66c06eed0a
后端： 1. execute 主链路重构为“上下文工具域 + 主动优化候选闭环”——移除 order_guard，粗排后默认进入主动微调，先诊断再从后端候选中选择 move/swap，避免 LLM 自由全局乱搜 2. 工具体系升级为动态注入协议——新增 context_tools_add / remove、工具域与二级包映射、主动优化白名单；schedule / taskclass / web 工具按域按包暴露，msg0 规则包与 execute 上下文同步重写 3. analyze_health 升级为主动优化唯一裁判入口——补齐 rhythm / tightness / profile / feasibility 指标、候选扫描与复诊打分、停滞信号、forced imperfection 判定，并把连续优化状态写回运行态 4. 任务类能力并入新 Agent 执行链——新增 upsert_task_class 写工具与启动注入事务写入；任务类模型补充学科画像与整天屏蔽配置，粗排支持 excluded_days_of_week，steady 策略改为基于目标位置/单日负载/分散度/缓冲的候选打分 5. 运行态与路由补齐优化模式语义——新增 active tool domain/packs、pending context hook、active optimize only、taskclass 写入回盘快照；区分 first_full / global_reopt / local_adjust，并完善首次粗排后默认 refine 的判定 前端： 6. 助手时间线渲染细化——推理内容改为独立 reasoning block，支持与工具/状态/正文按时序交错展示，自动收口折叠，修正 confirm reject 恢复动作 仓库： 7. newAgent 文档整体迁入 docs/backend，补充主动优化执行规划与顺序约束拆解文档，删除旧调试日志文件 PS:这次科研了2天，总算是有些进展了——LLM永远只适合做选择题、判断题，不适合做开放创新题。
355 lines
13 KiB
Go
355 lines
13 KiB
Go
package cmd
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import (
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"context"
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"fmt"
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"log"
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"os"
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"strings"
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"time"
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"github.com/LoveLosita/smartflow/backend/api"
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"github.com/LoveLosita/smartflow/backend/dao"
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kafkabus "github.com/LoveLosita/smartflow/backend/infra/kafka"
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infrallm "github.com/LoveLosita/smartflow/backend/infra/llm"
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outboxinfra "github.com/LoveLosita/smartflow/backend/infra/outbox"
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infrarag "github.com/LoveLosita/smartflow/backend/infra/rag"
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ragconfig "github.com/LoveLosita/smartflow/backend/infra/rag/config"
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"github.com/LoveLosita/smartflow/backend/inits"
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"github.com/LoveLosita/smartflow/backend/memory"
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memoryobserve "github.com/LoveLosita/smartflow/backend/memory/observe"
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"github.com/LoveLosita/smartflow/backend/middleware"
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"github.com/LoveLosita/smartflow/backend/model"
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newagentconv "github.com/LoveLosita/smartflow/backend/newAgent/conv"
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newagentmodel "github.com/LoveLosita/smartflow/backend/newAgent/model"
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newagenttools "github.com/LoveLosita/smartflow/backend/newAgent/tools"
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"github.com/LoveLosita/smartflow/backend/newAgent/tools/web"
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"github.com/LoveLosita/smartflow/backend/pkg"
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"github.com/LoveLosita/smartflow/backend/routers"
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"github.com/LoveLosita/smartflow/backend/service"
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eventsvc "github.com/LoveLosita/smartflow/backend/service/events"
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"github.com/spf13/viper"
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)
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// loadConfig 加载应用配置。
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func loadConfig() error {
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viper.SetConfigName("config")
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viper.SetConfigType("yaml")
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viper.AddConfigPath(".")
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if err := viper.ReadInConfig(); err != nil {
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return fmt.Errorf("failed to read config file: %w", err)
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}
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log.Println("Config loaded successfully")
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return nil
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}
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// Start 是应用启动入口。
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func Start() {
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if err := loadConfig(); err != nil {
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log.Fatalf("Failed to load config: %v", err)
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}
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db, err := inits.ConnectDB()
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if err != nil {
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log.Fatalf("Failed to connect to database: %v", err)
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}
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rdb := inits.InitRedis()
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limiter := pkg.NewRateLimiter(rdb)
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aiHub, err := inits.InitEino()
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if err != nil {
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log.Fatalf("Failed to initialize Eino: %v", err)
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}
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ragCfg := ragconfig.LoadFromViper()
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var ragRuntime infrarag.Runtime
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if ragCfg.Enabled {
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// 1. 当前项目尚未完成全局观测平台建设，这里先注入一层轻量 Observer；
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// 2. RAG 内部只依赖 Observer 接口，后续若全项目统一日志/指标系统，只需替换这里；
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// 3. 这样可以避免 RAG 单独自建一套割裂的日志基础设施。
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ragLogger := log.Default()
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ragRuntime, err = infrarag.NewRuntimeFromConfig(context.Background(), ragCfg, infrarag.FactoryDeps{
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Logger: ragLogger,
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Observer: infrarag.NewLoggerObserver(ragLogger),
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})
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if err != nil {
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log.Fatalf("Failed to initialize RAG runtime: %v", err)
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}
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log.Printf("RAG runtime initialized: store=%s embed=%s reranker=%s", ragCfg.Store, ragCfg.EmbedProvider, ragCfg.RerankerProvider)
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} else {
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log.Println("RAG runtime is disabled")
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}
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// 1. memory 模块对启动层只暴露一个门面。
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// 2. 后续若接入统一 DI 容器，也优先注入这个门面，而不是继续暴露内部 repo/service。
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memoryCfg := memory.LoadConfigFromViper()
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memoryObserver := memoryobserve.NewLoggerObserver(log.Default())
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memoryMetrics := memoryobserve.NewMetricsRegistry()
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memoryModule := memory.NewModuleWithObserve(
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db,
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infrallm.WrapArkClient(aiHub.Pro),
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ragRuntime,
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memoryCfg,
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memory.ObserveDeps{
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Observer: memoryObserver,
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Metrics: memoryMetrics,
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},
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)
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// DAO 层初始化。
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cacheRepo := dao.NewCacheDAO(rdb)
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agentCacheRepo := dao.NewAgentCache(rdb)
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_ = db.Use(middleware.NewGormCachePlugin(cacheRepo))
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userRepo := dao.NewUserDAO(db)
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taskRepo := dao.NewTaskDAO(db)
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courseRepo := dao.NewCourseDAO(db)
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taskClassRepo := dao.NewTaskClassDAO(db)
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scheduleRepo := dao.NewScheduleDAO(db)
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manager := dao.NewManager(db)
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agentRepo := dao.NewAgentDAO(db)
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outboxRepo := outboxinfra.NewRepository(db)
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// outbox 通用事件总线接线（第二阶段）：
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// 1. 读取 Kafka 配置；
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// 2. 创建 infra 级 EventBus；
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// 3. 显式注册业务事件处理器；
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// 4. 启动总线后台 dispatch/consume 循环。
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kafkaCfg := kafkabus.LoadConfig()
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eventBus, err := outboxinfra.NewEventBus(outboxRepo, kafkaCfg)
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if err != nil {
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log.Fatalf("Failed to initialize outbox event bus: %v", err)
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}
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if eventBus != nil {
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// 1. 在启动前完成业务事件处理器注册。
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// 2. memory 事件处理器也统一通过 memoryModule 接入，避免启动层感知内部细节。
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if err = eventsvc.RegisterChatHistoryPersistHandler(eventBus, outboxRepo, manager); err != nil {
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log.Fatalf("Failed to register chat history event handler: %v", err)
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}
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if err = eventsvc.RegisterTaskUrgencyPromoteHandler(eventBus, outboxRepo, manager); err != nil {
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log.Fatalf("Failed to register task urgency promote event handler: %v", err)
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}
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if err = eventsvc.RegisterChatTokenUsageAdjustHandler(eventBus, outboxRepo, manager); err != nil {
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log.Fatalf("Failed to register chat token usage adjust event handler: %v", err)
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}
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if err = eventsvc.RegisterAgentStateSnapshotHandler(eventBus, outboxRepo, manager); err != nil {
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log.Fatalf("Failed to register agent state snapshot event handler: %v", err)
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}
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if err = eventsvc.RegisterMemoryExtractRequestedHandler(eventBus, outboxRepo, memoryModule); err != nil {
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log.Fatalf("Failed to register memory extract event handler: %v", err)
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}
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eventBus.Start(context.Background())
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defer eventBus.Close()
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log.Println("Outbox event bus started")
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} else {
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log.Println("Outbox event bus is disabled")
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}
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memoryModule.StartWorker(context.Background())
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// Service 层初始化。
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userService := service.NewUserService(userRepo, cacheRepo)
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taskSv := service.NewTaskService(taskRepo, cacheRepo, eventBus)
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courseImageResponsesClient := infrallm.NewArkResponsesClient(
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os.Getenv("ARK_API_KEY"),
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viper.GetString("agent.baseURL"),
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viper.GetString("courseImport.visionModel"),
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)
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courseService := service.NewCourseService(
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courseRepo,
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scheduleRepo,
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courseImageResponsesClient,
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service.NewCourseImageParseConfig(
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viper.GetInt64("courseImport.maxImageBytes"),
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viper.GetInt("courseImport.maxTokens"),
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),
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viper.GetString("courseImport.visionModel"),
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)
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taskClassService := service.NewTaskClassService(taskClassRepo, cacheRepo, scheduleRepo, manager)
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scheduleService := service.NewScheduleService(scheduleRepo, userRepo, taskClassRepo, manager, cacheRepo)
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agentService := service.NewAgentServiceWithSchedule(aiHub, agentRepo, taskRepo, cacheRepo, agentCacheRepo, eventBus, scheduleService, taskSv)
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// newAgent 依赖接线。
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agentService.SetAgentStateStore(dao.NewAgentStateStoreAdapter(cacheRepo))
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// 1. WebSearch provider 初始化：根据配置选择 mock/bocha；
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// 2. provider 为 nil 时，web_search / web_fetch 返回"暂未启用"，不阻断主流程。
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var webSearchProvider web.SearchProvider
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webProvider := viper.GetString("websearch.provider")
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switch webProvider {
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case "bocha":
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bochaKey := viper.GetString("websearch.apiKey")
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if bochaKey == "" {
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log.Println("WebSearch: 博查 API Key 为空，降级为 mock")
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webSearchProvider = &web.MockProvider{}
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} else {
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webSearchProvider = web.NewBochaProvider(bochaKey, "")
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log.Println("WebSearch provider: bocha")
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}
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case "mock", "":
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webSearchProvider = &web.MockProvider{}
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log.Println("WebSearch provider: mock（模拟模式）")
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default:
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// 未识别的 provider 类型降级为 mock 并输出警告。
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log.Printf("WebSearch provider %q 未识别，降级为 mock", webProvider)
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webSearchProvider = &web.MockProvider{}
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}
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agentService.SetToolRegistry(newagenttools.NewDefaultRegistryWithDeps(newagenttools.DefaultRegistryDeps{
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RAGRuntime: ragRuntime,
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WebSearchProvider: webSearchProvider,
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TaskClassWriteDeps: newagenttools.TaskClassWriteDeps{
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UpsertTaskClass: func(userID int, input newagenttools.TaskClassUpsertInput) (newagenttools.TaskClassUpsertPersistResult, error) {
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req := input.Request
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taskClassID := 0
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created := input.ID == 0
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err := taskClassRepo.Transaction(func(txDAO *dao.TaskClassDAO) error {
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// 1. 先构造任务类主体，保持与现有 AddOrUpdateTaskClass 口径一致。
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taskClass := &model.TaskClass{
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ID: input.ID,
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Name: &req.Name,
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Mode: &req.Mode,
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SubjectType: stringPtrOrNil(req.SubjectType),
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DifficultyLevel: stringPtrOrNil(req.DifficultyLevel),
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CognitiveIntensity: stringPtrOrNil(req.CognitiveIntensity),
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TotalSlots: &req.Config.TotalSlots,
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Strategy: &req.Config.Strategy,
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ExcludedSlots: req.Config.ExcludedSlots,
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ExcludedDaysOfWeek: req.Config.ExcludedDaysOfWeek,
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}
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taskClass.AllowFillerCourse = &req.Config.AllowFillerCourse
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// 2. 自动模式下写入日期范围；手动模式允许为空。
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if req.StartDate != "" {
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startDate, parseErr := time.ParseInLocation("2006-01-02", req.StartDate, time.Local)
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if parseErr != nil {
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return parseErr
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}
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taskClass.StartDate = &startDate
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}
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if req.EndDate != "" {
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endDate, parseErr := time.ParseInLocation("2006-01-02", req.EndDate, time.Local)
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if parseErr != nil {
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return parseErr
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}
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taskClass.EndDate = &endDate
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}
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// 3. upsert 主体后拿到稳定 task_class_id，供 items 绑定 category_id。
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updatedID, upsertErr := txDAO.AddOrUpdateTaskClass(userID, taskClass)
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if upsertErr != nil {
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return upsertErr
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}
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taskClassID = updatedID
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// 4. 构造任务块并批量 upsert。
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items := make([]model.TaskClassItem, 0, len(req.Items))
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for _, itemReq := range req.Items {
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categoryID := taskClassID
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order := itemReq.Order
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content := itemReq.Content
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status := model.TaskItemStatusUnscheduled
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items = append(items, model.TaskClassItem{
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ID: itemReq.ID,
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CategoryID: &categoryID,
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Order: &order,
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Content: &content,
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EmbeddedTime: itemReq.EmbeddedTime,
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Status: &status,
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})
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}
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return txDAO.AddOrUpdateTaskClassItems(userID, items)
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})
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if err != nil {
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return newagenttools.TaskClassUpsertPersistResult{}, err
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}
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return newagenttools.TaskClassUpsertPersistResult{
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TaskClassID: taskClassID,
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Created: created,
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}, nil
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},
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},
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}))
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agentService.SetScheduleProvider(newagentconv.NewScheduleProvider(scheduleRepo, taskClassRepo))
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agentService.SetCompactionStore(agentRepo)
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agentService.SetQuickTaskDeps(newagentmodel.QuickTaskDeps{
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CreateTask: func(userID int, title string, priorityGroup int, deadlineAt *time.Time, urgencyThresholdAt *time.Time) (int, error) {
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created, err := taskRepo.AddTask(&model.Task{
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UserID: userID,
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Title: title,
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Priority: priorityGroup,
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IsCompleted: false,
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DeadlineAt: deadlineAt,
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UrgencyThresholdAt: urgencyThresholdAt,
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})
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if err != nil {
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return 0, err
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}
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return created.ID, nil
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},
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QueryTasks: func(ctx context.Context, userID int, params newagenttools.TaskQueryParams) ([]newagenttools.TaskQueryResult, error) {
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req := newagentmodel.TaskQueryRequest{
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UserID: userID,
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Quadrant: params.Quadrant,
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SortBy: params.SortBy,
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Order: params.Order,
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Limit: params.Limit,
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IncludeCompleted: params.IncludeCompleted,
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Keyword: params.Keyword,
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DeadlineBefore: params.DeadlineBefore,
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DeadlineAfter: params.DeadlineAfter,
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}
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records, err := agentService.QueryTasksForTool(ctx, req)
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if err != nil {
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return nil, err
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}
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results := make([]newagenttools.TaskQueryResult, 0, len(records))
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for _, r := range records {
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deadlineStr := ""
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if r.DeadlineAt != nil {
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deadlineStr = r.DeadlineAt.In(time.Local).Format("2006-01-02 15:04")
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}
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results = append(results, newagenttools.TaskQueryResult{
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ID: r.ID,
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Title: r.Title,
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PriorityGroup: r.PriorityGroup,
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IsCompleted: r.IsCompleted,
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DeadlineAt: deadlineStr,
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})
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}
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return results, nil
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},
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})
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agentService.SetMemoryReader(memoryModule, memoryCfg)
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// API 层初始化。
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userApi := api.NewUserHandler(userService)
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taskApi := api.NewTaskHandler(taskSv)
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courseApi := api.NewCourseHandler(courseService)
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taskClassApi := api.NewTaskClassHandler(taskClassService)
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scheduleApi := api.NewScheduleAPI(scheduleService)
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agentApi := api.NewAgentHandler(agentService)
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memoryApi := api.NewMemoryHandler(memoryModule)
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handlers := &api.ApiHandlers{
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UserHandler: userApi,
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TaskHandler: taskApi,
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TaskClassHandler: taskClassApi,
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CourseHandler: courseApi,
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ScheduleHandler: scheduleApi,
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AgentHandler: agentApi,
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MemoryHandler: memoryApi,
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}
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r := routers.RegisterRouters(handlers, cacheRepo, userRepo, limiter)
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routers.StartEngine(r)
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}
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func stringPtrOrNil(value string) *string {
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trimmed := strings.TrimSpace(value)
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if trimmed == "" {
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return nil
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}
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return &trimmed
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}
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