后端: 1.新建Deliver节点:LLM生成任务总结,失败降级到机械格式化,伪流式输出 2.新建Confirm节点:确认卡片推送与状态持久化 3.新建Interrupt节点:追问/确认/默认中断三种处理路径 4.实现状态持久化体系:model层定义AgentStateStore接口+AgentStateSnapshot快照,dao/cache.go新增Redis CRUD,agent_nodes层每节点自动存快照、Deliver完成后清理 5.所有model struct补充JSON tags,支持Redis序列化/反序列化 前端:无 仓库:无
185 lines
5.2 KiB
Go
185 lines
5.2 KiB
Go
package newagentnode
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import (
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"context"
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"fmt"
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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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deliverStageName = "deliver"
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deliverStatusBlockID = "deliver.status"
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deliverSpeakBlockID = "deliver.speak"
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)
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// DeliverNodeInput 描述交付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. 只负责生成交付总结并推送给用户,不负责后续流程推进;
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// 2. RuntimeState 提供计划步骤和执行状态;
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// 3. ConversationContext 提供执行阶段的对话历史;
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// 4. 交付完成后标记流程结束。
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type DeliverNodeInput struct {
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RuntimeState *newagentmodel.AgentRuntimeState
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ConversationContext *newagentmodel.ConversationContext
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Client *newagentllm.Client
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ChunkEmitter *newagentstream.ChunkEmitter
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}
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// RunDeliverNode 执行一轮交付节点逻辑。
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//
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// 核心职责:
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// 1. 调 LLM 基于原始计划 + 执行历史生成交付总结;
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// 2. 伪流式推送总结给用户;
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// 3. 写入对话历史,保证上下文连续;
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// 4. 标记流程结束。
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//
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// 降级策略:
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// 1. LLM 调用失败时,回退到机械格式化总结,不中断流程;
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// 2. 机械总结包含计划步骤列表和完成进度。
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func RunDeliverNode(ctx context.Context, input DeliverNodeInput) error {
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runtimeState, conversationContext, emitter, err := prepareDeliverNodeInput(input)
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if err != nil {
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return err
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}
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flowState := runtimeState.EnsureCommonState()
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// 1. 推送交付阶段状态,让前端知道正在生成总结。
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if err := emitter.EmitStatus(
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deliverStatusBlockID,
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deliverStageName,
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"summarizing",
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"正在生成交付总结。",
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false,
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); err != nil {
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return fmt.Errorf("交付阶段状态推送失败: %w", err)
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}
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// 2. 调 LLM 生成交付总结。
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summary := generateDeliverSummary(ctx, input.Client, flowState, conversationContext)
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// 3. 伪流式推送总结。
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if strings.TrimSpace(summary) != "" {
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if err := emitter.EmitPseudoAssistantText(
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ctx,
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deliverSpeakBlockID,
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deliverStageName,
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summary,
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newagentstream.DefaultPseudoStreamOptions(),
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); err != nil {
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return fmt.Errorf("交付总结推送失败: %w", err)
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}
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conversationContext.AppendHistory(schema.AssistantMessage(summary, nil))
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}
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// 4. 推送最终完成状态。
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_ = emitter.EmitStatus(
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deliverStatusBlockID,
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deliverStageName,
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"done",
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"任务已完成。",
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true,
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)
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// 5. 标记流程结束。
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flowState.Done()
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return nil
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}
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// generateDeliverSummary 尝试调用 LLM 生成交付总结,失败时降级到机械格式化。
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func generateDeliverSummary(
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ctx context.Context,
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client *newagentllm.Client,
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flowState *newagentmodel.CommonState,
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conversationContext *newagentmodel.ConversationContext,
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) string {
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if client == nil {
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return buildMechanicalSummary(flowState)
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}
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messages := newagentprompt.BuildDeliverMessages(flowState, conversationContext)
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result, err := client.GenerateText(
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ctx,
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messages,
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newagentllm.GenerateOptions{
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Temperature: 0.5,
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MaxTokens: 800,
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Thinking: newagentllm.ThinkingModeDisabled,
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Metadata: map[string]any{
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"stage": deliverStageName,
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},
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},
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)
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if err != nil || result == nil || strings.TrimSpace(result.Text) == "" {
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return buildMechanicalSummary(flowState)
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}
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return strings.TrimSpace(result.Text)
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}
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// buildMechanicalSummary 在 LLM 不可用时,机械拼接一份最小可用总结。
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func buildMechanicalSummary(state *newagentmodel.CommonState) string {
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if state == nil {
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return "任务流程已结束。"
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}
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var sb strings.Builder
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current, total := state.PlanProgress()
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if !state.HasPlan() {
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return "任务流程已结束。"
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}
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if state.Exhausted() {
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sb.WriteString(fmt.Sprintf("任务因执行轮次耗尽提前结束,已完成 %d/%d 步。\n", current, total))
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} else {
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sb.WriteString("所有计划步骤已执行完毕。\n")
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}
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sb.WriteString("\n执行情况:\n")
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for i, step := range state.PlanSteps {
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marker := "[ ]"
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if i < current {
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marker = "[x]"
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}
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sb.WriteString(fmt.Sprintf("%s %s\n", marker, strings.TrimSpace(step.Content)))
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}
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if state.Exhausted() && current < total {
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sb.WriteString("\n如需继续完成剩余步骤,可以告诉我继续。")
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}
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return sb.String()
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}
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// prepareDeliverNodeInput 校验并准备交付节点的运行态依赖。
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func prepareDeliverNodeInput(input DeliverNodeInput) (
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*newagentmodel.AgentRuntimeState,
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*newagentmodel.ConversationContext,
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*newagentstream.ChunkEmitter,
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error,
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) {
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if input.RuntimeState == nil {
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return nil, nil, nil, fmt.Errorf("deliver node: runtime state 不能为空")
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}
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input.RuntimeState.EnsureCommonState()
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if input.ConversationContext == nil {
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input.ConversationContext = newagentmodel.NewConversationContext("")
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}
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if input.ChunkEmitter == nil {
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input.ChunkEmitter = newagentstream.NewChunkEmitter(
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newagentstream.NoopPayloadEmitter(), "", "", time.Now().Unix(),
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)
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}
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return input.RuntimeState, input.ConversationContext, input.ChunkEmitter, nil
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}
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