mlogclub
302 lines
14 KiB
Go
302 lines
14 KiB
Go
package registry
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import "agent-desk/internal/ai/workflow/dsl"
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const (
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NodeTypeStart = "start"
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NodeTypeConversationUnderstanding = "conversation_understanding"
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NodeTypeReplyPolicy = "reply_policy"
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NodeTypeKnowledgeRetrieve = "knowledge_retrieve"
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NodeTypeAnswerabilityGate = "answerability_gate"
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NodeTypeLLMReply = "llm_reply"
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NodeTypeCondition = "condition"
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NodeTypeAnalyzeConversation = "analyze_conversation"
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NodeTypePrepareTicketDraft = "prepare_ticket_draft"
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NodeTypeHumanConfirm = "human_confirm"
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NodeTypeCreateTicket = "create_ticket"
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NodeTypeHandoffToHuman = "handoff_to_human"
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NodeTypeSendReply = "send_reply"
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NodeTypeEnd = "end"
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)
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func DefaultRegistry() *Registry {
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return NewRegistry(
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NodeSpec{
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Type: NodeTypeStart,
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Title: "Start",
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Description: "Conversation workflow entry.",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("conversationId", VariableTypeInteger, "Conversation ID."),
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output("messageId", VariableTypeInteger, "Current user message ID."),
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output("aiAgentId", VariableTypeInteger, "AI Agent ID."),
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output("userMessage", VariableTypeString, "Current user message content."),
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output("knowledgeBaseIds", VariableTypeIntegerArray, "Knowledge bases bound to the AI Agent."),
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},
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},
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NodeSpec{
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Type: NodeTypeConversationUnderstanding,
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Title: "Conversation Understanding",
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Description: "Classify customer message intent and answer scope before retrieval.",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", VariableTypeString, "Current user message content."),
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},
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OutputSchema: []VariableSpec{
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output("normalizedMessage", VariableTypeString, "Normalized customer message."),
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enumOutput("messageIntent", "消息意图", "Detected customer message intent.", []VariableValueOption{
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valueOption("unknown", "未知意图", "系统暂时无法判断客户意图。"),
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valueOption("greeting", "打招呼", "客户在问候或开始对话。"),
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valueOption("thanks", "表达感谢", "客户在表示感谢。"),
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valueOption("end_conversation", "结束会话", "客户表示问题已处理或准备结束。"),
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valueOption("confirmation", "确认操作", "客户对上一步操作进行确认。"),
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valueOption("handoff_request", "要求人工", "客户明确要求转人工处理。"),
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valueOption("complaint", "投诉升级", "客户表达投诉、举报、起诉等升级风险。"),
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valueOption("ticket_request", "要求建单", "客户希望创建或跟进工单。"),
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valueOption("ambiguous_question", "问题不明确", "客户问题缺少必要上下文，需要追问。"),
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valueOption("business_question", "业务问题", "客户问题适合进入知识库检索。"),
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}),
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enumOutput("answerScope", "回复策略", "Recommended answer scope.", []VariableValueOption{
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valueOption("direct_reply", "直接回复客户", "无需检索知识库或转人工，可以直接生成回复。"),
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valueOption("needs_clarification", "追问补充信息", "当前信息不足，需要客户补充。"),
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valueOption("needs_handoff", "转人工处理", "需要人工客服介入。"),
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valueOption("needs_ticket", "创建工单", "需要进入工单处理流程。"),
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valueOption("needs_knowledge", "检索知识库", "需要先检索知识库再回答。"),
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}),
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output("confidence", VariableTypeNumber, "Classifier confidence."),
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output("riskSignals", VariableTypeStringArray, "Detected risk signals."),
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output("reason", VariableTypeString, "Decision reason."),
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},
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DefaultInputs: map[string]dsl.Value{
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"userMessage": dsl.RefValue("start_1", "userMessage"),
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},
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},
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NodeSpec{
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Type: NodeTypeReplyPolicy,
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Title: "Reply Policy",
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Description: "Decide the next customer-service action from understanding output and agent policy.",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("messageIntent", VariableTypeString, "Detected customer message intent."),
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requiredInput("answerScope", VariableTypeString, "Recommended answer scope."),
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optionalInput("userMessage", VariableTypeString, "Current user message content."),
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optionalInput("riskSignals", VariableTypeStringArray, "Detected risk signals."),
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optionalInput("answerability", VariableTypeString, "Knowledge answerability decision."),
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},
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OutputSchema: []VariableSpec{
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enumOutput("action", "处理策略", "Selected policy action.", []VariableValueOption{
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valueOption("direct_reply", "直接回复客户", "直接发送策略节点生成的回复。"),
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valueOption("clarify", "追问补充信息", "先让客户补充必要信息。"),
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valueOption("end_conversation", "结束会话", "发送结束语并结束本轮处理。"),
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valueOption("handoff_to_human", "转人工", "进入人工接待流程。"),
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valueOption("prepare_ticket", "创建工单", "整理工单草稿并等待确认。"),
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valueOption("retrieve_knowledge", "检索知识库", "进入知识检索和 AI 回复流程。"),
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valueOption("knowledge_fallback", "知识库兜底", "知识库结果不足，发送兜底回复。"),
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}),
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output("replyText", VariableTypeString, "Customer-visible reply text when the policy can answer directly."),
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output("reason", VariableTypeString, "Policy decision reason."),
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output("requiresFlow", VariableTypeBoolean, "Whether the decision should continue into workflow actions."),
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enumOutput("targetFlow", "目标流程", "Suggested target flow.", []VariableValueOption{
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valueOption("handoff_to_human", "转人工流程", "继续执行转人工节点。"),
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valueOption("prepare_ticket", "工单流程", "继续执行工单草稿和确认节点。"),
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valueOption("knowledge", "知识库流程", "继续执行知识检索节点。"),
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}),
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enumOutput("finalReplySource", "回复来源", "Source category for the final reply.", []VariableValueOption{
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valueOption("direct_reply", "策略直接回复", "由回复策略节点直接生成回复。"),
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valueOption("clarification", "追问回复", "用于追问客户补充信息。"),
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valueOption("handoff_notice", "转人工提示", "用于提示客户已进入人工处理。"),
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valueOption("ticket_result", "工单结果", "用于提示建单结果。"),
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valueOption("knowledge_answer", "知识库回答", "用于发送基于知识库生成的回复。"),
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valueOption("knowledge_fallback", "知识库兜底", "用于知识库信息不足时的兜底回复。"),
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}),
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},
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},
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NodeSpec{
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Type: NodeTypeKnowledgeRetrieve,
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Title: "Knowledge Retrieve",
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Description: "Retrieve knowledge for the current user message.",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("query", VariableTypeString, "Search query."),
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},
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OutputSchema: []VariableSpec{
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output("items", VariableTypeObjectArray, "Retrieved knowledge items."),
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output("summary", VariableTypeString, "Short retrieval summary."),
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},
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DefaultInputs: map[string]dsl.Value{
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"query": dsl.RefValue("start_1", "userMessage"),
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},
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},
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NodeSpec{
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Type: NodeTypeAnswerabilityGate,
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Title: "Answerability Gate",
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Description: "Decide whether retrieved knowledge is enough to answer.",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", VariableTypeString, "Current user message content."),
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requiredInput("knowledgeItems", VariableTypeObjectArray, "Retrieved knowledge items."),
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},
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OutputSchema: []VariableSpec{
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enumOutput("answerability", "可回答性", "Answerability decision.", []VariableValueOption{
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valueOption("answerable", "可以回答", "检索结果足够支撑回答。"),
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valueOption("unanswerable", "无法回答", "检索结果不足，应该走兜底或追问。"),
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}),
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output("reason", VariableTypeString, "Decision reason."),
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},
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},
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NodeSpec{
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Type: NodeTypeLLMReply,
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Title: "LLM Reply",
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Description: "Generate a reply or structured analysis with the configured model.",
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RiskLevel: NodeRiskLevelMedium,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", VariableTypeString, "Current user message content."),
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optionalInput("knowledgeItems", VariableTypeObjectArray, "Retrieved knowledge items."),
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},
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OutputSchema: []VariableSpec{
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output("replyText", VariableTypeString, "Generated reply text."),
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},
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},
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NodeSpec{
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Type: NodeTypeCondition,
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Title: "Condition",
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Description: "Route by controlled workflow variables.",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("matched", VariableTypeBoolean, "Whether the condition matched."),
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},
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},
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NodeSpec{
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Type: NodeTypeAnalyzeConversation,
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Title: "Analyze Conversation",
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Description: "Analyze intent, risk, and recommended next action.",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", VariableTypeString, "Current user message content."),
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},
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OutputSchema: []VariableSpec{
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output("intent", VariableTypeString, "Detected user intent."),
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output("riskLevel", VariableTypeString, "Detected risk level."),
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output("needTicket", VariableTypeBoolean, "Whether a ticket is recommended."),
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output("needHumanHandoff", VariableTypeBoolean, "Whether human handoff is recommended."),
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},
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},
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NodeSpec{
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Type: NodeTypePrepareTicketDraft,
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Title: "Prepare Ticket Draft",
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Description: "Build a ticket draft from conversation context.",
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RiskLevel: NodeRiskLevelMedium,
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InputSchema: []VariableSpec{
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requiredInput("issue", VariableTypeString, "Issue summary."),
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},
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OutputSchema: []VariableSpec{
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output("ticketDraft", VariableTypeObject, "Draft ticket payload."),
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},
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},
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NodeSpec{
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Type: NodeTypeHumanConfirm,
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Title: "Human Confirm",
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Description: "Interrupt and wait for explicit user confirmation.",
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RiskLevel: NodeRiskLevelMedium,
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Interruptible: true,
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InputSchema: []VariableSpec{
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requiredInput("prompt", VariableTypeString, "Confirmation prompt."),
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},
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OutputSchema: []VariableSpec{
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output("confirmed", VariableTypeBoolean, "Whether the user confirmed."),
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output("responseText", VariableTypeString, "Confirmation response text."),
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},
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},
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NodeSpec{
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Type: NodeTypeCreateTicket,
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Title: "Create Ticket",
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Description: "Create a ticket from a confirmed draft.",
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RiskLevel: NodeRiskLevelHigh,
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RequiresConfirmationPredecessor: true,
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InputSchema: []VariableSpec{
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requiredInput("ticketDraft", VariableTypeObject, "Confirmed draft ticket payload."),
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requiredInput("confirmed", VariableTypeBoolean, "Confirmation result."),
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},
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OutputSchema: []VariableSpec{
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output("ticketId", VariableTypeInteger, "Created ticket ID."),
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output("ticketNo", VariableTypeString, "Created ticket number."),
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output("created", VariableTypeBoolean, "Whether the ticket was created."),
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output("message", VariableTypeString, "Customer-visible ticket creation result."),
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},
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},
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NodeSpec{
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Type: NodeTypeHandoffToHuman,
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Title: "Handoff To Human",
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Description: "Transfer the conversation to human support.",
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RiskLevel: NodeRiskLevelHigh,
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InputSchema: []VariableSpec{
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requiredInput("reason", VariableTypeString, "Handoff reason."),
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optionalInput("confirmed", VariableTypeBoolean, "Confirmation result."),
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},
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OutputSchema: []VariableSpec{
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output("handoffId", VariableTypeInteger, "Handoff operation ID."),
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output("reason", VariableTypeString, "Handoff reason."),
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enumOutput("decision", "转人工结果", "Handoff dispatch decision.", []VariableValueOption{
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valueOption("assigned", "已分配客服", "已成功分配给人工客服。"),
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valueOption("team_pool", "团队队列等待", "暂未分配到客服，进入团队等待队列。"),
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valueOption("global_pool", "全局队列等待", "非服务时间或无可用团队，进入全局等待队列。"),
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valueOption("off_hours", "非服务时间", "当前不在人工客服服务时间内。"),
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valueOption("cancelled", "已取消转人工", "由于未确认或条件不满足，未执行转人工。"),
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}),
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output("teamId", VariableTypeInteger, "Assigned or pending team ID."),
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output("assigneeId", VariableTypeInteger, "Assigned agent user ID."),
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output("message", VariableTypeString, "Customer-visible handoff notice."),
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},
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},
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NodeSpec{
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Type: NodeTypeSendReply,
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Title: "Send Reply",
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Description: "Return or commit customer-visible reply text.",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("replyText", VariableTypeString, "Customer-visible reply text."),
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},
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OutputSchema: []VariableSpec{
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output("sent", VariableTypeBoolean, "Whether the reply was sent."),
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output("replyMessageId", VariableTypeInteger, "Reply message ID."),
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},
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},
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NodeSpec{
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Type: NodeTypeEnd,
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Title: "End",
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Description: "End workflow execution.",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("status", VariableTypeString, "Workflow terminal status."),
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},
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},
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)
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}
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func requiredInput(name string, variableType VariableType, description string) VariableSpec {
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return VariableSpec{Name: name, Type: variableType, Required: true, Description: description}
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}
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func optionalInput(name string, variableType VariableType, description string) VariableSpec {
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return VariableSpec{Name: name, Type: variableType, Description: description}
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}
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func output(name string, variableType VariableType, description string) VariableSpec {
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return VariableSpec{Name: name, Type: variableType, Description: description}
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}
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func enumOutput(name string, label string, description string, options []VariableValueOption) VariableSpec {
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return VariableSpec{
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Name: name,
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Label: label,
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Type: VariableTypeString,
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Description: description,
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Operators: []string{"eq", "neq"},
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ValueOptions: options,
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}
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}
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func valueOption(value any, label string, description string) VariableValueOption {
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return VariableValueOption{Value: value, Label: label, Description: description}
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}
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