262 lines
8.4 KiB
Python
262 lines
8.4 KiB
Python
import time
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import json
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from itertools import chain
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from celery import shared_task
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from celery import Task
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from app.utils.utils import *
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from app.utils.yd_utils import get_token, get_activity_info
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from app.utils.feishu import create_doc, get_doc_block, create_doc_block, get_messages
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from app.utils.utils import update_record
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def parse_history_message(data):
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sender_id = ""
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message_content_data = []
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message_images_data = []
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items = data.get("items")
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for index, item in enumerate(items):
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print("=======================")
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sender_id_item = item.get("sender").get("id")
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if index == 0:
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sender_id = sender_id_item
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if sender_id != sender_id_item:
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continue
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item_content = json.loads(item.get("body").get("content"))
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message_id = item.get("message_id")
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if item_content.get("text"):
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message_content_data.append(item_content.get("text"))
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if item_content.get("content"):
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message_content_content_data = item_content.get("content")
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tmp_content_data = []
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for message_content_content_item in message_content_content_data:
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for message_content_content_item_item in message_content_content_item:
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tmp_content_data.append(message_content_content_item_item)
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for tmp_content_data_item in tmp_content_data:
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print(tmp_content_data_item)
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if tmp_content_data_item.get("tag") == "text":
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message_content_data.append(tmp_content_data_item.get("text"))
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if tmp_content_data_item.get("tag") == "img":
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message_images_data.append({"message_id": message_id, "image_id": tmp_content_data_item.get("image_key")})
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print(message_content_data)
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print(message_images_data)
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return message_content_data, message_images_data
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@shared_task(include_result=False)
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def process_message_callback(
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app_id, app_secret, bitable_token, table_id, cache_dir, data
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) -> None:
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"""
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记录问题到多维表格逻辑
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"""
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# 如果 @机器人 等于"记录问题", 获取当前的话题
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event_message = data.get("event")
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sender_info = event_message.get("sender")
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message_data = event_message.get("message")
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sender_id = sender_info.get("sender_id").get("open_id")
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thread_id = message_data.get("thread_id")
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message_type = message_data.get("message_type")
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content = message_data.get("content")
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message_id = message_data.get("message_id")
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if not message_data.get("mentions"):
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# 忽略非@人的消息
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lark.logger.info("忽略非@人的消息")
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return
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mentions_data = message_data.get("mentions")
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if "官方应用指令" not in [mention.get("name") for mention in mentions_data]:
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# 忽略@官方应用指令的消息
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lark.logger.info("忽略非@官方应用的消息")
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return
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if message_type != "text":
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# 忽略非文本消息
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lark.logger.info("忽略非文本消息")
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return
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content = json.loads(message_data.get("content"))
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content_text = content.get("text")
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if "记录问题" not in content_text:
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# 忽略非记录问题的消息
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lark.logger.info("忽略非记录问题的消息")
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return
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record_category = "官方指令" if "指令" in content_text else "官方应用"
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record = {}
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images = []
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images_token = []
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lark.logger.info(f"message_content: {content_text}")
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# 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
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client = (
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lark.Client.builder()
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.app_id(app_id)
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.app_secret(app_secret)
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.log_level(lark.LogLevel.DEBUG)
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.build()
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)
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record["创建人"] = [{"id": sender_id}]
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# record["处理人"] = [{"id": sender_id}]
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record["反馈渠道"] = "机器人"
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record["工单状态"] = "处理中"
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record["紧急程度"] = "一般"
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record["分类"] = record_category
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history_message_data = get_messages(client, "thread", thread_id)
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lark.logger.info(f"history_message_data: {history_message_data}")
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message_content_data, message_images_data = parse_history_message(
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history_message_data
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)
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record["问题概述"] = "\n".join(message_content_data)
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for message_dict in message_images_data:
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image_path = get_message_resource(
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client,
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message_dict.get("message_id"),
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message_dict.get("image_id"),
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"image",
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cache_dir,
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)
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print(f"下载文件成功: {image}, {image_path}")
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file_token = upload_media(client, image_path, "bitable_image", bitable_token)
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print("上传文件成功:", file_token)
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images_token.append(file_token)
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lark.logger.info(f"images_token: {images_token}")
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if message_images_data:
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record["附件"] = [{"file_token": image} for image in images_token]
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record_id = add_record(client, bitable_token, table_id, record)
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lark.logger.debug(f"record_id: {record_id}")
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time.sleep(1)
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# update_data = {"处理人": {"id": sender_id}}
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# update_record(client, bitable_token, table_id, record_id, update_data)
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# 回复消息
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content = f'{{"text": "问题已经记录到多维表格, 及时更新工单状态💕"}}'
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send_group_message(client, message_id, content)
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@shared_task()
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def sync_xbot_activity_info():
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app_id = os.environ["APP_ID"]
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app_secret = os.environ["APP_SECRET"]
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bitable_token = os.environ["OFFICE_XBOT_BITABLE_TOKEN"]
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table_id = os.environ["OFFICE_XBOT_TABLE_ID"]
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view_id = os.environ["OFFICE_XBOT_VIEW_ID"]
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xbot_username = os.environ["XBOT_USERNAME"]
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xbot_password = os.environ["XBOT_PASSWORD"]
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client = lark.Client.builder().app_id(app_id).app_secret(app_secret).build()
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token = get_token(xbot_username, xbot_password)
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handle_list = []
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# 同步应用数据
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# office_app_uuids = get_office_app_uuids()
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# print(f"office_activity_uuids count: {len(office_app_uuids)}")
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# 同步指令数据
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office_activity_uuids = get_activity_info(token)
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print(f"office_activity_uuids count: {len(office_activity_uuids)}")
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for item in office_activity_uuids:
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robot_uuid = item.get("robotUuid")
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package_view_name = item.get("packageViewName")
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print("=====================================")
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print(f"同步信息: {robot_uuid}, {package_view_name}")
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record_id = get_filtered_record_by_uuid(
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client, bitable_token, table_id, view_id, "UUID", robot_uuid
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)
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if record_id:
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print(f"{robot_uuid}已同步多维表格中")
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update_record(
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client, bitable_token, table_id, record_id, {"名称": package_view_name}
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)
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else:
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handle_list.append(robot_uuid)
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print(f"{robot_uuid}: {package_view_name} 未同步多维表格中")
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add_record(
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client,
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bitable_token,
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table_id,
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{"UUID": robot_uuid, "名称": package_view_name, "分类": "官方指令"},
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)
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print(f"新增的数量: {len(handle_list)}")
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print("新增的uuid: ", handle_list)
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@shared_task(include_result=False)
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def process_new_demand(app_id, app_secret, table_id, record_id, data):
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title = data.get("title")
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background = data.get("background")
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features = data.get("features")
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category = data.get("category")
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client = (
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lark.Client.builder()
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.app_id(app_id)
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.app_secret(app_secret)
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.log_level(lark.LogLevel.DEBUG)
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.build()
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)
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space_id = "7268552249415319554"
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bitable_token = os.environ["OFFICE_XBOT_BITABLE_TOKEN"]
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# 放官方应用下
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if category == "opt5xydmUE":
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parent_node_token = "F4ivwKrgyiQ4zOkuLVFcTq9Bnee"
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# 放到官方指令下
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if category == "optRTwYcra":
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parent_node_token = "SvWCwlWJ8iuFKpkXp1rcd9u2n3c"
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doc_node_token, doc_obj_token = create_doc(
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client, space_id, parent_node_token, title
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)
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block_id = get_doc_block(client, doc_obj_token)
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create_doc_block(client, doc_obj_token, block_id, background, features)
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doc_node_url = f"https://ying-dao.feishu.cn/wiki/{doc_node_token}"
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update_data = {"需求文档链接": doc_node_url, "状态": "待评估"}
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update_record(client, bitable_token, table_id, record_id, update_data)
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