refactor(video): 预置 AI 算法改为 SQL 种子数据，移除 @PostConstruct 初始化
原 AiAlgorithmServiceImpl.initPresetAlgorithms() 在 @PostConstruct 里插入 4 条预置算法，带来两个问题： 1. 启动时无登录上下文，MP 自动填充 creator 失效 → 启动失败 2. 算法清单硬编码在 Java 代码，迭代要重编译发布 改为 video.sql 种子数据管理： - video.sql 的预置算法 INSERT 扩展为 4 条（leave_post / intrusion / illegal_parking / vehicle_congestion），参数 schema 与边缘端对齐 - 使用 ON DUPLICATE KEY UPDATE 保证幂等：新库初始化 + 存量库升级 都走同一条语句，param_schema / description 会被自动校正 - 保留用户侧可修改的字段（is_active / global_params）不被覆盖 代码层： - 删除 initPresetAlgorithms() 方法与 PRESET_ALGORITHMS 静态 Map - 删除 SYSTEM_USER 常量 - 删除 @PostConstruct / HashMap 相关 import - 保留 syncFromEdge() 作为边缘端主动同步的运行时入口 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -935,12 +935,30 @@ CREATE TABLE `video_ai_algo_template` (
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-- ============================================================================
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-- 预置算法（与 FastAPI 边缘端保持一致）
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-- 幂等：已存在则更新 name/target_class/param_schema/description，保持 is_active 与用户设置
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INSERT INTO `video_ai_algorithm` (`algo_code`, `algo_name`, `target_class`, `param_schema`, `description`, `is_active`, `creator`, `create_time`, `updater`, `update_time`, `deleted`, `tenant_id`) VALUES
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('leave_post', '离岗检测', 'person',
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'{"confirm_on_duty_sec":{"type":"int","default":10,"min":1},"confirm_leave_sec":{"type":"int","default":30,"min":1},"leave_countdown_sec":{"type":"int","default":300,"min":0},"cooldown_sec":{"type":"int","default":600,"min":0},"working_hours":{"type":"list","default":[]}}',
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'检测人员是否在岗，支持工作时间段配置', 1, 'system', NOW(), 'system', NOW(), b'0', 0),
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'{"leave_countdown_sec":{"type":"int","default":300,"min":0},"working_hours":{"type":"list","default":[]}}',
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'检测人员是否在岗，支持工作时间段配置。算法抽帧频率：3帧/秒（固定）',
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1, '1', NOW(), '1', NOW(), b'0', 0),
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('intrusion', '周界入侵检测', 'person',
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'{"cooldown_seconds":{"type":"int","default":120,"min":0},"confirm_seconds":{"type":"int","default":5,"min":1}}',
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'检测人员进入指定区域', 1, 'system', NOW(), 'system', NOW(), b'0', 0);
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'{"cooldown_seconds":{"type":"int","default":300,"min":0},"confirm_seconds":{"type":"int","default":5,"min":1},"confirm_intrusion_seconds":{"type":"int","default":5,"min":1},"confirm_clear_seconds":{"type":"int","default":180,"min":1}}',
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'检测人员进入指定区域。算法抽帧频率：1帧/秒（固定）。持续检测到人5秒触发告警，持续无人180秒自动结束告警。消失确认期间短暂有人(<5秒)不影响倒计时。',
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1, '1', NOW(), '1', NOW(), b'0', 0),
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('illegal_parking', '车辆违停检测', 'car,truck,bus,motorcycle',
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'{"confirm_vehicle_sec":{"type":"int","default":15,"min":5},"parking_countdown_sec":{"type":"int","default":300,"min":60},"confirm_clear_sec":{"type":"int","default":30,"min":10},"cooldown_sec":{"type":"int","default":600,"min":0}}',
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'检测禁停区域内是否有车辆违规停放。确认车辆停留15秒后开始5分钟倒计时，超时触发告警。车辆离开30秒后自动结束告警。',
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1, '1', NOW(), '1', NOW(), b'0', 0),
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('vehicle_congestion', '车辆拥堵检测', 'car,truck,bus,motorcycle',
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'{"count_threshold":{"type":"int","default":3,"min":1},"confirm_congestion_sec":{"type":"int","default":60,"min":10},"confirm_clear_sec":{"type":"int","default":120,"min":10},"cooldown_sec":{"type":"int","default":600,"min":0}}',
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'检测区域内车辆是否拥堵。当平均车辆数达到阈值并持续60秒触发告警，车辆减少并持续120秒后自动结束告警。',
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1, '1', NOW(), '1', NOW(), b'0', 0)
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ON DUPLICATE KEY UPDATE
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`algo_name` = VALUES(`algo_name`),
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`target_class` = VALUES(`target_class`),
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`param_schema` = VALUES(`param_schema`),
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`description` = VALUES(`description`),
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`updater` = VALUES(`updater`),
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`update_time` = NOW();
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SET FOREIGN_KEY_CHECKS = 1;
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@@ -5,14 +5,12 @@ import com.viewsh.module.video.aiot.config.AiServiceConfig;
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import com.viewsh.module.video.aiot.dao.AiAlgorithmMapper;
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import com.viewsh.module.video.aiot.service.IAiAlgorithmService;
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import com.viewsh.module.video.aiot.service.IAiConfigLogService;
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import jakarta.annotation.PostConstruct;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import org.springframework.web.client.RestTemplate;
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import java.time.LocalDateTime;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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@@ -29,64 +27,6 @@ public class AiAlgorithmServiceImpl implements IAiAlgorithmService {
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@Autowired
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private IAiConfigLogService configLogService;
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/**
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* 预置算法定义，启动时自动校正数据库中的乱码数据
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* 注意：仅包含边缘端实际实现的算法
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*/
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private static final Map<String, String[]> PRESET_ALGORITHMS = new HashMap<>();
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static {
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// algoCode -> {algoName, targetClass, description, paramSchema}
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PRESET_ALGORITHMS.put("leave_post", new String[]{
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"离岗检测", "person", "检测人员是否在岗，支持工作时间段配置。算法抽帧频率：3帧/秒（固定）",
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"{\"leave_countdown_sec\":{\"type\":\"int\",\"default\":300,\"min\":0},\"working_hours\":{\"type\":\"list\",\"default\":[]}}"
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});
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PRESET_ALGORITHMS.put("intrusion", new String[]{
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"周界入侵检测", "person", "检测人员进入指定区域。算法抽帧频率：1帧/秒（固定）。持续检测到人5秒触发告警，持续无人180秒自动结束告警。消失确认期间短暂有人(<5秒)不影响倒计时。",
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"{\"cooldown_seconds\":{\"type\":\"int\",\"default\":300,\"min\":0},\"confirm_seconds\":{\"type\":\"int\",\"default\":5,\"min\":1},\"confirm_intrusion_seconds\":{\"type\":\"int\",\"default\":5,\"min\":1},\"confirm_clear_seconds\":{\"type\":\"int\",\"default\":180,\"min\":1}}"
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});
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PRESET_ALGORITHMS.put("illegal_parking", new String[]{
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"车辆违停检测", "car,truck,bus,motorcycle", "检测禁停区域内是否有车辆违规停放。确认车辆停留15秒后开始5分钟倒计时，超时触发告警。车辆离开30秒后自动结束告警。",
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"{\"confirm_vehicle_sec\":{\"type\":\"int\",\"default\":15,\"min\":5},\"parking_countdown_sec\":{\"type\":\"int\",\"default\":300,\"min\":60},\"confirm_clear_sec\":{\"type\":\"int\",\"default\":30,\"min\":10},\"cooldown_sec\":{\"type\":\"int\",\"default\":600,\"min\":0}}"
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});
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PRESET_ALGORITHMS.put("vehicle_congestion", new String[]{
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"车辆拥堵检测", "car,truck,bus,motorcycle", "检测区域内车辆是否拥堵。当平均车辆数达到阈值并持续60秒触发告警，车辆减少并持续120秒后自动结束告警。",
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"{\"count_threshold\":{\"type\":\"int\",\"default\":3,\"min\":1},\"confirm_congestion_sec\":{\"type\":\"int\",\"default\":60,\"min\":10},\"confirm_clear_sec\":{\"type\":\"int\",\"default\":120,\"min\":10},\"cooldown_sec\":{\"type\":\"int\",\"default\":600,\"min\":0}}"
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});
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}
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/** 系统级初始化使用的 creator/updater，@PostConstruct 无登录上下文时 MP 自动填充会留空 */
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private static final String SYSTEM_USER = "1";
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@PostConstruct
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public void initPresetAlgorithms() {
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for (Map.Entry<String, String[]> entry : PRESET_ALGORITHMS.entrySet()) {
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String code = entry.getKey();
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String[] vals = entry.getValue();
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AiAlgorithm existing = algorithmMapper.queryByCode(code);
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if (existing == null) {
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AiAlgorithm algo = new AiAlgorithm();
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algo.setAlgoCode(code);
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algo.setAlgoName(vals[0]);
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algo.setTargetClass(vals[1]);
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algo.setDescription(vals[2]);
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algo.setParamSchema(vals[3]);
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algo.setIsActive(true);
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algo.setCreator(SYSTEM_USER);
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algo.setUpdater(SYSTEM_USER);
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algorithmMapper.add(algo);
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log.info("[AI算法] 初始化预置算法: {}", code);
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} else {
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existing.setAlgoName(vals[0]);
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existing.setTargetClass(vals[1]);
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existing.setDescription(vals[2]);
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existing.setParamSchema(vals[3]);
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existing.setUpdater(SYSTEM_USER);
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algorithmMapper.updateByCode(existing);
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log.info("[AI算法] 校正预置算法数据: {}", code);
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}
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}
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}
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@Override
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public List<AiAlgorithm> queryAll() {
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return algorithmMapper.queryAll();
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