21b864390b
后端： 1. 粗排后分流与顺序守卫落地，支持“无明确微调偏好时粗排后直接收口”，并新增 allow_reorder / needs_refine_after_rough_build 语义，打通 chat→rough_build→execute/order_guard→deliver 路由。 2. execute 工具执行链路修复：清理乱码坏块与重复分支；新增 min_context_switch 未授权拦截；补齐 suggested 顺序基线初始化与顺序守卫联动。 3. 新增复合写工具 min_context_switch（减少上下文切换）并接入注册、参数解析、写工具白名单、提示词与文档；仅在用户明确允许打乱顺序时可用。 4. 工具口径升级：find_first_free 支持 day/day_start/day_end 范围参数并统一文案；移除 find_free 兼容别名；读写工具输出统一到“第N天(星期X)”格式。 5. prompt 同步升级：chat/execute/execute_context 增加粗排后是否继续微调、顺序授权、min_context_switch 使用边界与返回示例约束。 6. handoff 文档重命名并重写下班交接重点：下一步聚焦“工具收敛能力研究 + 运行态必要参数重置（不丢运行态）”。 7. 同步更新调试日志文件。 前端：无 仓库：无
340 lines
11 KiB
Go
340 lines
11 KiB
Go
package newagentnode
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import (
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"context"
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"fmt"
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"log"
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"strconv"
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"strings"
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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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)
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const (
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roughBuildStageName = "rough_build"
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roughBuildStatusBlock = "rough_build.status"
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roughBuildSampleLimit = 3
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)
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type roughBuildApplyStats struct {
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AppliedCount int
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DayMappingMissCount int
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TaskItemMatchMissCount int
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DayMappingMissSamples []string
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TaskItemMatchMissSamples []string
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}
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// RunRoughBuildNode 执行粗排节点逻辑。
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//
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// 步骤说明：
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// 1. 推送"正在粗排"状态给前端；
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// 2. 从 CommonState 读取 TaskClassIDs，确认有需要排课的任务类；
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// 3. 加载 ScheduleState（含 DayMapping）；
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// 4. 调用 RoughBuildFunc 拿到粗排结果（[]RoughBuildPlacement）；
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// 5. 把粗排结果写入 ScheduleState，把已落位任务标记为 suggested；
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// 6. 若粗排后仍存在真实 pending，则写入正式 abort 结果并结束本轮；
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// 7. 否则按“是否需要粗排后立即微调”分流：
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// - 无明确微调诉求：直接 Done -> Deliver；
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// - 有明确微调诉求：进入 Execute。
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func RunRoughBuildNode(ctx context.Context, st *newagentmodel.AgentGraphState) error {
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if st == nil {
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return fmt.Errorf("rough build node: state is nil")
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}
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flowState := st.EnsureFlowState()
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emitter := st.EnsureChunkEmitter()
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// 1. 推送状态：告知前端进入粗排环节。
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_ = emitter.EmitStatus(
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roughBuildStatusBlock,
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roughBuildStageName,
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"rough_building",
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"正在为你生成初始排课方案，请稍候。",
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true,
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)
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// 2. 校验依赖。
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if st.Deps.RoughBuildFunc == nil {
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return fmt.Errorf("rough build node: RoughBuildFunc 未注入")
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}
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// 3. 读取任务类 IDs。
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taskClassIDs := flowState.TaskClassIDs
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if len(taskClassIDs) == 0 {
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// 没有任务类 ID 时静默跳过粗排，直接进入执行阶段。
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flowState.Phase = newagentmodel.PhaseExecuting
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flowState.NeedsRoughBuild = false
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flowState.NeedsRefineAfterRoughBuild = false
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return nil
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}
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// 4. 加载 ScheduleState（含 DayMapping，用于坐标转换）。
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scheduleState, err := st.EnsureScheduleState(ctx)
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if err != nil {
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return fmt.Errorf("rough build node: 加载日程状态失败: %w", err)
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}
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if scheduleState == nil {
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return fmt.Errorf("rough build node: ScheduleState 为空，无法执行粗排")
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}
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// 5. 调用粗排算法。
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placements, err := st.Deps.RoughBuildFunc(ctx, flowState.UserID, taskClassIDs)
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if err != nil {
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return fmt.Errorf("rough build node: 粗排算法失败: %w", err)
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}
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// 6. 把粗排结果写入 ScheduleState。
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applyStats := applyRoughBuildPlacements(scheduleState, placements)
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// 7. 先校验粗排后是否仍有真实 pending。
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stillPending := countPendingTasks(scheduleState, taskClassIDs)
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log.Printf(
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"[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",
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taskClassIDs,
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len(placements),
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applyStats.AppliedCount,
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applyStats.DayMappingMissCount,
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applyStats.TaskItemMatchMissCount,
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stillPending,
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len(scheduleState.Tasks),
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len(scheduleState.Window.DayMapping),
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)
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if applyStats.DayMappingMissCount > 0 {
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log.Printf(
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"[DEBUG] rough_build day_mapping_miss_samples=%v window=%s",
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applyStats.DayMappingMissSamples,
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summarizeRoughBuildWindow(scheduleState),
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)
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}
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if applyStats.TaskItemMatchMissCount > 0 {
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log.Printf(
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"[DEBUG] rough_build task_item_match_miss_samples=%v scoped_task_samples=%v",
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applyStats.TaskItemMatchMissSamples,
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collectScopedTaskSamples(scheduleState, taskClassIDs),
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)
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}
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if stillPending > 0 {
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failureMessage := fmt.Sprintf(
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"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。",
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stillPending,
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)
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_ = emitter.EmitStatus(
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roughBuildStatusBlock,
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roughBuildStageName,
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"rough_build_failed",
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failureMessage,
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true,
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)
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flowState.NeedsRoughBuild = false
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flowState.Abort(
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roughBuildStageName,
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"rough_build_pending_remaining",
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failureMessage,
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fmt.Sprintf("rough build finished with %d real pending tasks remaining", stillPending),
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)
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return nil
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}
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// 8. 计算是否需要“粗排后立即微调”。
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//
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// 1. 只在“无计划直执行”链路下应用该止血分流；
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// 2. 有计划链路依旧进入 execute，避免改变既有 plan->execute 语义；
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// 3. chat 路由明确标记 needs_refine_after_rough_build=true 时才进微调。
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shouldRefineAfterRoughBuild := flowState.HasPlan() || flowState.NeedsRefineAfterRoughBuild
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// 9. 推送完成状态（区分“继续微调”与“直接收口”两种路径）。
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doneStatus := "rough_build_done"
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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))
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if !shouldRefineAfterRoughBuild {
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doneStatus = "rough_build_done_no_refine"
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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))
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}
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_ = emitter.EmitStatus(
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roughBuildStatusBlock,
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roughBuildStageName,
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doneStatus,
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doneMessage,
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false,
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)
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// 10. 把粗排完成信息写入 pinned context，让后续节点能拿到一致事实。
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// 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。
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idParts := make([]string, len(taskClassIDs))
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for i, id := range taskClassIDs {
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idParts[i] = strconv.Itoa(id)
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}
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idStr := strings.Join(idParts, ", ")
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pinnedContent := fmt.Sprintf(
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"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"+
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"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"+
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"本轮不需要再调用 place，也无需再次触发粗排。",
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idStr, len(placements),
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)
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if shouldRefineAfterRoughBuild {
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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。"
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} else {
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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。"
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}
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st.EnsureConversationContext().UpsertPinnedBlock(newagentmodel.ContextBlock{
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Key: "rough_build_done",
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Title: "粗排已完成",
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Content: pinnedContent,
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})
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// 11. 清除粗排标记，并按分流结果进入执行或直接收口。
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//
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// 1. 无明确微调诉求：直接标记 completed，graph 会路由到 deliver；
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// 2. 有明确微调诉求：进入 execute 节点继续工具微调；
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// 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。
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flowState.NeedsRoughBuild = false
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flowState.NeedsRefineAfterRoughBuild = false
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if !shouldRefineAfterRoughBuild {
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flowState.Done()
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return nil
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}
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flowState.Phase = newagentmodel.PhaseExecuting
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return nil
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}
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// countPendingTasks 统计粗排后仍无位置的待安排任务数。
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//
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// 说明：
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// 1. 第一轮修复后，粗排成功会把任务直接标记为 suggested；
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// 2. 为兼容旧快照，仍按“pending 且 Slots 为空”认定真正未覆盖；
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// 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。
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func countPendingTasks(state *newagenttools.ScheduleState, taskClassIDs []int) int {
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if state == nil {
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return 0
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}
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count := 0
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for i := range state.Tasks {
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task := state.Tasks[i]
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if !newagenttools.IsPendingTask(task) {
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continue
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}
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if len(taskClassIDs) > 0 && !newagenttools.IsTaskInRequestedClassScope(task, taskClassIDs) {
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continue
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}
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if newagenttools.IsPendingTask(task) {
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count++
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}
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}
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return count
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}
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// applyRoughBuildPlacements 把粗排结果写入 ScheduleState 对应任务的 Slots。
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//
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// 设计说明：
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// 1. 通过 task_item_id（SourceID）定位任务；
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// 2. 用 DayMapping 把 (week, dayOfWeek) 转为 day_index；
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// 3. 对成功落位的任务写入 Slots，并显式标记为 suggested；
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// 4. suggested 表示“粗排建议位”，后续可用 move/swap/unplace 微调；
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// 5. 转换失败的条目静默跳过，不中断整体流程。
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func applyRoughBuildPlacements(
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state *newagenttools.ScheduleState,
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placements []newagentmodel.RoughBuildPlacement,
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) roughBuildApplyStats {
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stats := roughBuildApplyStats{}
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if state == nil {
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return stats
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}
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taskIndexByItemID := make(map[int][]int)
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for i := range state.Tasks {
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task := state.Tasks[i]
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if task.Source != "task_item" {
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continue
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}
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taskIndexByItemID[task.SourceID] = append(taskIndexByItemID[task.SourceID], i)
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}
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for _, p := range placements {
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day, ok := state.WeekDayToDay(p.Week, p.DayOfWeek)
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if !ok {
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stats.DayMappingMissCount++
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stats.DayMappingMissSamples = appendPlacementSample(stats.DayMappingMissSamples, p)
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continue // DayMapping 里没有对应 day，跳过
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}
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matched := false
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for _, index := range taskIndexByItemID[p.TaskItemID] {
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t := &state.Tasks[index]
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t.Slots = []newagenttools.TaskSlot{
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{Day: day, SlotStart: p.SectionFrom, SlotEnd: p.SectionTo},
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}
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t.Status = newagenttools.TaskStatusSuggested
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stats.AppliedCount++
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matched = true
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break
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}
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if !matched {
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stats.TaskItemMatchMissCount++
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stats.TaskItemMatchMissSamples = appendPlacementSample(stats.TaskItemMatchMissSamples, p)
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}
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}
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return stats
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}
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// appendPlacementSample 记录有限数量的 miss 样本，避免 debug 日志爆量。
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func appendPlacementSample(samples []string, placement newagentmodel.RoughBuildPlacement) []string {
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if len(samples) >= roughBuildSampleLimit {
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return samples
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}
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return append(samples, fmt.Sprintf(
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"task_item_id=%d week=%d day=%d sections=%d-%d",
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placement.TaskItemID,
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placement.Week,
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placement.DayOfWeek,
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placement.SectionFrom,
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placement.SectionTo,
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))
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}
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// summarizeRoughBuildWindow 提供 DayMapping 的紧凑摘要，便于判断窗口是否退化到错误周。
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func summarizeRoughBuildWindow(state *newagenttools.ScheduleState) string {
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if state == nil || len(state.Window.DayMapping) == 0 {
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return "empty"
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}
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first := state.Window.DayMapping[0]
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last := state.Window.DayMapping[len(state.Window.DayMapping)-1]
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return fmt.Sprintf(
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"days=%d first=W%dD%d last=W%dD%d",
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len(state.Window.DayMapping),
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first.Week,
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first.DayOfWeek,
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last.Week,
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last.DayOfWeek,
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)
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}
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// 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。
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func collectScopedTaskSamples(state *newagenttools.ScheduleState, taskClassIDs []int) []string {
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if state == nil {
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return nil
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}
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samples := make([]string, 0, roughBuildSampleLimit)
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for i := range state.Tasks {
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task := state.Tasks[i]
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if task.Source != "task_item" {
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continue
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}
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if len(taskClassIDs) > 0 && !newagenttools.IsTaskInRequestedClassScope(task, taskClassIDs) {
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continue
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}
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samples = append(samples, fmt.Sprintf(
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"source_id=%d task_class_id=%d status=%s name=%q",
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task.SourceID,
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task.TaskClassID,
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task.Status,
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task.Name,
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))
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if len(samples) >= roughBuildSampleLimit {
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break
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}
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}
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return samples
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}
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