后端: 1. chat 路由新增“二次粗排硬闸门”,避免粗排完成后的微调请求误触发再次 rough_build - 更新 node/chat.go:当上下文已存在 rough_build_done 且用户未明确要求“重新粗排/从头重排”时,强制关闭 needs_rough_build / needs_refine_after_rough_build;补充路由调试日志维度(needs_rough_build、allow_reorder、has_rough_build_done 等) - 更新 prompt/chat.go:补齐二次粗排强约束,明确“移动/微调/优化/均匀化/调顺序”默认走 refine,不再次触发 rough build 2. execute 历史分层与工具调用写回链路增强 - 更新 node/execute.go:next_plan 推进后写入 execute_step_advanced marker,供 prompt 按步骤边界归档 loop;新增统一 appendToolCallResultHistory,标准化 assistant tool_call + tool observation 配对写回 - 更新 node/execute.go:confirm accept 路径补齐 min_context_switch 顺序护栏,避免通过确认链路绕过“未授权打乱顺序”限制 - 更新 prompt/execute_context.go:ReAct 边界识别从 loop_closed 扩展到 loop_closed/step_advanced;执行态文案收敛为“existing 仅作事实参考不作为可移动目标”,并新增参数纪律提示 - 更新 service/agentsvc/agent_newagent.go:冷恢复重置时仅在 completed 场景补写 execute_loop_closed marker,保证下一轮上下文归档一致 3. 工具参数严格校验落地(禁止自造字段) - 新建 tools/arg_guard.go:新增 validateToolArgsStrict 白名单校验,未知字段直接报错(含 day_from/day_to -> day_start/day_end 提示) - 更新 tools/read_filter_tools.go:query_available_slots / query_target_tasks 接入参数白名单校验 - 更新 tools/compound_tools.go:spread_even 接入参数白名单校验 - 更新 prompt/execute.go:系统提示补齐“参数必须严格使用 schema 字段”强约束与非法别名示例 4. execute 范围护栏辅助能力预埋 - 更新 node/execute.go:新增步骤范围解析与日历参数解析辅助(周/天/周几提取、候选 day 估算、batch_move new_day 提取等),为后续步骤级范围拦截提供基础能力 5. 记忆模块方案文档升级(吸收 Mem0 机制) - 更新 memory/记忆模块实施计划.md:补充 Mem0 借鉴与取舍,新增 ADD/UPDATE/DELETE/NONE 决策状态机、UUID 映射防幻觉、JSON 容错链、threshold->reranker->fallback、三维隔离过滤与对应指标/测试项 6. 同步更新调试日志文件 - 更新 newAgent/Log.txt 前端:无 仓库:无
595 lines
19 KiB
Go
595 lines
19 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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"strings"
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"time"
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"github.com/cloudwego/eino/schema"
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newagentllm "github.com/LoveLosita/smartflow/backend/newAgent/llm"
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newagentmodel "github.com/LoveLosita/smartflow/backend/newAgent/model"
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newagentprompt "github.com/LoveLosita/smartflow/backend/newAgent/prompt"
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newagentstream "github.com/LoveLosita/smartflow/backend/newAgent/stream"
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)
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const (
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chatStageName = "chat"
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chatStatusBlockID = "chat.status"
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chatSpeakBlockID = "chat.speak"
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// chatHistoryKindKey 用于在 history 中打运行态标记,供 prompt 层做上下文分层。
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chatHistoryKindKey = "newagent_history_kind"
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// chatHistoryKindExecuteLoopClosed 表示“上一轮 execute loop 已正常收口”。
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// prompt 侧会据此把旧 loop 归档到 msg1,而不是继续占用 msg2 窗口。
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chatHistoryKindExecuteLoopClosed = "execute_loop_closed"
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)
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type reorderPreference int
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const (
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reorderUnknown reorderPreference = iota
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reorderAllow
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reorderDisallow
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)
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// ChatNodeInput 描述聊天节点单轮运行所需的最小依赖。
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//
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// 职责边界:
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// 1. 只承载"本轮 chat"需要的输入,不负责持久化;
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// 2. RuntimeState 提供 pending interaction 与流程状态;
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// 3. ConversationContext 提供历史对话;
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// 4. ConfirmAction 仅在 confirm 恢复场景下由前端传入 "accept" / "reject"。
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type ChatNodeInput struct {
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RuntimeState *newagentmodel.AgentRuntimeState
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ConversationContext *newagentmodel.ConversationContext
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UserInput string
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ConfirmAction string
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Client *newagentllm.Client
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ChunkEmitter *newagentstream.ChunkEmitter
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}
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// RunChatNode 执行一轮聊天节点逻辑。
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//
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// 核心职责:
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// 1. 恢复判定:有 pending interaction 则处理恢复;
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// 2. 路由分流:无 pending 时,调 LLM 判断复杂度并路由;
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// 3. direct_reply:简单任务,直接输出回复 → END;
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// 4. execute:中等任务,推 Execute ReAct;
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// 5. deep_answer:复杂问答,原地开 thinking 深度回答 → END;
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// 6. plan:复杂规划,推 Plan 节点。
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func RunChatNode(ctx context.Context, input ChatNodeInput) error {
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runtimeState, conversationContext, emitter, err := prepareChatNodeInput(input)
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if err != nil {
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return err
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}
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// 1. 有 pending interaction → 纯状态传递,处理恢复。
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if runtimeState.HasPendingInteraction() {
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return handleChatResume(input, runtimeState, emitter)
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}
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// 2. 无 pending → 路由决策(一次快速 LLM 调用,不开 thinking)。
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flowState := runtimeState.EnsureCommonState()
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if !runtimeState.HasPendingInteraction() && flowState.Phase == newagentmodel.PhaseDone {
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terminalBefore := flowState.TerminalStatus()
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roundBefore := flowState.RoundUsed
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// 1. 只有“正常完成(completed)”才打 loop 收口标记:
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// 1.1 这样下一轮进入 execute 时,msg2 会只保留“当前活跃循环”窗口;
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// 1.2 异常收口(exhausted/aborted)不打标记,允许后续“继续”时沿用上一轮 loop 轨迹。
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if terminalBefore == newagentmodel.FlowTerminalStatusCompleted {
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appendExecuteLoopClosedMarker(conversationContext)
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}
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flowState.ResetForNextRun()
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log.Printf(
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"[DEBUG] chat reset runtime for next run chat=%s round_before=%d terminal_before=%s",
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flowState.ConversationID,
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roundBefore,
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terminalBefore,
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)
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}
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messages := newagentprompt.BuildChatRoutingMessages(conversationContext, input.UserInput, flowState)
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decision, rawResult, err := newagentllm.GenerateJSON[newagentmodel.ChatRoutingDecision](
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ctx,
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input.Client,
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messages,
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newagentllm.GenerateOptions{
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Temperature: 0.1,
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MaxTokens: 500,
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Thinking: newagentllm.ThinkingModeDisabled,
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Metadata: map[string]any{
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"stage": chatStageName,
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"phase": "routing",
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},
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},
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)
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rawText := ""
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if rawResult != nil {
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rawText = strings.TrimSpace(rawResult.Text)
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}
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if err != nil {
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// 路由失败 → 保守:走 plan。
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log.Printf("[WARN] chat routing LLM failed chat=%s raw=%s err=%v",
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flowState.ConversationID, rawText, err)
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flowState.Phase = newagentmodel.PhasePlanning
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return nil
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}
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if validateErr := decision.Validate(); validateErr != nil {
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log.Printf("[WARN] chat routing decision invalid chat=%s raw=%s err=%v",
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flowState.ConversationID, rawText, validateErr)
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flowState.Phase = newagentmodel.PhasePlanning
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return nil
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}
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// 1. 二次粗排硬闸门:若上下文已存在 rough_build_done 且用户未明确要求“重新粗排”,
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// 则强制关闭 needs_rough_build,避免“微调请求被误判成再次粗排”。
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// 2. 该闸门只收紧粗排开关,不改路由 route,确保 execute 微调链路仍可继续。
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// 3. 一旦用户明确表达“从头重排/重新粗排”,仍允许 needs_rough_build=true 生效。
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if shouldDisableRoughBuildForRefine(conversationContext, input.UserInput, decision) {
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decision.NeedsRoughBuild = false
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decision.NeedsRefineAfterRoughBuild = false
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}
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log.Printf(
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"[DEBUG] chat routing chat=%s route=%s needs_rough_build=%v needs_refine_after_rough_build=%v allow_reorder=%v has_rough_build_done=%v task_class_count=%d reason=%s",
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flowState.ConversationID,
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decision.Route,
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decision.NeedsRoughBuild,
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decision.NeedsRefineAfterRoughBuild,
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decision.AllowReorder,
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hasRoughBuildDoneMarker(conversationContext),
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len(flowState.TaskClassIDs),
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decision.Reason,
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)
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flowState.AllowReorder = resolveAllowReorder(input.UserInput, decision.AllowReorder)
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// 3. 按路由决策推进。
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switch decision.Route {
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case newagentmodel.ChatRouteDirectReply:
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return handleDirectReply(ctx, decision, conversationContext, emitter, flowState)
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case newagentmodel.ChatRouteExecute:
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return handleRouteExecute(decision, emitter, flowState)
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case newagentmodel.ChatRouteDeepAnswer:
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return handleDeepAnswer(ctx, input, decision, conversationContext, emitter, flowState)
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case newagentmodel.ChatRoutePlan:
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return handleRoutePlan(decision, emitter, flowState)
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default:
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flowState.Phase = newagentmodel.PhasePlanning
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return nil
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}
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}
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// appendExecuteLoopClosedMarker 在 history 中写入“execute loop 已正常收口”标记。
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//
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// 职责边界:
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// 1. 只负责写一个轻量 marker,供 prompt 分层;
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// 2. 不负责历史裁剪,不负责消息摘要;
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// 3. 若末尾已经是同类 marker,则幂等跳过,避免重复写入。
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func appendExecuteLoopClosedMarker(conversationContext *newagentmodel.ConversationContext) {
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if conversationContext == nil {
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return
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}
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history := conversationContext.HistorySnapshot()
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if len(history) > 0 {
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last := history[len(history)-1]
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if isExecuteLoopClosedMarker(last) {
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return
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}
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}
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conversationContext.AppendHistory(&schema.Message{
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Role: schema.Assistant,
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Content: "",
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Extra: map[string]any{
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chatHistoryKindKey: chatHistoryKindExecuteLoopClosed,
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},
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})
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}
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func isExecuteLoopClosedMarker(msg *schema.Message) bool {
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if msg == nil || msg.Extra == nil {
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return false
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}
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kind, ok := msg.Extra[chatHistoryKindKey].(string)
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if !ok {
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return false
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}
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return strings.TrimSpace(kind) == chatHistoryKindExecuteLoopClosed
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}
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// handleDirectReply 处理简单任务:直接输出回复。
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func handleDirectReply(
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ctx context.Context,
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decision *newagentmodel.ChatRoutingDecision,
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conversationContext *newagentmodel.ConversationContext,
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emitter *newagentstream.ChunkEmitter,
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flowState *newagentmodel.CommonState,
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) error {
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if strings.TrimSpace(decision.Speak) != "" {
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if err := emitter.EmitPseudoAssistantText(
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ctx, chatSpeakBlockID, chatStageName,
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decision.Speak,
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newagentstream.DefaultPseudoStreamOptions(),
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); err != nil {
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return fmt.Errorf("闲聊回复推送失败: %w", err)
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}
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conversationContext.AppendHistory(schema.AssistantMessage(decision.Speak, nil))
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}
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flowState.Phase = newagentmodel.PhaseChatting
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return nil
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}
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// handleRouteExecute 处理中等任务:推送简短确认,设 PhaseExecuting。
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//
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// 不把 speak 写入 history,因为真正的回复由 Execute 节点产出。
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func handleRouteExecute(
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decision *newagentmodel.ChatRoutingDecision,
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emitter *newagentstream.ChunkEmitter,
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flowState *newagentmodel.CommonState,
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) error {
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speak := strings.TrimSpace(decision.Speak)
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if speak == "" {
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speak = "好的,我来处理。"
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}
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// 推送轻量状态通知,让前端知道请求已接收。
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_ = emitter.EmitStatus(chatStatusBlockID, chatStageName, "accepted", speak, false)
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// 清空旧 PlanSteps 并设 PhaseExecuting,避免上一次任务残留的步骤被 HasPlan() 误判。
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flowState.StartDirectExecute()
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// 1. 默认不走粗排与粗排后微调,避免沿用上轮遗留标记。
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// 2. 只有 route 判定为“需要粗排”且确实有 task_class_ids 时,才打开粗排开关。
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// 3. 粗排后是否立即进入微调,完全由路由决策显式标记控制。
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flowState.NeedsRoughBuild = false
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flowState.NeedsRefineAfterRoughBuild = false
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if decision.NeedsRoughBuild && len(flowState.TaskClassIDs) > 0 {
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flowState.NeedsRoughBuild = true
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flowState.NeedsRefineAfterRoughBuild = decision.NeedsRefineAfterRoughBuild
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}
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return nil
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}
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// resolveAllowReorder 统一计算“本轮是否允许打乱顺序”。
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//
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// 步骤化说明:
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// 1. 后端先做显式语义判定:用户明确允许/明确禁止时,直接以后端判定为准;
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// 2. 若后端未识别到显式语义,再回退到路由模型的 allow_reorder 字段;
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// 3. 默认返回 false,确保“保持顺序”是系统默认行为。
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func resolveAllowReorder(userInput string, modelAllowReorder bool) bool {
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switch detectReorderPreference(userInput) {
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case reorderAllow:
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return true
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case reorderDisallow:
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return false
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default:
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return modelAllowReorder
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}
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}
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// detectReorderPreference 识别用户是否“明确授权打乱顺序”。
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//
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// 职责边界:
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// 1. 只负责关键词级别的显式意图识别,不做复杂语义推理;
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// 2. 若同时命中“允许”与“禁止”,优先按“禁止”处理,避免误放开顺序约束;
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// 3. 未命中显式表达时返回 unknown,交给上层兜底策略。
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func detectReorderPreference(userInput string) reorderPreference {
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text := strings.ToLower(strings.TrimSpace(userInput))
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if text == "" {
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return reorderUnknown
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}
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disallowPhrases := []string{
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"不要打乱顺序",
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"不允许打乱顺序",
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"保持顺序",
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"顺序不变",
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"按原顺序",
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"不要乱序",
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"别打乱",
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}
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if containsAnyPhrase(text, disallowPhrases) {
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return reorderDisallow
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}
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allowPhrases := []string{
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"可以打乱顺序",
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"允许打乱顺序",
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"顺序不重要",
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"顺序无所谓",
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"顺序不限",
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"允许乱序",
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"可以乱序",
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"允许重排顺序",
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"reorder is fine",
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"any order",
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}
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if containsAnyPhrase(text, allowPhrases) {
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return reorderAllow
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}
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return reorderUnknown
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}
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func containsAnyPhrase(text string, phrases []string) bool {
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for _, phrase := range phrases {
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if strings.Contains(text, phrase) {
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return true
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}
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}
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return false
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}
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// shouldDisableRoughBuildForRefine 判断是否应在 chat 路由阶段关闭“再次粗排”。
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//
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// 判定规则:
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// 1. 当前决策未请求粗排时,直接不干预;
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// 2. 上下文不存在 rough_build_done 时,不干预(首次粗排仍可走);
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// 3. 若用户未明确要求“重新粗排/从头重排”,则关闭粗排开关,避免误触发。
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func shouldDisableRoughBuildForRefine(
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conversationContext *newagentmodel.ConversationContext,
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userInput string,
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decision *newagentmodel.ChatRoutingDecision,
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) bool {
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if decision == nil || !decision.NeedsRoughBuild {
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return false
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}
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if !hasRoughBuildDoneMarker(conversationContext) {
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return false
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}
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return !isExplicitRoughBuildRequest(userInput)
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}
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func hasRoughBuildDoneMarker(conversationContext *newagentmodel.ConversationContext) bool {
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if conversationContext == nil {
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return false
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}
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for _, block := range conversationContext.PinnedBlocksSnapshot() {
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if strings.TrimSpace(block.Key) == "rough_build_done" {
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return true
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}
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}
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return false
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}
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// isExplicitRoughBuildRequest 识别用户是否明确要求“重新粗排/从头重排”。
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func isExplicitRoughBuildRequest(userInput string) bool {
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text := strings.ToLower(strings.TrimSpace(userInput))
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if text == "" {
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return false
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}
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keywords := []string{
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"重新粗排",
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"重做粗排",
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"从头排",
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"从头重排",
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"重新排一遍",
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"重新排课",
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"重排全部",
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"全部重排",
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"重置排程",
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"重置后重排",
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"重新生成初稿",
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"rebuild",
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"from scratch",
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}
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return containsAnyPhrase(text, keywords)
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}
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|
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// handleDeepAnswer 处理复杂问答:推送过渡语 → 原地开 thinking 再调一次 LLM → 输出深度回答。
|
||
func handleDeepAnswer(
|
||
ctx context.Context,
|
||
input ChatNodeInput,
|
||
decision *newagentmodel.ChatRoutingDecision,
|
||
conversationContext *newagentmodel.ConversationContext,
|
||
emitter *newagentstream.ChunkEmitter,
|
||
flowState *newagentmodel.CommonState,
|
||
) error {
|
||
// 1. 推送过渡语。
|
||
briefSpeak := strings.TrimSpace(decision.Speak)
|
||
if briefSpeak == "" {
|
||
briefSpeak = "让我想想。"
|
||
}
|
||
if err := emitter.EmitPseudoAssistantText(
|
||
ctx, chatSpeakBlockID, chatStageName,
|
||
briefSpeak,
|
||
newagentstream.DefaultPseudoStreamOptions(),
|
||
); err != nil {
|
||
return fmt.Errorf("过渡文案推送失败: %w", err)
|
||
}
|
||
|
||
// 2. 第二次 LLM 调用:开 thinking,深度回答。
|
||
deepMessages := newagentprompt.BuildDeepAnswerMessages(conversationContext, input.UserInput)
|
||
deepResult, err := input.Client.GenerateText(ctx, deepMessages, newagentllm.GenerateOptions{
|
||
Temperature: 0.5,
|
||
MaxTokens: 2000,
|
||
Thinking: newagentllm.ThinkingModeEnabled,
|
||
Metadata: map[string]any{
|
||
"stage": chatStageName,
|
||
"phase": "deep_answer",
|
||
},
|
||
})
|
||
|
||
if err != nil || deepResult == nil {
|
||
// 深度回答失败 → 降级,只保留过渡语。
|
||
log.Printf("[WARN] deep answer LLM failed chat=%s err=%v", flowState.ConversationID, err)
|
||
conversationContext.AppendHistory(schema.AssistantMessage(briefSpeak, nil))
|
||
flowState.Phase = newagentmodel.PhaseChatting
|
||
return nil
|
||
}
|
||
|
||
// 3. 输出深度回答。
|
||
deepText := strings.TrimSpace(deepResult.Text)
|
||
if deepText == "" {
|
||
conversationContext.AppendHistory(schema.AssistantMessage(briefSpeak, nil))
|
||
flowState.Phase = newagentmodel.PhaseChatting
|
||
return nil
|
||
}
|
||
|
||
if err := emitter.EmitPseudoAssistantText(
|
||
ctx, chatSpeakBlockID, chatStageName,
|
||
deepText,
|
||
newagentstream.DefaultPseudoStreamOptions(),
|
||
); err != nil {
|
||
return fmt.Errorf("深度回答推送失败: %w", err)
|
||
}
|
||
|
||
// 将完整回复(过渡语 + 深度回答)写入 history。
|
||
fullReply := briefSpeak + "\n\n" + deepText
|
||
conversationContext.AppendHistory(schema.AssistantMessage(fullReply, nil))
|
||
|
||
flowState.Phase = newagentmodel.PhaseChatting
|
||
return nil
|
||
}
|
||
|
||
// handleRoutePlan 处理复杂规划:推送确认语,设 PhasePlanning。
|
||
func handleRoutePlan(
|
||
decision *newagentmodel.ChatRoutingDecision,
|
||
emitter *newagentstream.ChunkEmitter,
|
||
flowState *newagentmodel.CommonState,
|
||
) error {
|
||
speak := strings.TrimSpace(decision.Speak)
|
||
if speak == "" {
|
||
speak = "好的,让我来规划一下。"
|
||
}
|
||
|
||
_ = emitter.EmitStatus(chatStatusBlockID, chatStageName, "planning", speak, false)
|
||
|
||
flowState.Phase = newagentmodel.PhasePlanning
|
||
return nil
|
||
}
|
||
|
||
// ─── 恢复处理(保持原有逻辑不变)───
|
||
|
||
// handleChatResume 处理 pending interaction 恢复。
|
||
//
|
||
// 职责边界:
|
||
// 1. 只做状态传递:吞掉用户输入、写回历史、恢复 phase;
|
||
// 2. 不生成 speak,真正的回复由下游 Plan / Execute 节点产出;
|
||
// 3. 只推送轻量 status 通知前端"已收到回复,正在继续"。
|
||
func handleChatResume(
|
||
input ChatNodeInput,
|
||
runtimeState *newagentmodel.AgentRuntimeState,
|
||
emitter *newagentstream.ChunkEmitter,
|
||
) error {
|
||
pending := runtimeState.PendingInteraction
|
||
flowState := runtimeState.EnsureCommonState()
|
||
|
||
// 用户输入在 service 层进入 graph 前已经统一追加到 ConversationContext。
|
||
// 这里不再二次写入,避免 pending 恢复路径把同一轮 user message 追加两次。
|
||
|
||
switch pending.Type {
|
||
case newagentmodel.PendingInteractionTypeAskUser:
|
||
// 用户回答了问题 → 恢复 phase,交给下游节点继续。
|
||
runtimeState.ResumeFromPending()
|
||
_ = emitter.EmitStatus(
|
||
chatStatusBlockID, chatStageName,
|
||
"resumed", "收到回复,继续处理。", false,
|
||
)
|
||
return nil
|
||
|
||
case newagentmodel.PendingInteractionTypeConfirm:
|
||
return handleConfirmResume(input, runtimeState, flowState, pending, emitter)
|
||
|
||
default:
|
||
// connection_lost 等其他类型 → 直接恢复。
|
||
runtimeState.ResumeFromPending()
|
||
return nil
|
||
}
|
||
}
|
||
|
||
// handleConfirmResume 处理 confirm 类型恢复。
|
||
//
|
||
// 分支逻辑:
|
||
// 1. accept → 恢复后 phase 设为 executing,下游 Execute 节点接管;
|
||
// 2. reject + 有 PendingTool(工具确认)→ 回到 executing 让 Execute 节点换策略;
|
||
// 3. reject + 无 PendingTool(计划确认)→ 清空计划,回到 planning 重新规划。
|
||
func handleConfirmResume(
|
||
input ChatNodeInput,
|
||
runtimeState *newagentmodel.AgentRuntimeState,
|
||
flowState *newagentmodel.CommonState,
|
||
pending *newagentmodel.PendingInteraction,
|
||
emitter *newagentstream.ChunkEmitter,
|
||
) error {
|
||
action := strings.ToLower(strings.TrimSpace(input.ConfirmAction))
|
||
|
||
switch action {
|
||
case "accept":
|
||
// 恢复前保存待执行工具,Execute 节点需要它。
|
||
pendingTool := pending.PendingTool
|
||
runtimeState.ResumeFromPending()
|
||
// 将待执行工具放回临时邮箱,供 Execute 节点执行。
|
||
if pendingTool != nil {
|
||
copied := *pendingTool
|
||
runtimeState.PendingConfirmTool = &copied
|
||
}
|
||
flowState.Phase = newagentmodel.PhaseExecuting
|
||
_ = emitter.EmitStatus(
|
||
chatStatusBlockID, chatStageName,
|
||
"confirmed", "已确认,开始执行。", false,
|
||
)
|
||
|
||
case "reject":
|
||
runtimeState.ResumeFromPending()
|
||
if pending.PendingTool != nil {
|
||
// 工具确认被拒 → 回到 executing 换策略。
|
||
flowState.Phase = newagentmodel.PhaseExecuting
|
||
} else {
|
||
// 计划确认被拒 → 清空计划,回到 planning。
|
||
flowState.RejectPlan()
|
||
}
|
||
_ = emitter.EmitStatus(
|
||
chatStatusBlockID, chatStageName,
|
||
"rejected", "已取消,准备重新规划。", false,
|
||
)
|
||
|
||
default:
|
||
// 无合法 confirm action → 保守:等同于 reject。
|
||
runtimeState.ResumeFromPending()
|
||
if pending.PendingTool != nil {
|
||
flowState.Phase = newagentmodel.PhaseExecuting
|
||
} else {
|
||
flowState.RejectPlan()
|
||
}
|
||
}
|
||
return nil
|
||
}
|
||
|
||
// prepareChatNodeInput 校验并准备聊天节点的运行态依赖。
|
||
func prepareChatNodeInput(input ChatNodeInput) (
|
||
*newagentmodel.AgentRuntimeState,
|
||
*newagentmodel.ConversationContext,
|
||
*newagentstream.ChunkEmitter,
|
||
error,
|
||
) {
|
||
if input.RuntimeState == nil {
|
||
return nil, nil, nil, fmt.Errorf("chat node: runtime state 不能为空")
|
||
}
|
||
if input.Client == nil {
|
||
return nil, nil, nil, fmt.Errorf("chat node: chat client 未注入")
|
||
}
|
||
|
||
input.RuntimeState.EnsureCommonState()
|
||
if input.ConversationContext == nil {
|
||
input.ConversationContext = newagentmodel.NewConversationContext("")
|
||
}
|
||
if input.ChunkEmitter == nil {
|
||
input.ChunkEmitter = newagentstream.NewChunkEmitter(
|
||
newagentstream.NoopPayloadEmitter(), "", "", time.Now().Unix(),
|
||
)
|
||
}
|
||
return input.RuntimeState, input.ConversationContext, input.ChunkEmitter, nil
|
||
}
|