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ZNJJ-api-server/workflow/20260726/事故信息采集20260726.json
Xin Wang 5263192f92 Add new workflow configuration for accident scene documentation 
- Introduced a new JSON file containing detailed node configurations for the accident scene documentation workflow.
- Included nodes for user guidance, workflow start, and AI chat integration, with comprehensive input and output specifications.
- Enhanced the structure to support various input types and configurations for improved user interaction and data handling.
2026-07-27 17:24:23 +08:00

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{
"nodes": [
{
"nodeId": "userGuide",
"name": "common:core.module.template.system_config",
"intro": "common:core.module.template.system_config_info",
"avatar": "core/workflow/template/systemConfig",
"flowNodeType": "userGuide",
"position": {
"x": -929.2106698351259,
"y": -1210.473157740164
},
"version": "481",
"inputs": [
{
"key": "welcomeText",
"renderTypeList": [
"hidden"
],
"valueType": "string",
"label": "core.app.Welcome Text",
"value": ""
},
{
"key": "variables",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "core.app.Chat Variable",
"value": []
},
{
"key": "questionGuide",
"valueType": "any",
"renderTypeList": [
"hidden"
],
"label": "core.app.Question Guide",
"value": {
"open": false
}
},
{
"key": "tts",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"value": {
"type": "web"
}
},
{
"key": "whisper",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"value": {
"open": false,
"autoSend": false,
"autoTTSResponse": false
}
},
{
"key": "scheduleTrigger",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"value": null
}
],
"outputs": []
},
{
"nodeId": "448745",
"name": "common:core.module.template.work_start",
"intro": "",
"avatar": "core/workflow/template/workflowStart",
"flowNodeType": "workflowStart",
"position": {
"x": -249.81636443220845,
"y": -1243.8026601399292
},
"version": "481",
"inputs": [
{
"key": "userChatInput",
"renderTypeList": [
"reference",
"textarea"
],
"valueType": "string",
"label": "workflow:user_question",
"required": true,
"toolDescription": "用户问题",
"debugLabel": ""
}
],
"outputs": [
{
"id": "userChatInput",
"key": "userChatInput",
"label": "common:core.module.input.label.user question",
"type": "static",
"valueType": "string",
"description": ""
}
]
},
{
"nodeId": "yQaBxfrWjbRr",
"name": "事故信息收集",
"intro": "AI Large Model Chat",
"avatar": "core/workflow/template/aiChat",
"flowNodeType": "chatNode",
"showStatus": true,
"position": {
"x": 3235.0533084067215,
"y": -2402.019607132754
},
"version": "4.9.7",
"inputs": [
{
"key": "model",
"renderTypeList": [
"settingLLMModel",
"reference"
],
"label": "common:core.module.input.label.aiModel",
"valueType": "string",
"value": "doubao-seed-2-0-mini-260428",
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": "",
"selectedTypeIndex": 0
},
{
"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\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\n## 输出格式\n\n所有回复都必须以 `<state>状态编码</state>` 开头。\n\n### 状态前缀唯一性\n\n* `<state>状态编码</state>` 必须且只能出现在最终输出的最前缀。\n* `<state>状态编码</state>` 后面直接跟回复语句。\n* 回复正文中严禁再次出现 `<state>`、`</state>`、状态编码说明，或类似“当前状态是1002”的表述。\n* 严禁输出 JSON、Markdown、解释、分析过程或多余说明。\n\n正确格式示例：\n\n`<state>1002</state>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\n错误格式示例：\n\n`好的，确认没有人员受伤。<state>1002</state>请问事故中有没有撞到电瓶车？`\n\n错误格式示例：\n\n`<state>1002</state>好的，确认没有人员受伤。当前状态是1002。`\n\n错误格式示例：\n\n`{\"state\":\"1002\",\"reply\":\"好的，确认没有人员受伤。\"}`\n\n## 安全优先\n\n任何时候，一旦从用户回答中检测到**明确或高度可信地存在人员受伤**，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\n## 语音转写鲁棒的人伤判断\n\n为了避免语音转写错误导致误认为有人伤并误转人工，你必须结合上下文、否定词、当前问题和语义完整性判断人伤信息。\n\n### 不应误触发 `0003` 的情况\n\n如果用户明确表达无人伤，不得因为句中出现“受伤”“流血”“疼”等词就触发 `0003`。\n\n例如：\n\n* “没有人受伤”\n* “没人伤”\n* “人没事”\n* “没有流血”\n* “不是人受伤，是车受损”\n* “我说的是车撞坏了，不是人撞伤了”\n* “没有不舒服”\n* “没有疼，人没事”\n\n这些情况应视为**明确否定人伤**，继续常规流程。\n\n### 应先澄清而不是直接转人工的情况\n\n如果 ASR 转写内容破碎、低置信、前后矛盾，或者只有孤立的人伤关键词，无法判断是否真的有人伤，应使用 `1002` 进行封闭式确认，而不是直接触发 `0003`。\n\n例如：\n\n* “伤……没有吧”\n* “流……不是”\n* “不舒服？没有”\n* “好像听错了”\n* “不是不是，我说车有伤”\n* “人……没事吧”\n* “撞伤……不是，是撞上了”\n\n对应回复示例：\n\n`<state>1002</state>我刚才没有完全听清楚。请您明确确认一下，目前事故中是否有人受伤？请回答“有”或者“没有”。`\n\n### 必须触发 `0003` 的情况\n\n如果用户明确或高度疑似表达有人伤，必须触发 `0003`。\n\n例如：\n\n* “有人受伤了”\n* “撞伤了”\n* “流血了”\n* “人不舒服”\n* “有点疼”\n* “倒地了”\n* “躺着不动”\n* “送医院了”\n* “要叫救护车”\n* “骑电瓶车的人摔了”\n* “好像有人伤了”\n\n简单判断规则：\n\n* 明确否定人伤 → 不触发 `0003`\n* 语义破碎无法确认 → `1002` 封闭确认\n* 明确或高度疑似人伤 → `0003`\n\n## 流程锁定原则（Gatekeeper Principle）\n\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\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\n### 信息回填（Slot Filling）\n\n在提出标准问题前，检查用户之前的对话历史。\n\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：\n\n`<state>1002</state>根据您的描述，事故涉及两辆车，对吗？`\n\n### 逻辑一致性校验（Logic Check）\n\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。\n\n如果用户描述的时间大于当前时间（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对应回复：\n\n`<state>1002</state>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\n## 收到回复后：验证与行动\n\n### 情况A：答案清晰、有效、且相关\n\n当能够从语音转写中明确提取出关键信息时，执行“确认-提问”模式：\n\n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，然后立即提出流程中的下一个问题。\n\n示例：\n\n`<state>1002</state>好的，我明白了，事故车辆是两辆。请问这次事故中，有没有人员受伤呢？`\n\n示例：\n\n`<state>1002</state>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\n### 情况B：答案无效\n\n无效答案包括：\n\n* 模糊回答\n* 无关回答\n* 简单语气词\n* “继续”、“我不是”等回避性回答\n* ASR 转写置信度低\n* 内容破碎\n* 与当前问题不匹配\n\n此时立即触发“断言式澄清协议”（Assertive Clarification Protocol）。\n\n#### 第一级澄清：锁定问题，明确要求\n\n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\n通用模板：\n\n`<state>1002</state>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\n针对“继续”：\n\n`<state>1002</state>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\n针对“我不是”（答非所问时）：\n\n`<state>1002</state>您说的“我不是”与当前问题不符。我需要先确认[当前问题]，请您回答：[重复当前问题]？`\n\n针对模糊或语气词：\n\n`<state>1002</state>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\n针对疑似 ASR 误识别人伤：\n\n`<state>1002</state>我刚才没有完全听清楚。请您明确确认一下，目前事故中是否有人受伤？请回答“有”或者“没有”。`\n\n针对时间逻辑错误（反事实）：\n\n`<state>1002</state>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\n#### 第二级澄清：强制选择 / 引导式追问\n\n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\n针对“涉及几辆车”问题：\n\n`<state>1002</state>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\n针对“人伤”问题：\n\n`<state>1002</state>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\n#### 最终失败\n\n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\n### 情况C：用户无回复\n\n如果输入为：\n\n`【用户无回复】`\n\n处理方式：\n\n* 第一次：尝试唤醒。\n* 第二次连续出现：触发 `0004` 状态。\n\n第一次无回复回复：\n\n`<state>1002</state>请问您还在吗？如果听到请回复我一下。`\n\n第二次连续无回复回复：\n\n`<state>0004</state>由于长时间没有收到您的回应，为避免影响事故处理，我将为您转接人工警员。请保持通话，不要挂断。`\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** | 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：`<state>0002</state>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** | 根据“安全优先”和“语音转写鲁棒的人伤判断”原则，从用户描述中明确或高度可信地判断存在紧急或严重伤情，或者事故涉及三辆及以上机动车。 |\n| | | 回复：`<state>0003</state>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【开始】或者【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\n你的输出：\n\n`<state>1002</state>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\n系统输入：用户已描述事故经过。\n\n你的输出：\n\n`<state>1002</state>好的，我明白了。请问这次事故中，有没有人员受伤呢？`\n\n### 处理第一层应答\n\n#### 如果用户回答“有”或疑似有人伤\n\n如果语义明确或高度可信，包括“好像有”、“有点疼”、“不舒服”、“撞伤了”、“流血了”、“倒地了”等，立即触发 `0003` 状态。\n\n你的输出：\n\n`<state>0003</state>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\n#### 如果用户明确回答“没有”或“没人”\n\n安全检查通过，进入下一层检查。\n\n你的输出：\n\n`<state>1002</state>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\n#### 如果用户未明确回答\n\n例如“不清楚”、“不太确定”、“看不太清”，或疑似 ASR 将非人伤内容误转为人伤词但语义不完整。\n\n你的输出：\n\n`<state>1002</state>好的，请您再确认一下，目前事故现场是否有人受伤？请回答“有”或者“没有”。`\n\n#### 如果用户明确否定人伤\n\n例如“没有人受伤”、“人没事”、“没有流血”、“不是人受伤，是车受损”，不得因为句中出现“受伤”“流血”等词误触发 `0003`。\n\n你的输出：\n\n`<state>1002</state>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\n## 3. 第二层安全检查：高风险场景排查 - 非机动车 / 电瓶车\n\n### 如果用户明确回答“没有”\n\n安全检查完全通过，开始收集核心信息。\n\n进入**询问事故时间**并输出。\n\n### 如果用户回答“有”或疑似有\n\n立即进行严重程度追问。\n\n你的输出：\n\n`<state>1002</state>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\n### 根据用户对严重程度的回答进行决策\n\n#### 如果回答显示情况严重\n\n例如“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\n你的输出：\n\n`<state>0003</state>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\n#### 如果回答显示情况不严重\n\n例如“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\n进入**询问事故时间**并输出，记得安抚“请务必注意安全”。\n\n#### 如果回答语义破碎或疑似 ASR 误识别人伤\n\n无法判断是否严重时，先确认。\n\n你的输出：\n\n`<state>1002</state>我刚才没有完全听清楚。请您明确确认一下，被撞到的人或车情况是否严重？是否有人受伤，或者需要呼叫救护车？`\n\n### 如果用户未明确回答\n\n例如“不清楚”、“没注意”、“好像有”。\n\n你的输出：\n\n`<state>1002</state>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---\n\n# 阶段二：核心信息收集\n\n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\n当前时间：`{{$VARIABLE_NODE_ID.cTime$}}`\n\n### 思考逻辑\n\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\n### 执行分支\n\n#### 分支A：用户未提及\n\n你的输出：\n\n`<state>1002</state>请问事故大概是什么时候发生的？请告诉我具体时间点。`\n\n#### 分支B：用户已提及，且时间合理\n\n进入**复述标准时间并确认**并输出。\n\n#### 分支C：用户已提及，但时间在未来 / 反事实\n\n你的输出：\n\n`<state>1002</state>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\n## 5. 复述标准时间并确认\n\n当前时间：`{{$VARIABLE_NODE_ID.cTime$}}`\n\n### 思考逻辑\n\n无论上一步是询问还是确认，用户在此步给出最终回复后，你必须再次进行反事实检测。\n\n用户提到的时间，或即将输入的时间，是否晚于当前系统时间（精确到小时）？\n\n如果是，视为无效回答。\n\n### 时间格式\n\n你一定使用 `XXXX年XX月XX日XX点XX分` 的形式向用户确认时间。\n\n你的输出示例：\n\n`<state>1002</state>好的，我记录的时间是2025年1月1日8点30分，请问这个时间对吗？`\n\n### 执行分支\n\n#### 分支A：用户确认，但时间在未来 / 反事实\n\n如果时间在未来，即反事实，你输出：\n\n`<state>1002</state>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\n#### 分支B：用户确认，且时间小于等于当前时间\n\n进入**询问用户是否在事故现场**并输出。\n\n#### 分支C：用户否定\n\n进入**询问事故时间**重新询问。\n\n## 6. 询问用户是否在事故现场\n\n前提：确保此信息未在用户初始的事故描述中提及。\n\n你的输出：\n\n`<state>1002</state>请问您现在还在事故现场吗？`\n\n## 7. 询问车辆数量情况（关键信息点）\n\n### 思考逻辑\n\n用户在之前的描述中是否已经提及了车辆数量情况？\n\n### 执行分支\n\n#### 分支A：车辆数量已经提及\n\n你的输出：\n\n`<state>1002</state>请确认一下事故车辆数量是x辆，对吗？`\n\n#### 分支B：车辆数量未提及\n\n你的输出：\n\n`<state>1002</state>请问有几辆汽车卷入了这次事故呢？请您告诉我一个具体的数字。`\n\n你需要记住这个数字。\n\n---\n\n# 阶段三：信息收集完毕，根据情况分流\n\n## 8. 根据车辆数量进行调度\n\n触发条件：在获得用户关于“车辆数量”的有效回复后，立即执行。\n\n此时，你必须根据已收集到的车辆信息（来自步骤7或用户初始描述）和安全检查结果进行判断。\n\n### 如果事故只涉及 1 辆机动车，且无非机动车 / 行人、无人伤\n\n你的输出：\n\n`<state>2000</state>好的，信息已记录。接下来将引导您对车辆进行拍照。请对准车辆前方，看清车牌，拍摄一张车前方照片。`\n\n### 如果事故涉及 2 辆机动车，且无非机动车 / 行人、无人伤\n\n你的输出：\n\n`<state>2010</state>好的，信息已记录。接下来将引导您和对方驾驶员进行拍照。请对准第一辆车的侧前方，看清车牌，拍摄照片。`\n\n### 如果事故涉及 3 辆或以上机动车，或任何数量的非机动车 / 行人，或有人伤亡\n\n即使情况不严重，也优先转人工。\n\n你的输出：\n\n`<state>0003</state>感谢您的配合。由于事故情况较复杂，为确保处理无误，我将为您转接人工警员做进一步处理。请不要挂断电话。`\n\n---\n\n# 最终输出自检\n\n在每次输出前，必须完成以下检查：\n\n1. 最终回复是否以 `<state>状态编码</state>` 开头。\n2. `<state>状态编码</state>` 是否只出现一次。\n3. `<state>状态编码</state>` 是否只位于最前缀。\n4. 回复正文中是否没有再次出现 `<state>`、`</state>` 或状态编码说明。\n5. 是否没有输出 JSON、Markdown、解释或分析过程。\n6. 是否遵守安全优先原则。\n7. 是否避免因 ASR 孤立关键词、否定句或语义破碎而误判人伤。\n8. 是否没有跳过当前尚未获得有效答案的问题。\n",
"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": "知识库引用",
"description": "",
"valueType": "datasetQuote",
"valueDesc": "",
"toolDescription": ""
},
{
"key": "fileUrlList",
"renderTypeList": [
"reference",
"input"
],
"label": "app:workflow.user_file_input",
"debugLabel": "文件链接",
"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": "用户问题",
"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": "将本次回复内容拼接上历史记录，作为新的上下文返回",
"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": "将在 stream 回复完毕后触发",
"valueType": "string",
"type": "static"
},
{
"id": "reasoningText",
"key": "reasoningText",
"required": false,
"label": "workflow:reasoning_content",
"valueType": "string",
"type": "static",
"invalid": false,
"description": ""
},
{
"id": "system_error_text",
"key": "system_error_text",
"type": "error",
"valueType": "string",
"label": "workflow:error_text",
"description": ""
}
],
"catchError": false
},
{
"nodeId": "agZJVmMQXusk",
"name": "解析状态",
"intro": "Execute a simple script code, usually for complex data processing.",
"avatar": "core/workflow/template/codeRun",
"flowNodeType": "code",
"showStatus": true,
"position": {
"x": 5010,
"y": -2115
},
"version": "482",
"inputs": [
{
"key": "system_addInputParam",
"renderTypeList": [
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],
"valueType": "dynamic",
"label": "",
"required": false,
"description": "workflow:these_variables_will_be_input_parameters_for_code_execution",
"customInputConfig": {
"selectValueTypeList": [
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"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"arrayAny",
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"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": [
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],
"label": "",
"value": "function extractStateAndContent(data1) {\n // Regular expression to match the <state>STATE</state>content format.\n const regex = /<state>(.*?)<\\/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": [
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],
"valueType": "string",
"canEdit": true,
"key": "data1",
"label": "data1",
"customInputConfig": {
"selectValueTypeList": [
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"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"arrayAny",
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"chatHistory",
"datasetQuote",
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"selectDataset",
"selectApp"
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"showDescription": false,
"showDefaultValue": true
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"required": true,
"value": [
"yQaBxfrWjbRr",
"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": "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": "doubao-seed-2-0-mini-260428",
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": ""
},
{
"key": "temperature",
"renderTypeList": [
"hidden"
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"value": "# 角色\n\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\n**全局中断指令（最高优先级）**：\n\n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**：\n\n`<state>0001</state>好的，正在为您转接人工客服，请稍候。`\n\n**客户端连续拍摄识别失败指令（高优先级）**：\n\n在单车拍照流程的任何阶段，只要收到一次格式为：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n的客户端输入，就表示客户端已经完成3次拍摄识别重试，并且3次均未成功。\n\n你必须：\n\n1. 立即停止当前单车拍照流程。\n2. 不得继续要求用户重新拍摄。\n3. 不得进入下一个拍照或信息确认阶段。\n4. 不得重复当前状态的拍照引导指令。\n5. 无论“原因”部分是什么内容，都必须只输出：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n该指令的优先级高于`【拍摄完成】`、用户自然语言回答和当前步骤的其他处理规则。\n\n**严格的输出格式**：\n\n你的所有回复都**必须**以 `<state>状态编码</state>` 开头。\n\n**混合流程锁定协议（Hybrid Process Lock Protocol）**：\n\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\n- **行为模式A（针对步骤2000、2001、2002、2003）**：\n - **唯一正常推进触发**：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 - **客户端连续失败触发**：如果接收到`【客户端连续3次拍摄识别失败：原因】`，立即停止当前流程并返回0005。\n - **无效输入处理**：对于既不是`【拍摄完成】`，也不是`【客户端连续3次拍摄识别失败：原因】`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\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 - **客户端连续失败触发**：如果接收到`【客户端连续3次拍摄识别失败：原因】`，立即停止当前流程并返回0005。\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\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**：用户主动要求转人工。 |\n| **0002** | **流程异常转人工**：未能成功记录相关信息，为确保信息准确，转人工处理。 |\n| **0005** | **客户端连续拍摄识别失败**：客户端完成3次拍摄识别重试后仍未成功，停止自动拍照流程并转人工。 |\n\n---\n\n# 客户端连续拍摄识别失败示例\n\n**输入**：\n\n`【客户端连续3次拍摄识别失败：未识别到完整车牌】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n**输入**：\n\n`【客户端连续3次拍摄识别失败：照片上传失败】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n**输入**：\n\n`【客户端连续3次拍摄识别失败：当前无法使用摄像头】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n---\n\n# 任务流程（体现混合模式）\n\n## 流程起点：步骤2000\n\n**你的初始输出**：\n\n`<state>2000</state>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\n**当系统输入为**：\n\n`【拍摄完成】`\n\n**你的输出**：\n\n`<state>2001</state>请对准车辆碰撞部位拍摄照片。`\n\n**当系统输入为**：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n**当用户输入为任何其他内容时**，例如“好的”“拍好了”：\n\n**你的输出（重复指令）**：\n\n`<state>2000</state>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\n**当系统输入为**：\n\n`【拍摄完成】`\n\n**你的输出**：\n\n`<state>2002</state>请对准被撞物品拍摄照片。`\n\n**当系统输入为**：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n**当用户输入为任何其他内容时**，例如“OK”“已经拍了”：\n\n**你的输出（重复指令）**：\n\n`<state>2001</state>请对准车辆碰撞部位拍摄照片。`\n\n---\n\n## 步骤2002 -> 步骤2003（行为模式A）\n\n**当系统输入为**：\n\n`【拍摄完成】`\n\n**你的输出**：\n\n`<state>2003</state>请切换摄像头对准本人拍摄一张正面照片。`\n\n**当系统输入为**：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n**当用户输入为任何其他内容时**：\n\n**你的输出（重复指令）**：\n\n`<state>2002</state>请对准被撞物品拍摄照片。`\n\n---\n\n## 步骤2003 -> 步骤2004（行为模式A切换到行为模式B）\n\n**当系统输入为**：\n\n`【拍摄完成】`\n\n**你的输出**：\n\n`<state>2004</state>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**当系统输入为**：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n**当用户输入为任何其他内容时**：\n\n**你的输出（重复指令）**：\n\n`<state>2003</state>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 -> 步骤2005（合并后的确认与纠错流程）\n\n**AI当前状态为2004。**\n\n### 场景A：用户确认车牌正确\n\n**当用户输入为**：“是的”“没错”“对的”等肯定回答。\n\n**你的输出（继续主流程）**：\n\n`<state>2005</state>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\n### 场景B：用户提供新的车牌号\n\n**当用户输入为**：“不对，车牌号是苏BXXXXX”“我的车牌是沪A12345”等直接提供新信息的回答。\n\n**你的输出（记录新信息并继续主流程）**：\n\n`<state>2005</state>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\n### 场景C：用户回答不清晰或无关\n\n**当用户输入为**：“不是这辆车”“不对”“什么意思？”等否定但未提供新信息或无关回答。\n\n**你的输出（重复当前问题，引导用户）**：\n\n`<state>2004</state>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### 场景D：收到客户端连续失败事件\n\n**当系统输入为**：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n\n---\n\n# 流程终点：步骤2005（行为模式B）\n\n**AI当前状态为2005。**\n\n### 用户提供有效车损位置\n\n**当用户输入为**：“是车子的左前方。”等有效自然语言回答。\n\n**你的输出**：\n\n`<state>3001</state>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\n### 用户第一次输入无效\n\n**当用户输入为**：“什么意思？”等无效自然语言回答。\n\n**你的输出（重复完整指令）**：\n\n`<state>2005</state>请确认车损位置是在车辆前方、后方还是侧面？`\n\n### 用户第二次输入仍然无效\n\n**你的输出（转接人工）**：\n\n`<state>0002</state>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。`\n\n### 收到客户端连续失败事件\n\n**当系统输入为**：\n\n`【客户端连续3次拍摄识别失败：原因】`\n\n**你的输出**：\n\n`<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`",
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"condition": "equalTo",
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},
{
"variable": [
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"status_code"
],
"condition": "equalTo",
"value": "0005",
"valueType": "input"
}
]
}
],
"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": [
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"label": "common:core.module.input.label.aiModel",
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"value": "doubao-seed-2-0-mini-260428",
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"description": "",
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"toolDescription": ""
},
{
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],
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},
{
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],
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},
{
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],
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"value": true,
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},
{
"key": "aiChatQuoteRole",
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],
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"valueType": "string",
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"description": "",
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},
{
"key": "quoteTemplate",
"renderTypeList": [
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],
"label": "",
"valueType": "string",
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"description": "",
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},
{
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],
"label": "",
"valueType": "string",
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"description": "",
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},
{
"key": "aiChatVision",
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],
"label": "",
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"description": "",
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},
{
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],
"label": "",
"valueType": "boolean",
"value": true,
"valueDesc": "",
"description": "",
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},
{
"key": "aiChatTopP",
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],
"label": "",
"valueType": "number",
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"description": "",
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"toolDescription": ""
},
{
"key": "aiChatStopSign",
"renderTypeList": [
"hidden"
],
"label": "",
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"description": "",
"debugLabel": "",
"toolDescription": ""
},
{
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"hidden"
],
"label": "",
"valueType": "string",
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": ""
},
{
"key": "aiChatJsonSchema",
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"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\n **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** `<state>0001</state>好的，正在为您转接人工客服，请稍候。`\n\n **客户端连续拍摄识别失败指令**:\n- 在对话的**任何阶段**，如果接收到格式为 `【客户端连续3次拍摄识别失败：原因】` 的客户端输入，例如：\n - `【客户端连续3次拍摄识别失败：未识别到完整车牌】`\n - `【客户端连续3次拍摄识别失败：摄像头启动失败】`\n - `【客户端连续3次拍摄识别失败：图片过于模糊】`\n- 你必须理解这是客户端已经连续三次无法完成拍摄或识别。\n- 无论当前处于 `2010` 至 `2016` 中的哪个步骤，都必须**立即停止当前拍照与核验流程**。\n- 你必须**只输出**：\n `<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n- 不得继续原步骤、不得重复拍摄指令、不得要求用户再次拍摄，也不得自行尝试解决失败原因。\n- 只要收到一次符合上述格式的输入，就立即进入 `0005` 状态，不需要累计或判断失败次数。失败次数由客户端负责统计。\n\n **严格的输出格式**: 你的所有回复都**必须**以 `<state>状态编码</state>` 开头。\n\n **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- **例外情况**: 全局转人工指令、客户端连续拍摄识别失败指令和流程异常转人工不受上述顺序限制。\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**: 对于既不是 `【拍摄完成】`，也不符合全局中断指令或客户端连续拍摄识别失败指令的输入，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\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| **0005** | **(客户端连续拍摄识别失败转人工)** 多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。 |\n\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**: `<state>2010</state>请对准第一辆车的侧前方，看清车牌拍摄。`\n\n---\n\n**客户端连续拍摄识别失败处理（适用于整个流程）**\n- **当客户端输入格式为**: `【客户端连续3次拍摄识别失败：原因】`\n- **例如**: `【客户端连续3次拍摄识别失败：未识别到完整车牌】`\n- **你的输出**: `<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`\n- 输出 `0005` 后立即终止当前拍照与核验流程。\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**: `<state>2011</state>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**（不包括全局中断指令和客户端连续拍摄识别失败指令，例如：“拍了”）\n - **你的输出（重复指令）**: `<state>2010</state>请对准第一辆车的侧前方，看清车牌拍摄。`\n\n---\n\n**步骤 2011 -> 2012 (行为模式A)**\n- **当系统输入为**: `【拍摄完成】`\n - **你的输出**: `<state>2012</state>请对准第二辆车碰撞部位拍摄。`\n- **当用户输入为**: **任何其他内容**（不包括全局中断指令和客户端连续拍摄识别失败指令）\n - **你的输出（重复指令）**: `<state>2011</state>请对准第一辆车碰撞部位拍摄。`\n\n---\n\n**步骤 2012 -> 2013 (行为模式A)**\n- **当系统输入为**: `【拍摄完成】`\n - **你的输出**: `<state>2013</state>请对准第二方车辆侧后方，看清车牌拍摄。`\n- **当用户输入为**: **任何其他内容**（不包括全局中断指令和客户端连续拍摄识别失败指令）\n - **你的输出（重复指令）**: `<state>2012</state>请对准第二辆车碰撞部位拍摄。`\n\n---\n\n**步骤 2013 -> 2014 (行为模式A)**\n- **当系统输入为**: `【拍摄完成】`\n - **你的输出**: `<state>2014</state>请拍摄另一方驾驶人的正面照片。`\n- **当用户输入为**: **任何其他内容**（不包括全局中断指令和客户端连续拍摄识别失败指令）\n - **你的输出（重复指令）**: `<state>2013</state>请对准第二方车辆侧后方，看清车牌拍摄。`\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**: `<state>2015</state>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**（不包括全局中断指令和客户端连续拍摄识别失败指令）\n - **你的输出（重复指令）**: `<state>2014</state>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**: `<state>2016</state>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**（不包括全局中断指令和客户端连续拍摄识别失败指令）\n - **你的输出（重复指令）**: `<state>2015</state>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\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”等肯定回答\n - **你的输出（结束流程）**: `<state>3002</state>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\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”等直接提供新信息的回答\n - **你的输出（记录新信息并结束流程）**: `<state>3002</state>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\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？”等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）**: `<state>2016</state>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\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）**: `<state>0002</state>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- **场景E: 客户端报告连续拍摄识别失败**\n - **当输入格式为**: `【客户端连续3次拍摄识别失败：原因】`\n - **你的输出（立即转接人工）**: `<state>0005</state>多次拍摄识别仍未成功，为确保信息准确，正在为您转接人工处理，请稍候。`",
"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": "知识库引用",
"description": "",
"valueType": "datasetQuote",
"valueDesc": "",
"toolDescription": ""
},
{
"key": "fileUrlList",
"renderTypeList": [
"reference",
"input"
],
"label": "app:workflow.user_file_input",
"debugLabel": "文件链接",
"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": "用户问题",
"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": "将本次回复内容拼接上历史记录，作为新的上下文返回",
"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": "将在 stream 回复完毕后触发",
"valueType": "string",
"type": "static"
},
{
"id": "reasoningText",
"key": "reasoningText",
"required": false,
"label": "workflow:reasoning_content",
"valueType": "string",
"type": "static",
"invalid": false,
"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": "doubao-seed-2-0-mini-260428",
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": ""
},
{
"key": "temperature",
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"hidden"
],
"label": "",
"valueType": "number",
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": ""
},
{
"key": "maxToken",
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],
"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 `<state>状态编码</state>` 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)**: `<state>3001</state>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**: `<state>3001</state>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**: `<state>3001</state>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**: `<state>3001</state>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**: `<state>3001</state>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: <state>3001</state>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: <state>3001</state>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**: `<state>3001</state>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: <state>3001</state>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: <state>3001</state>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**: `<state>0000</state>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": "知识库引用",
"description": "",
"valueType": "datasetQuote",
"valueDesc": "",
"toolDescription": ""
},
{
"key": "fileUrlList",
"renderTypeList": [
"reference",
"input"
],
"label": "app:workflow.user_file_input",
"debugLabel": "文件链接",
"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": "用户问题",
"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": "将本次回复内容拼接上历史记录，作为新的上下文返回",
"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": "将在 stream 回复完毕后触发",
"valueType": "string",
"type": "static"
},
{
"id": "reasoningText",
"key": "reasoningText",
"required": false,
"label": "workflow:reasoning_content",
"valueType": "string",
"type": "static",
"invalid": false,
"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 <state>STATE</state>content format.\n const regex = /<state>(.*?)<\\/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",
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"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 `<state>状态编码</state>` 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)**: `<state>3002</state>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**: `<state>3002</state>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：`<state>3002</state>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**: `<state>3002</state>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**: `<state>3002</state>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: <state>3001</state>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: <state>3001</state>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**: `<state>3002</state>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: <state>3001</state>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: <state>3001</state>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**: `<state>3002</state>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**: `<state>3002</state>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：`<state>3002</state>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**: `<state>3002</state>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**: `<state>3002</state>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**: `<state>3002</state>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**: `<state>0000</state>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。`",
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"isRichText": true
},
{
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"renderTypeList": [
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"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": "",
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},
{
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"renderTypeList": [
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],
"label": "",
"debugLabel": "知识库引用",
"description": "",
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},
{
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],
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},
{
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],
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"required": true,
"value": [
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"valueDesc": "",
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}
],
"outputs": [
{
"id": "history",
"key": "history",
"required": true,
"label": "common:core.module.output.label.New context",
"description": "将本次回复内容拼接上历史记录，作为新的上下文返回",
"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": "将在 stream 回复完毕后触发",
"valueType": "string",
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},
{
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"key": "reasoningText",
"required": false,
"label": "workflow:reasoning_content",
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{
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"value": [
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"valueDesc": "",
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],
"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",
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"customFieldConfig": {
"selectValueTypeList": [
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"boolean",
"object",
"arrayString",
"arrayNumber",
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"arrayObject",
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"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": "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
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"version": "481",
"inputs": [
{
"key": "ifElseList",
"renderTypeList": [
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],
"valueType": "any",
"label": "",
"value": [
{
"condition": "AND",
"list": [
{
"variable": [
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"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": {
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"version": "481",
"inputs": [
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"valueType": "any",
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"renderTypeList": [
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"value": [
{
"variable": [
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"status_code"
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"value": "function extractStateAndContent(data1) {\n // Regular expression to match the <state>STATE</state>content format.\n const regex = /<state>(.*?)<\\/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 <state>STATE</state>content format.\n const regex = /<state>(.*?)<\\/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"
},
{
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"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": "<state>{{$VARIABLE_NODE_ID.status_code$}}</state>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": "<state>{{$VARIABLE_NODE_ID.status_code$}}</state>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. Non-string content will be converted to string for output.",
"avatar": "core/workflow/template/reply",
"flowNodeType": "answerNode",
"position": {
"x": 1102.2926613349941,
"y": -1883.0499157125691
},
"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": "<state>1001</state>您好，这里是无锡交警，我将为您远程处理交通事故。请将人员撤离至路侧安全区域，开启危险报警双闪灯、放置三角警告牌、做好安全防护，谨防二次事故伤害。若您已经准备好了，请点击继续办理，如需人工服务，请说转人工。",
"valueDesc": "",
"debugLabel": "",
"toolDescription": "",
"isRichText": false,
"maxLength": 100000
}
],
"outputs": []
},
{
"nodeId": "mErEqe061uAd",
"name": "Variable Update#6",
"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": 1815,
"y": -1530
},
"version": "481",
"inputs": [
{
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"valueType": "any",
"label": "",
"renderTypeList": [
"hidden"
],
"value": [
{
"variable": [
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"is_first_message"
],
"value": [
"",
""
],
"valueType": "boolean",
"renderType": "input"
}
],
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": ""
}
],
"outputs": []
},
{
"nodeId": "ffV7U6t2Wrkc",
"name": "Condition#9",
"intro": "Execute different branches based on conditions.",
"avatar": "core/workflow/template/ifelse",
"flowNodeType": "ifElseNode",
"showStatus": true,
"position": {
"x": 436.7701670253358,
"y": -1391.7660436128006
},
"version": "481",
"inputs": [
{
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"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"value": [
{
"condition": "AND",
"list": [
{
"variable": [
"VARIABLE_NODE_ID",
"is_first_message"
],
"condition": "equalTo",
"value": "true"
}
]
}
],
"valueDesc": "",
"description": "",
"debugLabel": "",
"toolDescription": ""
}
],
"outputs": [
{
"id": "ifElseResult",
"key": "ifElseResult",
"label": "workflow:judgment_result",
"valueType": "string",
"type": "static",
"description": ""
}
]
},
{
"nodeId": "dDTqgmBFNDPh0DwX",
"name": "Condition#10",
"intro": "Execute different branches based on conditions.",
"avatar": "core/workflow/template/ifelse",
"flowNodeType": "ifElseNode",
"showStatus": true,
"position": {
"x": 3075,
"y": -3165
},
"inputs": [
{
"key": "ifElseList",
"renderTypeList": [
"hidden"
],
"valueType": "any",
"label": "",
"value": [
{
"condition": "AND",
"list": [
{
"variable": [
"VARIABLE_NODE_ID",
"zl8sNWrf"
],
"condition": "equalTo",
"value": "true",
"valueType": "input"
}
]
}
],
"debugLabel": "",
"toolDescription": ""
}
],
"outputs": [
{
"id": "ifElseResult",
"key": "ifElseResult",
"label": "workflow:judgment_result",
"valueType": "string",
"type": "static",
"valueDesc": "",
"description": ""
}
]
},
{
"nodeId": "znnXN7FuRHfCwJmw",
"name": "文本内容提取事故信息",
"intro": "Can extract specified data from text, such as SQL statements, search keywords, code, etc.",
"avatar": "core/workflow/template/extractJson",
"flowNodeType": "contentExtract",
"showStatus": true,
"position": {
"x": 4245,
"y": -3405
},
"version": "4.9.2",
"inputs": [
{
"key": "model",
"renderTypeList": [
"selectLLMModel",
"reference"
],
"label": "common:core.module.input.label.aiModel",
"required": true,
"valueType": "string",
"llmModelType": "extractFields",
"value": "doubao-seed-2-0-mini-260428",
"debugLabel": "",
"toolDescription": ""
},
{
"key": "description",
"renderTypeList": [
"textarea",
"reference"
],
"valueType": "string",
"label": "workflow:extraction_requirements_description",
"description": "workflow:extraction_requirements_description_detail",
"placeholder": "workflow:extraction_requirements_placeholder",
"value": "目前表单为：\n{{$VARIABLE_NODE_ID.bNJkeXot$}}\n从对话中仅提取相对目前表单可以更新的数据，不更新的字段可以不返回\n事故发生时间要记录准确时间例如2026年6月17日10点51分",
"debugLabel": "",
"toolDescription": ""
},
{
"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,
"debugLabel": "",
"toolDescription": ""
},
{
"key": "content",
"renderTypeList": [
"reference",
"textarea"
],
"label": "workflow:text_to_extract",
"required": true,
"valueType": "string",
"toolDescription": "需要检索的内容",
"value": [
"448745",
"userChatInput"
],
"debugLabel": ""
},
{
"key": "extractKeys",
"renderTypeList": [
"custom"
],
"label": "",
"valueType": "any",
"description": "workflow:target_fields_description",
"value": [
{
"valueType": "object",
"required": true,
"defaultValue": "",
"desc": "表单更新数据",
"key": "formUpdate",
"enum": ""
}
],
"debugLabel": "",
"toolDescription": ""
}
],
"outputs": [
{
"id": "success",
"key": "success",
"label": "workflow:full_field_extraction",
"required": true,
"description": "提取字段全部填充时返回 true （模型提取或使用默认值均属于成功）",
"valueType": "boolean",
"type": "static",
"valueDesc": ""
},
{
"id": "fields",
"key": "fields",
"label": "workflow:complete_extraction_result",
"required": true,
"description": "一个 JSON 字符串，例如：{\"name:\":\"YY\",\"Time\":\"2023/7/2 18:00\"}",
"valueType": "string",
"type": "static",
"valueDesc": ""
},
{
"id": "system_error_text",
"key": "system_error_text",
"type": "error",
"valueType": "string",
"label": "workflow:error_text",
"valueDesc": "",
"description": ""
},
{
"id": "t304GMFxQwoG9Gqk",
"key": "formUpdate",
"label": "Extraction Results-formUpdate",
"valueType": "object",
"type": "static"
}
],
"catchError": false
},
{
"nodeId": "ywRJRfv7ytNbITE9",
"name": "更新表单",
"intro": "Execute a simple script code, usually for complex data processing.",
"avatar": "core/workflow/template/codeRun",
"flowNodeType": "code",
"showStatus": true,
"position": {
"x": 5205,
"y": -3345
},
"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
},
"debugLabel": "",
"toolDescription": ""
},
{
"key": "codeType",
"renderTypeList": [
"hidden"
],
"label": "",
"valueType": "string",
"value": "js",
"debugLabel": "",
"toolDescription": ""
},
{
"key": "code",
"renderTypeList": [
"custom"
],
"label": "",
"valueType": "string",
"value": "function main({ form, formUpdate }) {\n // 1. 安全校验：确保输入为对象，否则使用空对象\n const baseForm = (form && typeof form === 'object') ? form : {};\n const updateData = (formUpdate && typeof formUpdate === 'object') ? formUpdate : {};\n\n // 2. 初始化结果对象，基于 baseForm 的所有键\n let formNew = {};\n\n // 3. 遍历 baseForm 的所有键\n for (let key in baseForm) {\n if (Object.prototype.hasOwnProperty.call(baseForm, key)) {\n // 4. 如果 updateData 中存在该键且有值，则更新；否则保留原值\n if (updateData.hasOwnProperty(key)) {\n formNew[key] = updateData[key];\n } else {\n formNew[key] = baseForm[key];\n }\n }\n }\n\n return {\n formNew: formNew\n };\n}",
"debugLabel": "",
"toolDescription": ""
},
{
"renderTypeList": [
"reference"
],
"valueType": "object",
"canEdit": true,
"key": "formUpdate",
"label": "formUpdate",
"customInputConfig": {
"selectValueTypeList": [
"string",
"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"arrayAny",
"any",
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"datasetQuote",
"dynamic",
"selectDataset",
"selectApp"
],
"showDescription": false,
"showDefaultValue": true
},
"required": true,
"value": [
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"t304GMFxQwoG9Gqk"
]
},
{
"renderTypeList": [
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],
"valueType": "object",
"canEdit": true,
"key": "form",
"label": "form",
"customInputConfig": {
"selectValueTypeList": [
"string",
"number",
"boolean",
"object",
"arrayString",
"arrayNumber",
"arrayBoolean",
"arrayObject",
"arrayAny",
"any",
"chatHistory",
"datasetQuote",
"dynamic",
"selectDataset",
"selectApp"
],
"showDescription": false,
"showDefaultValue": true
},
"required": true,
"value": [
"VARIABLE_NODE_ID",
"bNJkeXot"
]
}
],
"outputs": [
{
"id": "system_rawResponse",
"key": "system_rawResponse",
"label": "workflow:full_response_data",
"valueType": "object",
"type": "static",
"valueDesc": "",
"description": ""
},
{
"id": "error",
"key": "error",
"label": "workflow:error_text",
"valueType": "string",
"type": "error",
"valueDesc": "",
"description": ""
},
{
"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": "formNew",
"valueType": "object",
"label": "formNew",
"valueDesc": "",
"description": ""
}
],
"catchError": false
},
{
"nodeId": "zbwLMJrAICiypHwX",
"name": "Variable Update#7",
"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": 6420,
"y": -3030
},
"inputs": [
{
"key": "updateList",
"valueType": "any",
"label": "",
"renderTypeList": [
"hidden"
],
"value": [
{
"variable": [
"VARIABLE_NODE_ID",
"bNJkeXot"
],
"value": [
"ywRJRfv7ytNbITE9",
"qLUQfhG0ILRX"
],
"valueType": "object",
"renderType": "reference"
}
],
"debugLabel": "",
"toolDescription": ""
}
],
"outputs": []
}
],
"edges": [
{
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}
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