mlogclub
371 lines
20 KiB
Go
371 lines
20 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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NodeTypeLLM = "llm"
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NodeTypeHTTP = "http"
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NodeTypeCode = "code"
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NodeTypeVariable = "variable"
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NodeTypeMultiCondition = "multi-condition"
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NodeTypeLoop = "loop"
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NodeTypeBlockStart = "block-start"
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NodeTypeBlockEnd = "block-end"
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NodeTypeComment = "comment"
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NodeTypeContinue = "continue"
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NodeTypeBreak = "break"
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NodeTypeGroup = "group"
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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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Icon: "PlayCircleIcon",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("conversationId", "会话 ID", VariableTypeInteger, "当前客户会话的内部编号。"),
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output("messageId", "消息 ID", VariableTypeInteger, "客户本轮消息的内部编号。"),
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output("aiAgentId", "AI Agent ID", VariableTypeInteger, "当前处理会话的 AI Agent 编号。"),
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output("userMessage", "用户消息", VariableTypeString, "客户本轮发送的原始消息内容。"),
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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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Icon: "MessageCircleIcon",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", "用户消息", VariableTypeString, "客户本轮发送的原始消息内容。"),
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},
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OutputSchema: []VariableSpec{
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output("normalizedMessage", "规范化消息", VariableTypeString, "经过清洗和规范化后的客户消息。"),
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enumOutput("messageIntent", "消息意图", "客户消息的意图分类。", []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", "系统建议采用的回复处理范围。", []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", "置信度", VariableTypeNumber, "意图和回复策略判断的置信度。"),
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output("riskSignals", "风险信号", VariableTypeStringArray, "识别到的投诉、升级、人工介入等风险线索。"),
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output("reason", "判断原因", VariableTypeString, "本次意图和回复策略判断的原因说明。"),
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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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Icon: "ShieldCheckIcon",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("messageIntent", "消息意图", VariableTypeString, "上游理解节点识别出的客户消息意图。"),
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requiredInput("answerScope", "回复策略", VariableTypeString, "上游理解节点建议采用的回复处理范围。"),
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optionalInput("userMessage", "用户消息", VariableTypeString, "客户本轮发送的原始消息内容。"),
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optionalInput("riskSignals", "风险信号", VariableTypeStringArray, "上游识别到的风险线索列表。"),
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optionalInput("answerability", "可回答性", VariableTypeString, "知识库结果是否足够支撑回答的判断。"),
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},
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OutputSchema: []VariableSpec{
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enumOutput("action", "处理策略", "回复策略节点选择的下一步处理动作。", []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", "回复内容", VariableTypeString, "可直接发送给客户的回复文本。"),
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output("reason", "策略原因", VariableTypeString, "选择当前处理策略的原因说明。"),
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output("requiresFlow", "需要继续流程", VariableTypeBoolean, "是否需要继续执行后续工作流节点。"),
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enumOutput("targetFlow", "目标流程", "建议继续执行的业务流程。", []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", "最终回复内容的来源类别。", []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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Icon: "BookOpenIcon",
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RiskLevel: NodeRiskLevelLow,
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ConfigSchema: map[string]any{
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"knowledgeBaseIds": map[string]any{
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"type": string(VariableTypeIntegerArray),
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"label": "知识库",
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"required": true,
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"description": "本节点检索时使用的知识库列表，按顺序表示优先级。",
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},
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},
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InputSchema: []VariableSpec{
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requiredInput("query", "检索问题", VariableTypeString, "用于检索知识库的客户问题或查询文本。"),
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},
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OutputSchema: []VariableSpec{
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output("items", "知识条目", VariableTypeObjectArray, "从知识库命中的原始知识条目列表。"),
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output("summary", "检索摘要", VariableTypeString, "对本次知识检索结果的简短摘要。"),
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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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Icon: "HelpCircleIcon",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", "用户消息", VariableTypeString, "客户本轮发送的原始消息内容。"),
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requiredInput("knowledgeItems", "知识条目", VariableTypeObjectArray, "上游知识检索节点命中的知识条目列表。"),
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},
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OutputSchema: []VariableSpec{
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enumOutput("answerability", "可回答性", "知识库结果是否足够支撑回答的判断。", []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", "判断原因", VariableTypeString, "可回答性判断的原因说明。"),
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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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Icon: "BotIcon",
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RiskLevel: NodeRiskLevelMedium,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", "用户消息", VariableTypeString, "客户本轮发送的原始消息内容。"),
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optionalInput("knowledgeItems", "知识条目", VariableTypeObjectArray, "可用于生成回复的知识库检索结果。"),
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},
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OutputSchema: []VariableSpec{
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output("replyText", "回复内容", VariableTypeString, "大模型生成的客户可见回复文本。"),
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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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Icon: "GitBranchIcon",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("matched", "是否命中", VariableTypeBoolean, "条件节点是否命中了某个条件分支。"),
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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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Icon: "SearchIcon",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("userMessage", "用户消息", VariableTypeString, "客户本轮发送的原始消息内容。"),
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},
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OutputSchema: []VariableSpec{
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output("intent", "用户意图", VariableTypeString, "从会话中识别出的客户意图。"),
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output("riskLevel", "风险等级", VariableTypeString, "本轮会话的风险等级判断。"),
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output("needTicket", "需要工单", VariableTypeBoolean, "是否建议进入工单处理流程。"),
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output("needHumanHandoff", "需要转人工", VariableTypeBoolean, "是否建议转人工客服处理。"),
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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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Icon: "ClipboardListIcon",
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RiskLevel: NodeRiskLevelMedium,
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InputSchema: []VariableSpec{
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requiredInput("issue", "问题摘要", VariableTypeString, "需要整理进工单的客户问题摘要。"),
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},
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OutputSchema: []VariableSpec{
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output("ticketDraft", "工单草稿", VariableTypeObject, "根据会话内容整理出的待确认工单草稿。"),
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output("ready", "草稿就绪", VariableTypeBoolean, "工单草稿是否已具备创建所需的关键信息。"),
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output("title", "工单标题", VariableTypeString, "工单草稿标题。"),
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output("description", "工单描述", VariableTypeString, "工单草稿描述。"),
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output("missingFields", "缺失字段", VariableTypeStringArray, "仍需客户补充的字段列表。"),
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output("followUpQuestions", "追问问题", VariableTypeStringArray, "用于补齐工单信息的追问问题。"),
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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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Icon: "UserCheckIcon",
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RiskLevel: NodeRiskLevelMedium,
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Interruptible: true,
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InputSchema: []VariableSpec{
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requiredInput("prompt", "确认提示", VariableTypeString, "发送给客户用于确认操作的提示文本。"),
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},
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OutputSchema: []VariableSpec{
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output("confirmed", "已确认", VariableTypeBoolean, "客户是否明确确认继续执行。"),
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output("responseText", "确认回复", VariableTypeString, "客户针对确认提示给出的回复文本。"),
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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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Icon: "TicketIcon",
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RiskLevel: NodeRiskLevelHigh,
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RequiresConfirmationPredecessor: true,
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InputSchema: []VariableSpec{
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requiredInput("ticketDraft", "工单草稿", VariableTypeObject, "已经由客户确认的工单草稿内容。"),
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requiredInput("confirmed", "已确认", VariableTypeBoolean, "客户是否已确认创建工单。"),
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},
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OutputSchema: []VariableSpec{
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output("ticketId", "工单 ID", VariableTypeInteger, "创建成功后的工单内部编号。"),
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output("ticketNo", "工单编号", VariableTypeString, "创建成功后的客户可见工单编号。"),
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output("created", "已创建", VariableTypeBoolean, "工单是否已经成功创建。"),
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output("message", "结果消息", VariableTypeString, "发送给客户的工单创建结果说明。"),
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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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Icon: "HeadphonesIcon",
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RiskLevel: NodeRiskLevelHigh,
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RequiresConfirmationPredecessor: true,
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InputSchema: []VariableSpec{
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requiredInput("reason", "转人工原因", VariableTypeString, "触发转人工处理的业务原因。"),
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requiredInput("confirmed", "已确认", VariableTypeBoolean, "客户是否已确认转人工。"),
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},
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OutputSchema: []VariableSpec{
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output("handoffId", "转人工记录 ID", VariableTypeInteger, "本次转人工操作的内部记录编号。"),
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output("reason", "转人工原因", VariableTypeString, "本次转人工处理的原因说明。"),
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enumOutput("decision", "转人工结果", "转人工分配或排队结果。", []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", "客服组 ID", VariableTypeInteger, "已分配或等待中的客服组编号。"),
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output("assigneeId", "客服 ID", VariableTypeInteger, "已分配的人工客服用户编号。"),
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output("message", "转人工提示", VariableTypeString, "发送给客户的转人工结果提示。"),
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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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Icon: "SendIcon",
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RiskLevel: NodeRiskLevelLow,
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InputSchema: []VariableSpec{
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requiredInput("replyText", "回复内容", VariableTypeString, "将发送或返回给客户的最终回复文本。"),
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},
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OutputSchema: []VariableSpec{
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output("sent", "已发送", VariableTypeBoolean, "回复是否已经成功发送或返回。"),
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output("replyMessageId", "回复消息 ID", VariableTypeInteger, "发送成功后的回复消息编号。"),
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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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Icon: "FlagIcon",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("status", "结束状态", VariableTypeString, "工作流执行结束时的状态。"),
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},
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},
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NodeSpec{
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Type: NodeTypeLLM,
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Title: "LLM",
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Description: "Call the large language model and generate responses.",
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RiskLevel: NodeRiskLevelLow,
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OutputSchema: []VariableSpec{
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output("result", "Result", VariableTypeString, "The generated model response."),
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},
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},
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officialNodeSpec(NodeTypeHTTP, "HTTP", "Send an HTTP request."),
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officialNodeSpec(NodeTypeCode, "Code", "Run JavaScript code."),
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officialNodeSpec(NodeTypeVariable, "Variable", "Assign workflow variables."),
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officialNodeSpec(NodeTypeMultiCondition, "Multi Condition", "Route through multiple condition branches."),
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officialNodeSpec(NodeTypeLoop, "Loop", "Iterate over an array in a sub-canvas."),
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officialNodeSpec(NodeTypeBlockStart, "Block Start", "Start a container block."),
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officialNodeSpec(NodeTypeBlockEnd, "Block End", "End a container block."),
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officialNodeSpec(NodeTypeComment, "Comment", "Add a canvas annotation."),
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officialNodeSpec(NodeTypeContinue, "Continue", "Continue the current loop."),
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officialNodeSpec(NodeTypeBreak, "Break", "Break the current loop."),
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officialNodeSpec(NodeTypeGroup, "Group", "Group related workflow nodes."),
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)
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}
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func officialNodeSpec(nodeType string, title string, description string) NodeSpec {
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return NodeSpec{
|
|
Type: nodeType,
|
|
Title: title,
|
|
Description: description,
|
|
Icon: "",
|
|
RiskLevel: NodeRiskLevelLow,
|
|
}
|
|
}
|
|
|
|
func requiredInput(name string, label string, variableType VariableType, description string) VariableSpec {
|
|
return VariableSpec{Name: name, Label: label, Type: variableType, Required: true, Description: description}
|
|
}
|
|
|
|
func optionalInput(name string, label string, variableType VariableType, description string) VariableSpec {
|
|
return VariableSpec{Name: name, Label: label, Type: variableType, Description: description}
|
|
}
|
|
|
|
func output(name string, label string, variableType VariableType, description string) VariableSpec {
|
|
return VariableSpec{Name: name, Label: label, Type: variableType, Description: description}
|
|
}
|
|
|
|
func enumOutput(name string, label string, description string, options []VariableValueOption) VariableSpec {
|
|
return VariableSpec{
|
|
Name: name,
|
|
Label: label,
|
|
Type: VariableTypeString,
|
|
Description: description,
|
|
Operators: []string{"eq", "neq"},
|
|
ValueOptions: options,
|
|
}
|
|
}
|
|
|
|
func valueOption(value any, label string, description string) VariableValueOption {
|
|
return VariableValueOption{Value: value, Label: label, Description: description}
|
|
}
|