LongArticlesJob/coldStartTasks/publish/publishCategoryArticles.py

"""
@author: luojunhui
品类文章发布到aigc系统的冷启层
"""
import datetime
import json
import time
import traceback

from pandas import DataFrame

from applications import aiditApi, log, bot
from config import apolloConfig

apollo = apolloConfig()
DAILY_CRAWLER_MAX_NUM = 1000
SIMILARITY_MIN_SCORE = 0.4
TITLE_NOT_SENSITIVE = 0


class CategoryColdStartTask(object):
    """
    品类冷启动发布任务
    """
    PUBLISHED_STATUS = 2
    INIT_STATUS = 1
    BAD_STATUS = 0

    def __init__(self, db_client):
        """

        :param db_client:
        """
        self.db_client = db_client
        self.category_map = json.loads(apollo.getConfigValue("category_cold_start_map"))
        self.category_cold_start_threshold = json.loads(apollo.getConfigValue("category_cold_start_threshold"))
        self.READ_THRESHOLD = self.category_cold_start_threshold.get("READ_THRESHOLD", 5000)
        self.READ_TIMES_THRESHOLD = self.category_cold_start_threshold.get("READ_TIMES_THRESHOLD", 1.3)
        self.LIMIT_TITLE_LENGTH = self.category_cold_start_threshold.get("LIMIT_TITLE_LENGTH", 15)
        self.TITLE_LENGTH_MAX = self.category_cold_start_threshold.get("TITLE_LENGTH_MAX", 50)
        log(
            task="category_publish_task",
            function="__init__",
            message="数据库初始化连接完成，apollo配置获取完成",
            data={
                "category": self.category_map,
                "threshold": self.category_cold_start_threshold
            }
        )

    def insert_into_db(self, crawler_plan_id, crawler_plan_name, create_timestamp):
        """
        插入抓取计划到数据库中
        :param create_timestamp:
        :param crawler_plan_id:
        :param crawler_plan_name:
        :return:
        """
        insert_sql = f"""
            INSERT INTO article_crawler_plan
            (crawler_plan_id, name, create_timestamp)
            values 
            (%s, %s, %s)
        """
        try:
            self.db_client.update(
                sql=insert_sql,
                params=(crawler_plan_id, crawler_plan_name, create_timestamp)
            )
        except Exception as e:
            bot(
                title="品类冷启任务，记录抓取计划id失败",
                detail={
                    "error": str(e),
                    "error_msg": traceback.format_exc(),
                    "crawler_plan_id": crawler_plan_id,
                    "crawler_plan_name": crawler_plan_name
                }
            )

    def get_articles_from_meta_table(self, category, article_source):
        """
        从长文 meta 库中获取冷启文章
        :return:

        """
        sql = f"""
        SELECT 
            article_id, out_account_id, article_index, title, link, read_cnt, status, llm_sensitivity, score
        FROM
            crawler_meta_article
        WHERE 
            category = "{category}" and platform = "{article_source}" and title_sensitivity = {TITLE_NOT_SENSITIVE}
        ORDER BY score DESC;
        """
        article_list = self.db_client.select(sql)
        log(
            task="category_publish_task",
            function="get_articles_from_meta_table",
            message="获取品类文章总数",
            data={
                "total_articles": len(article_list),
                "category": category
            }
        )
        article_df = DataFrame(article_list,
                               columns=['article_id', 'gh_id', 'position', 'title', 'link', 'read_cnt', 'status',
                                        'llm_sensitivity', 'score'])
        return article_df

    def filter_each_category(self, category):
        """
        过滤单个生成计划类别的文章
        """
        plan_id = self.category_map.get(category)
        if plan_id:
            article_list = aiditApi.get_generated_article_list(plan_id)
            title_list = [i[1] for i in article_list]
            if title_list:
                # update
                update_sql = f"""
                UPDATE 
                    crawler_meta_article
                SET
                    status = %s
                WHERE
                    title in %s and status = %s;
                """
                affected_rows = self.db_client.update(
                    sql=update_sql,
                    params=(self.PUBLISHED_STATUS, tuple(title_list), self.INIT_STATUS)
                )
                print(affected_rows)
        else:
            print("未获取到计划id")
            return

    def published_articles_title_filter(self):
        """
        已经发布到生成计划中的 id，
        :return:
        """
        category_list = list(self.category_map.keys())
        for category in category_list:
            try:
                self.filter_each_category(category)
            except Exception as e:
                log(
                    task="category_publish_task",
                    function="published_articles_title_filter",
                    message="过滤已发布文章失败",
                    data={
                        "error": str(e),
                        "error_msg": traceback.format_exc(),
                        "category": category
                    }
                )

    def change_article_status_while_publishing(self, article_id_list):
        """

        :param: article_id_list: 文章的唯一 id
        :return:
        """
        update_sql = f"""
                    UPDATE 
                        crawler_meta_article
                    SET
                        status = %s
                    WHERE
                        article_id in %s and status = %s;
                    """
        affect_rows = self.db_client.update(
            sql=update_sql,
            params=(self.PUBLISHED_STATUS, tuple(article_id_list), self.INIT_STATUS)
        )
        if affect_rows != len(article_id_list):
            bot(
                title="品类冷启任务中，出现更新状文章状态失败异常",
                detail={
                    "affected_rows": affect_rows,
                    "task_rows": len(article_id_list)
                }
            )

    def filter_weixin_articles(self, articles_df, category):
        """
        微信抓取文章过滤漏斗
        """
        articles_df['average_read'] = articles_df.groupby(['gh_id', 'position'])['read_cnt'].transform('mean')
        articles_df['read_times'] = articles_df['read_cnt'] / articles_df['average_read']
        total_length = articles_df.shape[0]
        # 第0层过滤已经发布的文章
        filter_df = articles_df[articles_df['status'] == self.INIT_STATUS]
        length_level0 = filter_df.shape[0]

        # 第一层漏斗通过阅读均值倍数过滤
        filter_df = filter_df[filter_df['read_times'] >= self.READ_TIMES_THRESHOLD]
        length_level1 = filter_df.shape[0]

        # 第二层漏斗通过阅读量过滤
        filter_df = filter_df[
            filter_df['read_cnt'] >= self.READ_THRESHOLD
            ]
        length_level2 = filter_df.shape[0]

        # 第三层漏斗通过标题长度过滤
        filter_df = filter_df[
            (filter_df['title'].str.len() >= self.LIMIT_TITLE_LENGTH)
            & (filter_df['title'].str.len() <= self.TITLE_LENGTH_MAX)
            ]
        length_level3 = filter_df.shape[0]

        # 第四层通过敏感词过滤
        filter_df = filter_df[
            (~filter_df['title'].str.contains('农历'))
            & (~filter_df['title'].str.contains('太极'))
            & (~filter_df['title'].str.contains('节'))
            & (~filter_df['title'].str.contains('早上好'))
            & (~filter_df['title'].str.contains('赖清德'))
            & (~filter_df['title'].str.contains('普京'))
            & (~filter_df['title'].str.contains('俄'))
            & (~filter_df['title'].str.contains('南海'))
            & (~filter_df['title'].str.contains('台海'))
            & (~filter_df['title'].str.contains('解放军'))
            & (~filter_df['title'].str.contains('蔡英文'))
            & (~filter_df['title'].str.contains('中国'))
            ]
        length_level4 = filter_df.shape[0]
        # 第五层通过LLM敏感度过滤
        filter_df = filter_df[
            ~(filter_df['llm_sensitivity'] > 0)
        ]
        length_level5 = filter_df.shape[0]

        # 第六层通过相关性分数过滤
        filter_df = filter_df[filter_df['score'] > SIMILARITY_MIN_SCORE]
        length_level6 = filter_df.shape[0]

        log(
            task="category_publish_task",
            function="publish_filter_articles",
            message="过滤后文章总数",
            data={
                "total_articles": length_level5,
                "category": category
            }
        )
        bot(
            title="冷启任务发布通知",
            detail={
                "总文章数量": total_length,
                "通过已经发布状态过滤": "过滤数量: {}    剩余数量: {}".format(
                    total_length - length_level0, length_level0),
                "通过阅读均值倍数过滤": "过滤数量: {}    剩余数量: {}".format(
                    length_level0 - length_level1, length_level1),
                "通过阅读量过滤": "过滤数量: {}    剩余数量: {}".format(
                    length_level1 - length_level2, length_level2),
                "通过标题长度过滤": "过滤数量: {}    剩余数量: {}".format(
                    length_level2 - length_level3, length_level3),
                "通过敏感词过滤": "过滤数量: {}    剩余数量: {}".format(
                    length_level3 - length_level4, length_level4),
                "通过LLM敏感度过滤": "过滤数量: {}    剩余数量: {}".format(
                    length_level4 - length_level5, length_level5
                ),
                "通过相关性分数过滤": "过滤数量: {}    剩余数量: {}".format(
                    length_level5 - length_level6, length_level6
                ),
                "品类": category,
                "阅读均值倍数阈值": self.READ_TIMES_THRESHOLD,
                "阅读量阈值": self.READ_THRESHOLD,
                "标题长度阈值": self.LIMIT_TITLE_LENGTH
            },
            mention=False
        )
        return filter_df[:DAILY_CRAWLER_MAX_NUM]

    def filter_toutiao_articles(self, articles_df, category):
        """
        头条文章过滤漏斗
        """
        total_length = articles_df.shape[0]
        # 第一层漏斗通过状态过滤
        zero_level_funnel_df = articles_df[articles_df['status'] == self.INIT_STATUS]
        zero_level_funnel_length = zero_level_funnel_df.shape[0]
        bot(
            title="账号冷启动---头条推荐流发布",
            detail={
                "category": category,
                "总文章数量": total_length,
                "通过已经发布状态过滤": "过滤数量: {}    剩余数量: {}".format(total_length - zero_level_funnel_length,
                                                                              zero_level_funnel_length),
            },
            mention=False
        )
        return zero_level_funnel_df

    def publish_filter_articles(self, category, articles_df, article_source):
        """
        过滤文章
        :param category: 文章品类
        :param articles_df: 该品类下的文章data_frame
        :param article_source: 文章来源
        :return:
        """
        match article_source:
            case "weixin":
                filtered_articles_df = self.filter_weixin_articles(articles_df, category)
                input_source_channel = 5
            case "toutiao":
                filtered_articles_df = self.filter_toutiao_articles(articles_df, category)
                input_source_channel = 6
            case _:
                return

        url_list = filtered_articles_df['link'].values.tolist()
        if url_list:
            # create_crawler_plan
            crawler_plan_response = aiditApi.auto_create_crawler_task(
                plan_id=None,
                plan_name="自动绑定-{}--{}--{}".format(category, datetime.date.today().__str__(), len(url_list)),
                plan_tag="品类冷启动",
                article_source=article_source,
                url_list=url_list
            )
            log(
                task="category_publish_task",
                function="publish_filter_articles",
                message="成功创建抓取计划",
                data=crawler_plan_response
            )
            # save to db
            create_timestamp = int(time.time()) * 1000
            crawler_plan_id = crawler_plan_response['data']['id']
            crawler_plan_name = crawler_plan_response['data']['name']
            self.insert_into_db(crawler_plan_id, crawler_plan_name, create_timestamp)

            # auto bind to generate plan
            new_crawler_task_list = [
                {
                    "contentType": 1,
                    "inputSourceType": 2,
                    "inputSourceSubType": None,
                    "fieldName": None,
                    "inputSourceValue": crawler_plan_id,
                    "inputSourceLabel": crawler_plan_name,
                    "inputSourceModal": 3,
                    "inputSourceChannel": input_source_channel
                }
            ]
            generate_plan_response = aiditApi.bind_crawler_task_to_generate_task(
                crawler_task_list=new_crawler_task_list,
                generate_task_id=self.category_map[category]
            )
            log(
                task="category_publish_task",
                function="publish_filter_articles",
                message="成功绑定到生成计划",
                data=generate_plan_response
            )

            # change article status
            article_id_list = filtered_articles_df['article_id'].values.tolist()
            self.change_article_status_while_publishing(article_id_list=article_id_list)

    def do_job(self, article_source, category_list=None):
        """
        执行任务
        :return:
        """
        if not category_list:
            category_list = self.category_map.keys()

        log(
            task="category_publish_task",
            function="do_job",
            message="开始自动创建品类文章抓取计划",
            data={
                "category_list": list(category_list)
            }
        )
        for category in category_list:
            try:
                # 已发布标题去重
                self.published_articles_title_filter()

                category_df = self.get_articles_from_meta_table(category=category, article_source=article_source)
                self.publish_filter_articles(
                    category=category,
                    articles_df=category_df,
                    article_source=article_source
                )
            except Exception as e:
                bot(
                    title="品类冷启任务报错",
                    detail={
                        "category": category,
                        "error": str(e),
                        "function": "do_job",
                        "traceback": traceback.format_exc()
                    }
                )