package newagentnode import ( "context" "fmt" "log" "strconv" "strings" newagentmodel "github.com/LoveLosita/smartflow/backend/newAgent/model" "github.com/LoveLosita/smartflow/backend/newAgent/tools/schedule" ) const ( roughBuildStageName = "rough_build" roughBuildStatusBlock = "rough_build.status" roughBuildSampleLimit = 3 ) type roughBuildApplyStats struct { AppliedCount int DayMappingMissCount int TaskItemMatchMissCount int DayMappingMissSamples []string TaskItemMatchMissSamples []string } // RunRoughBuildNode 执行粗排节点逻辑。 // // 步骤说明: // 1. 推送"正在粗排"状态给前端; // 2. 从 CommonState 读取 TaskClassIDs,确认有需要排课的任务类; // 3. 加载 ScheduleState(含 DayMapping); // 4. 调用 RoughBuildFunc 拿到粗排结果([]RoughBuildPlacement); // 5. 把粗排结果写入 ScheduleState,把已落位任务标记为 suggested; // 6. 若粗排后仍存在真实 pending,则写入正式 abort 结果并结束本轮; // 7. 否则按“是否需要粗排后立即微调”分流: // - 无明确微调诉求:直接 Done -> Deliver; // - 有明确微调诉求:进入 Execute。 func RunRoughBuildNode(ctx context.Context, st *newagentmodel.AgentGraphState) error { if st == nil { return fmt.Errorf("rough build node: state is nil") } flowState := st.EnsureFlowState() emitter := st.EnsureChunkEmitter() // 1. 推送状态:告知前端进入粗排环节。 _ = emitter.EmitStatus( roughBuildStatusBlock, roughBuildStageName, "rough_building", "正在为你生成初始排课方案,请稍候。", true, ) // 2. 校验依赖。 if st.Deps.RoughBuildFunc == nil { return fmt.Errorf("rough build node: RoughBuildFunc 未注入") } // 3. 读取任务类 IDs。 taskClassIDs := flowState.TaskClassIDs if len(taskClassIDs) == 0 { // 没有任务类 ID 时静默跳过粗排,直接进入执行阶段。 flowState.Phase = newagentmodel.PhaseExecuting flowState.NeedsRoughBuild = false flowState.NeedsRefineAfterRoughBuild = false return nil } // 4. 加载 ScheduleState(含 DayMapping,用于坐标转换)。 scheduleState, err := st.EnsureScheduleState(ctx) if err != nil { return fmt.Errorf("rough build node: 加载日程状态失败: %w", err) } if scheduleState == nil { return fmt.Errorf("rough build node: ScheduleState 为空,无法执行粗排") } // 5. 调用粗排算法。 placements, err := st.Deps.RoughBuildFunc(ctx, flowState.UserID, taskClassIDs) if err != nil { return fmt.Errorf("rough build node: 粗排算法失败: %w", err) } // 6. 把粗排结果写入 ScheduleState。 applyStats := applyRoughBuildPlacements(scheduleState, placements) // 7. 先校验粗排后是否仍有真实 pending。 stillPending := countPendingTasks(scheduleState, taskClassIDs) log.Printf( "[DEBUG] rough_build scope_task_classes=%v placements=%d applied=%d day_mapping_miss=%d task_item_match_miss=%d pending_in_scope=%d total_tasks=%d window_days=%d", taskClassIDs, len(placements), applyStats.AppliedCount, applyStats.DayMappingMissCount, applyStats.TaskItemMatchMissCount, stillPending, len(scheduleState.Tasks), len(scheduleState.Window.DayMapping), ) if applyStats.DayMappingMissCount > 0 { log.Printf( "[DEBUG] rough_build day_mapping_miss_samples=%v window=%s", applyStats.DayMappingMissSamples, summarizeRoughBuildWindow(scheduleState), ) } if applyStats.TaskItemMatchMissCount > 0 { log.Printf( "[DEBUG] rough_build task_item_match_miss_samples=%v scoped_task_samples=%v", applyStats.TaskItemMatchMissSamples, collectScopedTaskSamples(scheduleState, taskClassIDs), ) } if stillPending > 0 { failureMessage := fmt.Sprintf( "初始排课方案构建异常:粗排后仍有 %d 个任务未获得初始落位。按当前规则,本轮不进入微调,请检查粗排算法或任务数据。", stillPending, ) _ = emitter.EmitStatus( roughBuildStatusBlock, roughBuildStageName, "rough_build_failed", failureMessage, true, ) flowState.NeedsRoughBuild = false flowState.Abort( roughBuildStageName, "rough_build_pending_remaining", failureMessage, fmt.Sprintf("rough build finished with %d real pending tasks remaining", stillPending), ) return nil } // 8. 计算是否需要“粗排后立即微调”。 // // 1. 只在“无计划直执行”链路下应用该止血分流; // 2. 有计划链路依旧进入 execute,避免改变既有 plan->execute 语义; // 3. chat 路由明确标记 needs_refine_after_rough_build=true 时才进微调。 shouldRefineAfterRoughBuild := flowState.HasPlan() || flowState.NeedsRefineAfterRoughBuild // 9. 推送完成状态(区分“继续微调”与“直接收口”两种路径)。 doneStatus := "rough_build_done" doneMessage := fmt.Sprintf("初始排课方案已生成,共 %d 个任务已预排,进入微调阶段。", len(placements)) if !shouldRefineAfterRoughBuild { doneStatus = "rough_build_done_no_refine" doneMessage = fmt.Sprintf("初始排课方案已生成,共 %d 个任务已预排。本轮按默认策略先结束;如需优化,请继续告诉我你的偏好。", len(placements)) } _ = emitter.EmitStatus( roughBuildStatusBlock, roughBuildStageName, doneStatus, doneMessage, false, ) // 10. 把粗排完成信息写入 pinned context,让后续节点能拿到一致事实。 // 构造任务类 ID 字符串,供 pinned block 明确标注,避免 Execute LLM 因找不到 task_class_id 来源而 ask_user。 idParts := make([]string, len(taskClassIDs)) for i, id := range taskClassIDs { idParts[i] = strconv.Itoa(id) } idStr := strings.Join(idParts, ", ") pinnedContent := fmt.Sprintf( "后端已自动运行粗排算法(任务类 ID:[%s]),初始排课方案已写入日程状态(共 %d 个任务已预排)。\n"+ "这些预排任务已标记为 suggested,表示“可继续优化的建议落位”,不是待补排任务。\n"+ "本轮不需要再调用 place,也无需再次触发粗排。", idStr, len(placements), ) if shouldRefineAfterRoughBuild { pinnedContent += "\n请先调用 get_overview 查看整体分布,再使用 move / swap / unplace 微调不合理的位置。" } else { pinnedContent += "\n当前未收到明确微调偏好,流程将先收口;如需进一步优化,请基于本次结果提出调整要求。" } st.EnsureConversationContext().UpsertPinnedBlock(newagentmodel.ContextBlock{ Key: "rough_build_done", Title: "粗排已完成", Content: pinnedContent, }) // 11. 清除粗排标记,并按分流结果进入执行或直接收口。 // // 1. 无明确微调诉求:直接标记 completed,graph 会路由到 deliver; // 2. 有明确微调诉求:进入 execute 节点继续工具微调; // 3. 无论哪条路径,都要重置粗排相关标记,避免污染后续轮次。 flowState.NeedsRoughBuild = false flowState.NeedsRefineAfterRoughBuild = false if !shouldRefineAfterRoughBuild { flowState.Done() return nil } flowState.Phase = newagentmodel.PhaseExecuting return nil } // countPendingTasks 统计粗排后仍无位置的待安排任务数。 // // 说明: // 1. 第一轮修复后,粗排成功会把任务直接标记为 suggested; // 2. 为兼容旧快照,仍按“pending 且 Slots 为空”认定真正未覆盖; // 3. 只要这里仍大于 0,就应视为粗排异常,而不是交给 LLM 补排。 func countPendingTasks(state *schedule.ScheduleState, taskClassIDs []int) int { if state == nil { return 0 } count := 0 for i := range state.Tasks { task := state.Tasks[i] if !schedule.IsPendingTask(task) { continue } if len(taskClassIDs) > 0 && !schedule.IsTaskInRequestedClassScope(task, taskClassIDs) { continue } if schedule.IsPendingTask(task) { count++ } } return count } // applyRoughBuildPlacements 把粗排结果写入 ScheduleState 对应任务的 Slots。 // // 设计说明: // 1. 通过 task_item_id(SourceID)定位任务; // 2. 用 DayMapping 把 (week, dayOfWeek) 转为 day_index; // 3. 对成功落位的任务写入 Slots,并显式标记为 suggested; // 4. suggested 表示“粗排建议位”,后续可用 move/swap/unplace 微调; // 5. 转换失败的条目静默跳过,不中断整体流程。 func applyRoughBuildPlacements( state *schedule.ScheduleState, placements []newagentmodel.RoughBuildPlacement, ) roughBuildApplyStats { stats := roughBuildApplyStats{} if state == nil { return stats } taskIndexByItemID := make(map[int][]int) for i := range state.Tasks { task := state.Tasks[i] if task.Source != "task_item" { continue } taskIndexByItemID[task.SourceID] = append(taskIndexByItemID[task.SourceID], i) } for _, p := range placements { day, ok := state.WeekDayToDay(p.Week, p.DayOfWeek) if !ok { stats.DayMappingMissCount++ stats.DayMappingMissSamples = appendPlacementSample(stats.DayMappingMissSamples, p) continue // DayMapping 里没有对应 day,跳过 } matched := false for _, index := range taskIndexByItemID[p.TaskItemID] { t := &state.Tasks[index] t.Slots = []schedule.TaskSlot{ {Day: day, SlotStart: p.SectionFrom, SlotEnd: p.SectionTo}, } t.Status = schedule.TaskStatusSuggested stats.AppliedCount++ matched = true break } if !matched { stats.TaskItemMatchMissCount++ stats.TaskItemMatchMissSamples = appendPlacementSample(stats.TaskItemMatchMissSamples, p) } } return stats } // appendPlacementSample 记录有限数量的 miss 样本,避免 debug 日志爆量。 func appendPlacementSample(samples []string, placement newagentmodel.RoughBuildPlacement) []string { if len(samples) >= roughBuildSampleLimit { return samples } return append(samples, fmt.Sprintf( "task_item_id=%d week=%d day=%d sections=%d-%d", placement.TaskItemID, placement.Week, placement.DayOfWeek, placement.SectionFrom, placement.SectionTo, )) } // summarizeRoughBuildWindow 提供 DayMapping 的紧凑摘要,便于判断窗口是否退化到错误周。 func summarizeRoughBuildWindow(state *schedule.ScheduleState) string { if state == nil || len(state.Window.DayMapping) == 0 { return "empty" } first := state.Window.DayMapping[0] last := state.Window.DayMapping[len(state.Window.DayMapping)-1] return fmt.Sprintf( "days=%d first=W%dD%d last=W%dD%d", len(state.Window.DayMapping), first.Week, first.DayOfWeek, last.Week, last.DayOfWeek, ) } // collectScopedTaskSamples 提供当前 state 中可用于匹配的 task_item 样本,便于排查 ID 对不上。 func collectScopedTaskSamples(state *schedule.ScheduleState, taskClassIDs []int) []string { if state == nil { return nil } samples := make([]string, 0, roughBuildSampleLimit) for i := range state.Tasks { task := state.Tasks[i] if task.Source != "task_item" { continue } if len(taskClassIDs) > 0 && !schedule.IsTaskInRequestedClassScope(task, taskClassIDs) { continue } samples = append(samples, fmt.Sprintf( "source_id=%d task_class_id=%d status=%s name=%q", task.SourceID, task.TaskClassID, task.Status, task.Name, )) if len(samples) >= roughBuildSampleLimit { break } } return samples }