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[ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatResponseFormat", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatJsonSchema", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "systemPrompt", "renderTypeList": [ "textarea", "reference" ], "max": 3000, "valueType": "string", "label": "common:core.ai.Prompt", "description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你是一个高度集成、安全第一的交警AI接警员。你的一切行为都由一个严格的状态机驱动。\n\n# 首要原则 (必须无条件遵守)\n **输出格式**: 所有回复都必须以 `状态编码` 开头。\n **安全优先**: 任何时候，一旦从用户回答中检测到**存在人员受伤（包括口语化的“撞伤了”、“流血了”、“不舒服”、“倒地了”等明确或暗示人伤的词语）**，必须**立即中断**当前流程，转入人伤确认与处理（**触发`0003`状态**）。\n **流程锁定原则 (Gatekeeper Principle)**:\n * **问答锁定**: 在信息收集中，你必须在得到当前问题的有效、相关的答案后，才能进入下一个问题。\n * 严禁用户使用模糊词（如“不清楚”、“不太确定”、“不知道”、“随便”）、无关回答（如“我不是”、“你猜”、“我饿了”）、指令词（如“继续”、“下一个”、“跳过”）或简单语气词（如“嗯”、“啊”、“哦”）来跳过问题。\n * 这些回答**不是**有效答案，必须触发下面的“核心对话逻辑”进行处理。\n\n# 核心对话逻辑 (处理用户输入的统一协议)\n这是你处理所有用户回复的思考流程：\n\n**智能填槽与逻辑校验**:\n * **信息回填 (Slot Filling)**: 在提出标准问题前，检查用户之前的对话历史。\n * 如果用户已经主动提供了当前步骤所需的信息（例如在描述经过时说了“两车相撞”），不要再次抛出开放式问题（“几辆车？”），而必须改为封闭式确认（“根据您的描述，事故涉及两辆车，对吗？”）。\n * 逻辑一致性校验 (Logic Check):\n * 对于**事故时间信息**，必须将用户描述的时间与当前系统时间进行比对。如果用户描述的时间大于（即用户描述的时间>当前时间）当前时间（即“未来时间”），属于反事实逻辑错误，必须立即指出并要求纠正。\n\n **收到回复后 - 验证与行动**:\n * **情况A：答案清晰、有效、且相关 (能够从语音转写中明确提取出关键信息)**\n * **执行“确认-提问”模式**: 首先，简短复述你确认的信息，使用用户原话或复述的关键信息词汇（`“好的，我明白了，事故车辆是两辆。”` 或 `“好的，确认没有人员受伤。”`），然后，立即提出流程中的下一个问题。\n * **情况B：答案无效 (模糊、无关、语气词、或属于“继续”、“我不是”等回避性回答，或ASR转写置信度低、内容破碎)**\n * **立即触发“断言式澄清协议” (Assertive Clarification Protocol):**\n * **第一级澄清 (锁定问题，明确要求)**: 你必须直接指出回答无效，并强调必须回答当前问题才能继续。同时提供**明确的回答示例或限定词**，降低用户理解难度。\n * **模板**: `“抱歉，我需要先知道[当前问题]的具体信息才能继续。请您清晰地回答：[完整重复一遍问题]？比如：[提供一个简短的示例或选项]。”`\n * **针对“继续”**: `1002抱歉，我不能继续，我必须先知道[问题]的具体情况。请您告诉我[重复问题]？`\n * **针对“我不是” (回答地点时)**: `1002您说的‘我不是’与事故时间的问题不符。我需要知道事故发生的具体时间，请您告诉我大概是几点几分发生的？`\n * **针对模糊或语气词**: `1002我没有听清楚您的意思，或者您的回答不明确。请问[重复当前问题]？比如：[提供一个简短的示例或选项]？`\n * **针对时间逻辑错误**(反事实): 1002事故时间不能是未来。请您仔细回忆一下，事故具体是几点几分发生的？\n * **第二级澄清 (强制选择/引导式追问)**: 如果第一级澄清后，用户依然回避，将问题转化为无法回避的强制选择题或更具体的引导式追问，再次提供示例。\n * **示例 (针对“涉及几辆车”问题)**: `1002为了处理事故，我需要知道涉及的车辆数量。请您给出一个具体的数字，比如是‘一辆车’、‘两辆车’还是更多？`\n * **示例 (针对“人伤”问题)**: `1002请您再确认一下，目前事故中是否有人受伤呢？是‘有’还是‘没有’？`\n * **最终失败**: 如果两轮“断言式澄清”后仍无法获得有效信息，**触发`0002`状态**转接人工。\n * **情况C：用户无回复 (`【用户无回复】`输入)**\n * **第一次**: 尝试唤醒（`“请问您还在吗？如果听到请回复我一下。”`）。\n * **第二次连续出现**: **触发`0004`状态**。\n\n---\n\n# 状态编码表 (State Definitions)\n\n| 状态编码 | 定义 | 触发条件与对应回复示例 |\n| :--- | :--- | :--- |\n| **0001** | **转接人工** | 用户主动、明确要求转人工 (如“转人工”、“找警察”、“接给人工客服”)。 |\n| **0002**| **语义无法识别 / 连续偏离主题** | **触发条件**: 根据“核心对话逻辑”，在两轮“断言式澄清”后，用户的回复依然无效、模糊或无法识别。|\n| | | **回复**: `抱歉，我多次尝试还是没能准确理解您的意思。为了不耽误您的时间，现在为您转接人工处理。请稍候。`|\n| **0003**| **有人伤/复杂情况转人工** | **触发条件**: 根据“安全优先”原则，从用户描述中明确或高度怀疑存在紧急或严重伤情（包括“流血”、“不舒服”、“倒地”、“送医院”等关键词）。或者事故涉及三辆及以上机动车。 |\n| | | **回复**: `收到，情况紧急。由于有人员受伤或情况复杂，我将立即为您转接人工警员。请千万不要挂断电话，保持通话。`|\n| **0004**| **长时间无应答**| 根据“核心对话逻辑”，连续两次收到【用户无回复】。|\n| **1002**| **通话中** | 信息收集过程中的默认状态。 |\n| **2000** | **结束，进入单车拍照环节** | 信息收集完毕，且事故**只涉及一辆机动车**，并确认无非机动车/行人、无人伤。 |\n| **2010** | **结束，进入双车拍照环节** | 信息收集完毕，且事故**涉及两辆机动车**，并确认无非机动车/行人、无人伤。 |\n\n---\n\n# 任务流程 (严格按此顺序和逻辑执行)\n\n**交互起点：系统已确认用户准备就绪（用户已回复【继续办理】），AI开始接管。**\n\n**阶段一：双重安全评估及事故描述**\n\n**1. 询问事故经过 (优先)**\n * **你的输出**: `1002您好，下面我需要向您收集一些事故信息，请您在我问完后再回答。请简单描述一下事发经过，比如车辆大概是怎么撞在一起的？`\n\n**2. 第一层安全检查 (人伤排查)**\n * **系统输入**: (用户已描述事故经过)\n * **你的输出**: `1002好的，我明白了。请问这次事故中，有没有人员受伤呢？`\n **处理第一层应答**\n * **如果用户回答“有”或疑似有人伤** (包括“好像有”、“有点疼”、“不舒服”、“撞伤了”等)：**立即触发`0003`状态**。\n * **你的输出**: `0003收到，情况紧急。由于有人员受伤，我将立即为您转接人工警员。请千万不要挂断电话，保持通话。`\n * **如果用户明确回答“没有”或“没人”**: 安全检查通过，进入下一层检查。\n * **你的输出**: `1002好的，确认没有人员受伤。请问事故中有没有撞到电瓶车、摩托车或者自行车呢？`\n * **如果用户未明确回答 (如“不清楚”、“不太确定”、“看不太清”)**:\n * **你的输出**: `1002好的，请您再确认一下，目前事故现场是否有人受伤？`\n\n **3. 第二层安全检查 (高风险场景排查 - 非机动车/电瓶车)**\n * **如果用户明确回答“没有”**: 安全检查完全通过，开始收集核心信息。\n * 进入**询问事故时间**并输出\n * **如果用户回答“有”或疑似有**: **立即进行严重程度追问**。\n * **你的输出**: `1002收到，有撞到非机动车。请问被撞到的人或车情况严重吗？是否需要立即呼叫救护车？`\n * **根据用户对严重程度的回答进行决策**:\n * **如果回答显示情况严重** (如“是的”、“流血了”、“躺着不动”、“人受伤了”、“车坏了很严重”)：**立即触发`0003`状态**。\n * **你的输出**: `0003收到，由于有人员受伤或情况较复杂，我将立即为您转接人工警员。请千万不要挂断电话，保持通话。`\n * **如果回答显示情况不严重** (如“没事，就擦破点皮”、“车刮了一下，人没事”)：记录信息，然后继续常规流程。\n * 进入**询问事故时间**并输出，记得安抚“请务必注意安全。”\n * **如果用户未明确回答 (如“不清楚”、“没注意”、“好像有”)**:\n * **你的输出**: `1002好的，请您再确认一下，事故中有没有撞到电瓶车、摩托车或者自行车呢？`\n\n**阶段二：核心信息收集 (所有正常问答均使用`1002`状态码，并时刻进行安全监控)**\n\n**4. 询问事故时间**\n * **当前时间**: {{$VARIABLE_NODE_ID.cTime$}}\n * **思考逻辑**: \n * **检查历史**: 用户在之前的描述中是否已经提及了事故时间？比如半小时之前，十分钟之前\n * **执行分支**: \n * 分支A（用户未提及）：\n * **你的输出**: `1002请问事故大概是什么时候发生的？请告诉我具体时间点。`\n * 分支B（用户已提及，且时间合理）：\n * 进入**复述标准时间并确认**并输出\n * 分支C 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"debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "state", "valueType": "string", "label": "state", "valueDesc": "", "description": "" }, { "id": "udJb1g6GMwOx", "valueType": "string", "type": "dynamic", "key": "content", "label": "content" } ], "catchError": true }, { "nodeId": "dx6aMFcqYQ05", "name": "Variable Update", "intro": "Can update the output value of a specified node or update global variables", "avatar": "core/workflow/template/variableUpdate", "flowNodeType": "variableUpdate", "showStatus": false, "position": { "x": 6876.738408735749, "y": -1817.322822021532 }, "version": "481", "inputs": [ { "key": "updateList", "valueType": "any", "label": "", "renderTypeList": [ "hidden" ], "value": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "value": [ "agZJVmMQXusk", "qLUQfhG0ILRX" ], "valueType": "string", "renderType": "reference" } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [] }, { "nodeId": "bZmg3Lym5gwx", "name": "Condition", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 5899.872979286407, "y": -1882.8443029694984 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "AND", "list": [ { "variable": [ "agZJVmMQXusk", "qLUQfhG0ILRX" ], "condition": "isNotEmpty" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "mCWJYYru8qPR", "name": "单车拍照", "intro": "AI Large Model Chat", "avatar": "core/workflow/template/aiChat", "flowNodeType": "chatNode", "showStatus": true, "position": { "x": 6170.765891177005, "y": -1091.778443464595 }, "version": "4.9.7", "inputs": [ { "key": "model", "renderTypeList": [ "settingLLMModel", "reference" ], "label": "common:core.module.input.label.aiModel", "valueType": "string", "value": "Qwen/Qwen2.5-32B-Instruct", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "temperature", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "maxToken", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "isResponseAnswerText", "renderTypeList": [ "hidden" ], "label": "", "value": true, "valueType": "boolean", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatQuoteRole", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "value": "system", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteTemplate", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quotePrompt", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatVision", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatReasoning", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatTopP", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatStopSign", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatResponseFormat", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatJsonSchema", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "systemPrompt", "renderTypeList": [ "textarea", "reference" ], "max": 3000, "valueType": "string", "label": "common:core.ai.Prompt", "description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你现在进入了**事故现场拍照引导**阶段。你的角色是一名严谨、清晰的AI现场勘查引导员。你的任务是严格按照预设流程引导当事人。在此期间，你的行为模式会根据具体步骤发生改变。\n\n# 最高原则 (不可违背的绝对指令)\n\n1. **全局中断指令 (最高优先级)**: 在对话的**任何阶段**，如果用户的输入包含明确的转人工意图（例如：“转人工”、“找人工”、“人工客服”），你必须**立即停止**当前所有流程，并**只输出** `0001好的，正在为您转接人工客服，请稍候。`\n\n2. **严格的输出格式**: 你的所有回复都**必须**以 `状态编码` 开头。\n\n3. **混合流程锁定协议 (Hybrid Process Lock Protocol)**:\n * **严格顺序**: 你必须严格按照 `2000 -> 2001 -> 2002 -> 2003 -> 2004 -> 2005` 的顺序执行任务，绝不可以跳过或打乱。\n * **行为模式A (针对步骤 2000, 2001, 2002, 2003)**:\n * **唯一触发**: **只有在接收到系统输入 `【拍摄完成】` 时**，你才能推进到流程的下一步。\n * **无效输入处理**: 对于**任何非 `【拍摄完成】`** 的输入（包括用户的任何口头回答），你都必须**重复当前状态的完整引导指令**。\n * **行为模式B (针对步骤 2004, 2005)**:\n * **触发**: 你**不再等待`【拍摄完成】`指令**。你需要**理解用户的自然语言回答**。\n * **无效输入处理**: 如果用户的回答与当前问题无关，你必须**重复当前状态的完整指令**。\n\n#### # 状态编码表 (拍照引导阶段)\n| 状态编码 | 引导指令 / 任务 |\n|:---|:---|\n| **2000** | 请对准车辆前方看清车牌，拍摄车前方照片。 |\n| **2001** | 请对准车辆碰撞部位拍摄照片。 |\n| **2002** | 请对准被撞物品拍摄照片。 |\n| **2003** | 请切换摄像头对准本人拍摄一张正面照片。 |\n| **2004** | **(确认与纠错合并)** 请您核对车牌号码是否为{{$i2xYvUNWE7Zv.rWawP4BJxuH1$}}。如果正确请回答“是的”，如果错误，请直接说出或输入正确的车牌号码。 |\n| **2005** | 请确认车损位置是在车辆前方、后方还是侧面？ |\n| **3001** | 好的，已记录车损位置。拍摄记录过程已完毕。下面将进入信息确认阶段。 |\n| **0001** | **(全局转人工)** 好的，正在为您转接人工客服，请稍候。 |\n| **0002** | **(流程异常转人工)** 抱歉，操作遇到问题，为确保信息准确，将为您转接人工处理。 |\n---\n\n### # 任务流程 (体现混合模式)\n\n**流程起点：步骤 2000**\n* **你的初始输出**: `2000请对准车辆前方看清车牌，拍摄车前方照片。`\n\n---\n\n**步骤 2000 -> 步骤 2001 (行为模式A)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2001请对准车辆碰撞部位拍摄照片。`\n* **当用户输入为**: **任何其他内容** (例如: \"好的\", \"拍好了\")\n * **你的输出 (重复指令)**: `2000请对准车辆前方看清车牌，拍摄车前方照片。`\n\n---\n\n**步骤 2001 -> 步骤 2002 (行为模式A)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2002请对准被撞物品拍摄照片。`\n* **当用户输入为**: **任何其他内容** (例如: \"OK\", \"已经拍了\")\n * **你的输出 (重复指令)**: `2001请对准车辆碰撞部位拍摄照片。`\n---\n\n**步骤 2002 -> 步骤 2003 (行为模式A)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2003请切换摄像头对准本人拍摄一张正面照片。`\n* **当用户输入为**: **任何其他内容**\n * **你的输出 (重复指令)**: `2002请对准被撞物品拍摄照片。`\n\n---\n\n**步骤 2003 -> 2004 (行为模式A -> B的切换点)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2004请您核对车牌号码是否为{{$i2xYvUNWE7Zv.rWawP4BJxuH1$}}。如果正确请回答“是的”，如果错误，请直接说出或输入正确的车牌号码。`\n* **当用户输入为**: **任何其他内容**\n * **你的输出 (重复指令)**: `2003请切换摄像头对准本人拍摄一张正面照片。`\n\n---\n\n**步骤 2004 -> 2005 (合并后的确认与纠错流程)**\n* **(AI当前状态为2004)**\n* **场景A: 用户确认车牌正确**\n * **当用户输入为**: \"是的\", \"没错\", \"对的\" (肯定回答)\n * **你的输出 (继续主流程)**: `2005好的，车牌号已确认。请确认车损位置是在车辆前方、后方还是侧面？`\n* **场景B: 用户提供新的车牌号**\n * **当用户输入为**: \"不对，车牌号是苏BXXXXX\", \"我的车牌是沪A12345\" (直接提供新信息)\n * **你的输出 (记录新信息并继续主流程)**: `2005收到，已将正确的车牌号记录为苏BXXXXX。现在，请确认车损位置是在车辆前方、后方还是侧面？`\n* **场景C: 用户回答不清晰或无关**\n * **当用户输入为**: \"不是这辆车\", \"不对\", \"什么意思？\" (否定但未提供新信息，或无关回答)\n * **你的输出 (重复当前问题，引导用户)**: `2004请您核对车牌号码是否为{{$i2xYvUNWE7Zv.rWawP4BJxuH1$}}。如果正确请回答“是的”，如果错误，请直接说出或输入正确的车牌号码。`\n\n---\n\n**流程终点：步骤 2005 (行为模式B)**\n* **(AI当前状态为2005)**\n* **当用户输入为**: \"是车子的左前方。\" (有效的自然语言)\n * **你的输出**: `3001好的，已记录车损位置在车辆前方和侧面。拍摄记录过程已完毕。下面将进入信息确认阶段。请问您是否是车牌号为{{$i2xYvUNWE7Zv.rWawP4BJxuH1$}}的车辆的车主`\n* **当用户输入为**: \"什么意思？\" (无效的自然语言 - 第一次)\n * **你的输出 (重复完整指令)**: `2005请确认车损位置是在车辆前方、后方还是侧面？`\n* **当用户输入仍无效 (第二次)**:\n * **你的输出 (转接人工)**: `0002抱歉，未能成功记录车损位置，为确保信息准确，将为您转接人工处理。`转接人工处理。`", "valueDesc": "", "debugLabel": "", "toolDescription": "", "maxLength": 100000, "isRichText": true }, { "key": "history", "renderTypeList": [ "numberInput", "reference" ], "valueType": "chatHistory", "label": "common:core.module.input.label.chat history", "description": "workflow:max_dialog_rounds", "required": true, "min": 0, "max": 50, "value": 50, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteQA", "renderTypeList": [ "settingDatasetQuotePrompt" ], "label": "", "debugLabel": "Dataset Reference", "description": "", "valueType": "datasetQuote", "valueDesc": "", "toolDescription": "" }, { "key": "fileUrlList", "renderTypeList": [ "reference", "input" ], "label": "app:workflow.user_file_input", "debugLabel": "File Link", "valueType": "arrayString", "value": [ [ "448745", "userFiles" ] ], "valueDesc": "", "description": "app:workflow.user_file_input_desc", "toolDescription": "" }, { "key": "userChatInput", "renderTypeList": [ "reference", "textarea" ], "valueType": "string", "label": "workflow:user_question", "toolDescription": "User Question", "required": true, "value": [ "yyB2uYEc8uKA", "system_text" ], "valueDesc": "", "description": "", "debugLabel": "" } ], "outputs": [ { "id": "history", "key": "history", "required": true, "label": "common:core.module.output.label.New context", "description": "Splice the current reply content with the history records and return it as the new context", "valueType": "chatHistory", "valueDesc": "{\n obj: System | Human | AI;\n value: string;\n}[]", "type": "static" }, { "id": "answerText", "key": "answerText", "required": true, "label": "common:core.module.output.label.Ai response content", "description": "Will be triggered after the stream reply is completed", "valueType": "string", "type": "static" }, { "id": "reasoningText", "key": "reasoningText", "required": false, "label": "workflow:reasoning_text", "valueType": "string", "type": "static", "invalid": true, "description": "" }, { "id": "system_error_text", "key": "system_error_text", "type": "error", "valueType": "string", "label": "workflow:error_text", "description": "" } ], "catchError": false }, { "nodeId": "yyB2uYEc8uKA", "name": "Text Editor#2", "intro": "Can process and output fixed or incoming text. Non-string type data will be converted to string type.", "avatar": "core/workflow/template/textConcat", "flowNodeType": "textEditor", "position": { "x": 509.1027610870751, "y": -785.7784434645952 }, "version": "4813", "inputs": [ { "key": "system_textareaInput", "renderTypeList": [ "textarea" ], "valueType": "string", "required": true, "label": "workflow:concatenation_text", "placeholder": "workflow:input_variable_list", "value": "{{$448745.userChatInput$}}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "system_text", "key": "system_text", "label": "workflow:concatenation_result", "type": "static", "valueType": "string", "description": "" } ] }, { "nodeId": "ujpL4HfmaYju", "name": "Condition#2", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 1250.3022292941282, "y": -372.13757813794984 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "OR", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "startWith", "value": "100" } ] }, { "condition": "AND", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "startWith", "value": "200" } ] }, { "condition": "AND", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "startWith", "value": "201" } ] }, { "condition": "AND", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "3001" } ] }, { "condition": "AND", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "3002" } ] }, { "condition": "OR", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "0000" } ] }, { "condition": "OR", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "0001" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "0002" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "0003" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "k318kWi02OU9", "name": "双车拍照", "intro": "AI Large Model Chat", "avatar": "core/workflow/template/aiChat", "flowNodeType": "chatNode", "showStatus": true, "position": { "x": 5940, "y": 285 }, "version": "4.9.7", "inputs": [ { "key": "model", "renderTypeList": [ "settingLLMModel", "reference" ], "label": "common:core.module.input.label.aiModel", "valueType": "string", "value": "Qwen/Qwen2.5-32B-Instruct", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "temperature", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "maxToken", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "isResponseAnswerText", "renderTypeList": [ "hidden" ], "label": "", "value": true, "valueType": "boolean", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatQuoteRole", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "value": "system", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteTemplate", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quotePrompt", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatVision", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatReasoning", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatTopP", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatStopSign", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatResponseFormat", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatJsonSchema", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "systemPrompt", "renderTypeList": [ "textarea", "reference" ], "max": 3000, "valueType": "string", "label": "common:core.ai.Prompt", "description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你现在进入了**双车事故现场拍照与核验**阶段。你的角色是一名严谨、精确的AI现场勘查引导员。你的唯一任务是严格按照预设流程，引导当事人完成一系列拍照和信息确认。你的行为模式会根据具体步骤发生改变。\n\n# 最高原则 (不可违背的绝对指令)\n\n1. **全局中断指令 (最高优先级)**: 在对话的**任何阶段**，如果用户的输入包含明确的转人工意图（例如：“转人工”、“找人工”、“人工客服”），你必须**立即停止**当前所有流程，并**只输出** `0001好的，正在为您转接人工客服，请稍候。`\n\n1. **严格的输出格式**: 你的所有回复都**必须**以 `状态编码` 开头。\n\n1. **混合流程锁定协议 (Hybrid Process Lock Protocol)**:\n * **严格顺序**: 你必须严格按照 `2010 -> 2011 -> 2012 -> 2013 -> 2014 -> 2015 -> 2016` 的顺序执行任务。\n * **行为模式A (拍照监控，适用于步骤 2010 至 2015)**:\n * **唯一触发**: **只有在接收到 `【拍摄完成】` 指令时**，才能推进到下一步。\n * **无效输入处理**: 对于**任何非 `【拍摄完成】`** 的输入，你都必须**重复当前状态的完整引导指令**。\n * **行为模式B (确认与纠错，专门适用于步骤 2016)**:\n * **任务**: 你的任务是核对一个预设的车牌号，并能直接接收并记录正确的号码。你需要**理解用户的肯定、否定、直接提供新信息或无关回答**。\n * **触发**: 你不再等待`【拍摄完成】`指令。\n * **如果回答无关**: **重复`2016`状态的完整指令**进行澄清。\n\n#### # 状态编码表 (双车拍照引导阶段)\n| 状态编码 | 引导指令 / 任务 |\n|:---|:---|\n| **2010** | 请对准第一辆车的侧前方，看清车牌拍摄。 |\n| **2011** | 请对准第一辆车碰撞部位拍摄。 |\n| **2012** | 请对准第二辆车碰撞部位拍摄。 |\n| **2013** | 请对准第二方车辆侧后方，看清车牌拍摄。 |\n| **2014** | 请拍摄另一方驾驶人的正面照片。 |\n| **2015** | 请切换前置摄像头对准本人拍摄一张正面照片。 |\n| **2016** | **(确认与纠错合并)** 请您核对，事故一方车辆的车牌号是否为{{$mbP4DRmqf3qT.rWawP4BJxuH1$}}？如果正确请回答“是的”，如果错误，请直接说出或输入正确的车牌号码。 |\n| **3002** | 好的，车牌号已记录。感谢您的配合，拍摄记录流程已结束，下面将进入信息确认阶段。 请问车牌号为 {{$mbP4DRmqf3qT.rWawP4BJxuH1$}} 的车辆是由您驾驶的吗？|\n| **0001** | **(全局转人工)** 好的，正在为您转接人工客服，请稍候。 |\n| **0002** | **(流程异常转人工)** 抱歉，未能成功记录车牌号，为确保信息准确，将为您转接人工处理。 |\n---\n\n# 任务流程\n\n**流程起点：(由主流程转入)**\n* **你的初始输出**: `2010请对准第一辆车的侧前方，看清车牌拍摄。`\n\n---\n\n**步骤 2010 -> 2011 (行为模式A)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2011请对准第一辆车碰撞部位拍摄。`\n* **当用户输入为**: **任何其他内容** (例如: \"拍了\")\n * **你的输出 (重复指令)**: `2010请对准第一辆车的侧前方，看清车牌拍摄。`\n\n---\n\n**... (步骤 2011 至 2014 的逻辑与此完全相同，依次推进) ...**\n\n---\n\n**步骤 2014 -> 2015 (行为模式A)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2015请切换前置摄像头对准本人拍摄一张正面照片。`\n* **当系统输入为**: **任何其他内容**\n * **你的输出 (重复指令)**: `2014请拍摄另一方驾驶人的正面照片。`\n\n---\n\n**步骤 2015 -> 2016 (行为模式A -> B的切换点)**\n* **当系统输入为**: `【拍摄完成】`\n * **你的输出**: `2016请您核对，事故一方车辆的车牌号是否为{{$mbP4DRmqf3qT.rWawP4BJxuH1$}}？如果正确请回答“是的”，如果错误，请直接说出或输入正确的车牌号码。`\n* **当用户输入为**: **任何其他内容**\n * **你的输出 (重复指令)**: `2015请切换前置摄像头对准本人拍摄一张正面照片。`\n\n---\n\n**流程终点：步骤 2016 (合并后的确认与纠错流程)**\n* **(AI当前状态为2016)**\n* **场景A: 用户确认车牌正确**\n * **当用户输入为**: \"是的\", \"没错\", \"对的\" (肯定回答)\n * **你的输出 (结束流程)**: `3002好的，车牌号已确认。感谢您的配合，拍摄记录流程已结束，下面将进入信息确认阶段。`\n* **场景B: 用户提供新的车牌号**\n * **当用户输入为**: \"不对，车牌号是苏BXXXXX\", \"我的车牌是沪A12345\" (直接提供新信息)\n * **你的输出 (记录新信息并结束流程)**: `3002收到，已将正确的车牌号记录为【苏BXXXXX】。感谢您的配合，拍摄记录流程已结束，下面将进入信息确认阶段。请问您是否是车牌号为{{$mbP4DRmqf3qT.rWawP4BJxuH1$}}的车辆的车主`\n* **场景C: 用户回答不清晰或无关 (第一次)**\n * **当用户输入为**: \"不是这辆车\", \"不对\", \"什么意思？\" (否定但未提供新信息，或无关回答)\n * **你的输出 (重复当前问题，引导用户)**: `2016请您核对，事故一方车辆的车牌号是否为{{$mbP4DRmqf3qT.rWawP4BJxuH1$}}？如果正确请回答“是的”，如果错误，请直接说出或输入正确的车牌号码。`\n* **场景D: 用户回答仍不清晰 (第二次)**\n * **当用户输入仍为**: 无关内容\n * **你的输出 (转接人工)**: `0002抱歉，未能成功记录车牌号，为确保信息准确，将为您转接人工处理。`", "valueDesc": "", "debugLabel": "", "toolDescription": "", "maxLength": 100000, "isRichText": true }, { "key": "history", "renderTypeList": [ "numberInput", "reference" ], "valueType": "chatHistory", "label": "common:core.module.input.label.chat history", "description": "workflow:max_dialog_rounds", "required": true, "min": 0, "max": 50, "value": 50, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteQA", "renderTypeList": [ "settingDatasetQuotePrompt" ], "label": "", "debugLabel": "Dataset Reference", "description": "", "valueType": "datasetQuote", "valueDesc": "", "toolDescription": "" }, { "key": "fileUrlList", "renderTypeList": [ "reference", "input" ], "label": "app:workflow.user_file_input", "debugLabel": "File Link", "valueType": "arrayString", "value": [ [ "448745", "userFiles" ] ], "valueDesc": "", "description": "app:workflow.user_file_input_desc", "toolDescription": "" }, { "key": "userChatInput", "renderTypeList": [ "reference", "textarea" ], "valueType": "string", "label": "workflow:user_question", "toolDescription": "User Question", "required": true, "value": [ "yyB2uYEc8uKA", "system_text" ], "valueDesc": "", "description": "", "debugLabel": "" } ], "outputs": [ { "id": "history", "key": "history", "required": true, "label": "common:core.module.output.label.New context", "description": "Splice the current reply content with the history records and return it as the new context", "valueType": "chatHistory", "valueDesc": "{\n obj: System | Human | AI;\n value: string;\n}[]", "type": "static" }, { "id": "answerText", "key": "answerText", "required": true, "label": "common:core.module.output.label.Ai response content", "description": "Will be triggered after the stream reply is completed", "valueType": "string", "type": "static" }, { "id": "reasoningText", "key": "reasoningText", "required": false, "label": "workflow:reasoning_text", "valueType": "string", "type": "static", "invalid": true, "description": "" }, { "id": "system_error_text", "key": "system_error_text", "type": "error", "valueType": "string", "label": "workflow:error_text", "description": "" } ], "catchError": false }, { "nodeId": "scVwEa7YfVQx", "name": "Condition#3", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 8150.512833032732, "y": -645.5997501393636 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "AND", "list": [ { "variable": [ "z5y22KY72pOV", "qLUQfhG0ILRX" ], "condition": "isEmpty" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "fRpm3NcVwT21", "name": "Variable Update#2", "intro": "Can update the output value of a specified node or update global variables", "avatar": "core/workflow/template/variableUpdate", "flowNodeType": "variableUpdate", "showStatus": false, "position": { "x": 9218.366266384397, "y": -580.0782691913971 }, "version": "481", "inputs": [ { "key": "updateList", "valueType": "any", "label": "", "renderTypeList": [ "hidden" ], "value": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "value": [ "z5y22KY72pOV", "qLUQfhG0ILRX" ], "valueType": "string", "renderType": "reference" } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [] }, { "nodeId": "liinRLFVMXdr", "name": "Condition#4", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 8176.327713138762, "y": 638.7194208193687 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "AND", "list": [ { "variable": [ "q3IxKaOW5gdV", "qLUQfhG0ILRX" ], "condition": "isNotEmpty" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "gyB85PcTuq7J", "name": "Variable Update#3", "intro": "Can update the output value of a specified node or update global variables", "avatar": "core/workflow/template/variableUpdate", "flowNodeType": "variableUpdate", "showStatus": false, "position": { "x": 9345.728294531928, "y": 712.206980460045 }, "version": "481", "inputs": [ { "key": "updateList", "valueType": "any", "label": "", "renderTypeList": [ "hidden" ], "value": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "value": [ "q3IxKaOW5gdV", "qLUQfhG0ILRX" ], "valueType": "string", "renderType": "reference" } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [] }, { "nodeId": "flCMEFjHRDaL", "name": "单车信息确认", "intro": "AI Large Model Chat", "avatar": "core/workflow/template/aiChat", "flowNodeType": "chatNode", "showStatus": true, "position": { "x": 3955.007222748157, "y": 1530.815839529571 }, "version": "4.9.7", "inputs": [ { "key": "model", "renderTypeList": [ "settingLLMModel", "reference" ], "label": "common:core.module.input.label.aiModel", "valueType": "string", "value": "deepseek-chat", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "temperature", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "maxToken", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "isResponseAnswerText", "renderTypeList": [ "hidden" ], "label": "", "value": true, "valueType": "boolean", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatQuoteRole", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "value": "system", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteTemplate", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quotePrompt", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatVision", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatReasoning", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatTopP", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatStopSign", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatResponseFormat", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatJsonSchema", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "systemPrompt", "renderTypeList": [ "textarea", "reference" ], "max": 3000, "valueType": "string", "label": "common:core.ai.Prompt", "description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你是一个高度集成、**安全第一**的AI信息核查员。你的一切行为都由一个严格的状态机驱动，其首要任务是在核实信息前，优先排查并处理任何与人员受伤相关的紧急情况。\n\n# 首要原则 (必须无条件遵守)\n **输出格式**: 所有回复都必须以 `状态编码` 开头。\n **安全优先**: **任何时候**，一旦从用户回答中检测到与**人员受伤**相关的词语（如“受伤了”、“撞到人了”、“流血了”），必须**立即中断**当前流程，转入人伤处理（**触发`0003`状态**）。这是最高指令。\n **流程锁定原则 (Gatekeeper Principle)**:\n * **你必须在得到当前问题的有效、相关的答案后，才能进入下一个问题。**\n * 严禁用户使用模糊词、无关回答或指令词来跳过问题。\n * 这些无效回答必须触发“核心对话逻辑”进行处理。\n **准确第一**: 在核对信息时，如果用户回答“不对”或“不是”，必须立刻追问正确的信息，并用追问到的信息覆盖预设值。\n\n# 核心对话逻辑 (处理用户输入的统一协议)\n这是你处理所有用户回复的思考流程：\n\n **收到回复后 - 验证与行动**:\n * **情况A：答案清晰、有效、且相关 (包括用户主动提供的更正信息)**\n * **执行“确认-提问”模式**: 首先，简短复述你确认的信息（`“好的，您的姓名是张三。”`），然后，立即提出流程中的下一个问题。\n * **情况B：答案无效 (模糊、无关、或属于“继续”等回避性回答)**\n * **立即触发“断言式澄清协议” (Assertive Clarification Protocol):**\n * **第一级澄清 (锁定问题，明确要求)**: 你必须直接指出回答无效，并强调必须回答当前问题才能继续。\n * **模板**: `“抱歉，我必须先确认[当前问题]的信息才能继续。请正面回答：[完整重复一遍问题]？”`\n * **第二级澄清 (强制选择)**: 如果第一级澄清后，用户依然回避，将问题转化为无法回避的强制选择题。\n * **示例 (针对“是否是车主”问题)**: `3001为了完成核实，我必须知道您与车辆的关系。请明确回答：您‘是’，还是‘不是’车主？`\n * **最终失败**: 如果两轮“断言式澄清”后仍无法获得有效信息，**触发`0002`状态**转接人工。\n * **情况C：用户无回复 (`【用户无回复】`输入)**\n * **第一次**: 尝试唤醒（`“请问您还在吗？”`）。\n * **第二次连续出现**: **触发`0004`状态**。\n\n---\n\n# 状态编码表 (State Definitions)\n\n| 状态编码 | 定义 | 触发条件与对应回复示例 |\n| :--- | :--- | :--- |\n| **0001** | **转接人工** | 用户主动、明确要求转人工。 |\n| **0002**| **语义无法识别 / 连续偏离主题** | 在两轮“断言式澄清”后，用户的回复依然无效或拒绝配合。 |\n| **0003**| **有人伤转人工** | **触发条件**: **根据“安全优先”原则，在对话的任何阶段确认存在人员受伤或紧急情况。** |\n| | | **回复**: `收到，情况紧急。我将立即为您转接人工警员，请千万不要挂断电话。`|\n| **0004**| **长时间无应答**| 连续两次收到【用户无回复】。|\n| **3001**| **通话中** | 安全检查与信息收集中过程中的默认状态。 |\n| **0000** | **核实成功** | 在所有信息核实完毕后，准备转接人工。 |\n\n---\n\n# 任务流程 (严格按此顺序和逻辑执行)\n\n**阶段一：启动与身份初步确认**\n\n **转入通话中状态并核实车辆**\n * **你的输出**: `3001好的。请问您是否是车牌号为{{$sJHCC6Uh5j2u.rWawP4BJxuH1$}}的车辆的车主？`\n **处理车辆核实应答**\n * **如果用户回答“是”**: 继续流程。\n * **如果用户回答“不是”**:\n * **你的输出**: `3001请车牌号为{{$sJHCC6Uh5j2u.rWawP4BJxuH1$}}的车辆车主进行对话。\n\n**阶段二：核心信息收集与核对**\n\n **问候并询问姓名**\n * **你的输出**: `3001好的，车主您好。为了方便称呼，请问您的姓名是什么？`\n\n **核实身份证 (先报后四位，错误则追问并完整复述)**\n * **系统预设的身份证号码**: {{$sJHCC6Uh5j2u.qLUQfhG0ILRX$}}\n * **你的输出**: `3001好的，[用户姓名]。请问您的身份证号码后四位是否是[系统预设的身份证号码的后四位]？`\n * **处理逻辑**:\n * **如果用户回答“是”**: 确认信息，进入下一步。\n * **如果用户回答“不是”: **追问** `“好的，那么您正确的身份证号码是多少？”`\n * 处理分段输入/号码不完整:\n * 如果用户只提供了一部分号码（如长度明显少于18位，例如“开头是110101...”），严禁让用户重新输入。\n * 你的行动: 复述你听到的部分，并引导补充。\n * 输出示例: 3001好的，开头是110101，后面是多少呢？\n * 循环: 重复此“接收-引导”过程，直到拼凑出完整号码。\n * 记录并完整复述以供确认: 获得完整号码后，必须播报完整的号码进行二次确认。\n * 你的输出: 3001好的，我跟您确认，您正确的身份证号码是[用户提供的完整新号码]，对吗？\n * 处理二次确认:\n * 如果用户回答“对”，则用新号码覆盖预设值，进入下一步。\n * 如果用户回答“不对”，则重复步骤1“追问正确号码”。\n\n **核实手机号 (先报后四位，错误则追问并完整复述)**\n * **系统预设的手机号**: {{$sJHCC6Uh5j2u.gR0mkQpJ4Og8$}}\n * **你的输出**: `3001请问您的手机号码后四位是否是[系统预设手机号的后四位]？`\n * **处理逻辑**:\n * **如果用户回答“是”**: 确认信息，进入**第二部分**。\n * **如果用户回答“不是”**: **追问** `“好的，那么请告诉我您正在使用的手机号码？”`\n * 处理分段输入/号码不完整:\n * 如果用户只提供了一部分号码（如长度明显少于11位，例如“1380013...”），严禁让用户重新输入。\n * 你的行动: 复述你听到的部分，并引导补充。\n * 输出示例: 3001收到，1380013，接着是多少？\n * 循环: 重复此“接收-引导”过程，直到拼凑出完整号码。\n * 记录并完整复述以供确认: 获得完整号码后，必须播报完整的号码进行二次确认。\n * 你的输出: 3001跟您确认一下，您正在使用的手机号码是[用户提供的完整新号码]，对吗？\n * 处理二次确认:\n * 如果用户回答“对”，则用新号码覆盖预设值，进入阶段三。\n * 如果用户回答“不对”，则重复步骤1“追问正确号码”。\n\n**阶段三：结束流程**\n\n **信息确认完成并转接**\n * **触发**: 在手机号码核实无误后立即触发。\n * **你的输出**: `0000好的，信息已全部确认无误。感谢您的配合，下面将转接人工继续处理。`", "valueDesc": "", "debugLabel": "", "toolDescription": "", "maxLength": 100000, "isRichText": true }, { "key": "history", "renderTypeList": [ "numberInput", "reference" ], "valueType": "chatHistory", "label": "common:core.module.input.label.chat history", "description": "workflow:max_dialog_rounds", "required": true, "min": 0, "max": 50, "value": 50, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteQA", "renderTypeList": [ "settingDatasetQuotePrompt" ], "label": "", "debugLabel": "Dataset Reference", "description": "", "valueType": "datasetQuote", "valueDesc": "", "toolDescription": "" }, { "key": "fileUrlList", "renderTypeList": [ "reference", "input" ], "label": "app:workflow.user_file_input", "debugLabel": "File Link", "valueType": "arrayString", "value": [ [ "448745", "userFiles" ] ], "valueDesc": "", "description": "app:workflow.user_file_input_desc", "toolDescription": "" }, { "key": "userChatInput", "renderTypeList": [ "reference", "textarea" ], "valueType": "string", "label": "workflow:user_question", "toolDescription": "User Question", "required": true, "value": [ "yyB2uYEc8uKA", "system_text" ], "valueDesc": "", "description": "", "debugLabel": "" } ], "outputs": [ { "id": "history", "key": "history", "required": true, "label": "common:core.module.output.label.New context", "description": "Splice the current reply content with the history records and return it as the new context", "valueType": "chatHistory", "valueDesc": "{\n obj: System | Human | AI;\n value: string;\n}[]", "type": "static" }, { "id": "answerText", "key": "answerText", "required": true, "label": "common:core.module.output.label.Ai response content", "description": "Will be triggered after the stream reply is completed", "valueType": "string", "type": "static" }, { "id": "reasoningText", "key": "reasoningText", "required": false, "label": "workflow:reasoning_text", "valueType": "string", "type": "static", "invalid": true, "description": "" }, { "id": "system_error_text", "key": "system_error_text", "type": "error", "valueType": "string", "label": "workflow:error_text", "description": "" } ], "catchError": false }, { "nodeId": "cOeMtHzfTu96", "name": "解析状态#4", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 5037.393022505725, "y": 1728.3425878492474 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function extractStateAndContent(data1) {\n // Regular expression to match the STATEcontent format.\n const regex = /(.*?)<\\/state>(.*)/;\n\n // Attempt to match the regex against the input data.\n const match = data1.match(regex);\n\n // If a match is found, extract the state (group 1) and content (group 2).\n if (match && match.length > 2) {\n return {\n state: match[1],\n content: match[2],\n };\n } else {\n // If no match is found, return null or an appropriate error object.\n return { state: null, content: null }; // Or return { state: null, content: null }; or throw an error.\n }\n}\n\nfunction main({data1}){\n const extractedContent = extractStateAndContent(data1);\n const state = extractedContent.state;\n const content = extractedContent.content;\n return {\n content: content,\n state: state\n };\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "string", "canEdit": true, "key": "data1", "label": "data1", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "value": [ "flCMEFjHRDaL", "answerText" ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "state", "valueType": "string", "label": "state", "valueDesc": "", "description": "" }, { "id": "udJb1g6GMwOx", "valueType": "string", "type": "dynamic", "key": "content", "label": "content" } ], "catchError": true }, { "nodeId": "i5yBQcW0h923", "name": "Condition#5", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 6094.872979286407, "y": 1957.8425878492471 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "AND", "list": [ { "variable": [ "cOeMtHzfTu96", "qLUQfhG0ILRX" ], "condition": "isNotEmpty" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "aln2gMrtCYOo", "name": "Variable Update#4", "intro": "Can update the output value of a specified node or update global variables", "avatar": "core/workflow/template/variableUpdate", "flowNodeType": "variableUpdate", "showStatus": false, "position": { "x": 7080.003590875616, "y": 2009.8425878492471 }, "version": "481", "inputs": [ { "key": "updateList", "valueType": "any", "label": "", "renderTypeList": [ "hidden" ], "value": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "value": [ "cOeMtHzfTu96", "qLUQfhG0ILRX" ], "valueType": "string", "renderType": "reference" } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [] }, { "nodeId": "tBpOv2BTrsvA", "name": "双车信息确认", "intro": "AI Large Model Chat", "avatar": "core/workflow/template/aiChat", "flowNodeType": "chatNode", "showStatus": true, "position": { "x": 3414.232981050866, "y": 2994.3781381449016 }, "version": "4.9.7", "inputs": [ { "key": "model", "renderTypeList": [ "settingLLMModel", "reference" ], "label": "common:core.module.input.label.aiModel", "valueType": "string", "value": "deepseek-chat", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "temperature", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "maxToken", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "isResponseAnswerText", "renderTypeList": [ "hidden" ], "label": "", "value": true, "valueType": "boolean", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatQuoteRole", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "value": "system", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteTemplate", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "quotePrompt", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatVision", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatReasoning", "renderTypeList": [ "hidden" ], "label": "", "valueType": "boolean", "value": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatTopP", "renderTypeList": [ "hidden" ], "label": "", "valueType": "number", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatStopSign", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatResponseFormat", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "aiChatJsonSchema", "renderTypeList": [ "hidden" ], "label": "", "valueType": "string", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" }, { "key": "systemPrompt", "renderTypeList": [ "textarea", "reference" ], "max": 3000, "valueType": "string", "label": "common:core.ai.Prompt", "description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你是一个高度集成、**安全第一**的AI信息核查员。你的一切行为都由一个严格的状态机驱动，其首要任务是在核实信息前，优先排查并处理任何与人员受伤相关的紧急情况。\n\n# 首要原则 (必须无条件遵守)\n **输出格式**: 所有回复都必须以 `状态编码` 开头。\n **安全优先**: **任何时候**，一旦从用户回答中检测到与**人员受伤**相关的词语（如“受伤了”、“撞到人了”、“流血了”），必须**立即中断**当前流程，转入人伤处理（**触发`0003`状态**）。这是最高指令。\n **流程锁定原则 (Gatekeeper Principle)**:\n * **你必须在得到当前问题的有效、相关的答案后，才能进入下一个问题。**\n * 严禁用户使用模糊词、无关回答或指令词来跳过问题。\n * 这些无效回答必须触发“核心对话逻辑”进行处理。\n **准确第一**: 在核对信息时，如果用户回答“不对”或“不是”，必须立刻追问正确的信息，并用追问到的信息覆盖预设值。\n\n# 核心对话逻辑 (处理用户输入的统一协议)\n这是你处理所有用户回复的思考流程：\n\n **收到回复后 - 验证与行动**:\n * **情况A：答案清晰、有效、且相关 (包括用户主动提供的更正信息)**\n * **执行“确认-提问”模式**: 首先，简短复述你确认的信息（`“好的，您的姓名是张三。”`），然后，立即提出流程中的下一个问题。\n * **情况B：答案无效 (模糊、无关、或属于“继续”等回避性回答)**\n * **立即触发“断言式澄清协议” (Assertive Clarification Protocol):**\n * **第一级澄清 (锁定问题, 明确要求)**: 你必须直接指出回答无效，并强调必须回答当前问题才能继续。\n * **模板**: `“抱歉，我必须先确认[当前问题]的信息才能继续。请正面回答：[完整重复一遍问题]？”`\n * **第二级澄清 (强制选择)**: 如果第一级澄清后，用户依然回避，将问题转化为无法回避的强制选择题。\n * **示例 (针对“是否是驾驶员”问题)**: `3002为了完成核实，我必须知道您是否是该车辆的驾驶员。请明确回答：您‘是’，还是‘不是’？`\n * **最终失败**: 如果两轮“断言式澄清”后仍无法获得有效信息，**触发`0002`状态**转接人工。\n * **情况C：用户无回复 (`【用户无回复】`输入)**\n * **第一次**: 尝试唤醒（`“请问您还在吗？”`）。\n * **第二次连续出现**: **触发`0004`状态**。\n\n---\n\n# 状态编码表 (State Definitions)\n\n| 状态编码 | 定义 | 触发条件与对应回复示例 |\n| :--- | :--- | :--- |\n| **0001** | **转接人工** | 用户主动、明确要求转人工。 |\n| **0002**| **语义无法识别 / 连续偏离主题** | 在两轮“断言式澄清”后，用户的回复依然无效或拒绝配合。 |\n| **0003**| **有人伤转人工** | **触发条件**: **根据“安全优先”原则，在对话的任何阶段确认存在人员受伤或紧急情况。** |\n| | | **回复**: `收到，情况紧急。我将立即为您转接人工警员，请千万不要挂断电话。`|\n| **0004**| **长时间无应答**| 连续两次收到【用户无回复】。|\n| **3002**| **通话中** | 安全检查与信息收集中过程中的默认状态。 |\n| **0000** | **核实成功** | 所有驾驶员信息均核实完毕，准备转接人工。 |\n\n---\n\n# 任务流程 (严格按此顺序和逻辑执行)\n\n## **第一部分：采集第一位驾驶员信息**\n\n **启动并核实驾驶员身份**\n * **你的输出**: `3002您好。请问车牌号为 {{$fsWVpSkboqW3.rWawP4BJxuH1$}} 的车辆是由您驾驶的吗？`\n * **处理逻辑**:\n * 如用户答“是”，则记录信息并进入下一步。\n * 如用户答“不是”，则要求更换通话人：`3002好的，请车牌号为 {{$fsWVpSkboqW3.rWawP4BJxuH1$}} 的车辆驾驶员来接听电话。`\n\n **问候并询问姓名**\n * **你的输出**: `3002好的，驾驶员您好。为了方便称呼，请问您的姓名是什么？`\n\n **核实身份证**\n * **系统预设的身份证号码**: {{$fsWVpSkboqW3.qLUQfhG0ILRX$}}\n * **你的输出**: `3002好的，[用户姓名]。请问您的身份证号码后四位是否是[系统预设的身份证号码的后四位]？`\n * **处理逻辑**:\n * **如果用户回答“是”**: 确认信息，进入下一步。\n * **如果用户回答“不是”: **追问** `“好的，那么您正确的身份证号码是多少？”`\n * 处理分段输入/号码不完整:\n * 如果用户只提供了一部分号码（如长度明显少于18位，例如“开头是110101...”），严禁让用户重新输入。\n * 你的行动: 复述你听到的部分，并引导补充。\n * 输出示例: 3001好的，开头是110101，后面是多少呢？\n * 循环: 重复此“接收-引导”过程，直到拼凑出完整号码。\n * 记录并完整复述以供确认: 获得完整号码后，必须播报完整的号码进行二次确认。\n * 你的输出: 3001好的，我跟您确认，您正确的身份证号码是[用户提供的完整新号码]，对吗？\n * 处理二次确认:\n * 如果用户回答“对”，则用新号码覆盖预设值，进入下一步。\n * 如果用户回答“不对”，则重复步骤1“追问正确号码”。\n\n **核实手机号**\n * **系统预设的手机号**: {{$fsWVpSkboqW3.gR0mkQpJ4Og8$}}\n * **你的输出**: `3002请问您的手机号码后四位是否是[系统预设手机号的后四位]？`\n * **处理逻辑**:\n * **如果用户回答“是”**: 确认信息，进入**第二部分**。\n * **如果用户回答“不是”**: **追问** `“好的，那么请告诉我您正在使用的手机号码？”`\n * 处理分段输入/号码不完整:\n * 如果用户只提供了一部分号码（如长度明显少于11位，例如“1380013...”），严禁让用户重新输入。\n * 你的行动: 复述你听到的部分，并引导补充。\n * 输出示例: 3001收到，1380013，接着是多少？\n * 循环: 重复此“接收-引导”过程，直到拼凑出完整号码。\n * 记录并完整复述以供确认: 获得完整号码后，必须播报完整的号码进行二次确认。\n * 你的输出: 3001跟您确认一下，您正在使用的手机号码是[用户提供的完整新号码]，对吗？\n * 处理二次确认:\n * 如果用户回答“对”，则用新号码覆盖预设值，进入阶段三。\n * 如果用户回答“不对”，则重复步骤1“追问正确号码”。\n\n## **第二部分：采集第二位驾驶员信息**\n\n **请求转接电话**\n * **触发**: 第一位驾驶员手机号核实完毕后。\n * **你的输出**: `3002好的，第一位驾驶员的信息已核实完毕。现在请您将电话交给另一位当事驾驶员，然后告诉我移交完毕。`\n\n **核实第二位驾驶员身份**\n * **你的输出**: `3002您好。请问车牌号为 {{$fsWVpSkboqW3.wHUmHTU2Rhlb$}} 的车辆是由您驾驶的吗？`\n * **处理逻辑**:\n * 如用户答“是”，则记录信息并进入下一步。\n * 如用户答“不是”，则必须要求更换通话人：`3002好的，为了完成核实，必须由该车驾驶员本人接听。请将电话交给他。` 然后**停留在此步骤**，直到确认为本人。\n\n **询问姓名**\n * **你的输出**: `3002好的，驾驶员您好。请问您的姓名是？`\n\n **核实身份证**\n * **系统预设的身份证号码**: {{$fsWVpSkboqW3.cUeHVjpSQUr1$}}\n * **你的输出**: `3002好的，[用户姓名]。请问您的身份证号码后四位是否是[系统预设的身份证号码的后四位]？`\n * **处理逻辑**: 与第一位驾驶员相同，确认后进入下一步。\n\n **核实手机号**\n * **系统预设的手机号**: {{$fsWVpSkboqW3.bXzM05j1bbwn$}}\n * **你的输出**: `3002请问您的手机号码后四位是否是[系统预设手机号的后四位]？`\n * **处理逻辑**: 与第一位驾驶员相同。确认后进入**第三部分**。\n\n## **第三部分：结束流程**\n\n**完成核实并转接**\n * **触发条件**: 第二位驾驶员手机号核实完毕后。\n * **你的输出**: `0000好的，两位驾驶员的信息均已核实完毕。感谢您的配合，下面将转接人工继续处理。`", "valueDesc": "", "debugLabel": "", "toolDescription": "", "maxLength": 100000, "isRichText": true }, { "key": "history", "renderTypeList": [ "numberInput", "reference" ], "valueType": "chatHistory", "label": "common:core.module.input.label.chat history", "description": "workflow:max_dialog_rounds", "required": true, "min": 0, "max": 50, "value": 50, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "quoteQA", "renderTypeList": [ "settingDatasetQuotePrompt" ], "label": "", "debugLabel": "Dataset Reference", "description": "", "valueType": "datasetQuote", "valueDesc": "", "toolDescription": "" }, { "key": "fileUrlList", "renderTypeList": [ "reference", "input" ], "label": "app:workflow.user_file_input", "debugLabel": "File Link", "valueType": "arrayString", "value": [ [ "448745", "userFiles" ] ], "valueDesc": "", "description": "app:workflow.user_file_input_desc", "toolDescription": "" }, { "key": "userChatInput", "renderTypeList": [ "reference", "textarea" ], "valueType": "string", "label": "workflow:user_question", "toolDescription": "User Question", "required": true, "value": [ "yyB2uYEc8uKA", "system_text" ], "valueDesc": "", "description": "", "debugLabel": "" } ], 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"intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 4885.7185029331395, "y": 3121.0631098659824 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function extractStateAndContent(data1) {\n // Regular expression to match the STATEcontent format.\n const regex = /(.*?)<\\/state>(.*)/;\n\n // Attempt to match the regex against the input data.\n const match = data1.match(regex);\n\n // If a match is found, extract the state (group 1) and content (group 2).\n if (match && match.length > 2) {\n return {\n state: match[1],\n content: match[2],\n };\n } else {\n // If no match is found, return null or an appropriate error object.\n return { state: null, content: null }; // Or return { state: null, content: null }; or throw an error.\n }\n}\n\nfunction main({data1}){\n const extractedContent = extractStateAndContent(data1);\n const state = extractedContent.state;\n const content = extractedContent.content;\n return {\n content: content,\n state: state\n };\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "string", "canEdit": true, "key": "data1", "label": "data1", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "value": [ "tBpOv2BTrsvA", "answerText" ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", 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The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "state", "valueType": "string", "label": "state", "valueDesc": "", "description": "" }, { "id": "udJb1g6GMwOx", "valueType": "string", "type": "dynamic", "key": "content", "label": "content" } ], "catchError": true }, { "nodeId": "euRwFTajqcRO", "name": "Condition#6", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 5853.466296984162, "y": 3338.8749119355352 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "AND", "list": [ { "variable": [ "k4pGjQ0cd04e", "qLUQfhG0ILRX" ], "condition": "isEmpty" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "io07e4nO84k2", "name": "Variable Update#5", "intro": "Can update the output value of a specified node or update global variables", "avatar": "core/workflow/template/variableUpdate", "flowNodeType": "variableUpdate", "showStatus": false, "position": { "x": 7154.397349538959, "y": 3465.415610920879 }, "version": "481", "inputs": [ { "key": "updateList", "valueType": "any", "label": "", "renderTypeList": [ "hidden" ], "value": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "value": [ "k4pGjQ0cd04e", "qLUQfhG0ILRX" ], "valueType": "string", "renderType": "reference" } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [] }, { "nodeId": "krClalszmq68", "name": "Condition#7", "intro": "Execute different branches based on conditions.", "avatar": "core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, 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"core/workflow/template/ifelse", "flowNodeType": "ifElseNode", "showStatus": true, "position": { "x": 3534.6261499054604, "y": 226.47271316136192 }, "version": "481", "inputs": [ { "key": "ifElseList", "renderTypeList": [ "hidden" ], "valueType": "any", "label": "", "value": [ { "condition": "OR", "list": [ { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "2010" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "2011" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "2012" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "2013" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "2014" }, { "variable": [ "VARIABLE_NODE_ID", "status_code" ], "condition": "equalTo", "value": "2015" } ] } ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "ifElseResult", "key": "ifElseResult", "label": "workflow:judgment_result", "valueType": "string", "type": "static", "description": "" } ] }, { "nodeId": "fsWVpSkboqW3", "name": "Code Sandbox#7", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 2587.8879951603426, "y": 2099.7067792182334 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", 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"selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "value": [ "VARIABLE_NODE_ID", "state" ] } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "driver1ID", "valueType": "string", "label": "driver1ID", "valueDesc": "", "description": "" }, { "id": "gR0mkQpJ4Og8", "type": "dynamic", "key": "driver1Phonenumber", "valueType": "string", "label": "driver1Phonenumber", "valueDesc": "", "description": "" }, { "id": "wHUmHTU2Rhlb", "valueType": "string", "type": "dynamic", "key": "driver2License", "label": "driver2License" }, { "id": "cUeHVjpSQUr1", "valueType": "string", "type": "dynamic", "key": "driver2ID", "label": "driver2ID" }, { "id": "rWawP4BJxuH1", "valueType": "string", "type": "dynamic", "key": "driver1License", "label": "driver1License" }, { "id": "bXzM05j1bbwn", "valueType": "string", "type": "dynamic", "key": "driver2Phonenumber", "label": "driver2Phonenumber" } ], "catchError": true }, { "nodeId": "sJHCC6Uh5j2u", "name": "Code Sandbox#10", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 3135, "y": 945 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function main({state}){\n return {driver1License: state.hphm1,\n driver1ID: state.driver1ID,\n driver1Phonenumber: state.driver1Phonenumber,\n driver2License: state.hphm2,\n driver2ID: state.driver2ID,\n driver2Phonenumber: state.driver2Phonenumber\n }\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "object", "canEdit": true, "key": "state", "label": "state", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "value": [ "VARIABLE_NODE_ID", "state" ] } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "driver1ID", "valueType": "string", "label": "driver1ID", "valueDesc": "", "description": "" }, { "id": "gR0mkQpJ4Og8", "type": "dynamic", "key": "driver1Phonenumber", "valueType": "string", "label": "driver1Phonenumber", "valueDesc": "", "description": "" }, { "id": "wHUmHTU2Rhlb", "valueType": "string", "type": "dynamic", "key": "driver2License", "label": "driver2License" }, { "id": "cUeHVjpSQUr1", "valueType": "string", "type": "dynamic", "key": "driver2ID", "label": "driver2ID" }, { "id": "rWawP4BJxuH1", "valueType": "string", "type": "dynamic", "key": "driver1License", "label": "driver1License" }, { "id": "bXzM05j1bbwn", "valueType": "string", "type": "dynamic", "key": "driver2Phonenumber", "label": "driver2Phonenumber" } ], "catchError": true }, { "nodeId": "mbP4DRmqf3qT", "name": "Code Sandbox#9", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 4885.7185029331395, "y": 168.96756250333965 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function main({state}){\n return {driver1License: state.hphm1,\n driver1ID: state.driver1ID,\n driver1Phonenumber: state.driver1Phonenumber,\n driver2License: state.hphm2,\n driver2ID: state.driver2ID,\n driver2Phonenumber: state.driver2Phonenumber\n }\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "object", "canEdit": true, "key": "state", "label": "state", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "value": [ "VARIABLE_NODE_ID", "state" ] } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "driver1ID", "valueType": "string", "label": "driver1ID", "valueDesc": "", "description": "" }, { "id": "gR0mkQpJ4Og8", "type": "dynamic", "key": "driver1Phonenumber", "valueType": "string", "label": "driver1Phonenumber", "valueDesc": "", "description": "" }, { "id": "wHUmHTU2Rhlb", "valueType": "string", "type": "dynamic", "key": "driver2License", "label": "driver2License" }, { "id": "cUeHVjpSQUr1", "valueType": "string", "type": "dynamic", "key": "driver2ID", "label": "driver2ID" }, { "id": "rWawP4BJxuH1", "valueType": "string", "type": "dynamic", "key": "driver1License", "label": "driver1License" }, { "id": "bXzM05j1bbwn", "valueType": "string", "type": "dynamic", "key": "driver2Phonenumber", "label": "driver2Phonenumber" } ], "catchError": true }, { "nodeId": "i2xYvUNWE7Zv", "name": "Code Sandbox#9", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 5138.581271863097, "y": -999.6250337216792 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function main({state}){\n return {driver1License: state.hphm1,\n driver1ID: state.driver1ID,\n driver1Phonenumber: state.driver1Phonenumber,\n driver2License: state.hphm2,\n driver2ID: state.driver2ID,\n driver2Phonenumber: state.driver2Phonenumber\n }\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "object", "canEdit": true, "key": "state", "label": "state", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "value": [ "VARIABLE_NODE_ID", "state" ] } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "driver1ID", "valueType": "string", "label": "driver1ID", "valueDesc": "", "description": "" }, { "id": "gR0mkQpJ4Og8", "type": "dynamic", "key": "driver1Phonenumber", "valueType": "string", "label": "driver1Phonenumber", "valueDesc": "", "description": "" }, { "id": "wHUmHTU2Rhlb", "valueType": "string", "type": "dynamic", "key": "driver2License", "label": "driver2License" }, { "id": "cUeHVjpSQUr1", "valueType": "string", "type": "dynamic", "key": "driver2ID", "label": "driver2ID" }, { "id": "rWawP4BJxuH1", "valueType": "string", "type": "dynamic", "key": "driver1License", "label": "driver1License" }, { "id": "bXzM05j1bbwn", "valueType": "string", "type": "dynamic", "key": "driver2Phonenumber", "label": "driver2Phonenumber" } ], "catchError": true }, { "nodeId": "z5y22KY72pOV", "name": "解析状态#10", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 7425.995331671787, "y": -955.0997501393636 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function extractStateAndContent(data1) {\n // Regular expression to match the STATEcontent format.\n const regex = /(.*?)<\\/state>(.*)/;\n\n // Attempt to match the regex against the input data.\n const match = data1.match(regex);\n\n // If a match is found, extract the state (group 1) and content (group 2).\n if (match && match.length > 2) {\n return {\n state: match[1],\n content: match[2],\n };\n } else {\n // If no match is found, return null or an appropriate error object.\n return { state: null, content: null }; // Or return { state: null, content: null }; or throw an error.\n }\n}\n\nfunction main({data1}){\n const extractedContent = extractStateAndContent(data1);\n const state = extractedContent.state;\n const content = extractedContent.content;\n return {\n content: content,\n state: state\n };\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "string", "canEdit": true, "key": "data1", "label": "data1", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "value": [ "mCWJYYru8qPR", "answerText" ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "state", "valueType": "string", "label": "state", "valueDesc": "", "description": "" }, { "id": "udJb1g6GMwOx", "valueType": "string", "type": "dynamic", "key": "content", "label": "content" } ], "catchError": true }, { "nodeId": "q3IxKaOW5gdV", "name": "解析状态#9", "intro": "Execute a simple script code, usually for complex data processing.", "avatar": "core/workflow/template/codeRun", "flowNodeType": "code", "showStatus": true, "position": { "x": 7095, "y": 465 }, "version": "482", "inputs": [ { "key": "system_addInputParam", "renderTypeList": [ "addInputParam" ], "valueType": "dynamic", "label": "", "required": false, "description": "workflow:these_variables_will_be_input_parameters_for_code_execution", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "valueDesc": "", "debugLabel": "", "toolDescription": "" }, { "key": "codeType", "renderTypeList": [ "hidden" ], "label": "", "value": "js", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "key": "code", "renderTypeList": [ "custom" ], "label": "", "value": "function extractStateAndContent(data1) {\n // Regular expression to match the STATEcontent format.\n const regex = /(.*?)<\\/state>(.*)/;\n\n // Attempt to match the regex against the input data.\n const match = data1.match(regex);\n\n // If a match is found, extract the state (group 1) and content (group 2).\n if (match && match.length > 2) {\n return {\n state: match[1],\n content: match[2],\n };\n } else {\n // If no match is found, return null or an appropriate error object.\n return { state: null, content: null }; // Or return { state: null, content: null }; or throw an error.\n }\n}\n\nfunction main({data1}){\n const extractedContent = extractStateAndContent(data1);\n const state = extractedContent.state;\n const content = extractedContent.content;\n return {\n content: content,\n state: state\n };\n}", "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "", "valueType": "string" }, { "renderTypeList": [ "reference" ], "valueType": "string", "canEdit": true, "key": "data1", "label": "data1", "customInputConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": true }, "required": true, "value": [ "k318kWi02OU9", "answerText" ], "valueDesc": "", "description": "", "debugLabel": "", "toolDescription": "" } ], "outputs": [ { "id": "system_rawResponse", "key": "system_rawResponse", "label": "workflow:full_response_data", "valueType": "object", "type": "static", "description": "" }, { "id": "error", "key": "error", "label": "workflow:error_text", "description": "Error information of code execution, returns empty on success", "valueType": "string", "type": "error" }, { "id": "system_addOutputParam", "key": "system_addOutputParam", "type": "dynamic", "valueType": "dynamic", "label": "", "customFieldConfig": { "selectValueTypeList": [ "string", "number", "boolean", "object", "arrayString", "arrayNumber", "arrayBoolean", "arrayObject", "arrayAny", "any", "chatHistory", "datasetQuote", "dynamic", "selectDataset", "selectApp" ], "showDescription": false, "showDefaultValue": false }, "description": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.", "valueDesc": "" }, { "id": "qLUQfhG0ILRX", "type": "dynamic", "key": "state", "valueType": "string", "label": "state", "valueDesc": "", "description": "" }, { "id": "udJb1g6GMwOx", "valueType": "string", "type": "dynamic", "key": "content", "label": "content" } ], "catchError": true }, { "nodeId": "kbba6T0A0cME", "name": "Assigned Reply#2", "intro": "This module can directly reply with a specified content. Commonly used for guidance or prompts. Non-string content will be converted to string for output.", "avatar": "core/workflow/template/reply", "flowNodeType": "answerNode", "position": { "x": 2091.8142617646504, "y": 1167.9675625033396 }, "version": "481", "inputs": [ { "key": "text", "renderTypeList": [ "textarea", "reference" ], "valueType": "any", "required": true, "label": "common:core.module.input.label.Response content", "description": "common:core.module.input.description.Response content", "placeholder": "common:core.module.input.description.Response content", "value": "{{$VARIABLE_NODE_ID.status_code$}}所有信息以收集完毕，正在转接人工，请稍候", "valueDesc": "", "debugLabel": "", "toolDescription": "", "isRichText": false, "maxLength": 100000 } ], "outputs": [] }, { "nodeId": "mzDpCKsdDlZd", "name": "Assigned Reply#3", "intro": "This module can directly reply with a specified content. Commonly used for guidance or prompts. Non-string content will be converted to string for output.", "avatar": "core/workflow/template/reply", "flowNodeType": "answerNode", "position": { "x": 1873.8183718024648, "y": 1684.8778651206744 }, "version": "481", "inputs": [ { "key": "text", "renderTypeList": [ "textarea", "reference" ], "valueType": "any", "required": true, "label": "common:core.module.input.label.Response content", "description": "common:core.module.input.description.Response content", "placeholder": "common:core.module.input.description.Response content", "value": "{{$VARIABLE_NODE_ID.status_code$}}正在转接人工，请稍候", "valueDesc": "", "debugLabel": "", "toolDescription": "", "isRichText": false, "maxLength": 100000 } ], "outputs": [] }, { "nodeId": "xWEWw9JV6GFa", "name": "Assigned Reply#3", "intro": "This module can directly reply with a specified content. Commonly used for guidance or prompts. 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