mirror of
https://github.com/labring/FastGPT.git
synced 2025-07-23 21:13:50 +00:00
template add i18n (#2558)
* template add i18n * add English translation
This commit is contained in:
papapatrick
@@ -9,8 +9,9 @@ export const Input_Template_History: FlowNodeInputItemType = {
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key: NodeInputKeyEnum.history,
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renderTypeList: [FlowNodeInputTypeEnum.numberInput, FlowNodeInputTypeEnum.reference],
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valueType: WorkflowIOValueTypeEnum.chatHistory,
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label: 'core.module.input.label.chat history',
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description: '最多携带多少轮对话记录',
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label: i18nT('common:core.module.input.label.chat history'),
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description: i18nT('workflow:max_dialog_rounds'),
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required: true,
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min: 0,
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max: 50,
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@@ -21,7 +22,7 @@ export const Input_Template_UserChatInput: FlowNodeInputItemType = {
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key: NodeInputKeyEnum.userChatInput,
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renderTypeList: [FlowNodeInputTypeEnum.reference, FlowNodeInputTypeEnum.textarea],
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valueType: WorkflowIOValueTypeEnum.string,
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label: '用户问题',
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label: i18nT('workflow:user_question'),
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required: true
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};
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@@ -36,14 +37,14 @@ export const Input_Template_DynamicInput: FlowNodeInputItemType = {
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export const Input_Template_SelectAIModel: FlowNodeInputItemType = {
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key: NodeInputKeyEnum.aiModel,
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renderTypeList: [FlowNodeInputTypeEnum.selectLLMModel, FlowNodeInputTypeEnum.reference],
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label: 'core.module.input.label.aiModel',
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label: i18nT('common:core.module.input.label.aiModel'),
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required: true,
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valueType: WorkflowIOValueTypeEnum.string
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};
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export const Input_Template_SettingAiModel: FlowNodeInputItemType = {
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key: NodeInputKeyEnum.aiModel,
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renderTypeList: [FlowNodeInputTypeEnum.settingLLMModel, FlowNodeInputTypeEnum.reference],
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label: 'core.module.input.label.aiModel',
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label: i18nT('common:core.module.input.label.aiModel'),
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valueType: WorkflowIOValueTypeEnum.string
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};
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@@ -52,7 +53,7 @@ export const Input_Template_System_Prompt: FlowNodeInputItemType = {
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renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
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max: 3000,
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valueType: WorkflowIOValueTypeEnum.string,
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label: 'core.ai.Prompt',
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label: i18nT('common:core.ai.Prompt'),
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description: chatNodeSystemPromptTip,
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placeholder: chatNodeSystemPromptTip
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};
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@@ -61,7 +62,7 @@ export const Input_Template_Dataset_Quote: FlowNodeInputItemType = {
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key: NodeInputKeyEnum.aiChatDatasetQuote,
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renderTypeList: [FlowNodeInputTypeEnum.settingDatasetQuotePrompt],
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label: '',
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debugLabel: '知识库引用',
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debugLabel: i18nT('workflow:knowledge_base_reference'),
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description: '',
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valueType: WorkflowIOValueTypeEnum.datasetQuote
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};
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@@ -81,22 +81,23 @@ export const AiChatModule: FlowNodeTemplateType = {
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// settings modal ---
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{
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...Input_Template_System_Prompt,
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label: 'core.ai.Prompt',
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label: i18nT('common:core.ai.Prompt'),
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description: chatNodeSystemPromptTip,
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placeholder: chatNodeSystemPromptTip
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},
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Input_Template_History,
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Input_Template_Dataset_Quote,
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Input_Template_Text_Quote,
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{ ...Input_Template_UserChatInput, toolDescription: '用户问题' }
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{ ...Input_Template_UserChatInput, toolDescription: i18nT('workflow:user_question') }
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],
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outputs: [
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{
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id: NodeOutputKeyEnum.history,
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key: NodeOutputKeyEnum.history,
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required: true,
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label: 'core.module.output.label.New context',
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description: 'core.module.output.description.New context',
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label: i18nT('common:core.module.output.label.New context'),
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description: i18nT('common:core.module.output.description.New context'),
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valueType: WorkflowIOValueTypeEnum.chatHistory,
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valueDesc: chatHistoryValueDesc,
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type: FlowNodeOutputTypeEnum.static
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@@ -105,8 +106,8 @@ export const AiChatModule: FlowNodeTemplateType = {
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id: NodeOutputKeyEnum.answerText,
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key: NodeOutputKeyEnum.answerText,
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required: true,
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label: 'core.module.output.label.Ai response content',
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description: 'core.module.output.description.Ai response content',
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label: i18nT('common:core.module.output.label.Ai response content'),
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description: i18nT('common:core.module.output.description.Ai response content'),
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valueType: WorkflowIOValueTypeEnum.string,
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type: FlowNodeOutputTypeEnum.static
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}
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@@ -6,6 +6,7 @@ import {
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FlowNodeTemplateTypeEnum
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} from '../../constants';
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import { getHandleConfig } from '../utils';
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import { i18nT } from '../../../../../web/i18n/utils';
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export const AssignedAnswerModule: FlowNodeTemplateType = {
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id: FlowNodeTypeEnum.answerNode,
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@@ -14,9 +15,9 @@ export const AssignedAnswerModule: FlowNodeTemplateType = {
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sourceHandle: getHandleConfig(true, true, true, true),
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targetHandle: getHandleConfig(true, true, true, true),
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avatar: 'core/workflow/template/reply',
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name: '指定回复',
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intro:
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'该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。',
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name: i18nT('workflow:assigned_reply'),
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intro: i18nT('workflow:intro_assigned_reply'),
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version: '481',
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isTool: true,
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inputs: [
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@@ -25,9 +26,9 @@ export const AssignedAnswerModule: FlowNodeTemplateType = {
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renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
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valueType: WorkflowIOValueTypeEnum.any,
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required: true,
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label: 'core.module.input.label.Response content',
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description: 'core.module.input.description.Response content',
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placeholder: 'core.module.input.description.Response content'
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label: i18nT('common:core.module.input.label.Response content'),
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description: i18nT('common:core.module.input.description.Response content'),
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placeholder: i18nT('common:core.module.input.description.Response content')
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}
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],
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outputs: []
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@@ -18,6 +18,7 @@ import {
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import { Input_Template_System_Prompt } from '../../input';
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import { LLMModelTypeEnum } from '../../../../ai/constants';
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import { getHandleConfig } from '../../utils';
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import { i18nT } from '../../../../../../web/i18n/utils';
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export const ClassifyQuestionModule: FlowNodeTemplateType = {
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id: FlowNodeTypeEnum.classifyQuestion,
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@@ -26,8 +27,8 @@ export const ClassifyQuestionModule: FlowNodeTemplateType = {
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sourceHandle: getHandleConfig(false, false, false, false),
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targetHandle: getHandleConfig(true, false, true, true),
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avatar: 'core/workflow/template/questionClassify',
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name: '问题分类',
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intro: `根据用户的历史记录和当前问题判断该次提问的类型。可以添加多组问题类型，下面是一个模板例子：\n类型1: 打招呼\n类型2: 关于商品“使用”问题\n类型3: 关于商品“购买”问题\n类型4: 其他问题`,
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name: i18nT('workflow:question_classification'),
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intro: i18nT('workflow:intro_question_classification'),
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showStatus: true,
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version: '481',
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inputs: [
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@@ -50,15 +51,15 @@ export const ClassifyQuestionModule: FlowNodeTemplateType = {
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label: '',
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value: [
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{
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value: '打招呼',
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value: i18nT('workflow:greeting'),
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key: 'wqre'
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},
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{
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value: '关于 xxx 的问题',
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value: i18nT('workflow:about_xxx_question'),
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key: 'sdfa'
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},
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{
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value: '其他问题',
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value: i18nT('workflow:other_questions'),
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key: 'agex'
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}
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]
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@@ -69,7 +70,7 @@ export const ClassifyQuestionModule: FlowNodeTemplateType = {
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id: NodeOutputKeyEnum.cqResult,
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key: NodeOutputKeyEnum.cqResult,
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required: true,
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label: '分类结果',
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label: i18nT('workflow:classification_result'),
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valueType: WorkflowIOValueTypeEnum.string,
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type: FlowNodeOutputTypeEnum.static
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}
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@@ -13,6 +13,7 @@ import {
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import { Input_Template_SelectAIModel, Input_Template_History } from '../../input';
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import { LLMModelTypeEnum } from '../../../../ai/constants';
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import { getHandleConfig } from '../../utils';
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import { i18nT } from '../../../../../../web/i18n/utils';
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export const ContextExtractModule: FlowNodeTemplateType = {
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id: FlowNodeTypeEnum.contentExtract,
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@@ -21,8 +22,8 @@ export const ContextExtractModule: FlowNodeTemplateType = {
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sourceHandle: getHandleConfig(true, true, true, true),
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targetHandle: getHandleConfig(true, true, true, true),
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avatar: 'core/workflow/template/extractJson',
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name: '文本内容提取',
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intro: '可从文本中提取指定的数据，例如：sql语句、搜索关键词、代码等',
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name: i18nT('workflow:text_content_extraction'),
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intro: i18nT('workflow:intro_text_content_extraction'),
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showStatus: true,
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isTool: true,
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version: '481',
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@@ -35,27 +36,25 @@ export const ContextExtractModule: FlowNodeTemplateType = {
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key: NodeInputKeyEnum.description,
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renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
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valueType: WorkflowIOValueTypeEnum.string,
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label: '提取要求描述',
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description:
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'给AI一些对应的背景知识或要求描述，引导AI更好的完成任务。\n该输入框可使用全局变量。',
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placeholder:
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'例如: \n1. 当前时间为: {{cTime}}。你是一个实验室预约助手，你的任务是帮助用户预约实验室，从文本中获取对应的预约信息。\n2. 你是谷歌搜索助手，需要从文本中提取出合适的搜索词。'
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label: i18nT('workflow:extraction_requirements_description'),
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description: i18nT('workflow:extraction_requirements_description_detail'),
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placeholder: i18nT('workflow:extraction_requirements_placeholder')
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},
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Input_Template_History,
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{
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key: NodeInputKeyEnum.contextExtractInput,
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renderTypeList: [FlowNodeInputTypeEnum.reference, FlowNodeInputTypeEnum.textarea],
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label: '需要提取的文本',
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label: i18nT('workflow:text_to_extract'),
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required: true,
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valueType: WorkflowIOValueTypeEnum.string,
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toolDescription: '需要检索的内容'
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toolDescription: i18nT('workflow:content_to_retrieve')
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},
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{
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key: NodeInputKeyEnum.extractKeys,
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renderTypeList: [FlowNodeInputTypeEnum.custom],
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label: '',
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valueType: WorkflowIOValueTypeEnum.any,
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description: "由 '描述' 和 'key' 组成一个目标字段，可提取多个目标字段",
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description: i18nT('workflow:target_fields_description'),
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value: [] // {valueType: string; desc: string; key: string; required: boolean; enum: string[]}[]
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}
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],
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@@ -63,18 +62,18 @@ export const ContextExtractModule: FlowNodeTemplateType = {
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{
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id: NodeOutputKeyEnum.success,
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key: NodeOutputKeyEnum.success,
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label: '字段完全提取',
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label: i18nT('workflow:full_field_extraction'),
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required: true,
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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）',
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description: i18nT('workflow:full_field_extraction_description'),
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valueType: WorkflowIOValueTypeEnum.boolean,
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type: FlowNodeOutputTypeEnum.static
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},
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{
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id: NodeOutputKeyEnum.contextExtractFields,
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key: NodeOutputKeyEnum.contextExtractFields,
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label: '完整提取结果',
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label: i18nT('workflow:complete_extraction_result'),
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required: true,
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description: '一个 JSON 字符串，例如：{"name:":"YY","Time":"2023/7/2 18:00"}',
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description: i18nT('workflow:complete_extraction_result_description'),
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valueType: WorkflowIOValueTypeEnum.string,
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type: FlowNodeOutputTypeEnum.static
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}
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@@ -6,6 +6,7 @@ import {
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NodeInputKeyEnum
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} from '../../constants';
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import { getHandleConfig } from '../utils';
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import { i18nT } from '../../../../../web/i18n/utils';
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export const CustomFeedbackNode: FlowNodeTemplateType = {
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id: FlowNodeTypeEnum.customFeedback,
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@@ -14,8 +15,8 @@ export const CustomFeedbackNode: FlowNodeTemplateType = {
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sourceHandle: getHandleConfig(true, true, true, true),
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targetHandle: getHandleConfig(true, true, true, true),
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avatar: 'core/workflow/template/customFeedback',
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name: '自定义反馈',
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intro: '该模块被触发时，会给当前的对话记录增加一条反馈。可用于自动记录对话效果等。',
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name: i18nT('workflow:custom_feedback'),
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intro: i18nT('workflow:intro_custom_feedback'),
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version: '486',
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inputs: [
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{
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@@ -23,7 +24,7 @@ export const CustomFeedbackNode: FlowNodeTemplateType = {
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renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
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valueType: WorkflowIOValueTypeEnum.string,
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required: true,
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label: '反馈的文本'
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label: i18nT('workflow:feedback_text')
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}
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],
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outputs: []
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@@ -14,6 +14,7 @@ import {
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import { getNanoid } from '../../../../common/string/tools';
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import { getHandleConfig } from '../utils';
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import { FlowNodeInputItemType } from '../../type/io.d';
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import { i18nT } from '../../../../../web/i18n/utils';
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export const getOneQuoteInputTemplate = ({
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key = getNanoid(),
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@@ -24,8 +25,8 @@ export const getOneQuoteInputTemplate = ({
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}): FlowNodeInputItemType => ({
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key,
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renderTypeList: [FlowNodeInputTypeEnum.reference],
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label: `引用${index}`,
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debugLabel: '知识库引用',
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label: `${i18nT('workflow:quote_num')},{ num: ${index} }`,
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debugLabel: i18nT('workflow:knowledge_base_reference'),
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canEdit: true,
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valueType: WorkflowIOValueTypeEnum.datasetQuote
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});
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@@ -37,15 +38,17 @@ export const DatasetConcatModule: FlowNodeTemplateType = {
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sourceHandle: getHandleConfig(true, true, true, true),
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targetHandle: getHandleConfig(true, true, true, true),
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avatar: 'core/workflow/template/datasetConcat',
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name: '知识库搜索引用合并',
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intro: '可以将多个知识库搜索结果进行合并输出。使用 RRF 的合并方式进行最终排序输出。',
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name: i18nT('workflow:knowledge_base_search_merge'),
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intro: i18nT('workflow:intro_knowledge_base_search_merge'),
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showStatus: false,
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version: '486',
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inputs: [
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{
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key: NodeInputKeyEnum.datasetMaxTokens,
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renderTypeList: [FlowNodeInputTypeEnum.custom],
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label: '最大 Tokens',
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label: i18nT('workflow:max_tokens'),
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value: 3000,
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valueType: WorkflowIOValueTypeEnum.number
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},
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@@ -60,7 +63,7 @@ export const DatasetConcatModule: FlowNodeTemplateType = {
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{
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id: NodeOutputKeyEnum.datasetQuoteQA,
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key: NodeOutputKeyEnum.datasetQuoteQA,
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label: 'core.module.Dataset quote.label',
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label: i18nT('common:core.module.Dataset quote.label'),
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type: FlowNodeOutputTypeEnum.static,
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valueType: WorkflowIOValueTypeEnum.datasetQuote,
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valueDesc: datasetQuoteValueDesc
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@@ -34,7 +34,7 @@ export const DatasetSearchModule: FlowNodeTemplateType = {
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{
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key: NodeInputKeyEnum.datasetSelectList,
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renderTypeList: [FlowNodeInputTypeEnum.selectDataset, FlowNodeInputTypeEnum.reference],
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label: 'core.module.input.label.Select dataset',
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label: i18nT('common:core.module.input.label.Select dataset'),
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value: [],
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valueType: WorkflowIOValueTypeEnum.selectDataset,
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required: true
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@@ -90,34 +90,24 @@ export const DatasetSearchModule: FlowNodeTemplateType = {
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},
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{
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...Input_Template_UserChatInput,
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toolDescription: '需要检索的内容'
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toolDescription: i18nT('workflow:content_to_search')
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},
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{
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key: NodeInputKeyEnum.collectionFilterMatch,
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renderTypeList: [FlowNodeInputTypeEnum.JSONEditor, FlowNodeInputTypeEnum.reference],
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label: '集合元数据过滤',
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label: i18nT('workflow:collection_metadata_filter'),
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valueType: WorkflowIOValueTypeEnum.object,
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isPro: true,
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description: `目前支持标签和创建时间过滤，需按照以下格式填写：
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{
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"tags": {
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"$and": ["标签 1","标签 2"],
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"$or": ["有 $and 标签时，and 生效，or 不生效"]
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},
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"createTime": {
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"$gte": "YYYY-MM-DD HH:mm 格式即可，集合的创建时间大于该时间",
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"$lte": "YYYY-MM-DD HH:mm 格式即可，集合的创建时间小于该时间,可和 $gte 共同使用"
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}
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}
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`
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description: i18nT('workflow:filter_description')
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||||
}
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],
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outputs: [
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||||
{
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||||
id: NodeOutputKeyEnum.datasetQuoteQA,
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||||
key: NodeOutputKeyEnum.datasetQuoteQA,
|
||||
label: 'core.module.Dataset quote.label',
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description: '特殊数组格式，搜索结果为空时，返回空数组。',
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label: i18nT('common:core.module.Dataset quote.label'),
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description: i18nT('workflow:special_array_format'),
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type: FlowNodeOutputTypeEnum.static,
|
||||
valueType: WorkflowIOValueTypeEnum.datasetQuote,
|
||||
valueDesc: datasetQuoteValueDesc
|
||||
|
||||
@@ -13,6 +13,7 @@ import {
|
||||
import { Input_Template_DynamicInput } from '../input';
|
||||
import { Output_Template_AddOutput } from '../output';
|
||||
import { getHandleConfig } from '../utils';
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
|
||||
export const HttpNode468: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.httpRequest468,
|
||||
@@ -21,15 +22,15 @@ export const HttpNode468: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/httpRequest',
|
||||
name: 'HTTP 请求',
|
||||
intro: '可以发出一个 HTTP 请求，实现更为复杂的操作（联网搜索、数据库查询等）',
|
||||
name: i18nT('workflow:http_request'),
|
||||
intro: i18nT('workflow:intro_http_request'),
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
version: '481',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
description: 'core.module.input.description.HTTP Dynamic Input',
|
||||
description: i18nT('common:core.module.input.description.HTTP Dynamic Input'),
|
||||
customInputConfig: {
|
||||
selectValueTypeList: Object.values(WorkflowIOValueTypeEnum),
|
||||
showDescription: false,
|
||||
@@ -59,7 +60,7 @@ export const HttpNode468: FlowNodeTemplateType = {
|
||||
renderTypeList: [FlowNodeInputTypeEnum.hidden],
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
label: '',
|
||||
description: 'core.module.input.description.Http Request Url',
|
||||
description: i18nT('common:core.module.input.description.Http Request Url'),
|
||||
placeholder: 'https://api.ai.com/getInventory',
|
||||
required: false
|
||||
},
|
||||
@@ -69,8 +70,8 @@ export const HttpNode468: FlowNodeTemplateType = {
|
||||
valueType: WorkflowIOValueTypeEnum.any,
|
||||
value: [],
|
||||
label: '',
|
||||
description: 'core.module.input.description.Http Request Header',
|
||||
placeholder: 'core.module.input.description.Http Request Header',
|
||||
description: i18nT('common:core.module.input.description.Http Request Header'),
|
||||
placeholder: i18nT('common:core.module.input.description.Http Request Header'),
|
||||
required: false
|
||||
},
|
||||
{
|
||||
@@ -97,17 +98,17 @@ export const HttpNode468: FlowNodeTemplateType = {
|
||||
{
|
||||
id: NodeOutputKeyEnum.error,
|
||||
key: NodeOutputKeyEnum.error,
|
||||
label: '请求错误',
|
||||
description: 'HTTP请求错误信息，成功时返回空',
|
||||
label: i18nT('workflow:request_error'),
|
||||
description: i18nT('workflow:http_request_error_info'),
|
||||
valueType: WorkflowIOValueTypeEnum.object,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
},
|
||||
{
|
||||
id: NodeOutputKeyEnum.httpRawResponse,
|
||||
key: NodeOutputKeyEnum.httpRawResponse,
|
||||
label: '原始响应',
|
||||
required: true,
|
||||
description: 'HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。',
|
||||
label: i18nT('workflow:raw_response'),
|
||||
description: i18nT('workflow:http_raw_response_description'),
|
||||
valueType: WorkflowIOValueTypeEnum.any,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
}
|
||||
|
||||
@@ -1,3 +1,5 @@
|
||||
import { i18nT } from '../../../../../../web/i18n/utils';
|
||||
|
||||
export enum VariableConditionEnum {
|
||||
equalTo = 'equalTo',
|
||||
notEqual = 'notEqual',
|
||||
@@ -29,64 +31,85 @@ export enum IfElseResultEnum {
|
||||
}
|
||||
|
||||
export const stringConditionList = [
|
||||
{ label: '为空', value: VariableConditionEnum.isEmpty },
|
||||
{ label: '不为空', value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: '等于', value: VariableConditionEnum.equalTo },
|
||||
{ label: '不等于', value: VariableConditionEnum.notEqual },
|
||||
{ label: '正则', value: VariableConditionEnum.reg },
|
||||
{ label: '包含', value: VariableConditionEnum.include },
|
||||
{ label: '不包含', value: VariableConditionEnum.notInclude },
|
||||
{ label: '开始为', value: VariableConditionEnum.startWith },
|
||||
{ label: '结束为', value: VariableConditionEnum.endWith }
|
||||
{ label: i18nT('workflow:is_empty'), value: VariableConditionEnum.isEmpty },
|
||||
{ label: i18nT('workflow:is_not_empty'), value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: i18nT('workflow:is_equal_to'), value: VariableConditionEnum.equalTo },
|
||||
{ label: i18nT('workflow:is_not_equal'), value: VariableConditionEnum.notEqual },
|
||||
{ label: i18nT('workflow:regex'), value: VariableConditionEnum.reg },
|
||||
{ label: i18nT('workflow:contains'), value: VariableConditionEnum.include },
|
||||
{ label: i18nT('workflow:not_contains'), value: VariableConditionEnum.notInclude },
|
||||
{ label: i18nT('workflow:start_with'), value: VariableConditionEnum.startWith },
|
||||
{ label: i18nT('workflow:end_with'), value: VariableConditionEnum.endWith }
|
||||
];
|
||||
export const numberConditionList = [
|
||||
{ label: '为空', value: VariableConditionEnum.isEmpty },
|
||||
{ label: '不为空', value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: '等于', value: VariableConditionEnum.equalTo },
|
||||
{ label: '不等于', value: VariableConditionEnum.notEqual },
|
||||
{ label: '大于', value: VariableConditionEnum.greaterThan },
|
||||
{ label: '大于等于', value: VariableConditionEnum.greaterThanOrEqualTo },
|
||||
{ label: '小于', value: VariableConditionEnum.lessThan },
|
||||
{ label: '小于等于', value: VariableConditionEnum.lessThanOrEqualTo }
|
||||
{ label: i18nT('workflow:is_empty'), value: VariableConditionEnum.isEmpty },
|
||||
{ label: i18nT('workflow:is_not_empty'), value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: i18nT('workflow:is_equal_to'), value: VariableConditionEnum.equalTo },
|
||||
{ label: i18nT('workflow:is_not_equal'), value: VariableConditionEnum.notEqual },
|
||||
{ label: i18nT('workflow:greater_than'), value: VariableConditionEnum.greaterThan },
|
||||
{
|
||||
label: i18nT('workflow:greater_than_or_equal_to'),
|
||||
value: VariableConditionEnum.greaterThanOrEqualTo
|
||||
},
|
||||
{ label: i18nT('workflow:less_than'), value: VariableConditionEnum.lessThan },
|
||||
{ label: i18nT('workflow:less_than_or_equal_to'), value: VariableConditionEnum.lessThanOrEqualTo }
|
||||
];
|
||||
export const booleanConditionList = [
|
||||
{ label: '为空', value: VariableConditionEnum.isEmpty },
|
||||
{ label: '不为空', value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: '等于', value: VariableConditionEnum.equalTo }
|
||||
{ label: i18nT('workflow:is_empty'), value: VariableConditionEnum.isEmpty },
|
||||
{ label: i18nT('workflow:is_not_empty'), value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: i18nT('workflow:is_equal_to'), value: VariableConditionEnum.equalTo }
|
||||
];
|
||||
export const arrayConditionList = [
|
||||
{ label: '为空', value: VariableConditionEnum.isEmpty },
|
||||
{ label: '不为空', value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: '包含', value: VariableConditionEnum.include },
|
||||
{ label: '不包含', value: VariableConditionEnum.notInclude },
|
||||
{ label: '长度等于', value: VariableConditionEnum.lengthEqualTo },
|
||||
{ label: '长度不等于', value: VariableConditionEnum.lengthNotEqualTo },
|
||||
{ label: '长度大于', value: VariableConditionEnum.lengthGreaterThan },
|
||||
{ label: '长度大于等于', value: VariableConditionEnum.lengthGreaterThanOrEqualTo },
|
||||
{ label: '长度小于', value: VariableConditionEnum.lengthLessThan },
|
||||
{ label: '长度小于等于', value: VariableConditionEnum.lengthLessThanOrEqualTo }
|
||||
{ label: i18nT('workflow:is_empty'), value: VariableConditionEnum.isEmpty },
|
||||
{ label: i18nT('workflow:is_not_empty'), value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: i18nT('workflow:contains'), value: VariableConditionEnum.include },
|
||||
{ label: i18nT('workflow:not_contains'), value: VariableConditionEnum.notInclude },
|
||||
{ label: i18nT('workflow:length_equal_to'), value: VariableConditionEnum.lengthEqualTo },
|
||||
{ label: i18nT('workflow:length_not_equal_to'), value: VariableConditionEnum.lengthNotEqualTo },
|
||||
{ label: i18nT('workflow:length_greater_than'), value: VariableConditionEnum.lengthGreaterThan },
|
||||
{
|
||||
label: i18nT('workflow:length_greater_than_or_equal_to'),
|
||||
value: VariableConditionEnum.lengthGreaterThanOrEqualTo
|
||||
},
|
||||
{ label: i18nT('workflow:length_less_than'), value: VariableConditionEnum.lengthLessThan },
|
||||
{
|
||||
label: i18nT('workflow:length_less_than_or_equal_to'),
|
||||
value: VariableConditionEnum.lengthLessThanOrEqualTo
|
||||
}
|
||||
];
|
||||
export const objectConditionList = [
|
||||
{ label: '为空', value: VariableConditionEnum.isEmpty },
|
||||
{ label: '不为空', value: VariableConditionEnum.isNotEmpty }
|
||||
{ label: i18nT('workflow:is_empty'), value: VariableConditionEnum.isEmpty },
|
||||
{ label: i18nT('workflow:is_not_empty'), value: VariableConditionEnum.isNotEmpty }
|
||||
];
|
||||
export const allConditionList = [
|
||||
{ label: '为空', value: VariableConditionEnum.isEmpty },
|
||||
{ label: '不为空', value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: '等于', value: VariableConditionEnum.equalTo },
|
||||
{ label: '不等于', value: VariableConditionEnum.notEqual },
|
||||
{ label: '包含', value: VariableConditionEnum.include },
|
||||
{ label: '不包含', value: VariableConditionEnum.notInclude },
|
||||
{ label: '开始为', value: VariableConditionEnum.startWith },
|
||||
{ label: '结束为', value: VariableConditionEnum.endWith },
|
||||
{ label: '大于', value: VariableConditionEnum.greaterThan },
|
||||
{ label: '大于等于', value: VariableConditionEnum.greaterThanOrEqualTo },
|
||||
{ label: '小于', value: VariableConditionEnum.lessThan },
|
||||
{ label: '小于等于', value: VariableConditionEnum.lessThanOrEqualTo },
|
||||
{ label: '长度等于', value: VariableConditionEnum.lengthEqualTo },
|
||||
{ label: '长度不等于', value: VariableConditionEnum.lengthNotEqualTo },
|
||||
{ label: '长度大于', value: VariableConditionEnum.lengthGreaterThan },
|
||||
{ label: '长度大于等于', value: VariableConditionEnum.lengthGreaterThanOrEqualTo },
|
||||
{ label: '长度小于', value: VariableConditionEnum.lengthLessThan },
|
||||
{ label: '长度小于等于', value: VariableConditionEnum.lengthLessThanOrEqualTo }
|
||||
{ label: i18nT('workflow:is_empty'), value: VariableConditionEnum.isEmpty },
|
||||
{ label: i18nT('workflow:is_not_empty'), value: VariableConditionEnum.isNotEmpty },
|
||||
{ label: i18nT('workflow:is_equal_to'), value: VariableConditionEnum.equalTo },
|
||||
{ label: i18nT('workflow:is_not_equal'), value: VariableConditionEnum.notEqual },
|
||||
{ label: i18nT('workflow:contains'), value: VariableConditionEnum.include },
|
||||
{ label: i18nT('workflow:not_contains'), value: VariableConditionEnum.notInclude },
|
||||
{ label: i18nT('workflow:start_with'), value: VariableConditionEnum.startWith },
|
||||
{ label: i18nT('workflow:end_with'), value: VariableConditionEnum.endWith },
|
||||
{ label: i18nT('workflow:greater_than'), value: VariableConditionEnum.greaterThan },
|
||||
{
|
||||
label: i18nT('workflow:greater_than_or_equal_to'),
|
||||
value: VariableConditionEnum.greaterThanOrEqualTo
|
||||
},
|
||||
{ label: i18nT('workflow:less_than'), value: VariableConditionEnum.lessThan },
|
||||
{
|
||||
label: i18nT('workflow:less_than_or_equal_to'),
|
||||
value: VariableConditionEnum.lessThanOrEqualTo
|
||||
},
|
||||
{ label: i18nT('workflow:length_equal_to'), value: VariableConditionEnum.lengthEqualTo },
|
||||
{ label: i18nT('workflow:length_not_equal_to'), value: VariableConditionEnum.lengthNotEqualTo },
|
||||
{ label: i18nT('workflow:length_greater_than'), value: VariableConditionEnum.lengthGreaterThan },
|
||||
{
|
||||
label: i18nT('workflow:length_greater_than_or_equal_to'),
|
||||
value: VariableConditionEnum.lengthGreaterThanOrEqualTo
|
||||
},
|
||||
{ label: i18nT('workflow:length_less_than'), value: VariableConditionEnum.lengthLessThan },
|
||||
{
|
||||
label: i18nT('workflow:length_less_than_or_equal_to'),
|
||||
value: VariableConditionEnum.lengthLessThanOrEqualTo
|
||||
}
|
||||
];
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import { i18nT } from '../../../../../../web/i18n/utils';
|
||||
import {
|
||||
FlowNodeTemplateTypeEnum,
|
||||
NodeInputKeyEnum,
|
||||
@@ -19,8 +20,8 @@ export const IfElseNode: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(false, false, false, false),
|
||||
targetHandle: getHandleConfig(true, false, true, true),
|
||||
avatar: 'core/workflow/template/ifelse',
|
||||
name: '判断器',
|
||||
intro: '根据一定的条件，执行不同的分支。',
|
||||
name: i18nT('workflow:condition_checker'),
|
||||
intro: i18nT('workflow:execute_different_branches_based_on_conditions'),
|
||||
showStatus: true,
|
||||
version: '481',
|
||||
inputs: [
|
||||
@@ -47,7 +48,7 @@ export const IfElseNode: FlowNodeTemplateType = {
|
||||
{
|
||||
id: NodeOutputKeyEnum.ifElseResult,
|
||||
key: NodeOutputKeyEnum.ifElseResult,
|
||||
label: '判断结果',
|
||||
label: i18nT('workflow:judgment_result'),
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
}
|
||||
|
||||
@@ -13,6 +13,7 @@ import {
|
||||
import { Input_Template_DynamicInput } from '../input';
|
||||
import { Output_Template_AddOutput } from '../output';
|
||||
import { getHandleConfig } from '../utils';
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
|
||||
export const nodeLafCustomInputConfig = {
|
||||
selectValueTypeList: Object.values(WorkflowIOValueTypeEnum),
|
||||
@@ -27,15 +28,15 @@ export const LafModule: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/lafDispatch',
|
||||
name: 'Laf 函数调用（测试）',
|
||||
intro: '可以调用Laf账号下的云函数。',
|
||||
name: i18nT('workflow:laf_function_call_test'),
|
||||
intro: i18nT('workflow:intro_laf_function_call'),
|
||||
showStatus: true,
|
||||
isTool: true,
|
||||
version: '481',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
description: '接收前方节点的输出值作为变量，这些变量可以被 Laf 请求参数使用。',
|
||||
description: i18nT('workflow:dynamic_input_description'),
|
||||
customInputConfig: nodeLafCustomInputConfig
|
||||
},
|
||||
{
|
||||
@@ -52,8 +53,8 @@ export const LafModule: FlowNodeTemplateType = {
|
||||
{
|
||||
id: NodeOutputKeyEnum.httpRawResponse,
|
||||
key: NodeOutputKeyEnum.httpRawResponse,
|
||||
label: '原始响应',
|
||||
description: 'HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。',
|
||||
label: i18nT('workflow:raw_response'),
|
||||
description: i18nT('workflow:http_raw_response_description'),
|
||||
valueType: WorkflowIOValueTypeEnum.any,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
},
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
import { FlowNodeTemplateTypeEnum } from '../../constants';
|
||||
import { FlowNodeTypeEnum } from '../../node/constant';
|
||||
import { FlowNodeTemplateType } from '../../type/node';
|
||||
@@ -12,8 +13,8 @@ export const PluginInputModule: FlowNodeTemplateType = {
|
||||
unique: true,
|
||||
forbidDelete: true,
|
||||
avatar: 'core/workflow/template/workflowStart',
|
||||
name: '插件输入',
|
||||
intro: '可以配置插件需要哪些输入，利用这些输入来运行插件',
|
||||
name: i18nT('workflow:plugin_input'),
|
||||
intro: i18nT('workflow:intro_plugin_input'),
|
||||
showStatus: false,
|
||||
version: '481',
|
||||
inputs: [],
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
import { FlowNodeTemplateTypeEnum } from '../../constants';
|
||||
import { FlowNodeTypeEnum } from '../../node/constant';
|
||||
import { FlowNodeTemplateType } from '../../type/node';
|
||||
@@ -12,8 +13,8 @@ export const PluginOutputModule: FlowNodeTemplateType = {
|
||||
unique: true,
|
||||
forbidDelete: true,
|
||||
avatar: 'core/workflow/template/pluginOutput',
|
||||
name: '自定义插件输出',
|
||||
intro: '自定义配置外部输出，使用插件时，仅暴露自定义配置的输出',
|
||||
name: i18nT('workflow:custom_plugin_output'),
|
||||
intro: i18nT('workflow:intro_custom_plugin_output'),
|
||||
showStatus: false,
|
||||
version: '481',
|
||||
inputs: [],
|
||||
|
||||
@@ -17,6 +17,7 @@ import {
|
||||
} from '../input';
|
||||
import { LLMModelTypeEnum } from '../../../ai/constants';
|
||||
import { getHandleConfig } from '../utils';
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
|
||||
export const AiQueryExtension: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.queryExtension,
|
||||
@@ -25,9 +26,8 @@ export const AiQueryExtension: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/queryExtension',
|
||||
name: '问题优化',
|
||||
intro:
|
||||
'使用问题优化功能，可以提高知识库连续对话时搜索的精度。使用该功能后，会先利用 AI 根据上下文构建一个或多个新的检索词，这些检索词更利于进行知识库搜索。该模块已内置在知识库搜索模块中，如果您仅进行一次知识库搜索，可直接使用知识库内置的补全功能。',
|
||||
name: i18nT('workflow:question_optimization'),
|
||||
intro: i18nT('workflow:intro_question_optimization'),
|
||||
showStatus: true,
|
||||
version: '481',
|
||||
inputs: [
|
||||
@@ -38,11 +38,11 @@ export const AiQueryExtension: FlowNodeTemplateType = {
|
||||
{
|
||||
key: NodeInputKeyEnum.aiSystemPrompt,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.textarea, FlowNodeInputTypeEnum.reference],
|
||||
label: 'core.app.edit.Query extension background prompt',
|
||||
label: i18nT('common:core.app.edit.Query extension background prompt'),
|
||||
max: 300,
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
description: 'core.app.edit.Query extension background tip',
|
||||
placeholder: 'core.module.QueryExtension.placeholder'
|
||||
description: i18nT('common:core.app.edit.Query extension background tip'),
|
||||
placeholder: i18nT('common:core.module.QueryExtension.placeholder')
|
||||
},
|
||||
Input_Template_History,
|
||||
Input_Template_UserChatInput
|
||||
@@ -51,8 +51,8 @@ export const AiQueryExtension: FlowNodeTemplateType = {
|
||||
{
|
||||
id: NodeOutputKeyEnum.text,
|
||||
key: NodeOutputKeyEnum.text,
|
||||
label: 'core.module.output.label.query extension result',
|
||||
description: 'core.module.output.description.query extension result',
|
||||
label: i18nT('common:core.module.output.label.query extension result'),
|
||||
description: i18nT('common:core.module.output.description.query extension result'),
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
}
|
||||
|
||||
@@ -13,6 +13,7 @@ import {
|
||||
} from '../../../constants';
|
||||
import { Input_Template_History, Input_Template_UserChatInput } from '../../input';
|
||||
import { getHandleConfig } from '../../utils';
|
||||
import { i18nT } from '../../../../../../web/i18n/utils';
|
||||
|
||||
export const RunAppModule: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.runApp,
|
||||
@@ -21,8 +22,8 @@ export const RunAppModule: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/runApp',
|
||||
name: '应用调用',
|
||||
intro: '可以选择一个其他应用进行调用',
|
||||
name: i18nT('workflow:application_call'),
|
||||
intro: i18nT('workflow:select_another_application_to_call'),
|
||||
showStatus: true,
|
||||
version: '481',
|
||||
isTool: true,
|
||||
@@ -31,22 +32,22 @@ export const RunAppModule: FlowNodeTemplateType = {
|
||||
key: NodeInputKeyEnum.runAppSelectApp,
|
||||
renderTypeList: [FlowNodeInputTypeEnum.selectApp, FlowNodeInputTypeEnum.reference],
|
||||
valueType: WorkflowIOValueTypeEnum.selectApp,
|
||||
label: '选择一个应用',
|
||||
description: '选择一个其他应用进行调用',
|
||||
label: i18nT('workflow:select_an_application'),
|
||||
description: i18nT('workflow:choose_another_application_to_call'),
|
||||
required: true
|
||||
},
|
||||
Input_Template_History,
|
||||
{
|
||||
...Input_Template_UserChatInput,
|
||||
toolDescription: '用户问题'
|
||||
toolDescription: i18nT('workflow:user_question')
|
||||
}
|
||||
],
|
||||
outputs: [
|
||||
{
|
||||
id: NodeOutputKeyEnum.history,
|
||||
key: NodeOutputKeyEnum.history,
|
||||
label: '新的上下文',
|
||||
description: '将该应用回复内容拼接到历史记录中，作为新的上下文返回',
|
||||
label: i18nT('workflow:new_context'),
|
||||
description: i18nT('workflow:append_application_reply_to_history_as_new_context'),
|
||||
valueType: WorkflowIOValueTypeEnum.chatHistory,
|
||||
valueDesc: chatHistoryValueDesc,
|
||||
required: true,
|
||||
@@ -55,8 +56,8 @@ export const RunAppModule: FlowNodeTemplateType = {
|
||||
{
|
||||
id: NodeOutputKeyEnum.answerText,
|
||||
key: NodeOutputKeyEnum.answerText,
|
||||
label: '回复的文本',
|
||||
description: '将在应用完全结束后触发',
|
||||
label: i18nT('workflow:reply_text'),
|
||||
description: i18nT('workflow:trigger_after_application_completion'),
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
}
|
||||
|
||||
@@ -14,6 +14,7 @@ import { getHandleConfig } from '../../utils';
|
||||
import { Input_Template_DynamicInput } from '../../input';
|
||||
import { Output_Template_AddOutput } from '../../output';
|
||||
import { JS_TEMPLATE } from './constants';
|
||||
import { i18nT } from '../../../../../../web/i18n/utils';
|
||||
|
||||
export const CodeNode: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.code,
|
||||
@@ -22,14 +23,14 @@ export const CodeNode: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/codeRun',
|
||||
name: '代码运行',
|
||||
intro: '执行一段简单的脚本代码，通常用于进行复杂的数据处理。',
|
||||
name: i18nT('workflow:code_execution'),
|
||||
intro: i18nT('workflow:execute_a_simple_script_code_usually_for_complex_data_processing'),
|
||||
showStatus: true,
|
||||
version: '482',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
description: '这些变量会作为代码的运行的输入参数',
|
||||
description: i18nT('workflow:these_variables_will_be_input_parameters_for_code_execution'),
|
||||
customInputConfig: {
|
||||
selectValueTypeList: Object.values(WorkflowIOValueTypeEnum),
|
||||
showDescription: false,
|
||||
@@ -78,20 +79,20 @@ export const CodeNode: FlowNodeTemplateType = {
|
||||
outputs: [
|
||||
{
|
||||
...Output_Template_AddOutput,
|
||||
description: '将代码中 return 的对象作为输出，传递给后续的节点。变量名需要对应 return 的 key'
|
||||
description: i18nT('workflow:pass_returned_object_as_output_to_next_nodes')
|
||||
},
|
||||
{
|
||||
id: NodeOutputKeyEnum.rawResponse,
|
||||
key: NodeOutputKeyEnum.rawResponse,
|
||||
label: '完整响应数据',
|
||||
label: i18nT('workflow:full_response_data'),
|
||||
valueType: WorkflowIOValueTypeEnum.object,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
},
|
||||
{
|
||||
id: NodeOutputKeyEnum.error,
|
||||
key: NodeOutputKeyEnum.error,
|
||||
label: '运行错误',
|
||||
description: '代码运行错误信息，成功时返回空',
|
||||
label: i18nT('workflow:execution_error'),
|
||||
description: i18nT('workflow:error_info_returns_empty_on_success'),
|
||||
valueType: WorkflowIOValueTypeEnum.object,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
},
|
||||
|
||||
@@ -2,6 +2,7 @@ import { FlowNodeTypeEnum } from '../../node/constant';
|
||||
import { FlowNodeTemplateType } from '../../type/node';
|
||||
import { FlowNodeTemplateTypeEnum } from '../../constants';
|
||||
import { getHandleConfig } from '../utils';
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
|
||||
export const StopToolNode: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.stopTool,
|
||||
@@ -10,9 +11,8 @@ export const StopToolNode: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(false, false, false, false),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/stopTool',
|
||||
name: '工具调用终止',
|
||||
intro:
|
||||
'该模块需配置工具调用使用。当该模块被执行时，本次工具调用将会强制结束，并且不再调用AI针对工具调用结果回答问题。',
|
||||
name: i18nT('workflow:tool_call_termination'),
|
||||
intro: i18nT('workflow:intro_tool_call_termination'),
|
||||
version: '481',
|
||||
inputs: [],
|
||||
outputs: []
|
||||
|
||||
@@ -12,6 +12,7 @@ import {
|
||||
} from '../../constants';
|
||||
import { getHandleConfig } from '../utils';
|
||||
import { Input_Template_DynamicInput } from '../input';
|
||||
import { i18nT } from '../../../../../web/i18n/utils';
|
||||
|
||||
export const TextEditorNode: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.textEditor,
|
||||
@@ -20,13 +21,13 @@ export const TextEditorNode: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/textConcat',
|
||||
name: '文本拼接',
|
||||
intro: '可对固定或传入的文本进行加工后输出，非字符串类型数据最终会转成字符串类型。',
|
||||
name: i18nT('workflow:text_concatenation'),
|
||||
intro: i18nT('workflow:intro_text_concatenation'),
|
||||
version: '486',
|
||||
inputs: [
|
||||
{
|
||||
...Input_Template_DynamicInput,
|
||||
description: '可以引用其他节点的输出，作为文本拼接的变量，输入 / 唤起变量列表',
|
||||
description: i18nT('workflow:dynamic_input_description_concat'),
|
||||
customInputConfig: {
|
||||
selectValueTypeList: Object.values(WorkflowIOValueTypeEnum),
|
||||
showDescription: false,
|
||||
@@ -38,15 +39,15 @@ export const TextEditorNode: FlowNodeTemplateType = {
|
||||
renderTypeList: [FlowNodeInputTypeEnum.textarea],
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
required: true,
|
||||
label: '拼接文本',
|
||||
placeholder: '可输入 / 唤起变量列表'
|
||||
label: i18nT('workflow:concatenation_text'),
|
||||
placeholder: i18nT('workflow:input_variable_list')
|
||||
}
|
||||
],
|
||||
outputs: [
|
||||
{
|
||||
id: NodeOutputKeyEnum.text,
|
||||
key: NodeOutputKeyEnum.text,
|
||||
label: '拼接结果',
|
||||
label: i18nT('workflow:concatenation_result'),
|
||||
type: FlowNodeOutputTypeEnum.static,
|
||||
valueType: WorkflowIOValueTypeEnum.string
|
||||
}
|
||||
|
||||
@@ -61,7 +61,7 @@ export const ToolModule: FlowNodeTemplateType = {
|
||||
|
||||
{
|
||||
...Input_Template_System_Prompt,
|
||||
label: 'core.ai.Prompt',
|
||||
label: i18nT('common:core.ai.Prompt'),
|
||||
description: chatNodeSystemPromptTip,
|
||||
placeholder: chatNodeSystemPromptTip
|
||||
},
|
||||
@@ -72,8 +72,8 @@ export const ToolModule: FlowNodeTemplateType = {
|
||||
{
|
||||
id: NodeOutputKeyEnum.answerText,
|
||||
key: NodeOutputKeyEnum.answerText,
|
||||
label: 'core.module.output.label.Ai response content',
|
||||
description: 'core.module.output.description.Ai response content',
|
||||
label: i18nT('common:core.module.output.label.Ai response content'),
|
||||
description: i18nT('common:core.module.output.description.Ai response content'),
|
||||
valueType: WorkflowIOValueTypeEnum.string,
|
||||
type: FlowNodeOutputTypeEnum.static
|
||||
}
|
||||
|
||||
@@ -6,6 +6,7 @@ import {
|
||||
WorkflowIOValueTypeEnum
|
||||
} from '../../../constants';
|
||||
import { getHandleConfig } from '../../utils';
|
||||
import { i18nT } from '../../../../../../web/i18n/utils';
|
||||
|
||||
export const VariableUpdateNode: FlowNodeTemplateType = {
|
||||
id: FlowNodeTypeEnum.variableUpdate,
|
||||
@@ -14,8 +15,8 @@ export const VariableUpdateNode: FlowNodeTemplateType = {
|
||||
sourceHandle: getHandleConfig(true, true, true, true),
|
||||
targetHandle: getHandleConfig(true, true, true, true),
|
||||
avatar: 'core/workflow/template/variableUpdate',
|
||||
name: '变量更新',
|
||||
intro: '可以更新指定节点的输出值或更新全局变量',
|
||||
name: i18nT('workflow:variable_update'),
|
||||
intro: i18nT('workflow:update_specified_node_output_or_global_variable'),
|
||||
showStatus: false,
|
||||
isTool: false,
|
||||
version: '481',
|
||||
|
||||
@@ -31,7 +31,7 @@ export const WorkflowStart: FlowNodeTemplateType = {
|
||||
forbidDelete: true,
|
||||
unique: true,
|
||||
version: '481',
|
||||
inputs: [{ ...Input_Template_UserChatInput, toolDescription: '用户问题' }],
|
||||
inputs: [{ ...Input_Template_UserChatInput, toolDescription: i18nT('workflow:user_question') }],
|
||||
outputs: [
|
||||
{
|
||||
id: NodeOutputKeyEnum.userChatInput,
|
||||
|
||||
@@ -1,28 +1,110 @@
|
||||
{
|
||||
"Code": "Code",
|
||||
"about_xxx_question": "Questions about xxx",
|
||||
"add_new_input": "Add input",
|
||||
"append_application_reply_to_history_as_new_context": "Splice the app's reply content into the history and return it as new context",
|
||||
"application_call": "application call",
|
||||
"assigned_reply": "Specify reply",
|
||||
"choose_another_application_to_call": "Select a different app to call",
|
||||
"classification_result": "Classification results",
|
||||
"code": {
|
||||
"Reset template": "Reset template",
|
||||
"Reset template confirm": "Are you sure to restore the code template? All input and output to template values will be reset, please be careful to save the current code."
|
||||
},
|
||||
"code_execution": "code run",
|
||||
"collection_metadata_filter": "Collection metadata filtering",
|
||||
"complete_extraction_result": "Complete extraction results",
|
||||
"complete_extraction_result_description": "A JSON string, for example: {\"name:\":\"YY\",\"Time\":\"2023/7/2 18:00\"}",
|
||||
"concatenation_result": "Splicing result",
|
||||
"concatenation_text": "Splice text",
|
||||
"condition_checker": "Judger",
|
||||
"confirm_delete_field_tip": "Confirm to delete the field?",
|
||||
"contains": "Include",
|
||||
"content_to_retrieve": "Content to be retrieved",
|
||||
"content_to_search": "Content to be retrieved",
|
||||
"create_link_error": "Create link exception",
|
||||
"custom_feedback": "Custom feedback",
|
||||
"custom_input": "Custom input",
|
||||
"custom_plugin_output": "Custom plug-in output",
|
||||
"delete_api": "Are you sure you want to delete this API key? \nAfter deletion, the key will become invalid immediately and the corresponding conversation log will not be deleted. Please confirm!",
|
||||
"dynamic_input_description": "Receives the output value of the previous node as variables, which can be used by Laf request parameters.",
|
||||
"dynamic_input_description_concat": "Can reference the output of other nodes, as variables for text splicing, input/evoke variable lists",
|
||||
"edit_input": "Edit input",
|
||||
"end_with": "ends with",
|
||||
"error_info_returns_empty_on_success": "Code running error message, returns empty when successful",
|
||||
"execute_a_simple_script_code_usually_for_complex_data_processing": "Execute a simple script code, usually used for complex data processing.",
|
||||
"execute_different_branches_based_on_conditions": "Depending on certain conditions, different branches are executed.",
|
||||
"execution_error": "Run error",
|
||||
"extraction_requirements_description": "Extract requirement description",
|
||||
"extraction_requirements_description_detail": "Give the AI some corresponding background knowledge or description of requirements to guide the AI to complete the task better. \n\\nThis input box can use global variables.",
|
||||
"extraction_requirements_placeholder": "For example: \\n1. The current time is: {{cTime}}. \nYou are a laboratory reservation assistant. Your task is to help users make laboratory reservations and obtain the corresponding reservation information from the text. \n\\n2. You are the Google search assistant and need to extract appropriate search terms from the text.",
|
||||
"feedback_text": "Text of feedback",
|
||||
"field_description": "Field description",
|
||||
"field_description_placeholder": "Describes the functionality of this input field, which affects the quality of model generation if the parameter is called for a tool",
|
||||
"field_name_already_exists": "Field name already exists",
|
||||
"field_required": "Required",
|
||||
"field_used_as_tool_input": "As tool input",
|
||||
"filter_description": "Currently, label and creation time filtering is supported, which needs to be filled in according to the following format:\n\n{\n \n\"tags\": {\n \n\"$and\": [\"tag 1\",\"tag 2\"],\n \n\"$or\": [\"When there is $and tag, and takes effect, or does not take effect\"]\n \n},\n \n\"createTime\": {\n \n\"$gte\": \"YYYY-MM-DD HH:mm format is sufficient. The creation time of the collection is greater than this time\",\n \n\"$lte\": \"YYYY-MM-DD HH:mm format is sufficient. The creation time of the collection is less than this time. It can be used together with $gte\"\n \n}\n\n}",
|
||||
"full_field_extraction": "Complete extraction of fields",
|
||||
"full_field_extraction_description": "Returns true when the extracted fields are all filled in (model extraction or using default values is considered successful)",
|
||||
"full_response_data": "Complete response data",
|
||||
"greater_than": "greater than",
|
||||
"greater_than_or_equal_to": "Greater than or equal to",
|
||||
"greeting": "greet",
|
||||
"http_raw_response_description": "The raw response of the HTTP request. \nOnly string or JSON type response data can be accepted.",
|
||||
"http_request": "HTTP request",
|
||||
"http_request_error_info": "HTTP request error information, returns empty when successful",
|
||||
"ifelse": {
|
||||
"Input value": "Input",
|
||||
"Select value": "Select"
|
||||
},
|
||||
"input_description": "Input descriotion",
|
||||
"input_variable_list": "Enterable/evoked variable list",
|
||||
"intro_assigned_reply": "This module can directly reply to a specified piece of content. \nOften used for guidance and prompts. \nWhen non-string content is passed in, it will be converted into a string for output.",
|
||||
"intro_custom_feedback": "When this module is triggered, a piece of feedback will be added to the current conversation record. \nCan be used to automatically record dialogue effects, etc.",
|
||||
"intro_custom_plugin_output": "Customize the external output of the configuration. When using the plug-in, only the output of the custom configuration is exposed.",
|
||||
"intro_http_request": "You can issue an HTTP request to implement more complex operations (network search, database query, etc.)",
|
||||
"intro_knowledge_base_search_merge": "Multiple knowledge base search results can be combined and output. \nUse RRF's merge method for final sorting output.",
|
||||
"intro_laf_function_call": "You can call cloud functions under the Laf account.",
|
||||
"intro_plugin_input": "You can configure what inputs the plug-in requires and use these inputs to run the plug-in",
|
||||
"intro_question_classification": "Determine the type of question based on the user's history and current questions. \nMultiple sets of question types can be added. Here is an example template:\n\nType 1: Say hello\n\nType 2: Questions about the “use” of the product\n\nType 3: Questions about product “purchase”\n\nType 4: Other questions",
|
||||
"intro_question_optimization": "Using the question optimization function, you can improve the search accuracy during continuous dialogue in the knowledge base. \nAfter using this function, AI will first be used to construct one or more new search terms based on the context. These search terms are more conducive to knowledge base searches. \nThis module has been built into the knowledge base search module. If you only perform a knowledge base search, you can directly use the completion function built into the knowledge base.",
|
||||
"intro_text_concatenation": "Fixed or incoming text can be processed and output, and non-string type data will eventually be converted into string type.",
|
||||
"intro_text_content_extraction": "Specified data can be extracted from text, such as SQL statements, search keywords, codes, etc.",
|
||||
"intro_tool_call_termination": "This module needs to be called by the configuration tool. \nWhen this module is executed, this tool call will be forcibly ended, and AI will no longer be called to answer questions based on the tool call results.",
|
||||
"is_empty": "is empty",
|
||||
"is_equal_to": "equal",
|
||||
"is_not_empty": "Not empty",
|
||||
"is_not_equal": "not equal to",
|
||||
"judgment_result": "Judgment result",
|
||||
"knowledge_base_reference": "Knowledge base reference",
|
||||
"knowledge_base_search_merge": "Knowledge base search citation merge",
|
||||
"laf_function_call_test": "Laf function call (test)",
|
||||
"length_equal_to": "The length is equal to",
|
||||
"length_greater_than": "length greater than",
|
||||
"length_greater_than_or_equal_to": "length greater than",
|
||||
"length_less_than": "length less than",
|
||||
"length_less_than_or_equal_to": "length less than or equal to",
|
||||
"length_not_equal_to": "length is not equal to",
|
||||
"less_than": "less than",
|
||||
"less_than_or_equal_to": "less than or equal to",
|
||||
"max_dialog_rounds": "How many rounds of conversation records can be carried at most?",
|
||||
"max_tokens": "Maximum Tokens",
|
||||
"new_context": "new context",
|
||||
"not_contains": "Not included",
|
||||
"only_the_reference_type_is_supported": "Only the Reference type is supported",
|
||||
"optional_value_type": "Optional value type",
|
||||
"optional_value_type_tip": "One or more data types can be specified, and users can only select the configured type when adding fields in winter",
|
||||
"other_questions": "Other questions",
|
||||
"pass_returned_object_as_output_to_next_nodes": "Use the object returned in the code as output and pass it to subsequent nodes. \nThe variable name needs to correspond to the key of return",
|
||||
"plugin_input": "Plug-in input",
|
||||
"question_classification": "Problem classification",
|
||||
"question_optimization": "Problem optimization",
|
||||
"quote_num": "Reference {{num}}",
|
||||
"raw_response": "original response",
|
||||
"regex": "regular",
|
||||
"reply_text": "Reply text",
|
||||
"request_error": "Request error",
|
||||
"response": {
|
||||
"Code log": "Log",
|
||||
"Custom inputs": "Custom inputs",
|
||||
@@ -33,6 +115,11 @@
|
||||
"User_select_result": "User select result",
|
||||
"read files": "parsed document"
|
||||
},
|
||||
"select_an_application": "Choose an app",
|
||||
"select_another_application_to_call": "You can choose another application to call",
|
||||
"special_array_format": "Special array format, when the search result is empty, an empty array is returned.",
|
||||
"start_with": "Start with",
|
||||
"target_fields_description": "A target field is composed of 'description' and 'key', and multiple target fields can be extracted.",
|
||||
"template": {
|
||||
"ai_chat": "LLM chat",
|
||||
"ai_chat_intro": "Call the AI model for a conversation",
|
||||
@@ -43,9 +130,18 @@
|
||||
"tool_call_intro": "One or more function blocks are automatically selected for calling through the AI model, and plug-ins can also be called.",
|
||||
"workflow_start": "Process starts"
|
||||
},
|
||||
"text_concatenation": "Text splicing",
|
||||
"text_content_extraction": "Text content extraction",
|
||||
"text_to_extract": "Text to be extracted",
|
||||
"these_variables_will_be_input_parameters_for_code_execution": "These variables will be used as input parameters when the code is run.",
|
||||
"tool_call_termination": "Tool call terminated",
|
||||
"tool_input": "Tool",
|
||||
"trigger_after_application_completion": "will be triggered after the application has completely ended",
|
||||
"update_link_error": "Update link exception",
|
||||
"update_specified_node_output_or_global_variable": "You can update the output value of the specified node or update global variables",
|
||||
"user_question": "User issues",
|
||||
"variable_picker_tips": "enter node name or variable name to search",
|
||||
"variable_update": "variable update",
|
||||
"workflow": {
|
||||
"Back_to_current_version": "Back to current version",
|
||||
"My edit": "My edit",
|
||||
|
||||
@@ -1,28 +1,110 @@
|
||||
{
|
||||
"Code": "代码",
|
||||
"about_xxx_question": "关于 xxx 的问题",
|
||||
"add_new_input": "新增输入",
|
||||
"append_application_reply_to_history_as_new_context": "将该应用回复内容拼接到历史记录中，作为新的上下文返回",
|
||||
"application_call": "应用调用",
|
||||
"assigned_reply": "指定回复",
|
||||
"choose_another_application_to_call": "选择一个其他应用进行调用",
|
||||
"classification_result": "分类结果",
|
||||
"code": {
|
||||
"Reset template": "还原模板",
|
||||
"Reset template confirm": "确认还原代码模板？将会重置所有输入和输出至模板值，请注意保存当前代码。"
|
||||
},
|
||||
"code_execution": "代码运行",
|
||||
"collection_metadata_filter": "集合元数据过滤",
|
||||
"complete_extraction_result": "完整提取结果",
|
||||
"complete_extraction_result_description": "一个 JSON 字符串，例如：{\"name:\":\"YY\",\"Time\":\"2023/7/2 18:00\"}",
|
||||
"concatenation_result": "拼接结果",
|
||||
"concatenation_text": "拼接文本",
|
||||
"condition_checker": "判断器",
|
||||
"confirm_delete_field_tip": "确认删除该字段？",
|
||||
"contains": "包含",
|
||||
"content_to_retrieve": "需要检索的内容",
|
||||
"content_to_search": "需要检索的内容",
|
||||
"create_link_error": "创建链接异常",
|
||||
"custom_feedback": "自定义反馈",
|
||||
"custom_input": "自定义输入",
|
||||
"custom_plugin_output": "自定义插件输出",
|
||||
"delete_api": "确认删除该API密钥？删除后该密钥立即失效，对应的对话日志不会删除，请确认！",
|
||||
"dynamic_input_description": "接收前方节点的输出值作为变量，这些变量可以被 Laf 请求参数使用。",
|
||||
"dynamic_input_description_concat": "可以引用其他节点的输出，作为文本拼接的变量，输入 / 唤起变量列表",
|
||||
"edit_input": "编辑输入",
|
||||
"end_with": "结束为",
|
||||
"error_info_returns_empty_on_success": "代码运行错误信息，成功时返回空",
|
||||
"execute_a_simple_script_code_usually_for_complex_data_processing": "执行一段简单的脚本代码，通常用于进行复杂的数据处理。",
|
||||
"execute_different_branches_based_on_conditions": "根据一定的条件，执行不同的分支。",
|
||||
"execution_error": "运行错误",
|
||||
"extraction_requirements_description": "提取要求描述",
|
||||
"extraction_requirements_description_detail": "给AI一些对应的背景知识或要求描述，引导AI更好的完成任务。\\n该输入框可使用全局变量。",
|
||||
"extraction_requirements_placeholder": "例如: \\n1. 当前时间为: {{cTime}}。你是一个实验室预约助手，你的任务是帮助用户预约实验室，从文本中获取对应的预约信息。\\n2. 你是谷歌搜索助手，需要从文本中提取出合适的搜索词。",
|
||||
"feedback_text": "反馈的文本",
|
||||
"field_description": "字段描述",
|
||||
"field_description_placeholder": "描述该输入字段的功能，如果为工具调用参数，则该描述会影响模型生成的质量",
|
||||
"field_name_already_exists": "字段名已经存在",
|
||||
"field_required": "必填",
|
||||
"field_used_as_tool_input": "作为工具调用参数",
|
||||
"filter_description": "目前支持标签和创建时间过滤，需按照以下格式填写：\n{\n \"tags\": {\n \"$and\": [\"标签 1\",\"标签 2\"],\n \"$or\": [\"有 $and 标签时，and 生效，or 不生效\"]\n },\n \"createTime\": {\n \"$gte\": \"YYYY-MM-DD HH:mm 格式即可，集合的创建时间大于该时间\",\n \"$lte\": \"YYYY-MM-DD HH:mm 格式即可，集合的创建时间小于该时间,可和 $gte 共同使用\"\n }\n}",
|
||||
"full_field_extraction": "字段完全提取",
|
||||
"full_field_extraction_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）",
|
||||
"full_response_data": "完整响应数据",
|
||||
"greater_than": "大于",
|
||||
"greater_than_or_equal_to": "大于等于",
|
||||
"greeting": "打招呼",
|
||||
"http_raw_response_description": "HTTP请求的原始响应。只能接受字符串或JSON类型响应数据。",
|
||||
"http_request": "HTTP 请求",
|
||||
"http_request_error_info": "HTTP请求错误信息，成功时返回空",
|
||||
"ifelse": {
|
||||
"Input value": "输入值",
|
||||
"Select value": "选择值"
|
||||
},
|
||||
"input_description": "字段描述",
|
||||
"input_variable_list": "可输入 / 唤起变量列表",
|
||||
"intro_assigned_reply": "该模块可以直接回复一段指定的内容。常用于引导、提示。非字符串内容传入时，会转成字符串进行输出。",
|
||||
"intro_custom_feedback": "该模块被触发时，会给当前的对话记录增加一条反馈。可用于自动记录对话效果等。",
|
||||
"intro_custom_plugin_output": "自定义配置外部输出，使用插件时，仅暴露自定义配置的输出",
|
||||
"intro_http_request": "可以发出一个 HTTP 请求，实现更为复杂的操作（联网搜索、数据库查询等）",
|
||||
"intro_knowledge_base_search_merge": "可以将多个知识库搜索结果进行合并输出。使用 RRF 的合并方式进行最终排序输出。",
|
||||
"intro_laf_function_call": "可以调用Laf账号下的云函数。",
|
||||
"intro_plugin_input": "可以配置插件需要哪些输入，利用这些输入来运行插件",
|
||||
"intro_question_classification": "根据用户的历史记录和当前问题判断该次提问的类型。可以添加多组问题类型，下面是一个模板例子:\n类型1: 打招呼\n类型2: 关于商品“使用”问题\n类型3: 关于商品“购买”问题\n类型4: 其他问题",
|
||||
"intro_question_optimization": "使用问题优化功能，可以提高知识库连续对话时搜索的精度。使用该功能后，会先利用 AI 根据上下文构建一个或多个新的检索词，这些检索词更利于进行知识库搜索。该模块已内置在知识库搜索模块中，如果您仅进行一次知识库搜索，可直接使用知识库内置的补全功能。",
|
||||
"intro_text_concatenation": "可对固定或传入的文本进行加工后输出，非字符串类型数据最终会转成字符串类型。",
|
||||
"intro_text_content_extraction": "可从文本中提取指定的数据，例如：sql语句、搜索关键词、代码等",
|
||||
"intro_tool_call_termination": "该模块需配置工具调用使用。当该模块被执行时，本次工具调用将会强制结束，并且不再调用AI针对工具调用结果回答问题。",
|
||||
"is_empty": "为空",
|
||||
"is_equal_to": "等于",
|
||||
"is_not_empty": "不为空",
|
||||
"is_not_equal": "不等于",
|
||||
"judgment_result": "判断结果",
|
||||
"knowledge_base_reference": "知识库引用",
|
||||
"knowledge_base_search_merge": "知识库搜索引用合并",
|
||||
"laf_function_call_test": "Laf 函数调用（测试）",
|
||||
"length_equal_to": "长度等于",
|
||||
"length_greater_than": "长度大于",
|
||||
"length_greater_than_or_equal_to": "长度大于等",
|
||||
"length_less_than": "长度小于",
|
||||
"length_less_than_or_equal_to": "长度小于等于",
|
||||
"length_not_equal_to": "长度不等于",
|
||||
"less_than": "小于",
|
||||
"less_than_or_equal_to": "小于等于",
|
||||
"max_dialog_rounds": "最多携带多少轮对话记录",
|
||||
"max_tokens": "最大 Tokens",
|
||||
"new_context": "新的上下文",
|
||||
"not_contains": "不包含",
|
||||
"only_the_reference_type_is_supported": "仅支持引用类型",
|
||||
"optional_value_type": "可选的数据类型",
|
||||
"optional_value_type_tip": "可以指定 1 个或多个数据类型，用户在动态添加字段时，仅可选择配置的类型",
|
||||
"other_questions": "其他问题",
|
||||
"pass_returned_object_as_output_to_next_nodes": "将代码中 return 的对象作为输出，传递给后续的节点。变量名需要对应 return 的 key",
|
||||
"plugin_input": "插件输入",
|
||||
"question_classification": "问题分类",
|
||||
"question_optimization": "问题优化",
|
||||
"quote_num": "引用{{num}}",
|
||||
"raw_response": "原始响应",
|
||||
"regex": "正则",
|
||||
"reply_text": "回复的文本",
|
||||
"request_error": "请求错误",
|
||||
"response": {
|
||||
"Code log": "Log 日志",
|
||||
"Custom inputs": "自定义输入",
|
||||
@@ -33,6 +115,11 @@
|
||||
"User_select_result": "选择的结果",
|
||||
"read files": "解析的文档"
|
||||
},
|
||||
"select_an_application": "选择一个应用",
|
||||
"select_another_application_to_call": "可以选择一个其他应用进行调用",
|
||||
"special_array_format": "特殊数组格式，搜索结果为空时，返回空数组。",
|
||||
"start_with": "开始为",
|
||||
"target_fields_description": "由 '描述' 和 'key' 组成一个目标字段，可提取多个目标字段",
|
||||
"template": {
|
||||
"ai_chat": "AI 对话",
|
||||
"ai_chat_intro": "AI 大模型对话",
|
||||
@@ -43,9 +130,18 @@
|
||||
"tool_call_intro": "通过AI模型自动选择一个或多个功能块进行调用，也可以对插件进行调用。",
|
||||
"workflow_start": "流程开始"
|
||||
},
|
||||
"text_concatenation": "文本拼接",
|
||||
"text_content_extraction": "文本内容提取",
|
||||
"text_to_extract": "需要提取的文本",
|
||||
"these_variables_will_be_input_parameters_for_code_execution": "这些变量会作为代码的运行的输入参数",
|
||||
"tool_call_termination": "工具调用终止",
|
||||
"tool_input": "工具参数",
|
||||
"trigger_after_application_completion": "将在应用完全结束后触发",
|
||||
"update_link_error": "更新链接异常",
|
||||
"update_specified_node_output_or_global_variable": "可以更新指定节点的输出值或更新全局变量",
|
||||
"user_question": "用户问题",
|
||||
"variable_picker_tips": "可输入节点名或变量名搜索",
|
||||
"variable_update": "变量更新",
|
||||
"workflow": {
|
||||
"Back_to_current_version": "回到初始状态",
|
||||
"My edit": "我的编辑",
|
||||
|
||||
Reference in New Issue
Block a user