feat: 实现项目一键AI分类功能
- 添加ProjectBatchClassificationRequest和ProjectBatchClassificationResponse数据模型 - 在VideoClassificationService中实现create_project_batch_classification_tasks方法 - 添加start_project_batch_classification Tauri命令接口 - 在前端添加startProjectBatchClassification方法和相关类型定义 - 在项目详情页面添加一键AI分类按钮和队列状态监控 - 支持批量处理项目下所有符合条件的视频素材 - 集成现有的AI分类队列系统，确保兼容性
This commit is contained in:
imeepos
parent
5d8e2df8d0
commit
eeeef4ead4
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@ -43,7 +43,7 @@ pub struct TaskProgress {
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/// AI视频分类任务队列
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/// 遵循 Tauri 开发规范的业务层设计模式
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pub struct VideoClassificationQueue {
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service: Arc<VideoClassificationService>,
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pub service: Arc<VideoClassificationService>,
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status: Arc<RwLock<QueueStatus>>,
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current_task: Arc<Mutex<Option<String>>>,
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task_progress: Arc<RwLock<HashMap<String, TaskProgress>>>,
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@ -102,6 +102,105 @@ impl VideoClassificationService {
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Ok(tasks)
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}
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/// 为项目创建一键批量分类任务
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pub async fn create_project_batch_classification_tasks(&self, request: ProjectBatchClassificationRequest) -> Result<ProjectBatchClassificationResponse> {
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println!("🚀 开始项目一键分类");
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println!(" 项目ID: {}", request.project_id);
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// 验证项目是否存在
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let _project = self.material_repo.get_project_by_id(&request.project_id).await?
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.ok_or_else(|| anyhow!("项目不存在: {}", request.project_id))?;
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// 获取项目所有素材
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let all_materials = self.material_repo.get_by_project_id(&request.project_id)?;
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let total_materials = all_materials.len() as u32;
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println!(" 项目总素材数: {}", total_materials);
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// 过滤符合条件的素材
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let material_types = request.material_types.unwrap_or_else(|| vec![crate::data::models::material::MaterialType::Video]);
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let overwrite_existing = request.overwrite_existing.unwrap_or(false);
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let mut eligible_materials = Vec::new();
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let mut skipped_materials = Vec::new();
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for material in all_materials {
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// 检查素材类型
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if !material_types.contains(&material.material_type) {
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continue;
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}
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// 检查处理状态 - 只处理已完成处理的素材
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if material.processing_status != crate::data::models::material::ProcessingStatus::Completed {
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continue;
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}
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// 获取素材片段
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let segments = self.material_repo.get_segments(&material.id)?;
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if segments.is_empty() {
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continue;
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}
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// 检查是否已有分类记录
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if !overwrite_existing {
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let mut has_classification = false;
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for segment in &segments {
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if self.video_repo.is_segment_classified(&segment.id).await? {
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has_classification = true;
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break;
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}
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}
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if has_classification {
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skipped_materials.push(material.id.clone());
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continue;
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}
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}
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eligible_materials.push(material);
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}
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let eligible_count = eligible_materials.len() as u32;
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println!(" 符合条件的素材数: {}", eligible_count);
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println!(" 跳过的素材数: {}", skipped_materials.len());
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// 为每个符合条件的素材创建批量分类任务
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let mut all_task_ids = Vec::new();
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let mut created_tasks_count = 0u32;
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for material in eligible_materials {
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let batch_request = BatchClassificationRequest {
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material_id: material.id.clone(),
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project_id: request.project_id.clone(),
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overwrite_existing,
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priority: request.priority,
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};
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match self.create_batch_classification_tasks(batch_request).await {
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Ok(tasks) => {
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let task_ids: Vec<String> = tasks.iter().map(|t| t.id.clone()).collect();
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created_tasks_count += task_ids.len() as u32;
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all_task_ids.extend(task_ids);
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println!(" 为素材 {} 创建了 {} 个分类任务", material.name, tasks.len());
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}
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Err(e) => {
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println!(" 为素材 {} 创建分类任务失败: {}", material.name, e);
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// 继续处理其他素材，不因单个素材失败而中断整个流程
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}
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}
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}
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println!("✅ 项目一键分类任务创建完成");
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println!(" 总共创建任务数: {}", created_tasks_count);
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Ok(ProjectBatchClassificationResponse {
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total_materials,
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eligible_materials: eligible_count,
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created_tasks: created_tasks_count,
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task_ids: all_task_ids,
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skipped_materials,
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})
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}
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/// 处理单个分类任务
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pub async fn process_classification_task(&self, task_id: &str) -> Result<VideoClassificationRecord> {
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// 获取任务
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@ -117,6 +117,34 @@ pub struct BatchClassificationRequest {
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pub priority: Option<i32>,
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}
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/// 项目一键分类请求
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ProjectBatchClassificationRequest {
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/// 项目ID
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pub project_id: String,
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/// 是否覆盖已有分类
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pub overwrite_existing: Option<bool>,
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/// 要处理的素材类型（可选，默认只处理视频）
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pub material_types: Option<Vec<crate::data::models::material::MaterialType>>,
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/// 任务优先级
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pub priority: Option<i32>,
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}
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/// 项目一键分类响应
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ProjectBatchClassificationResponse {
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/// 项目中总素材数
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pub total_materials: u32,
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/// 符合条件的素材数
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pub eligible_materials: u32,
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/// 创建的任务数
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pub created_tasks: u32,
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/// 创建的任务ID列表
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pub task_ids: Vec<String>,
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/// 跳过的素材ID列表（已有分类）
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pub skipped_materials: Vec<String>,
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}
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/// 分类任务查询参数
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#[derive(Debug, Clone, Serialize, Deserialize, Default)]
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pub struct ClassificationTaskQuery {
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@ -106,6 +106,7 @@ pub fn run() {
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commands::ai_classification_commands::validate_ai_classification_name,
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// AI视频分类命令
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commands::video_classification_commands::start_video_classification,
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commands::video_classification_commands::start_project_batch_classification,
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commands::video_classification_commands::get_classification_queue_status,
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commands::video_classification_commands::get_project_classification_queue_status,
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commands::video_classification_commands::get_classification_task_progress,
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@ -61,6 +61,31 @@ pub async fn start_video_classification(
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Ok(task_ids)
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}
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/// 启动项目一键AI视频分类
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/// 遍历项目下所有符合条件的素材并添加到分类队列
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#[command]
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pub async fn start_project_batch_classification(
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request: ProjectBatchClassificationRequest,
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state: State<'_, AppState>,
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) -> Result<ProjectBatchClassificationResponse, String> {
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let queue = get_queue_instance(&state).await;
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// 创建项目批量分类任务
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let response = queue.service.create_project_batch_classification_tasks(request)
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.await
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.map_err(|e| e.to_string())?;
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// 启动队列（如果尚未启动）
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if let Err(e) = queue.start().await {
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// 如果队列已经在运行，忽略错误
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if !e.to_string().contains("已经在运行中") {
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return Err(e.to_string());
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}
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}
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Ok(response)
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}
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/// 获取分类队列状态
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#[command]
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pub async fn get_classification_queue_status(
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@ -127,10 +127,10 @@ export const VideoClassificationProgress: React.FC<VideoClassificationProgressPr
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// 计算进度百分比
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const getOverallProgress = useCallback(() => {
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const getOverallProgress = () => {
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if (!typedQueueStats || typedQueueStats.total_tasks === 0) return 0;
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return Math.round(((typedQueueStats.completed_tasks + typedQueueStats.failed_tasks) / typedQueueStats.total_tasks) * 100);
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}, [typedQueueStats]);
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};
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// 过滤相关任务
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const relevantTasks = materialId
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@ -142,9 +142,7 @@ export const VideoClassificationProgress: React.FC<VideoClassificationProgressPr
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}
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const statusInfo = typedQueueStats ? getStatusInfo(typedQueueStats.status) : null;
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const overallProgress = useMemo(() => {
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return getOverallProgress()
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}, [getOverallProgress]);
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const overallProgress = getOverallProgress()
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return (
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<div className="bg-white rounded-lg shadow-sm border border-gray-200 overflow-hidden">
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@ -1,10 +1,12 @@
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import React, { useEffect, useState } from 'react';
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import { useParams, useNavigate } from 'react-router-dom';
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import { ArrowLeft, FolderOpen, Settings, Upload, FileVideo, FileAudio, FileImage, HardDrive } from 'lucide-react';
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import { ArrowLeft, FolderOpen, Settings, Upload, FileVideo, FileAudio, FileImage, HardDrive, Brain, Loader2 } from 'lucide-react';
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import { useProjectStore } from '../store/projectStore';
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import { useMaterialStore } from '../store/materialStore';
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import { useVideoClassificationStore } from '../store/videoClassificationStore';
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import { Project } from '../types/project';
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import { MaterialImportResult } from '../types/material';
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import { ProjectBatchClassificationRequest, ProjectBatchClassificationResponse } from '../types/videoClassification';
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import { LoadingSpinner } from '../components/LoadingSpinner';
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import { ErrorMessage } from '../components/ErrorMessage';
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import { MaterialImportDialog } from '../components/MaterialImportDialog';
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@ -28,9 +30,17 @@ export const ProjectDetails: React.FC = () => {
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loadMaterialStats,
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isLoading: materialsLoading
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} = useMaterialStore();
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const {
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startProjectBatchClassification,
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isLoading: classificationLoading,
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error: classificationError,
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queueStats,
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getProjectQueueStatus
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} = useVideoClassificationStore();
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const [project, setProject] = useState<Project | null>(null);
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const [showImportDialog, setShowImportDialog] = useState(false);
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const [activeTab, setActiveTab] = useState<'materials' | 'debug' | 'ai-logs'>('materials');
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const [batchClassificationResult, setBatchClassificationResult] = useState<ProjectBatchClassificationResponse | null>(null);
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// 加载项目详情
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useEffect(() => {
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@ -53,6 +63,21 @@ export const ProjectDetails: React.FC = () => {
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}
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}, [id, projects, loadMaterials, loadMaterialStats]);
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// 监控AI分类队列状态
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useEffect(() => {
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if (!project) return;
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// 初始加载队列状态
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getProjectQueueStatus(project.id);
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// 设置定时刷新
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const interval = setInterval(() => {
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getProjectQueueStatus(project.id);
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}, 3000); // 每3秒刷新一次
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return () => clearInterval(interval);
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}, [project, getProjectQueueStatus]);
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// 返回项目列表
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const handleBack = () => {
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navigate('/');
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@ -109,6 +134,40 @@ export const ProjectDetails: React.FC = () => {
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}
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};
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// 一键AI分类处理
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const handleBatchClassification = async () => {
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if (!project) return;
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try {
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const request: ProjectBatchClassificationRequest = {
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project_id: project.id,
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overwrite_existing: false, // 默认不覆盖已有分类
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material_types: undefined, // 使用默认值（只处理视频）
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priority: undefined, // 使用默认优先级
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};
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const response = await startProjectBatchClassification(request);
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setBatchClassificationResult(response);
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// 显示结果提示
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const message = `一键分类启动成功！\n` +
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`项目总素材数: ${response.total_materials}\n` +
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`符合条件的素材数: ${response.eligible_materials}\n` +
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`创建的任务数: ${response.created_tasks}\n` +
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`跳过的素材数: ${response.skipped_materials.length}`;
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alert(message);
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// 刷新队列状态
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if (project) {
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getProjectQueueStatus(project.id);
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}
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} catch (error) {
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console.error('一键分类失败:', error);
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alert(`一键分类失败: ${error}`);
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}
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};
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if (isLoading) {
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return (
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<div className="flex items-center justify-center min-h-[400px]">
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@ -168,6 +227,21 @@ export const ProjectDetails: React.FC = () => {
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<span className="hidden sm:inline ml-2">导入素材</span>
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</button>
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<button
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onClick={handleBatchClassification}
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disabled={classificationLoading}
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className="inline-flex items-center px-3 sm:px-4 py-2 bg-gradient-to-r from-purple-500 to-pink-500 text-white rounded-lg hover:from-purple-600 hover:to-pink-600 disabled:opacity-50 disabled:cursor-not-allowed transition-all duration-200 shadow-sm hover:shadow-md text-sm"
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>
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{classificationLoading ? (
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<Loader2 className="w-4 h-4 animate-spin" />
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) : (
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<Brain className="w-4 h-4" />
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)}
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<span className="hidden sm:inline ml-2">
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{classificationLoading ? '分类中...' : '一键AI分类'}
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</span>
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</button>
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<button className="inline-flex items-center px-3 sm:px-4 py-2 bg-gray-100 text-gray-700 rounded-lg hover:bg-gray-200 transition-colors text-sm">
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<Settings className="w-4 h-4" />
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<span className="hidden sm:inline ml-2">项目设置</span>
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@ -177,7 +251,7 @@ export const ProjectDetails: React.FC = () => {
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</div>
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{/* 项目统计概览 */}
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<div className="grid grid-cols-2 md:grid-cols-4 gap-4 md:gap-6 mb-6">
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<div className="grid grid-cols-2 md:grid-cols-5 gap-4 md:gap-6 mb-6">
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{/* 总素材数 */}
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<div className="bg-white rounded-lg shadow-sm border border-gray-200 p-4 md:p-6">
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<div className="flex items-center justify-between">
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@ -229,6 +303,29 @@ export const ProjectDetails: React.FC = () => {
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</div>
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</div>
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</div>
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{/* AI分类状态 */}
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<div className="bg-white rounded-lg shadow-sm border border-gray-200 p-4 md:p-6">
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<div className="flex items-center justify-between">
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<div className="min-w-0 flex-1">
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<p className="text-xs md:text-sm font-medium text-gray-600 truncate">AI分类队列</p>
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<div className="flex items-center space-x-1">
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<p className="text-xl md:text-2xl font-bold text-gray-900">
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{queueStats?.pending_tasks || 0}
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</p>
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<span className="text-xs text-gray-500">待处理</span>
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</div>
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{queueStats?.processing_tasks && queueStats.processing_tasks > 0 && (
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<p className="text-xs text-blue-600 mt-1">
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{queueStats.processing_tasks} 个正在处理
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</p>
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)}
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</div>
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<div className="w-10 h-10 md:w-12 md:h-12 bg-gradient-to-br from-purple-100 to-pink-100 rounded-lg flex items-center justify-center ml-2">
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<Brain className="w-5 h-5 md:w-6 md:h-6 text-purple-600" />
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</div>
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</div>
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</div>
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</div>
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{/* 主要内容区域 */}
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@ -1,5 +1,9 @@
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import { create } from 'zustand';
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import { invoke } from '@tauri-apps/api/core';
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import {
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ProjectBatchClassificationRequest,
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ProjectBatchClassificationResponse
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} from '../types/videoClassification';
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// 类型定义
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export interface VideoClassificationRecord {
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@ -70,6 +74,7 @@ interface VideoClassificationState {
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// Actions
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startClassification: (request: BatchClassificationRequest) => Promise<string[]>;
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startProjectBatchClassification: (request: ProjectBatchClassificationRequest) => Promise<ProjectBatchClassificationResponse>;
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getQueueStatus: () => Promise<QueueStats>;
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getProjectQueueStatus: (projectId: string) => Promise<QueueStats>;
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getTaskProgress: (taskId: string) => Promise<TaskProgress | null>;
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@ -118,6 +123,24 @@ export const useVideoClassificationStore = create<VideoClassificationState>((set
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}
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},
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startProjectBatchClassification: async (request: ProjectBatchClassificationRequest) => {
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set({ isLoading: true, error: null });
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try {
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const response = await invoke<ProjectBatchClassificationResponse>('start_project_batch_classification', { request });
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// 刷新队列状态
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await get().refreshQueueStatus();
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await get().refreshTaskProgress();
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set({ isLoading: false });
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return response;
|
||||
} catch (error) {
|
||||
const errorMessage = typeof error === 'string' ? error : '启动项目一键分类失败';
|
||||
set({ error: errorMessage, isLoading: false });
|
||||
throw new Error(errorMessage);
|
||||
}
|
||||
},
|
||||
|
||||
getQueueStatus: async () => {
|
||||
try {
|
||||
const stats = await invoke<QueueStats>('get_classification_queue_status');
|
||||
|
|
|
|||
|
|
@ -0,0 +1,146 @@
|
|||
import { MaterialType } from './material';
|
||||
|
||||
/**
|
||||
* 任务状态枚举
|
||||
*/
|
||||
export enum TaskStatus {
|
||||
Pending = 'Pending',
|
||||
Uploading = 'Uploading',
|
||||
Analyzing = 'Analyzing',
|
||||
Completed = 'Completed',
|
||||
Failed = 'Failed',
|
||||
Cancelled = 'Cancelled',
|
||||
}
|
||||
|
||||
/**
|
||||
* 队列状态枚举
|
||||
*/
|
||||
export enum QueueStatus {
|
||||
Stopped = 'Stopped',
|
||||
Running = 'Running',
|
||||
Paused = 'Paused',
|
||||
}
|
||||
|
||||
/**
|
||||
* 分类状态枚举
|
||||
*/
|
||||
export enum ClassificationStatus {
|
||||
Classified = 'Classified',
|
||||
Failed = 'Failed',
|
||||
NeedsReview = 'NeedsReview',
|
||||
}
|
||||
|
||||
/**
|
||||
* 批量分类请求
|
||||
*/
|
||||
export interface BatchClassificationRequest {
|
||||
material_id: string;
|
||||
project_id: string;
|
||||
overwrite_existing: boolean;
|
||||
priority?: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* 项目一键分类请求
|
||||
*/
|
||||
export interface ProjectBatchClassificationRequest {
|
||||
project_id: string;
|
||||
overwrite_existing?: boolean;
|
||||
material_types?: MaterialType[];
|
||||
priority?: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* 项目一键分类响应
|
||||
*/
|
||||
export interface ProjectBatchClassificationResponse {
|
||||
total_materials: number;
|
||||
eligible_materials: number;
|
||||
created_tasks: number;
|
||||
task_ids: string[];
|
||||
skipped_materials: string[];
|
||||
}
|
||||
|
||||
/**
|
||||
* 任务进度信息
|
||||
*/
|
||||
export interface TaskProgress {
|
||||
task_id: string;
|
||||
status: TaskStatus;
|
||||
progress_percentage: number;
|
||||
current_step: string;
|
||||
error_message?: string;
|
||||
started_at?: string;
|
||||
estimated_completion?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 队列统计信息
|
||||
*/
|
||||
export interface QueueStats {
|
||||
status: QueueStatus;
|
||||
total_tasks: number;
|
||||
pending_tasks: number;
|
||||
processing_tasks: number;
|
||||
completed_tasks: number;
|
||||
failed_tasks: number;
|
||||
current_task_id?: string;
|
||||
processing_rate: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* 视频分类记录
|
||||
*/
|
||||
export interface VideoClassificationRecord {
|
||||
id: string;
|
||||
task_id: string;
|
||||
segment_id: string;
|
||||
material_id: string;
|
||||
project_id: string;
|
||||
video_file_path: string;
|
||||
classification_result: string;
|
||||
confidence_score: number;
|
||||
reasoning: string;
|
||||
features: string[];
|
||||
product_match: boolean;
|
||||
quality_score: number;
|
||||
gemini_file_uri: string;
|
||||
raw_response: string;
|
||||
status: ClassificationStatus;
|
||||
created_at: string;
|
||||
updated_at: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 分类统计信息
|
||||
*/
|
||||
export interface ClassificationStats {
|
||||
total_tasks: number;
|
||||
pending_tasks: number;
|
||||
processing_tasks: number;
|
||||
completed_tasks: number;
|
||||
failed_tasks: number;
|
||||
total_classifications: number;
|
||||
average_confidence_score: number;
|
||||
average_quality_score: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* 视频分类任务
|
||||
*/
|
||||
export interface VideoClassificationTask {
|
||||
id: string;
|
||||
segment_id: string;
|
||||
material_id: string;
|
||||
project_id: string;
|
||||
video_file_path: string;
|
||||
status: TaskStatus;
|
||||
priority: number;
|
||||
gemini_file_uri?: string;
|
||||
prompt_text?: string;
|
||||
error_message?: string;
|
||||
created_at: string;
|
||||
updated_at: string;
|
||||
started_at?: string;
|
||||
completed_at?: string;
|
||||
}
|
||||
Loading…
Reference in New Issue