refactor: flatten service packages
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wh
290
src/main/java/com/label/service/VideoProcessService.java
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290
src/main/java/com/label/service/VideoProcessService.java
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package com.label.service;
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import com.baomidou.mybatisplus.core.conditions.update.LambdaUpdateWrapper;
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import com.label.common.ai.AiServiceClient;
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import com.label.common.exception.BusinessException;
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import com.label.common.statemachine.SourceStatus;
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import com.label.common.statemachine.StateValidator;
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import com.label.entity.SourceData;
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import com.label.mapper.SourceDataMapper;
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import com.label.entity.VideoProcessJob;
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import com.label.mapper.VideoProcessJobMapper;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.http.HttpStatus;
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import org.springframework.stereotype.Service;
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import org.springframework.transaction.annotation.Transactional;
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import org.springframework.transaction.support.TransactionSynchronization;
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import org.springframework.transaction.support.TransactionSynchronizationManager;
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import java.time.LocalDateTime;
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import java.util.Map;
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/**
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* 视频处理服务：创建任务、处理回调、管理员重置。
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*
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* 状态流转：
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* - 创建时：source_data → PREPROCESSING，job → PENDING
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* - 回调成功：job → SUCCESS，source_data → PENDING（进入提取队列）
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* - 回调失败（可重试）：job → RETRYING，retryCount++，重新触发 AI
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* - 回调失败（超出上限）：job → FAILED，source_data → PENDING
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* - 管理员重置：job → PENDING（可手动重新触发）
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*
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* T074 设计说明：
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* AI 调用通过 TransactionSynchronizationManager.registerSynchronization().afterCommit()
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* 延迟到事务提交后执行，避免在持有 DB 连接期间进行 HTTP 调用。
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*/
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@Slf4j
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@Service
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@RequiredArgsConstructor
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public class VideoProcessService {
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private final VideoProcessJobMapper jobMapper;
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private final SourceDataMapper sourceDataMapper;
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private final AiServiceClient aiServiceClient;
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@Value("${rustfs.bucket:label-source-data}")
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private String bucket;
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// ------------------------------------------------------------------ 创建任务 --
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/**
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* 创建视频处理任务并在事务提交后触发 AI 服务。
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*
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* DB 写入（source_data→PREPROCESSING + 插入 job）在 @Transactional 内完成；
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* AI 触发通过 afterCommit() 在事务提交后执行，不占用 DB 连接。
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*
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* @param sourceId 资料 ID
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* @param jobType 任务类型（FRAME_EXTRACT / VIDEO_TO_TEXT）
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* @param params JSON 参数（如 {"frameInterval": 30}）
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* @param companyId 租户 ID
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* @return 新建的 VideoProcessJob
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*/
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@Transactional
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public VideoProcessJob createJob(Long sourceId, String jobType,
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String params, Long companyId) {
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SourceData source = sourceDataMapper.selectById(sourceId);
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if (source == null || !companyId.equals(source.getCompanyId())) {
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throw new BusinessException("NOT_FOUND", "资料不存在: " + sourceId, HttpStatus.NOT_FOUND);
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}
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validateJobType(jobType);
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// source_data → PREPROCESSING
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StateValidator.assertTransition(
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SourceStatus.TRANSITIONS,
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SourceStatus.valueOf(source.getStatus()), SourceStatus.PREPROCESSING);
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sourceDataMapper.update(null, new LambdaUpdateWrapper<SourceData>()
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.eq(SourceData::getId, sourceId)
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.set(SourceData::getStatus, "PREPROCESSING")
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.set(SourceData::getUpdatedAt, LocalDateTime.now()));
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// 插入 PENDING 任务
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VideoProcessJob job = new VideoProcessJob();
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job.setCompanyId(companyId);
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job.setSourceId(sourceId);
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job.setJobType(jobType);
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job.setStatus("PENDING");
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job.setParams(params != null ? params : "{}");
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job.setRetryCount(0);
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job.setMaxRetries(3);
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jobMapper.insert(job);
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// 事务提交后触发 AI（不在事务内，不占用 DB 连接）
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final Long jobId = job.getId();
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final String filePath = source.getFilePath();
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final String finalJobType = jobType;
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TransactionSynchronizationManager.registerSynchronization(new TransactionSynchronization() {
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@Override
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public void afterCommit() {
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triggerAi(jobId, sourceId, filePath, finalJobType);
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}
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});
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log.info("视频处理任务已创建（AI 将在事务提交后触发）: jobId={}, sourceId={}", jobId, sourceId);
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return job;
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}
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// ------------------------------------------------------------------ 处理回调 --
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/**
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* 处理 AI 服务异步回调（POST /api/video/callback，无需用户 Token）。
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*
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* 幂等：若 job 已为 SUCCESS，直接返回，防止重复处理。
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* 重试触发同样延迟到事务提交后（afterCommit），不在事务内执行。
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*
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* @param jobId 任务 ID
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* @param callbackStatus AI 回调状态（SUCCESS / FAILED）
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* @param outputPath 成功时的输出路径（可选）
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* @param errorMessage 失败时的错误信息（可选）
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*/
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@Transactional
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public void handleCallback(Long jobId, String callbackStatus,
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String outputPath, String errorMessage) {
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// video_process_job 在 IGNORED_TABLES 中（回调无 CompanyContext），此处显式校验
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VideoProcessJob job = jobMapper.selectById(jobId);
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if (job == null || job.getCompanyId() == null) {
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log.warn("视频处理回调：job 不存在，jobId={}", jobId);
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return;
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}
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// 幂等：已成功则忽略重复回调
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if ("SUCCESS".equals(job.getStatus())) {
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log.info("视频处理回调幂等：jobId={} 已为 SUCCESS，跳过", jobId);
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return;
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}
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if ("SUCCESS".equals(callbackStatus)) {
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handleSuccess(job, outputPath);
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} else {
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handleFailure(job, errorMessage);
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}
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}
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// ------------------------------------------------------------------ 管理员重置 --
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/**
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* 管理员手动重置失败任务（FAILED → PENDING）。
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*
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* 仅允许 FAILED 状态的任务重置，重置后 retryCount 清零，
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* 管理员可随后重新调用 createJob 触发处理。
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*
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* @param jobId 任务 ID
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* @param companyId 租户 ID
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*/
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@Transactional
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public VideoProcessJob reset(Long jobId, Long companyId) {
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VideoProcessJob job = jobMapper.selectById(jobId);
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if (job == null || !companyId.equals(job.getCompanyId())) {
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throw new BusinessException("NOT_FOUND", "视频处理任务不存在: " + jobId, HttpStatus.NOT_FOUND);
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}
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if (!"FAILED".equals(job.getStatus())) {
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throw new BusinessException("INVALID_TRANSITION",
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"只有 FAILED 状态的任务可以重置，当前状态: " + job.getStatus(),
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HttpStatus.BAD_REQUEST);
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}
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jobMapper.update(null, new LambdaUpdateWrapper<VideoProcessJob>()
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.eq(VideoProcessJob::getId, jobId)
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.set(VideoProcessJob::getStatus, "PENDING")
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.set(VideoProcessJob::getRetryCount, 0)
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.set(VideoProcessJob::getErrorMessage, null)
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.set(VideoProcessJob::getUpdatedAt, LocalDateTime.now()));
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job.setStatus("PENDING");
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job.setRetryCount(0);
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log.info("视频处理任务已重置: jobId={}", jobId);
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return job;
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}
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// ------------------------------------------------------------------ 查询 --
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public VideoProcessJob getJob(Long jobId, Long companyId) {
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VideoProcessJob job = jobMapper.selectById(jobId);
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if (job == null || !companyId.equals(job.getCompanyId())) {
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throw new BusinessException("NOT_FOUND", "视频处理任务不存在: " + jobId, HttpStatus.NOT_FOUND);
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}
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return job;
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}
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// ------------------------------------------------------------------ 私有方法 --
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private void handleSuccess(VideoProcessJob job, String outputPath) {
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// job → SUCCESS
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jobMapper.update(null, new LambdaUpdateWrapper<VideoProcessJob>()
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.eq(VideoProcessJob::getId, job.getId())
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.set(VideoProcessJob::getStatus, "SUCCESS")
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.set(VideoProcessJob::getOutputPath, outputPath)
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.set(VideoProcessJob::getCompletedAt, LocalDateTime.now())
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.set(VideoProcessJob::getUpdatedAt, LocalDateTime.now()));
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// source_data PREPROCESSING → PENDING（进入提取队列）
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sourceDataMapper.update(null, new LambdaUpdateWrapper<SourceData>()
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.eq(SourceData::getId, job.getSourceId())
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.set(SourceData::getStatus, "PENDING")
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.set(SourceData::getUpdatedAt, LocalDateTime.now()));
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log.info("视频处理成功：jobId={}, sourceId={}", job.getId(), job.getSourceId());
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}
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private void handleFailure(VideoProcessJob job, String errorMessage) {
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int newRetryCount = job.getRetryCount() + 1;
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int maxRetries = job.getMaxRetries() != null ? job.getMaxRetries() : 3;
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if (newRetryCount < maxRetries) {
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// 仍有重试次数：job → RETRYING，事务提交后重新触发 AI
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jobMapper.update(null, new LambdaUpdateWrapper<VideoProcessJob>()
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.eq(VideoProcessJob::getId, job.getId())
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.set(VideoProcessJob::getStatus, "RETRYING")
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.set(VideoProcessJob::getRetryCount, newRetryCount)
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.set(VideoProcessJob::getErrorMessage, errorMessage)
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.set(VideoProcessJob::getUpdatedAt, LocalDateTime.now()));
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log.warn("视频处理失败，开始第 {} 次重试：jobId={}, error={}",
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newRetryCount, job.getId(), errorMessage);
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// 重试 AI 触发延迟到事务提交后
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SourceData source = sourceDataMapper.selectById(job.getSourceId());
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if (source != null) {
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final Long jobId = job.getId();
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final Long sourceId = job.getSourceId();
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final String filePath = source.getFilePath();
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final String jobType = job.getJobType();
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TransactionSynchronizationManager.registerSynchronization(new TransactionSynchronization() {
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@Override
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public void afterCommit() {
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triggerAi(jobId, sourceId, filePath, jobType);
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}
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});
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}
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} else {
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// 超出最大重试次数：job → FAILED，source_data → PENDING
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jobMapper.update(null, new LambdaUpdateWrapper<VideoProcessJob>()
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.eq(VideoProcessJob::getId, job.getId())
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.set(VideoProcessJob::getStatus, "FAILED")
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.set(VideoProcessJob::getRetryCount, newRetryCount)
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.set(VideoProcessJob::getErrorMessage, errorMessage)
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.set(VideoProcessJob::getCompletedAt, LocalDateTime.now())
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.set(VideoProcessJob::getUpdatedAt, LocalDateTime.now()));
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// source_data PREPROCESSING → PENDING（管理员可重新处理）
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sourceDataMapper.update(null, new LambdaUpdateWrapper<SourceData>()
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.eq(SourceData::getId, job.getSourceId())
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.set(SourceData::getStatus, "PENDING")
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.set(SourceData::getUpdatedAt, LocalDateTime.now()));
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log.error("视频处理永久失败：jobId={}, sourceId={}, error={}",
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job.getId(), job.getSourceId(), errorMessage);
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}
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}
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private void triggerAi(Long jobId, Long sourceId, String filePath, String jobType) {
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AiServiceClient.VideoProcessRequest req = AiServiceClient.VideoProcessRequest.builder()
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.sourceId(sourceId)
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.filePath(filePath)
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.bucket(bucket)
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.params(Map.of("jobId", jobId, "jobType", jobType))
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.build();
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try {
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if ("FRAME_EXTRACT".equals(jobType)) {
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aiServiceClient.extractFrames(req);
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} else {
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aiServiceClient.videoToText(req);
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}
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log.info("AI 触发成功: jobId={}", jobId);
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} catch (Exception e) {
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log.error("触发视频处理 AI 失败（jobId={}）：{}，job 保持当前状态，需管理员手动重置", jobId, e.getMessage());
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}
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}
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private void validateJobType(String jobType) {
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if (!"FRAME_EXTRACT".equals(jobType) && !"VIDEO_TO_TEXT".equals(jobType)) {
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throw new BusinessException("INVALID_JOB_TYPE",
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"任务类型不合法，应为 FRAME_EXTRACT 或 VIDEO_TO_TEXT", HttpStatus.BAD_REQUEST);
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}
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}
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}
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