json

from itertools import chain

from celery import shared_task
from celery import Task

from app.utils.utils import *
from app.utils.yd_utils import get_token, get_activity_info
from app.utils.feishu import create_doc, get_doc_block, create_doc_block, get_messages
from app.utils.utils import update_record


def parse_history_message(data):
    sender_id = ""

    message_content_data = []
    message_images_data = []

    items = data.get("items")

    for index, item in enumerate(items):
        print("=======================")

        sender_id_item = item.get("sender").get("id")
        if index == 0:
            sender_id = sender_id_item

        if sender_id != sender_id_item:
            continue

        item_content = json.loads(item.get("body").get("content"))

        message_id = item.get("message_id")

        if item_content.get("text"):
            message_content_data.append(item_content.get("text"))

        if item_content.get("content"):
            message_content_content_data = item_content.get("content")

            tmp_content_data = []
            for message_content_content_item in message_content_content_data:
                for message_content_content_item_item in message_content_content_item:
                    tmp_content_data.append(message_content_content_item_item)

            for tmp_content_data_item in tmp_content_data:
                print(tmp_content_data_item)
                if tmp_content_data_item.get("tag") == "text":
                    message_content_data.append(tmp_content_data_item.get("text"))
                if tmp_content_data_item.get("tag") == "img":
                    message_images_data.append({"message_id": message_id, "image_id": tmp_content_data_item.get("image_key")})


    print(message_content_data)
    print(message_images_data)

    return message_content_data, message_images_data


@shared_task(include_result=False)
def process_message_callback(
    app_id, app_secret, bitable_token, table_id, cache_dir, data
) -> None:
    """
    记录问题到多维表格逻辑

    """

    # 如果 @机器人 等于"记录问题", 获取当前的话题
    event_message = data.get("event")
    sender_info = event_message.get("sender")
    message_data = event_message.get("message")

    sender_id = sender_info.get("sender_id").get("open_id")

    thread_id = message_data.get("thread_id")
    message_type = message_data.get("message_type")
    content = message_data.get("content")
    message_id = message_data.get("message_id")

    if not message_data.get("mentions"):
        # 忽略非@人的消息
        lark.logger.info("忽略非@人的消息")
        return

    mentions_data = message_data.get("mentions")

    if "官方应用指令" not in [mention.get("name") for mention in mentions_data]:
        # 忽略@官方应用指令的消息
        lark.logger.info("忽略非@官方应用的消息")
        return

    if message_type != "text":
        # 忽略非文本消息
        lark.logger.info("忽略非文本消息")
        return

    content = json.loads(message_data.get("content"))
    content_text = content.get("text")

    if "记录问题" not in content_text:
        # 忽略非记录问题的消息
        lark.logger.info("忽略非记录问题的消息")
        return

    record = {}
    images = []
    images_token = []

    lark.logger.info(f"message_content: {content_text}")

    # 从话题中提取问题发起人的所有消息和图片, 记录到多维表格中, 记录发消息人 openid 并将处理人设置为@机器人的人
    client = (
        lark.Client.builder()
        .app_id(app_id)
        .app_secret(app_secret)
        .log_level(lark.LogLevel.DEBUG)
        .build()
    )

    record["创建人"] = [{"id": sender_id}]

    history_message_data = get_messages(client, "thread", thread_id)
    lark.logger.info(f"history_message_data: {history_message_data}")

    message_content_data, message_images_data = parse_history_message(
        history_message_data
    )

    record["问题概述"] = "\n".join(message_content_data)

    for message_dict in message_images_data:
        image_path = get_message_resource(
            client,
            message_dict.get("message_id"),
            message_dict.get("image_id"),
            "image",
            cache_dir,
        )
        print(f"下载文件成功: {image}, {image_path}")
        file_token = upload_media(client, image_path, "bitable_image", bitable_token)
        print("上传文件成功:", file_token)
        images_token.append(file_token)

    lark.logger.info(f"images_token: {images_token}")

    # if images:
    #     record["附件"] = [{"file_token": image} for image in images_token]

    record_id = add_record(client, bitable_token, table_id, record)
    lark.logger.debug(f"record_id: {record_id}")

    time.sleep(1)

    # update_data = {"处理人": {"id": sender_id}}
    # update_record(client, bitable_token, table_id, record_id, update_data)

    # 回复消息
    content = f'{{"text": "问题已经记录到多维表格, 及时更新工单状态💕"}}'
    send_group_message(client, message_id, content)


@shared_task()
def sync_xbot_activity_info():
    app_id = os.environ["APP_ID"]
    app_secret = os.environ["APP_SECRET"]

    bitable_token = os.environ["OFFICE_XBOT_BITABLE_TOKEN"]
    table_id = os.environ["OFFICE_XBOT_TABLE_ID"]
    view_id = os.environ["OFFICE_XBOT_VIEW_ID"]

    xbot_username = os.environ["XBOT_USERNAME"]
    xbot_password = os.environ["XBOT_PASSWORD"]

    client = lark.Client.builder().app_id(app_id).app_secret(app_secret).build()

    token = get_token(xbot_username, xbot_password)

    handle_list = []

    # 同步应用数据
    # office_app_uuids = get_office_app_uuids()

    # print(f"office_activity_uuids count: {len(office_app_uuids)}")

    # 同步指令数据
    office_activity_uuids = get_activity_info(token)
    print(f"office_activity_uuids count: {len(office_activity_uuids)}")

    for item in office_activity_uuids:
        robot_uuid = item.get("robotUuid")
        package_view_name = item.get("packageViewName")
        print("=====================================")
        print(f"同步信息: {robot_uuid}, {package_view_name}")
        record_id = get_filtered_record_by_uuid(
            client, bitable_token, table_id, view_id, "UUID", robot_uuid
        )
        if record_id:
            print(f"{robot_uuid}已同步多维表格中")
            update_record(
                client, bitable_token, table_id, record_id, {"名称": package_view_name}
            )
        else:
            handle_list.append(robot_uuid)
            print(f"{robot_uuid}: {package_view_name} 未同步多维表格中")
            add_record(
                client,
                bitable_token,
                table_id,
                {"UUID": robot_uuid, "名称": package_view_name, "分类": "官方指令"},
            )
    print(f"新增的数量: {len(handle_list)}")
    print("新增的uuid: ", handle_list)


@shared_task(include_result=False)
def process_new_demand(app_id, app_secret, table_id, record_id, data):

    title = data.get("title")
    background = data.get("background")
    features = data.get("features")
    category = data.get("category")

    client = (
        lark.Client.builder()
        .app_id(app_id)
        .app_secret(app_secret)
        .log_level(lark.LogLevel.DEBUG)
        .build()
    )

    space_id = "7268552249415319554"
    bitable_token = os.environ["OFFICE_XBOT_BITABLE_TOKEN"]

    # 放官方应用下
    if category == "opt5xydmUE":
        parent_node_token = "F4ivwKrgyiQ4zOkuLVFcTq9Bnee"
    # 放到官方指令下
    if category == "optRTwYcra":
        parent_node_token = "SvWCwlWJ8iuFKpkXp1rcd9u2n3c"

    doc_node_token, doc_obj_token = create_doc(
        client, space_id, parent_node_token, title
    )
    block_id = get_doc_block(client, doc_obj_token)

    create_doc_block(client, doc_obj_token, block_id, background, features)

    doc_node_url = f"https://ying-dao.feishu.cn/wiki/{doc_node_token}"

    update_data = {"需求文档链接": doc_node_url, "状态": "待评估"}
    update_record(client, bitable_token, table_id, record_id, update_data)