video-insight/workers/video_insight_trigger_work.py

import asyncio
import json
import os
import sys
import orjson
from apscheduler.schedulers.asyncio import AsyncIOScheduler
from apscheduler.triggers.interval import IntervalTrigger
from loguru import logger
logger.add("/app/logs/consumption.log", rotation="10 MB")

sys.path.append('/app')

from utils.aliyun_log import AliyunLogger
from utils.google_ai_analyze import GoogleAI
from utils.piaoquan import PQ
from utils.redis import RedisHelper, content_video_trigger_data
from utils.mysql_db import MysqlHelper
from utils.aliyun_security import Security




class ConsumptionRecommend(object):
    @classmethod
    async def run(cls):
        logger.info(f"[处理 - trigger] 开始获取redis数据")

        while True:
            task = RedisHelper().get_client().rpop(name='task:video_trigger_insight')

            if not task:
                logger.info('[处理] 无待执行的扫描任务')
                return

            task = orjson.loads(task)
            logger.info(f"[处理 - trigger] 获取redis数据{task}")
            video_id = task['video_id']

            count_sql = f"""select count(1) from video_triggers_analysis where video_id = {video_id}"""
            count = MysqlHelper.get_values(count_sql)

            if not count or count[0][0] == 0:
                logger.info(f"[处理 - trigger] 视频ID {video_id} 可用")
                # 这里可以继续处理 video_id
                break
            else:
                logger.info(f"[处理 - trigger] 视频ID {video_id} 重复过滤，继续获取下一个任务")

        logger.info(f"[处理 - trigger] 开始获取原视频OSS地址")
        video_title, video_path, transed_video_path = PQ.get_pq_oss(video_id)
        # 优先使用transed_video_path，没有则使用video_path
        if not transed_video_path:
            transed_video_path = video_path
        if not video_path:
            return
        logger.info(f"[处理 - trigger] 获取原视频OSS地址，视频链接:{transed_video_path}")
        video_url = f"http://rescdn.yishihui.com/{transed_video_path}"
        logger.info(f"[处理 - trigger] 开始分析视频")
        api_key = os.getenv("VIDEO_INSIGHT_GEMINI_API_KEY")
        logger.info(f"[处理 - trigger] 使用的API_KEY:{api_key}")
        analysis_data, demand_list = GoogleAI.run(api_key, video_url)
        
        # 检查API分析是否成功
        if isinstance(analysis_data, str) and "[异常]" in analysis_data:
            logger.error(f"[处理 - trigger] API分析失败: {analysis_data}")
            content_video_trigger_data(json.dumps(task))
            return
            
        if not analysis_data or not demand_list:
            logger.error(f"[处理 - trigger] API分析结果为空")
            content_video_trigger_data(json.dumps(task))
            return
            
        # Parse JSON data for demand list
        try:
            data = json.loads(orjson.dumps(demand_list).decode())
            if not data:
                logger.error(f"[处理 - trigger] 需求列表为空")
                content_video_trigger_data(json.dumps(task))
                return
                
            # Generate SQL insert statement for triggers analysis
            sql = """
            INSERT INTO video_triggers_analysis (
                video_id, video_link, video_title,
                trigger_order, trigger_score, trigger_reason, trigger_text, trigger_question, trigger_category, trigger_time,
                audit_status,audit_desc
            ) VALUES
            """
            # Add values for each entry
            values = []
            link = f"""https://admin.piaoquantv.com/cms/post-detail/{video_id}/detail"""
            for index, entry in enumerate(data, 1):  # Start from 1 to match the original numbering
                try:
                    hook_desc = entry.get('钩子文案', '')
                    result, msg = Security.security(hook_desc)
                    audit_status = 0
                    if result:
                        audit_status = 1
                    else:
                        audit_status = 2
                    audit_desc = msg

                    value = f"""(
                        {video_id}, '{link}', '{video_title.replace("'", "''")}',
                        '{index}', '{entry.get('评分', '').replace("'", "''")}', '{entry.get('推测出该点需求的原因', '').replace("'", "''")}',
                        '{entry.get('钩子文案', '').replace("'", "''")}', '{entry.get('钩子到AI大模型的问题', '').replace("'", "''")}',
                        '{entry.get('钩子类型', '').replace("'", "''")}', '{entry.get('钩子出现时间', '').replace("'", "''")}',
                        '{audit_status}','{audit_desc.replace("'", "''")}'
                    )"""
                    values.append(value)
                except Exception as e:
                    logger.error(f"[处理 - trigger] 处理需求条目时出错: {e}")
                    continue
                    
            if not values:
                logger.error(f"[处理 - trigger] 没有有效的需求条目")
                content_video_trigger_data(json.dumps(task))
                return
                
            # Combine SQL statement and values
            sql += ",\n".join(values) + ";"
            # Print SQL statement
            logger.info(f"{sql}")
            MysqlHelper.update_values(sql)
            logger.info(f"[处理 - trigger] 需求列表写入数据库成功")

            # Parse JSON data for analysis summary
            try:
                # Generate SQL insert statement for demand score
                sql = """
                INSERT INTO video_demand_score (
                    video_id, video_link, video_title, analysis_summary, analysis_timeline
                ) VALUES
                """
                # Add values for each entry
                values = []
                link = f"""https://admin.piaoquantv.com/cms/post-detail/{video_id}/detail"""
                
                # 处理视频选题与要点理解
                analysis_summary = json.dumps(analysis_data.get('视频选题与要点理解', {}), ensure_ascii=False)
                analysis_timeline = json.dumps(analysis_data.get('视频分段与时间点分析', {}), ensure_ascii=False)
                
                # 使用参数化查询来避免 SQL 注入和转义问题
                value = f"""(
                    {video_id}, 
                    '{link}', 
                    '{video_title.replace("'", "''")}', 
                    '{analysis_summary.replace("'", "''")}', 
                    '{analysis_timeline.replace("'", "''")}'
                )"""
                values.append(value)
                # Combine SQL statement and values
                sql += ",\n".join(values) + """
                ON DUPLICATE KEY UPDATE
                    video_link = VALUES(video_link),
                    video_title = VALUES(video_title),
                    analysis_summary = VALUES(analysis_summary),
                    analysis_timeline = VALUES(analysis_timeline)
                ;"""
                # Print SQL statement
                # logger.info(f"{sql}")
                MysqlHelper.update_values(sql)
                # logger.info(f"[处理 - trigger] 视频分析结果写入数据库成功")
                
            except Exception as e:
                logger.error(f"[处理 - trigger] 写入视频分析结果时出错: {e}")
                content_video_trigger_data(json.dumps(task))
                return
                
        except Exception as e:
            logger.error(f"[处理 - trigger] 处理需求列表时出错: {e}")
            content_video_trigger_data(json.dumps(task))
            return


async def run():
    scheduler = AsyncIOScheduler()
    try:
        logger.info(f"[处理 - trigger] 开始启动")
        scheduler.add_job(ConsumptionRecommend.run, trigger=IntervalTrigger(minutes=5))  # 每5分钟启动一次
        scheduler.start()
        await asyncio.Event().wait()
    except KeyboardInterrupt:
        pass
    except Exception as e:
        logger.error(f"[处理] 启动异常，异常信息:{e}")
        pass
    finally:
        scheduler.shutdown()


if __name__ == '__main__':
    # asyncio.run(ConsumptionRecommend.run())
    loop = asyncio.get_event_loop()
    loop.run_until_complete(run())