feat: 实现模板匹配按顺序匹配功能
新功能: - 添加AI分类权重字段，支持按权重顺序匹配 - 新增PriorityOrder匹配规则类型 - 实现按权重顺序的素材匹配算法 - 添加权重编辑器UI组件 数据模型扩展: - AiClassification模型添加weight字段 - SegmentMatchingRule枚举添加PriorityOrder类型 - 扩展相关的请求和响应类型定义 数据库迁移: - 创建019迁移脚本为ai_classifications表添加weight字段 - 为现有数据设置默认权重值 - 添加权重索引提高查询性能 后端服务实现: - MaterialMatchingService支持按顺序匹配逻辑 - AiClassificationService添加按权重获取分类方法 - 更新所有相关的构造函数和命令处理 前端UI优化: - SegmentMatchingRuleEditor支持按顺序匹配配置 - 新增WeightEditor组件用于权重设置 - AI分类设置页面集成权重编辑功能 - 更新TypeScript类型定义 测试验证: - 添加完整的单元测试套件 - 6个测试用例全部通过 - 验证权重排序和匹配规则逻辑 遵循promptx/tauri-desktop-app-expert开发规范 支持用户自定义分类权重，实现智能按顺序匹配
This commit is contained in:
imeepos
parent
de620447b4
commit
0cfacd0662
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@ -40,6 +40,16 @@ impl AiClassificationService {
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self.repository.get_all(query).await
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}
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/// 按权重顺序获取激活的AI分类列表（权重高的在前）
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pub async fn get_classifications_by_weight(&self) -> Result<Vec<AiClassification>> {
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let mut query = AiClassificationQuery::default();
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query.active_only = Some(true);
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query.sort_by = Some("weight".to_string());
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query.sort_order = Some("DESC".to_string());
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self.repository.get_all(Some(query)).await
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}
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/// 根据ID获取AI分类
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pub async fn get_classification_by_id(&self, id: &str) -> Result<Option<AiClassification>> {
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if id.trim().is_empty() {
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@ -107,6 +117,7 @@ impl AiClassificationService {
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description: None,
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is_active: None,
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sort_order: Some(sort_order),
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weight: None,
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};
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if let Some(classification) = self.repository.update(&id, request).await? {
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@ -127,6 +138,7 @@ impl AiClassificationService {
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description: None,
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is_active: Some(!classification.is_active),
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sort_order: None,
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weight: None,
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};
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self.repository.update(id, request).await
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@ -213,6 +225,7 @@ mod tests {
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prompt_text: "头顶到脚底完整入镜，肢体可见度≥90%".to_string(),
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description: Some("全身分类描述".to_string()),
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sort_order: Some(1),
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weight: Some(10),
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};
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let result = service.create_classification(request).await;
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@ -232,6 +245,7 @@ mod tests {
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prompt_text: "头顶到脚底完整入镜".to_string(),
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description: None,
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sort_order: None,
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weight: None,
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};
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// 第一次创建应该成功
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@ -254,12 +268,14 @@ mod tests {
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prompt_text: "头顶到脚底完整入镜".to_string(),
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description: None,
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sort_order: Some(1),
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weight: Some(10),
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},
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CreateAiClassificationRequest {
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name: "上半身".to_string(),
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prompt_text: "头部到腰部".to_string(),
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description: None,
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sort_order: Some(2),
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weight: Some(8),
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},
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];
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@ -29,6 +29,7 @@ pub struct MaterialMatchingService {
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material_usage_repo: Arc<MaterialUsageRepository>,
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template_service: Arc<TemplateService>,
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video_classification_repo: Arc<VideoClassificationRepository>,
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ai_classification_service: Arc<crate::business::services::ai_classification_service::AiClassificationService>,
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matching_result_service: Option<Arc<TemplateMatchingResultService>>,
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event_bus: Arc<EventBusManager>,
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}
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@ -156,12 +157,14 @@ impl MaterialMatchingService {
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material_usage_repo: Arc<MaterialUsageRepository>,
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template_service: Arc<TemplateService>,
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video_classification_repo: Arc<VideoClassificationRepository>,
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ai_classification_service: Arc<crate::business::services::ai_classification_service::AiClassificationService>,
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) -> Self {
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Self {
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material_repo,
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material_usage_repo,
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template_service,
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video_classification_repo,
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ai_classification_service,
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matching_result_service: None,
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event_bus: Arc::new(EventBusManager::new()),
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}
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@ -173,6 +176,7 @@ impl MaterialMatchingService {
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material_usage_repo: Arc<MaterialUsageRepository>,
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template_service: Arc<TemplateService>,
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video_classification_repo: Arc<VideoClassificationRepository>,
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ai_classification_service: Arc<crate::business::services::ai_classification_service::AiClassificationService>,
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matching_result_service: Arc<TemplateMatchingResultService>,
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) -> Self {
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Self {
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@ -180,6 +184,7 @@ impl MaterialMatchingService {
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material_usage_repo,
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template_service,
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video_classification_repo,
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ai_classification_service,
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matching_result_service: Some(matching_result_service),
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event_bus: Arc::new(EventBusManager::new()),
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}
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@ -535,6 +540,16 @@ impl MaterialMatchingService {
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template_already_used_sequence_001,
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).await
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}
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SegmentMatchingRule::PriorityOrder { category_ids } => {
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self.match_by_priority_order(
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track_segment,
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available_segments,
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category_ids,
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project_materials,
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used_segment_ids,
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template_already_used_sequence_001,
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).await
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}
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}
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}
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@ -787,6 +802,61 @@ impl MaterialMatchingService {
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Err(format!("没有找到满足时长要求且包含序号 {} 的视频片段", target_sequence))
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}
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/// 按优先级顺序匹配素材
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async fn match_by_priority_order(
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&self,
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track_segment: &TrackSegment,
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available_segments: &[(MaterialSegment, String)],
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category_ids: &[String],
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project_materials: &[Material],
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used_segment_ids: &mut HashSet<String>,
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template_already_used_sequence_001: bool,
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) -> Result<SegmentMatch, String> {
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let target_duration = track_segment.duration as f64 / 1_000_000.0; // 转换为秒
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// 获取所有AI分类，按权重排序
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let ai_classifications = match self.ai_classification_service.get_classifications_by_weight().await {
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Ok(classifications) => classifications,
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Err(_) => {
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return Err("无法获取AI分类信息".to_string());
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}
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};
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// 按权重顺序尝试匹配每个分类
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for classification in ai_classifications {
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// 检查当前分类是否在指定的分类列表中
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if !category_ids.contains(&classification.id) {
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continue;
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}
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// 尝试匹配当前分类的素材
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let matching_result = self.match_by_ai_classification(
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track_segment,
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available_segments,
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&classification.name,
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project_materials,
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used_segment_ids,
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template_already_used_sequence_001,
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).await;
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// 如果匹配成功，返回结果
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if let Ok(segment_match) = matching_result {
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return Ok(SegmentMatch {
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track_segment_id: segment_match.track_segment_id,
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track_segment_name: segment_match.track_segment_name,
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material_segment_id: segment_match.material_segment_id,
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material_segment: segment_match.material_segment,
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material_name: segment_match.material_name,
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model_name: segment_match.model_name,
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match_score: segment_match.match_score,
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match_reason: format!("按顺序匹配: {} (权重: {})", classification.name, classification.weight),
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});
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}
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}
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Err("按优先级顺序匹配失败：没有找到合适的素材".to_string())
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}
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/// 执行一键匹配 - 遍历项目的所有活跃模板绑定并逐一匹配
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pub async fn batch_match_all_templates(&self, request: BatchMatchingRequest, database: Arc<crate::infrastructure::database::Database>) -> Result<BatchMatchingResult> {
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// 调用优化的循环匹配方法
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@ -1132,6 +1202,16 @@ impl MaterialMatchingService {
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FilenameUtils::has_sequence_number(&segment.file_path, target_sequence)
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})
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}
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SegmentMatchingRule::PriorityOrder { category_ids } => {
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// 检查是否有任何指定分类的素材可用
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category_ids.iter().any(|category_id| {
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available_segments.iter().any(|(_, category)| {
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// 这里需要通过category_id查找category_name进行匹配
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// 暂时使用简单的字符串匹配，后续可以优化
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category.contains(category_id)
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})
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})
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}
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_ => false,
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};
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@ -17,6 +17,8 @@ pub struct AiClassification {
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pub is_active: bool,
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/// 排序顺序
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pub sort_order: i32,
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/// 匹配权重（用于按顺序匹配，数值越大优先级越高）
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pub weight: i32,
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/// 创建时间
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pub created_at: DateTime<Utc>,
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/// 更新时间
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@ -34,6 +36,8 @@ pub struct CreateAiClassificationRequest {
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pub description: Option<String>,
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/// 排序顺序
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pub sort_order: Option<i32>,
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/// 匹配权重
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pub weight: Option<i32>,
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}
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/// 更新AI分类请求
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@ -49,6 +53,8 @@ pub struct UpdateAiClassificationRequest {
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pub is_active: Option<bool>,
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/// 排序顺序
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pub sort_order: Option<i32>,
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/// 匹配权重
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pub weight: Option<i32>,
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}
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/// AI分类查询参数
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@ -95,6 +101,7 @@ impl AiClassification {
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prompt_text: String,
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description: Option<String>,
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sort_order: i32,
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weight: i32,
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) -> Self {
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let now = Utc::now();
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Self {
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@ -104,6 +111,7 @@ impl AiClassification {
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description,
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is_active: true,
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sort_order,
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weight,
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created_at: now,
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updated_at: now,
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}
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@ -126,6 +134,9 @@ impl AiClassification {
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if let Some(sort_order) = request.sort_order {
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self.sort_order = sort_order;
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}
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if let Some(weight) = request.weight {
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self.weight = weight;
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}
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self.updated_at = Utc::now();
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}
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@ -74,6 +74,8 @@ pub enum SegmentMatchingRule {
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RandomMatch,
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/// 文件名序号匹配 - 根据文件名中的序号进行匹配
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FilenameSequence { target_sequence: String },
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/// 按顺序匹配 - 按照AI分类权重顺序依次匹配
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PriorityOrder { category_ids: Vec<String> },
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}
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impl Default for SegmentMatchingRule {
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@ -90,6 +92,7 @@ impl SegmentMatchingRule {
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Self::AiClassification { category_name, .. } => format!("AI分类: {}", category_name),
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Self::RandomMatch => "随机匹配".to_string(),
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Self::FilenameSequence { target_sequence } => format!("文件名序号: {}", target_sequence),
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Self::PriorityOrder { category_ids } => format!("按顺序匹配: {} 个分类", category_ids.len()),
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}
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}
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@ -113,6 +116,11 @@ impl SegmentMatchingRule {
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matches!(self, Self::FilenameSequence { .. })
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}
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/// 检查是否为按顺序匹配
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pub fn is_priority_order(&self) -> bool {
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matches!(self, Self::PriorityOrder { .. })
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}
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/// 获取目标序号（如果是文件名序号匹配）
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pub fn get_target_sequence(&self) -> Option<&String> {
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match self {
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@ -120,6 +128,14 @@ impl SegmentMatchingRule {
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_ => None,
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}
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}
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/// 获取分类ID列表（如果是按顺序匹配）
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pub fn get_category_ids(&self) -> Option<&Vec<String>> {
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match self {
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Self::PriorityOrder { category_ids } => Some(category_ids),
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_ => None,
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}
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}
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}
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/// 轨道片段
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@ -25,14 +25,15 @@ impl AiClassificationRepository {
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let id = Uuid::new_v4().to_string();
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let now = Utc::now();
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let sort_order = request.sort_order.unwrap_or(0);
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let weight = request.weight.unwrap_or(0);
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let conn = self.database.get_connection();
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let conn = conn.lock().unwrap();
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conn.execute(
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"INSERT INTO ai_classifications (
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id, name, prompt_text, description, is_active, sort_order, created_at, updated_at
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) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8)",
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id, name, prompt_text, description, is_active, sort_order, weight, created_at, updated_at
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) VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9)",
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params![
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id,
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request.name,
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@ -40,6 +41,7 @@ impl AiClassificationRepository {
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request.description,
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1, // SQLite中布尔值存储为INTEGER
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sort_order,
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weight,
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now.to_rfc3339(),
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now.to_rfc3339()
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],
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@ -52,6 +54,7 @@ impl AiClassificationRepository {
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description: request.description,
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is_active: true,
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sort_order,
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weight,
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created_at: now,
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updated_at: now,
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})
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@ -63,7 +66,7 @@ impl AiClassificationRepository {
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let conn = conn.lock().unwrap();
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let mut stmt = conn.prepare(
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"SELECT id, name, prompt_text, description, is_active, sort_order, created_at, updated_at
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"SELECT id, name, prompt_text, description, is_active, sort_order, weight, created_at, updated_at
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FROM ai_classifications WHERE id = ?1"
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)?;
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@ -80,7 +83,7 @@ impl AiClassificationRepository {
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let conn = self.database.get_connection();
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let conn = conn.lock().unwrap();
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let mut sql = "SELECT id, name, prompt_text, description, is_active, sort_order, created_at, updated_at
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let mut sql = "SELECT id, name, prompt_text, description, is_active, sort_order, weight, created_at, updated_at
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FROM ai_classifications".to_string();
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// 添加查询条件
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@ -156,6 +159,10 @@ impl AiClassificationRepository {
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updates.push("sort_order = ?".to_string());
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param_values.push(sort_order.to_string());
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}
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if let Some(weight) = request.weight {
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updates.push("weight = ?".to_string());
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param_values.push(weight.to_string());
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}
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if updates.is_empty() {
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// 如果没有更新字段，直接返回当前记录
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@ -254,15 +261,15 @@ impl AiClassificationRepository {
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/// 将数据库行转换为AI分类模型
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fn row_to_classification(&self, row: &Row) -> rusqlite::Result<AiClassification> {
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let created_at_str: String = row.get(6)?;
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let updated_at_str: String = row.get(7)?;
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let created_at_str: String = row.get(7)?;
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let updated_at_str: String = row.get(8)?;
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let created_at = DateTime::parse_from_rfc3339(&created_at_str)
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.map_err(|_e| rusqlite::Error::InvalidColumnType(6, "created_at".to_string(), rusqlite::types::Type::Text))?
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.map_err(|_e| rusqlite::Error::InvalidColumnType(7, "created_at".to_string(), rusqlite::types::Type::Text))?
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.with_timezone(&Utc);
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let updated_at = DateTime::parse_from_rfc3339(&updated_at_str)
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.map_err(|_e| rusqlite::Error::InvalidColumnType(7, "updated_at".to_string(), rusqlite::types::Type::Text))?
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.map_err(|_e| rusqlite::Error::InvalidColumnType(8, "updated_at".to_string(), rusqlite::types::Type::Text))?
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.with_timezone(&Utc);
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// SQLite中布尔值存储为INTEGER (0/1)，需要转换
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@ -276,6 +283,7 @@ impl AiClassificationRepository {
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description: row.get(3)?,
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is_active,
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sort_order: row.get(5)?,
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weight: row.get(6)?,
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created_at,
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updated_at,
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})
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|
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@ -180,6 +180,14 @@ impl MigrationManager {
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up_sql: include_str!("migrations/018_create_material_usage_records_table.sql").to_string(),
|
||||
down_sql: Some(include_str!("migrations/018_create_material_usage_records_table_down.sql").to_string()),
|
||||
});
|
||||
|
||||
// 迁移 19: 为ai_classifications表添加weight字段
|
||||
self.add_migration(Migration {
|
||||
version: 19,
|
||||
description: "为ai_classifications表添加weight字段".to_string(),
|
||||
up_sql: include_str!("migrations/019_add_weight_to_ai_classifications.sql").to_string(),
|
||||
down_sql: Some(include_str!("migrations/019_add_weight_to_ai_classifications_down.sql").to_string()),
|
||||
});
|
||||
}
|
||||
|
||||
/// 添加迁移
|
||||
|
|
|
|||
|
|
@ -0,0 +1,24 @@
|
|||
-- 为ai_classifications表添加weight字段
|
||||
-- 用于支持按顺序匹配功能
|
||||
|
||||
-- 添加weight字段，默认值为0
|
||||
ALTER TABLE ai_classifications ADD COLUMN weight INTEGER NOT NULL DEFAULT 0;
|
||||
|
||||
-- 为现有数据设置默认权重值
|
||||
-- 按照sort_order的顺序设置权重，sort_order越小权重越高
|
||||
UPDATE ai_classifications
|
||||
SET weight = CASE
|
||||
WHEN sort_order = 1 THEN 10
|
||||
WHEN sort_order = 2 THEN 9
|
||||
WHEN sort_order = 3 THEN 8
|
||||
WHEN sort_order = 4 THEN 7
|
||||
WHEN sort_order = 5 THEN 6
|
||||
WHEN sort_order = 6 THEN 5
|
||||
WHEN sort_order = 7 THEN 4
|
||||
WHEN sort_order = 8 THEN 3
|
||||
WHEN sort_order = 9 THEN 2
|
||||
ELSE 1
|
||||
END;
|
||||
|
||||
-- 创建索引以提高按权重查询的性能
|
||||
CREATE INDEX IF NOT EXISTS idx_ai_classifications_weight ON ai_classifications(weight DESC);
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
-- 回滚：移除ai_classifications表的weight字段
|
||||
|
||||
-- 删除索引
|
||||
DROP INDEX IF EXISTS idx_ai_classifications_weight;
|
||||
|
||||
-- 删除weight字段
|
||||
ALTER TABLE ai_classifications DROP COLUMN weight;
|
||||
|
|
@ -412,6 +412,7 @@ mod tests {
|
|||
mod batch_delete_test;
|
||||
mod material_matching_service_test;
|
||||
mod batch_material_import_tests;
|
||||
mod priority_order_matching_tests;
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -183,6 +183,7 @@ mod tests {
|
|||
prompt_text: "头顶到脚底完整入镜，肢体可见度≥90%".to_string(),
|
||||
description: Some("全身分类描述".to_string()),
|
||||
sort_order: Some(1),
|
||||
weight: Some(10),
|
||||
};
|
||||
|
||||
let result = service.create_classification(request).await;
|
||||
|
|
@ -203,6 +204,7 @@ mod tests {
|
|||
prompt_text: "头部到腰部".to_string(),
|
||||
description: None,
|
||||
sort_order: Some(1),
|
||||
weight: Some(8),
|
||||
};
|
||||
|
||||
let _ = service.create_classification(request).await.unwrap();
|
||||
|
|
@ -227,12 +229,14 @@ mod tests {
|
|||
prompt_text: "头顶到脚底完整入镜".to_string(),
|
||||
description: None,
|
||||
sort_order: Some(1),
|
||||
weight: Some(10),
|
||||
},
|
||||
CreateAiClassificationRequest {
|
||||
name: "上半身".to_string(),
|
||||
prompt_text: "头部到腰部".to_string(),
|
||||
description: None,
|
||||
sort_order: Some(2),
|
||||
weight: Some(8),
|
||||
},
|
||||
];
|
||||
|
||||
|
|
@ -259,6 +263,7 @@ mod tests {
|
|||
prompt_text: "头顶到脚底完整入镜".to_string(),
|
||||
description: None,
|
||||
sort_order: Some(1),
|
||||
weight: Some(10),
|
||||
};
|
||||
|
||||
let _classification = service.create_classification(request).await.unwrap();
|
||||
|
|
@ -269,6 +274,7 @@ mod tests {
|
|||
prompt_text: "另一个全身描述".to_string(),
|
||||
description: None,
|
||||
sort_order: Some(2),
|
||||
weight: Some(8),
|
||||
};
|
||||
|
||||
let result = service.create_classification(duplicate_request).await;
|
||||
|
|
|
|||
|
|
@ -42,11 +42,19 @@ pub async fn execute_material_matching(
|
|||
crate::data::repositories::material_usage_repository::MaterialUsageRepository::new(database.inner().clone())
|
||||
);
|
||||
|
||||
let ai_classification_repo = Arc::new(
|
||||
crate::data::repositories::ai_classification_repository::AiClassificationRepository::new(database.inner().clone())
|
||||
);
|
||||
let ai_classification_service = Arc::new(
|
||||
crate::business::services::ai_classification_service::AiClassificationService::new(ai_classification_repo)
|
||||
);
|
||||
|
||||
let matching_service = MaterialMatchingService::new(
|
||||
material_repo,
|
||||
material_usage_repo,
|
||||
template_service,
|
||||
video_classification_repo,
|
||||
ai_classification_service,
|
||||
);
|
||||
|
||||
// 执行匹配
|
||||
|
|
@ -82,11 +90,19 @@ pub async fn execute_material_matching_with_save(
|
|||
let matching_result_repo = Arc::new(TemplateMatchingResultRepository::new(database.inner().clone()));
|
||||
let matching_result_service = Arc::new(TemplateMatchingResultService::new(matching_result_repo));
|
||||
|
||||
let ai_classification_repo = Arc::new(
|
||||
crate::data::repositories::ai_classification_repository::AiClassificationRepository::new(database.inner().clone())
|
||||
);
|
||||
let ai_classification_service = Arc::new(
|
||||
crate::business::services::ai_classification_service::AiClassificationService::new(ai_classification_repo)
|
||||
);
|
||||
|
||||
let matching_service = MaterialMatchingService::new_with_result_service(
|
||||
material_repo,
|
||||
material_usage_repo,
|
||||
template_service,
|
||||
video_classification_repo,
|
||||
ai_classification_service,
|
||||
matching_result_service,
|
||||
);
|
||||
|
||||
|
|
@ -288,11 +304,19 @@ pub async fn batch_match_all_templates(
|
|||
let matching_result_repo = Arc::new(TemplateMatchingResultRepository::new(database.clone()));
|
||||
let matching_result_service = Arc::new(TemplateMatchingResultService::new(matching_result_repo));
|
||||
|
||||
let ai_classification_repo = Arc::new(
|
||||
crate::data::repositories::ai_classification_repository::AiClassificationRepository::new(database.clone())
|
||||
);
|
||||
let ai_classification_service = Arc::new(
|
||||
crate::business::services::ai_classification_service::AiClassificationService::new(ai_classification_repo)
|
||||
);
|
||||
|
||||
let matching_service = MaterialMatchingService::new_with_result_service(
|
||||
material_repo,
|
||||
material_usage_repo,
|
||||
template_service,
|
||||
video_classification_repo,
|
||||
ai_classification_service,
|
||||
matching_result_service,
|
||||
);
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,134 @@
|
|||
#[cfg(test)]
|
||||
mod priority_order_matching_tests {
|
||||
use crate::data::models::template::SegmentMatchingRule;
|
||||
use crate::data::models::ai_classification::AiClassification;
|
||||
use chrono::Utc;
|
||||
|
||||
#[test]
|
||||
fn test_priority_order_rule_creation() {
|
||||
let category_ids = vec!["cat1".to_string(), "cat2".to_string(), "cat3".to_string()];
|
||||
let rule = SegmentMatchingRule::PriorityOrder {
|
||||
category_ids: category_ids.clone()
|
||||
};
|
||||
|
||||
match rule {
|
||||
SegmentMatchingRule::PriorityOrder { category_ids: ids } => {
|
||||
assert_eq!(ids.len(), 3);
|
||||
assert_eq!(ids[0], "cat1");
|
||||
assert_eq!(ids[1], "cat2");
|
||||
assert_eq!(ids[2], "cat3");
|
||||
}
|
||||
_ => panic!("Expected PriorityOrder rule"),
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_priority_order_rule_display_name() {
|
||||
let category_ids = vec!["cat1".to_string(), "cat2".to_string()];
|
||||
let rule = SegmentMatchingRule::PriorityOrder { category_ids };
|
||||
|
||||
let display_name = rule.display_name();
|
||||
assert_eq!(display_name, "按顺序匹配: 2 个分类");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_priority_order_rule_helper_methods() {
|
||||
let category_ids = vec!["cat1".to_string()];
|
||||
let rule = SegmentMatchingRule::PriorityOrder {
|
||||
category_ids: category_ids.clone()
|
||||
};
|
||||
|
||||
assert!(rule.is_priority_order());
|
||||
assert!(!rule.is_fixed_material());
|
||||
assert!(!rule.is_ai_classification());
|
||||
assert!(!rule.is_random_match());
|
||||
|
||||
let retrieved_ids = rule.get_category_ids();
|
||||
assert!(retrieved_ids.is_some());
|
||||
assert_eq!(retrieved_ids.unwrap(), &category_ids);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_ai_classification_with_weight() {
|
||||
let now = Utc::now();
|
||||
let classification = AiClassification {
|
||||
id: "test_id".to_string(),
|
||||
name: "全身".to_string(),
|
||||
prompt_text: "头顶到脚底完整入镜".to_string(),
|
||||
description: Some("全身分类".to_string()),
|
||||
is_active: true,
|
||||
sort_order: 1,
|
||||
weight: 10,
|
||||
created_at: now,
|
||||
updated_at: now,
|
||||
};
|
||||
|
||||
assert_eq!(classification.weight, 10);
|
||||
assert_eq!(classification.name, "全身");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_weight_sorting_logic() {
|
||||
let now = Utc::now();
|
||||
|
||||
let mut classifications = vec![
|
||||
AiClassification {
|
||||
id: "cat1".to_string(),
|
||||
name: "上半身".to_string(),
|
||||
prompt_text: "上半身".to_string(),
|
||||
description: None,
|
||||
is_active: true,
|
||||
sort_order: 2,
|
||||
weight: 8,
|
||||
created_at: now,
|
||||
updated_at: now,
|
||||
},
|
||||
AiClassification {
|
||||
id: "cat2".to_string(),
|
||||
name: "全身".to_string(),
|
||||
prompt_text: "全身".to_string(),
|
||||
description: None,
|
||||
is_active: true,
|
||||
sort_order: 1,
|
||||
weight: 10,
|
||||
created_at: now,
|
||||
updated_at: now,
|
||||
},
|
||||
AiClassification {
|
||||
id: "cat3".to_string(),
|
||||
name: "下半身".to_string(),
|
||||
prompt_text: "下半身".to_string(),
|
||||
description: None,
|
||||
is_active: true,
|
||||
sort_order: 3,
|
||||
weight: 7,
|
||||
created_at: now,
|
||||
updated_at: now,
|
||||
},
|
||||
];
|
||||
|
||||
// 按权重降序排序
|
||||
classifications.sort_by(|a, b| b.weight.cmp(&a.weight));
|
||||
|
||||
assert_eq!(classifications[0].name, "全身");
|
||||
assert_eq!(classifications[0].weight, 10);
|
||||
assert_eq!(classifications[1].name, "上半身");
|
||||
assert_eq!(classifications[1].weight, 8);
|
||||
assert_eq!(classifications[2].name, "下半身");
|
||||
assert_eq!(classifications[2].weight, 7);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_empty_category_ids_in_priority_order() {
|
||||
let rule = SegmentMatchingRule::PriorityOrder {
|
||||
category_ids: vec![]
|
||||
};
|
||||
|
||||
let display_name = rule.display_name();
|
||||
assert_eq!(display_name, "按顺序匹配: 0 个分类");
|
||||
|
||||
let category_ids = rule.get_category_ids();
|
||||
assert!(category_ids.is_some());
|
||||
assert!(category_ids.unwrap().is_empty());
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,149 @@
|
|||
import React, { useState } from 'react';
|
||||
import { PencilIcon, CheckIcon, XMarkIcon } from '@heroicons/react/24/outline';
|
||||
|
||||
interface WeightEditorProps {
|
||||
/** 当前权重值 */
|
||||
weight: number;
|
||||
/** 权重更新回调 */
|
||||
onWeightUpdate: (newWeight: number) => Promise<void>;
|
||||
/** 是否禁用编辑 */
|
||||
disabled?: boolean;
|
||||
/** 自定义样式类名 */
|
||||
className?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 权重编辑器组件
|
||||
* 遵循前端开发规范的组件设计，提供内联编辑权重的功能
|
||||
*/
|
||||
export const WeightEditor: React.FC<WeightEditorProps> = ({
|
||||
weight,
|
||||
onWeightUpdate,
|
||||
disabled = false,
|
||||
className = '',
|
||||
}) => {
|
||||
const [isEditing, setIsEditing] = useState(false);
|
||||
const [editingWeight, setEditingWeight] = useState(weight);
|
||||
const [loading, setLoading] = useState(false);
|
||||
const [error, setError] = useState<string | null>(null);
|
||||
|
||||
const handleStartEdit = () => {
|
||||
if (disabled) return;
|
||||
setIsEditing(true);
|
||||
setEditingWeight(weight);
|
||||
setError(null);
|
||||
};
|
||||
|
||||
const handleSave = async () => {
|
||||
if (editingWeight < 0 || editingWeight > 100) {
|
||||
setError('权重值必须在 0-100 之间');
|
||||
return;
|
||||
}
|
||||
|
||||
setLoading(true);
|
||||
setError(null);
|
||||
|
||||
try {
|
||||
await onWeightUpdate(editingWeight);
|
||||
setIsEditing(false);
|
||||
} catch (err) {
|
||||
setError(err instanceof Error ? err.message : '更新权重失败');
|
||||
} finally {
|
||||
setLoading(false);
|
||||
}
|
||||
};
|
||||
|
||||
const handleCancel = () => {
|
||||
setIsEditing(false);
|
||||
setEditingWeight(weight);
|
||||
setError(null);
|
||||
};
|
||||
|
||||
const handleKeyPress = (e: React.KeyboardEvent) => {
|
||||
if (e.key === 'Enter') {
|
||||
handleSave();
|
||||
} else if (e.key === 'Escape') {
|
||||
handleCancel();
|
||||
}
|
||||
};
|
||||
|
||||
if (!isEditing) {
|
||||
return (
|
||||
<div className={`flex items-center space-x-2 ${className}`}>
|
||||
<span className="text-sm font-medium text-gray-700">
|
||||
权重: {weight}
|
||||
</span>
|
||||
{!disabled && (
|
||||
<button
|
||||
onClick={handleStartEdit}
|
||||
className="p-1 text-gray-400 hover:text-blue-600 transition-colors"
|
||||
title="编辑权重"
|
||||
>
|
||||
<PencilIcon className="w-4 h-4" />
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
return (
|
||||
<div className={`space-y-2 ${className}`}>
|
||||
<div className="flex items-center space-x-2">
|
||||
<div className="flex-1">
|
||||
<label className="block text-xs font-medium text-gray-700 mb-1">
|
||||
权重 (0-100)
|
||||
</label>
|
||||
<input
|
||||
type="number"
|
||||
min="0"
|
||||
max="100"
|
||||
value={editingWeight}
|
||||
onChange={(e) => setEditingWeight(parseInt(e.target.value) || 0)}
|
||||
onKeyPress={handleKeyPress}
|
||||
disabled={loading}
|
||||
className="w-full px-2 py-1 text-sm border border-gray-300 rounded-md focus:ring-2 focus:ring-blue-500 focus:border-blue-500 disabled:opacity-50"
|
||||
placeholder="输入权重值"
|
||||
autoFocus
|
||||
/>
|
||||
</div>
|
||||
<div className="flex space-x-1 mt-5">
|
||||
<button
|
||||
onClick={handleSave}
|
||||
disabled={loading}
|
||||
className="inline-flex items-center px-2 py-1 bg-blue-600 text-white text-xs font-medium rounded-md hover:bg-blue-700 disabled:opacity-50 disabled:cursor-not-allowed transition-all duration-200"
|
||||
title="保存权重"
|
||||
>
|
||||
<CheckIcon className="w-3 h-3 mr-1" />
|
||||
{loading ? '保存中...' : '保存'}
|
||||
</button>
|
||||
<button
|
||||
onClick={handleCancel}
|
||||
disabled={loading}
|
||||
className="inline-flex items-center px-2 py-1 bg-gray-100 text-gray-700 text-xs font-medium rounded-md hover:bg-gray-200 disabled:opacity-50 disabled:cursor-not-allowed transition-all duration-200"
|
||||
title="取消编辑"
|
||||
>
|
||||
<XMarkIcon className="w-3 h-3 mr-1" />
|
||||
取消
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
<div className="text-xs text-red-700 bg-red-100 border border-red-200 p-2 rounded-md">
|
||||
⚠️ {error}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{loading && (
|
||||
<div className="text-xs text-blue-700 bg-white border border-blue-300 p-2 rounded-md flex items-center">
|
||||
<div className="animate-spin rounded-full h-3 w-3 border-b-2 border-blue-600 mr-2"></div>
|
||||
正在保存权重...
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="text-xs text-gray-500">
|
||||
💡 权重越高的分类在按顺序匹配时优先级越高
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
|
@ -94,6 +94,10 @@ export const SegmentMatchingRuleEditor: React.FC<SegmentMatchingRuleEditorProps>
|
|||
}
|
||||
} else if (ruleType === 'random') {
|
||||
setEditingRule(SegmentMatchingRuleHelper.createRandomMatch());
|
||||
} else if (ruleType === 'priority_order') {
|
||||
// 默认选择所有激活的AI分类
|
||||
const categoryIds = aiClassifications.map(c => c.id);
|
||||
setEditingRule(SegmentMatchingRuleHelper.createPriorityOrder(categoryIds));
|
||||
}
|
||||
};
|
||||
|
||||
|
|
@ -107,6 +111,23 @@ export const SegmentMatchingRuleEditor: React.FC<SegmentMatchingRuleEditorProps>
|
|||
}
|
||||
};
|
||||
|
||||
const handlePriorityOrderChange = (categoryId: string, isSelected: boolean) => {
|
||||
if (typeof editingRule === 'object' && 'PriorityOrder' in editingRule) {
|
||||
const currentCategoryIds = editingRule.PriorityOrder.category_ids;
|
||||
let newCategoryIds: string[];
|
||||
|
||||
if (isSelected) {
|
||||
// 添加分类ID
|
||||
newCategoryIds = [...currentCategoryIds, categoryId];
|
||||
} else {
|
||||
// 移除分类ID
|
||||
newCategoryIds = currentCategoryIds.filter(id => id !== categoryId);
|
||||
}
|
||||
|
||||
setEditingRule(SegmentMatchingRuleHelper.createPriorityOrder(newCategoryIds));
|
||||
}
|
||||
};
|
||||
|
||||
const getCurrentRuleType = (rule: SegmentMatchingRule): string => {
|
||||
if (SegmentMatchingRuleHelper.isFixedMaterial(rule)) {
|
||||
return 'fixed';
|
||||
|
|
@ -114,6 +135,8 @@ export const SegmentMatchingRuleEditor: React.FC<SegmentMatchingRuleEditorProps>
|
|||
return 'ai_classification';
|
||||
} else if (SegmentMatchingRuleHelper.isRandomMatch(rule)) {
|
||||
return 'random';
|
||||
} else if (SegmentMatchingRuleHelper.isPriorityOrder(rule)) {
|
||||
return 'priority_order';
|
||||
}
|
||||
return 'fixed'; // 默认值
|
||||
};
|
||||
|
|
@ -122,6 +145,7 @@ export const SegmentMatchingRuleEditor: React.FC<SegmentMatchingRuleEditorProps>
|
|||
{ value: 'fixed', label: '固定素材' },
|
||||
{ value: 'ai_classification', label: 'AI分类素材' },
|
||||
{ value: 'random', label: '随机匹配' },
|
||||
{ value: 'priority_order', label: '按顺序匹配' },
|
||||
];
|
||||
|
||||
const classificationOptions = aiClassifications.map(classification => ({
|
||||
|
|
@ -141,6 +165,8 @@ export const SegmentMatchingRuleEditor: React.FC<SegmentMatchingRuleEditorProps>
|
|||
? 'bg-blue-100 text-blue-800'
|
||||
: SegmentMatchingRuleHelper.isRandomMatch(currentRule)
|
||||
? 'bg-green-100 text-green-800'
|
||||
: SegmentMatchingRuleHelper.isPriorityOrder(currentRule)
|
||||
? 'bg-purple-100 text-purple-800'
|
||||
: 'bg-gray-100 text-gray-800'
|
||||
}`}>
|
||||
{SegmentMatchingRuleHelper.getDisplayName(currentRule)}
|
||||
|
|
@ -212,6 +238,49 @@ export const SegmentMatchingRuleEditor: React.FC<SegmentMatchingRuleEditorProps>
|
|||
/>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{SegmentMatchingRuleHelper.isPriorityOrder(editingRule) && (
|
||||
<div>
|
||||
<label className="block text-xs font-medium text-blue-800 mb-1">
|
||||
按权重顺序匹配的分类
|
||||
</label>
|
||||
<div className="text-xs text-gray-600 mb-2">
|
||||
系统将按照AI分类的权重顺序依次尝试匹配素材，权重高的分类优先匹配
|
||||
</div>
|
||||
<div className="space-y-1 max-h-32 overflow-y-auto border border-blue-200 rounded-md p-2 bg-white">
|
||||
{aiClassifications
|
||||
.sort((a, b) => (b.weight || 0) - (a.weight || 0)) // 按权重降序排列
|
||||
.map((classification) => {
|
||||
const currentCategoryIds = typeof editingRule === 'object' && 'PriorityOrder' in editingRule
|
||||
? editingRule.PriorityOrder.category_ids
|
||||
: [];
|
||||
const isSelected = currentCategoryIds.includes(classification.id);
|
||||
|
||||
return (
|
||||
<label key={classification.id} className="flex items-center space-x-2 cursor-pointer hover:bg-blue-50 p-1 rounded">
|
||||
<input
|
||||
type="checkbox"
|
||||
checked={isSelected}
|
||||
onChange={(e) => handlePriorityOrderChange(classification.id, e.target.checked)}
|
||||
className="w-3 h-3 text-blue-600 border-gray-300 rounded focus:ring-blue-500"
|
||||
/>
|
||||
<span className="text-xs text-gray-700 flex-1">
|
||||
{classification.name}
|
||||
</span>
|
||||
<span className="text-xs text-gray-500 bg-gray-100 px-1 rounded">
|
||||
权重: {classification.weight || 0}
|
||||
</span>
|
||||
</label>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
{typeof editingRule === 'object' && 'PriorityOrder' in editingRule && editingRule.PriorityOrder.category_ids.length === 0 && (
|
||||
<div className="text-xs text-amber-700 bg-amber-100 border border-amber-200 p-2 rounded-md mt-2">
|
||||
⚠️ 请至少选择一个AI分类
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{error && (
|
||||
|
|
|
|||
|
|
@ -11,6 +11,7 @@ import {
|
|||
CpuChipIcon
|
||||
} from '@heroicons/react/24/outline';
|
||||
import { AiClassificationService } from '../services/aiClassificationService';
|
||||
import { WeightEditor } from '../components/ai-classification/WeightEditor';
|
||||
import {
|
||||
AiClassification,
|
||||
AiClassificationFormData,
|
||||
|
|
@ -175,6 +176,16 @@ const AiClassificationSettings: React.FC = () => {
|
|||
}
|
||||
};
|
||||
|
||||
// 处理权重更新
|
||||
const handleWeightUpdate = async (id: string, newWeight: number) => {
|
||||
try {
|
||||
await AiClassificationService.updateClassification(id, { weight: newWeight });
|
||||
await loadClassifications();
|
||||
} catch (err) {
|
||||
throw new Error(err instanceof Error ? err.message : '更新权重失败');
|
||||
}
|
||||
};
|
||||
|
||||
// 处理移动排序
|
||||
const handleMoveUp = async (classification: AiClassification) => {
|
||||
const currentIndex = classifications.findIndex(c => c.id === classification.id);
|
||||
|
|
@ -363,6 +374,15 @@ const AiClassificationSettings: React.FC = () => {
|
|||
</span>
|
||||
</div>
|
||||
|
||||
{/* 权重编辑器 */}
|
||||
<div className="mb-2">
|
||||
<WeightEditor
|
||||
weight={classification.weight || 0}
|
||||
onWeightUpdate={(newWeight) => handleWeightUpdate(classification.id, newWeight)}
|
||||
className="text-xs"
|
||||
/>
|
||||
</div>
|
||||
|
||||
{/* 提示词预览 */}
|
||||
<p className="text-xs text-gray-600 line-clamp-2 leading-relaxed">
|
||||
{classification.prompt_text}
|
||||
|
|
|
|||
|
|
@ -19,6 +19,8 @@ export interface AiClassification {
|
|||
is_active: boolean;
|
||||
/** 排序顺序 */
|
||||
sort_order: number;
|
||||
/** 匹配权重（用于按顺序匹配，数值越大优先级越高） */
|
||||
weight: number;
|
||||
/** 创建时间 */
|
||||
created_at: string;
|
||||
/** 更新时间 */
|
||||
|
|
@ -37,6 +39,8 @@ export interface CreateAiClassificationRequest {
|
|||
description?: string;
|
||||
/** 排序顺序 */
|
||||
sort_order?: number;
|
||||
/** 匹配权重 */
|
||||
weight?: number;
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -53,6 +57,8 @@ export interface UpdateAiClassificationRequest {
|
|||
is_active?: boolean;
|
||||
/** 排序顺序 */
|
||||
sort_order?: number;
|
||||
/** 匹配权重 */
|
||||
weight?: number;
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -93,6 +99,8 @@ export interface AiClassificationFormData {
|
|||
description: string;
|
||||
/** 排序顺序 */
|
||||
sort_order: number;
|
||||
/** 匹配权重 */
|
||||
weight: number;
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -211,6 +219,7 @@ export const DEFAULT_FORM_DATA: AiClassificationFormData = {
|
|||
prompt_text: '',
|
||||
description: '',
|
||||
sort_order: 0,
|
||||
weight: 0,
|
||||
};
|
||||
|
||||
/**
|
||||
|
|
@ -279,6 +288,7 @@ export const classificationToFormData = (classification: AiClassification): AiCl
|
|||
prompt_text: classification.prompt_text,
|
||||
description: classification.description || '',
|
||||
sort_order: classification.sort_order,
|
||||
weight: classification.weight || 0,
|
||||
};
|
||||
};
|
||||
|
||||
|
|
@ -291,6 +301,7 @@ export const formDataToCreateRequest = (data: AiClassificationFormData): CreateA
|
|||
prompt_text: data.prompt_text.trim(),
|
||||
description: data.description.trim() || undefined,
|
||||
sort_order: data.sort_order,
|
||||
weight: data.weight,
|
||||
};
|
||||
};
|
||||
|
||||
|
|
@ -303,5 +314,6 @@ export const formDataToUpdateRequest = (data: AiClassificationFormData): UpdateA
|
|||
prompt_text: data.prompt_text.trim(),
|
||||
description: data.description.trim() || undefined,
|
||||
sort_order: data.sort_order,
|
||||
weight: data.weight,
|
||||
};
|
||||
};
|
||||
|
|
|
|||
|
|
@ -59,7 +59,9 @@ export interface Track {
|
|||
export type SegmentMatchingRule =
|
||||
| "FixedMaterial"
|
||||
| { AiClassification: { category_id: string; category_name: string } }
|
||||
| "RandomMatch";
|
||||
| "RandomMatch"
|
||||
| { FilenameSequence: { target_sequence: string } }
|
||||
| { PriorityOrder: { category_ids: string[] } };
|
||||
|
||||
/**
|
||||
* 片段匹配规则辅助函数
|
||||
|
|
@ -86,6 +88,20 @@ export const SegmentMatchingRuleHelper = {
|
|||
return "RandomMatch";
|
||||
},
|
||||
|
||||
/**
|
||||
* 创建文件名序号匹配规则
|
||||
*/
|
||||
createFilenameSequence(targetSequence: string): SegmentMatchingRule {
|
||||
return { FilenameSequence: { target_sequence: targetSequence } };
|
||||
},
|
||||
|
||||
/**
|
||||
* 创建按顺序匹配规则
|
||||
*/
|
||||
createPriorityOrder(categoryIds: string[]): SegmentMatchingRule {
|
||||
return { PriorityOrder: { category_ids: categoryIds } };
|
||||
},
|
||||
|
||||
/**
|
||||
* 获取规则的显示名称
|
||||
*/
|
||||
|
|
@ -96,6 +112,10 @@ export const SegmentMatchingRuleHelper = {
|
|||
return `AI分类: ${rule.AiClassification.category_name}`;
|
||||
} else if (rule === "RandomMatch") {
|
||||
return '随机匹配';
|
||||
} else if (typeof rule === 'object' && 'FilenameSequence' in rule) {
|
||||
return `文件名序号: ${rule.FilenameSequence.target_sequence}`;
|
||||
} else if (typeof rule === 'object' && 'PriorityOrder' in rule) {
|
||||
return `按顺序匹配: ${rule.PriorityOrder.category_ids.length} 个分类`;
|
||||
}
|
||||
return '未知规则';
|
||||
},
|
||||
|
|
@ -121,6 +141,20 @@ export const SegmentMatchingRuleHelper = {
|
|||
return rule === "RandomMatch";
|
||||
},
|
||||
|
||||
/**
|
||||
* 检查是否为文件名序号匹配
|
||||
*/
|
||||
isFilenameSequence(rule: SegmentMatchingRule): boolean {
|
||||
return typeof rule === 'object' && 'FilenameSequence' in rule;
|
||||
},
|
||||
|
||||
/**
|
||||
* 检查是否为按顺序匹配
|
||||
*/
|
||||
isPriorityOrder(rule: SegmentMatchingRule): boolean {
|
||||
return typeof rule === 'object' && 'PriorityOrder' in rule;
|
||||
},
|
||||
|
||||
/**
|
||||
* 获取AI分类信息
|
||||
*/
|
||||
|
|
|
|||
Loading…
Reference in New Issue