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