Files
smartmate/backend/newAgent/node/chat.go
Losita ee34d5f111 Version: 0.9.12.dev.260410
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
2026-04-10 00:38:02 +08:00

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package newagentnode
import (
"context"
"fmt"
"log"
"strings"
"time"
"github.com/cloudwego/eino/schema"
newagentllm "github.com/LoveLosita/smartflow/backend/newAgent/llm"
newagentmodel "github.com/LoveLosita/smartflow/backend/newAgent/model"
newagentprompt "github.com/LoveLosita/smartflow/backend/newAgent/prompt"
newagentstream "github.com/LoveLosita/smartflow/backend/newAgent/stream"
)
const (
chatStageName = "chat"
chatStatusBlockID = "chat.status"
chatSpeakBlockID = "chat.speak"
// chatHistoryKindKey 用于在 history 中打运行态标记,供 prompt 层做上下文分层。
chatHistoryKindKey = "newagent_history_kind"
// chatHistoryKindExecuteLoopClosed 表示“上一轮 execute loop 已正常收口”。
// prompt 侧会据此把旧 loop 归档到 msg1而不是继续占用 msg2 窗口。
chatHistoryKindExecuteLoopClosed = "execute_loop_closed"
)
type reorderPreference int
const (
reorderUnknown reorderPreference = iota
reorderAllow
reorderDisallow
)
// ChatNodeInput 描述聊天节点单轮运行所需的最小依赖。
//
// 职责边界:
// 1. 只承载"本轮 chat"需要的输入,不负责持久化;
// 2. RuntimeState 提供 pending interaction 与流程状态;
// 3. ConversationContext 提供历史对话;
// 4. ConfirmAction 仅在 confirm 恢复场景下由前端传入 "accept" / "reject"。
type ChatNodeInput struct {
RuntimeState *newagentmodel.AgentRuntimeState
ConversationContext *newagentmodel.ConversationContext
UserInput string
ConfirmAction string
Client *newagentllm.Client
ChunkEmitter *newagentstream.ChunkEmitter
}
// RunChatNode 执行一轮聊天节点逻辑。
//
// 核心职责:
// 1. 恢复判定:有 pending interaction 则处理恢复;
// 2. 路由分流:无 pending 时,调 LLM 判断复杂度并路由;
// 3. direct_reply简单任务直接输出回复 → END
// 4. execute中等任务推 Execute ReAct
// 5. deep_answer复杂问答原地开 thinking 深度回答 → END
// 6. plan复杂规划推 Plan 节点。
func RunChatNode(ctx context.Context, input ChatNodeInput) error {
runtimeState, conversationContext, emitter, err := prepareChatNodeInput(input)
if err != nil {
return err
}
// 1. 有 pending interaction → 纯状态传递,处理恢复。
if runtimeState.HasPendingInteraction() {
return handleChatResume(input, runtimeState, emitter)
}
// 2. 无 pending → 路由决策(一次快速 LLM 调用,不开 thinking
flowState := runtimeState.EnsureCommonState()
if !runtimeState.HasPendingInteraction() && flowState.Phase == newagentmodel.PhaseDone {
terminalBefore := flowState.TerminalStatus()
roundBefore := flowState.RoundUsed
// 1. 只有“正常完成(completed)”才打 loop 收口标记:
// 1.1 这样下一轮进入 execute 时msg2 会只保留“当前活跃循环”窗口;
// 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。
if terminalBefore == newagentmodel.FlowTerminalStatusCompleted {
appendExecuteLoopClosedMarker(conversationContext)
}
flowState.ResetForNextRun()
log.Printf(
"[DEBUG] chat reset runtime for next run chat=%s round_before=%d terminal_before=%s",
flowState.ConversationID,
roundBefore,
terminalBefore,
)
}
messages := newagentprompt.BuildChatRoutingMessages(conversationContext, input.UserInput, flowState)
decision, rawResult, err := newagentllm.GenerateJSON[newagentmodel.ChatRoutingDecision](
ctx,
input.Client,
messages,
newagentllm.GenerateOptions{
Temperature: 0.1,
MaxTokens: 500,
Thinking: newagentllm.ThinkingModeDisabled,
Metadata: map[string]any{
"stage": chatStageName,
"phase": "routing",
},
},
)
rawText := ""
if rawResult != nil {
rawText = strings.TrimSpace(rawResult.Text)
}
if err != nil {
// 路由失败 → 保守:走 plan。
log.Printf("[WARN] chat routing LLM failed chat=%s raw=%s err=%v",
flowState.ConversationID, rawText, err)
flowState.Phase = newagentmodel.PhasePlanning
return nil
}
if validateErr := decision.Validate(); validateErr != nil {
log.Printf("[WARN] chat routing decision invalid chat=%s raw=%s err=%v",
flowState.ConversationID, rawText, validateErr)
flowState.Phase = newagentmodel.PhasePlanning
return nil
}
// 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”,
// 则强制关闭 needs_rough_build避免“微调请求被误判成再次粗排”。
// 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。
// 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。
if shouldDisableRoughBuildForRefine(conversationContext, input.UserInput, decision) {
decision.NeedsRoughBuild = false
decision.NeedsRefineAfterRoughBuild = false
}
log.Printf(
"[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",
flowState.ConversationID,
decision.Route,
decision.NeedsRoughBuild,
decision.NeedsRefineAfterRoughBuild,
decision.AllowReorder,
hasRoughBuildDoneMarker(conversationContext),
len(flowState.TaskClassIDs),
decision.Reason,
)
flowState.AllowReorder = resolveAllowReorder(input.UserInput, decision.AllowReorder)
// 3. 按路由决策推进。
switch decision.Route {
case newagentmodel.ChatRouteDirectReply:
return handleDirectReply(ctx, decision, conversationContext, emitter, flowState)
case newagentmodel.ChatRouteExecute:
return handleRouteExecute(decision, emitter, flowState)
case newagentmodel.ChatRouteDeepAnswer:
return handleDeepAnswer(ctx, input, decision, conversationContext, emitter, flowState)
case newagentmodel.ChatRoutePlan:
return handleRoutePlan(decision, emitter, flowState)
default:
flowState.Phase = newagentmodel.PhasePlanning
return nil
}
}
// appendExecuteLoopClosedMarker 在 history 中写入“execute loop 已正常收口”标记。
//
// 职责边界:
// 1. 只负责写一个轻量 marker供 prompt 分层;
// 2. 不负责历史裁剪,不负责消息摘要;
// 3. 若末尾已经是同类 marker则幂等跳过避免重复写入。
func appendExecuteLoopClosedMarker(conversationContext *newagentmodel.ConversationContext) {
if conversationContext == nil {
return
}
history := conversationContext.HistorySnapshot()
if len(history) > 0 {
last := history[len(history)-1]
if isExecuteLoopClosedMarker(last) {
return
}
}
conversationContext.AppendHistory(&schema.Message{
Role: schema.Assistant,
Content: "",
Extra: map[string]any{
chatHistoryKindKey: chatHistoryKindExecuteLoopClosed,
},
})
}
func isExecuteLoopClosedMarker(msg *schema.Message) bool {
if msg == nil || msg.Extra == nil {
return false
}
kind, ok := msg.Extra[chatHistoryKindKey].(string)
if !ok {
return false
}
return strings.TrimSpace(kind) == chatHistoryKindExecuteLoopClosed
}
// handleDirectReply 处理简单任务:直接输出回复。
func handleDirectReply(
ctx context.Context,
decision *newagentmodel.ChatRoutingDecision,
conversationContext *newagentmodel.ConversationContext,
emitter *newagentstream.ChunkEmitter,
flowState *newagentmodel.CommonState,
) error {
if strings.TrimSpace(decision.Speak) != "" {
if err := emitter.EmitPseudoAssistantText(
ctx, chatSpeakBlockID, chatStageName,
decision.Speak,
newagentstream.DefaultPseudoStreamOptions(),
); err != nil {
return fmt.Errorf("闲聊回复推送失败: %w", err)
}
conversationContext.AppendHistory(schema.AssistantMessage(decision.Speak, nil))
}
flowState.Phase = newagentmodel.PhaseChatting
return nil
}
// handleRouteExecute 处理中等任务:推送简短确认,设 PhaseExecuting。
//
// 不把 speak 写入 history因为真正的回复由 Execute 节点产出。
func handleRouteExecute(
decision *newagentmodel.ChatRoutingDecision,
emitter *newagentstream.ChunkEmitter,
flowState *newagentmodel.CommonState,
) error {
speak := strings.TrimSpace(decision.Speak)
if speak == "" {
speak = "好的,我来处理。"
}
// 推送轻量状态通知,让前端知道请求已接收。
_ = emitter.EmitStatus(chatStatusBlockID, chatStageName, "accepted", speak, false)
// 清空旧 PlanSteps 并设 PhaseExecuting避免上一次任务残留的步骤被 HasPlan() 误判。
flowState.StartDirectExecute()
// 1. 默认不走粗排与粗排后微调,避免沿用上轮遗留标记。
// 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。
// 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。
flowState.NeedsRoughBuild = false
flowState.NeedsRefineAfterRoughBuild = false
if decision.NeedsRoughBuild && len(flowState.TaskClassIDs) > 0 {
flowState.NeedsRoughBuild = true
flowState.NeedsRefineAfterRoughBuild = decision.NeedsRefineAfterRoughBuild
}
return nil
}
// resolveAllowReorder 统一计算“本轮是否允许打乱顺序”。
//
// 步骤化说明:
// 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;
// 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;
// 3. 默认返回 false确保“保持顺序”是系统默认行为。
func resolveAllowReorder(userInput string, modelAllowReorder bool) bool {
switch detectReorderPreference(userInput) {
case reorderAllow:
return true
case reorderDisallow:
return false
default:
return modelAllowReorder
}
}
// detectReorderPreference 识别用户是否“明确授权打乱顺序”。
//
// 职责边界:
// 1. 只负责关键词级别的显式意图识别,不做复杂语义推理;
// 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;
// 3. 未命中显式表达时返回 unknown交给上层兜底策略。
func detectReorderPreference(userInput string) reorderPreference {
text := strings.ToLower(strings.TrimSpace(userInput))
if text == "" {
return reorderUnknown
}
disallowPhrases := []string{
"不要打乱顺序",
"不允许打乱顺序",
"保持顺序",
"顺序不变",
"按原顺序",
"不要乱序",
"别打乱",
}
if containsAnyPhrase(text, disallowPhrases) {
return reorderDisallow
}
allowPhrases := []string{
"可以打乱顺序",
"允许打乱顺序",
"顺序不重要",
"顺序无所谓",
"顺序不限",
"允许乱序",
"可以乱序",
"允许重排顺序",
"reorder is fine",
"any order",
}
if containsAnyPhrase(text, allowPhrases) {
return reorderAllow
}
return reorderUnknown
}
func containsAnyPhrase(text string, phrases []string) bool {
for _, phrase := range phrases {
if strings.Contains(text, phrase) {
return true
}
}
return false
}
// shouldDisableRoughBuildForRefine 判断是否应在 chat 路由阶段关闭“再次粗排”。
//
// 判定规则:
// 1. 当前决策未请求粗排时,直接不干预;
// 2. 上下文不存在 rough_build_done 时,不干预(首次粗排仍可走);
// 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。
func shouldDisableRoughBuildForRefine(
conversationContext *newagentmodel.ConversationContext,
userInput string,
decision *newagentmodel.ChatRoutingDecision,
) bool {
if decision == nil || !decision.NeedsRoughBuild {
return false
}
if !hasRoughBuildDoneMarker(conversationContext) {
return false
}
return !isExplicitRoughBuildRequest(userInput)
}
func hasRoughBuildDoneMarker(conversationContext *newagentmodel.ConversationContext) bool {
if conversationContext == nil {
return false
}
for _, block := range conversationContext.PinnedBlocksSnapshot() {
if strings.TrimSpace(block.Key) == "rough_build_done" {
return true
}
}
return false
}
// isExplicitRoughBuildRequest 识别用户是否明确要求“重新粗排/从头重排”。
func isExplicitRoughBuildRequest(userInput string) bool {
text := strings.ToLower(strings.TrimSpace(userInput))
if text == "" {
return false
}
keywords := []string{
"重新粗排",
"重做粗排",
"从头排",
"从头重排",
"重新排一遍",
"重新排课",
"重排全部",
"全部重排",
"重置排程",
"重置后重排",
"重新生成初稿",
"rebuild",
"from scratch",
}
return containsAnyPhrase(text, keywords)
}
// 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
}