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perf: agent skill editor
This commit is contained in:
archer
parent
21b8bcace5
commit
1f100276f6
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@ -3,10 +3,10 @@ import type { AppDeleteJobData } from './index';
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import { findAppAndAllChildren, deleteAppDataProcessor } from '../controller';
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import { addLog } from '../../../common/system/log';
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import { batchRun } from '@fastgpt/global/common/system/utils';
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import type { AppSchema } from '@fastgpt/global/core/app/type';
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import type { AppSchemaType } from '@fastgpt/global/core/app/type';
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import { MongoApp } from '../schema';
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const deleteApps = async ({ teamId, apps }: { teamId: string; apps: AppSchema[] }) => {
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const deleteApps = async ({ teamId, apps }: { teamId: string; apps: AppSchemaType[] }) => {
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const results = await batchRun(
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apps,
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async (app) => {
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@ -9,7 +9,6 @@ import type {
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DispatchNodeResultType,
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ModuleDispatchProps
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} from '@fastgpt/global/core/workflow/runtime/type';
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import { getLLMModel } from '../../../../ai/model';
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import { getNodeErrResponse, getHistories } from '../../utils';
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import type { AIChatItemValueItemType, ChatItemType } from '@fastgpt/global/core/chat/type';
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import { ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
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@ -23,16 +22,14 @@ import { systemSubInfo } from './sub/constants';
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import { textAdaptGptResponse } from '@fastgpt/global/core/workflow/runtime/utils';
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import { dispatchPlanAgent, dispatchReplanAgent } from './sub/plan';
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import { getFileInputPrompt, readFileTool } from './sub/file/utils';
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import { getFileInputPrompt } from './sub/file/utils';
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import type { ChatCompletionMessageParam, ChatCompletionTool } from '@fastgpt/global/core/ai/type';
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import type { AgentPlanType } from './sub/plan/type';
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import type { localeType } from '@fastgpt/global/common/i18n/type';
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import { stepCall } from './master/call';
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import { addLog } from '../../../../../common/system/log';
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import { matchSkillForPlan } from './skillMatcher';
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import { matchSkillForId, matchSkillForPlan } from './skillMatcher';
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import type { SkillToolType } from '@fastgpt/global/core/ai/skill/type';
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import type { GetSubAppInfoFnType, SubAppRuntimeType } from './type';
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import { agentSkillToToolRuntime } from './sub/tool/utils';
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import type { SubAppRuntimeType } from './type';
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import { getSubapps } from './utils';
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export type DispatchAgentModuleProps = ModuleDispatchProps<{
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@ -84,7 +81,6 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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isAskAgent = true
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}
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} = props;
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const agentModel = getLLMModel(model);
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const chatHistories = getHistories(history, histories);
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const historiesMessages = chats2GPTMessages({
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messages: chatHistories,
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@ -135,22 +131,22 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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});
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// Get sub apps
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let { completionTools, subAppsMap } = await getSubapps({
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let { completionTools: agentCompletionTools, subAppsMap: agentSubAppsMap } = await getSubapps({
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tools: selectedTools,
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tmbId: runningAppInfo.tmbId,
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lang,
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filesMap
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});
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const getSubAppInfo = (id: string) => {
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const toolNode = subAppsMap.get(id) || systemSubInfo[id];
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const toolNode = agentSubAppsMap.get(id) || systemSubInfo[id];
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return {
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name: toolNode?.name || '',
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avatar: toolNode?.avatar || '',
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toolDescription: toolNode?.toolDescription || toolNode?.name || ''
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};
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};
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console.log(JSON.stringify(completionTools, null, 2), 'topAgent completionTools');
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console.log(subAppsMap, 'topAgent subAppsMap');
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// console.log(JSON.stringify(completionTools, null, 2), 'topAgent completionTools');
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// console.log(subAppsMap, 'topAgent subAppsMap');
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/* ===== AI Start ===== */
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@ -175,7 +171,62 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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if (taskIsComplexity) {
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/* ===== Plan Agent ===== */
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let currentSkillId: string | undefined = matchedSkillId;
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const mergeSkill = ({
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skillCompletionTools,
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skillSubAppsMap
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}: {
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skillCompletionTools: ChatCompletionTool[];
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skillSubAppsMap: Map<string, SubAppRuntimeType>;
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}) => {
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// 将 skill 的 completionTools 和 subAppsMap 合并到 topAgent，如果重复，则以 skill 的为准。
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agentCompletionTools = skillCompletionTools.concat(
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agentCompletionTools.filter(
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(item) =>
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!skillCompletionTools.some((item2) => item2.function.name === item.function.name)
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)
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);
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[...skillSubAppsMap].forEach(([id, item]) => {
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agentSubAppsMap.set(id, item);
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});
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console.log(JSON.stringify(agentCompletionTools, null, 2), 'merge completionTools');
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console.log(agentSubAppsMap, 'merge subAppsMap');
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};
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const skillMatch = async () => {
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const matchResult = await matchSkillForPlan({
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teamId: runningUserInfo.teamId,
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tmbId: runningAppInfo.tmbId,
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appId: runningAppInfo.id,
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userInput: lastInteractive ? interactiveInput : userChatInput,
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messages: historiesMessages, // 传入完整的对话历史
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model,
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lang
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});
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if (matchResult.matched) {
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matchedSkillId = String(matchResult.skill._id);
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mergeSkill({
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skillCompletionTools: matchResult.completionTools,
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skillSubAppsMap: matchResult.subAppsMap
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});
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// 可选: 推送匹配信息给前端
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workflowStreamResponse?.({
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event: SseResponseEventEnum.answer,
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data: textAdaptGptResponse({
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text: `📋 找到参考技能: ${matchResult.systemPrompt}`
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})
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});
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return {
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skillPrompt: matchResult.systemPrompt
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};
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}
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addLog.debug(`未匹配到 skill，原因: ${matchResult.reason}`);
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return {
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skillPrompt: ''
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};
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};
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const planCallFn = async () => {
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// 点了确认。此时肯定有 agentPlans
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if (
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@ -185,58 +236,16 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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) {
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planHistoryMessages = undefined;
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} else {
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// 🆕 执行 Skill 匹配（仅在 isPlanStep 且没有 planHistoryMessages 时）
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let skillSystemPrompt: string | undefined;
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// match skill
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const matchResult = await matchSkillForPlan({
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teamId: runningUserInfo.teamId,
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tmbId: runningAppInfo.tmbId,
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appId: runningAppInfo.id,
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userInput: lastInteractive ? interactiveInput : userChatInput,
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messages: historiesMessages, // 传入完整的对话历史
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model,
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lang
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});
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if (matchResult.matched) {
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skillSystemPrompt = matchResult.systemPrompt;
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currentSkillId = String(matchResult.skill._id);
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// 将 skill 的 completionTools 和 subAppsMap 合并到topAgent，如果重复，则以 skill 的为准。
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completionTools = matchResult.completionTools.concat(
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completionTools.filter(
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(item) =>
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!matchResult.completionTools.some(
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(item2) => item2.function.name === item.function.name
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)
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)
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);
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[...matchResult.subAppsMap].forEach(([id, item]) => {
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subAppsMap.set(id, item);
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});
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console.log(JSON.stringify(completionTools, null, 2), 'merge completionTools');
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console.log(subAppsMap, 'merge subAppsMap');
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// 可选: 推送匹配信息给前端
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workflowStreamResponse?.({
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event: SseResponseEventEnum.answer,
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data: textAdaptGptResponse({
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text: `📋 找到参考技能: ${matchResult.systemPrompt}`
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})
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});
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} else {
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addLog.debug(`未匹配到 skill，原因: ${matchResult.reason}`);
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}
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const { skillPrompt } = await skillMatch();
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const { answerText, plan, completeMessages, usages, interactiveResponse } =
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await dispatchPlanAgent({
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historyMessages: planHistoryMessages || historiesMessages,
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userInput: lastInteractive ? interactiveInput : userChatInput,
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interactive: lastInteractive,
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completionTools,
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completionTools: agentCompletionTools,
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getSubAppInfo,
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// TODO: 需要区分？systemprompt 需要替换成 role 和 target 么？
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systemPrompt: skillSystemPrompt || systemPrompt,
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systemPrompt: skillPrompt || systemPrompt,
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model,
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temperature,
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top_p: aiChatTopP,
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@ -301,7 +310,7 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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[DispatchNodeResponseKeyEnum.memories]: {
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[planMessagesKey]: filterMemoryMessages(completeMessages),
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[agentPlanKey]: agentPlan,
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[skillMatchKey]: currentSkillId
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[skillMatchKey]: matchedSkillId
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},
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[DispatchNodeResponseKeyEnum.interactive]: interactiveResponse
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};
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@ -326,7 +335,7 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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userInput: lastInteractive ? interactiveInput : userChatInput,
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plan,
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interactive: lastInteractive,
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completionTools,
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completionTools: agentCompletionTools,
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getSubAppInfo,
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systemPrompt,
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model,
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@ -420,41 +429,26 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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});
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if (result) return result;
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}
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// 如果有保存的 skill id，恢复 skill 的 tools
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else if (matchedSkillId) {
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addLog.debug(`恢复 skill tools, skill id: ${matchedSkillId}`);
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const skill = await matchSkillForId({
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id: matchedSkillId,
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tmbId: runningAppInfo.tmbId,
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lang
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});
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if (skill) {
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mergeSkill({
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skillCompletionTools: skill.skillTools,
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skillSubAppsMap: skill.skillSubAppsMap
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});
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}
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}
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addLog.debug(`Start master agent`, {
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agentPlan: JSON.stringify(agentPlan, null, 2)
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});
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// 如果有保存的 skill id，恢复 skill 的 tools
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if (matchedSkillId) {
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addLog.debug(`恢复 skill tools, skill id: ${matchedSkillId}`);
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try {
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const { MongoAiSkill } = await import('../../../../ai/skill/schema');
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const skill = await MongoAiSkill.findById(matchedSkillId).lean();
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if (skill && skill.tools) {
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const { completionTools: skillTools, subAppsMap: skillSubAppsMap } = await getSubapps({
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tools: skill.tools,
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tmbId: runningAppInfo.tmbId,
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lang
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});
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// 合并 skill 的 tools 到 completionTools
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completionTools = skillTools.concat(
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completionTools.filter(
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(item) => !skillTools.some((item2) => item2.function.name === item.function.name)
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)
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);
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[...skillSubAppsMap].forEach(([id, item]) => {
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subAppsMap.set(id, item);
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});
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addLog.debug(`成功恢复 skill tools`);
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}
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} catch (error) {
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addLog.error(`恢复 skill tools 失败:`, error);
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}
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}
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/* ===== Master agent, 逐步执行 plan ===== */
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if (!agentPlan) return Promise.reject('没有 plan');
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@ -470,10 +464,10 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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...props,
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getSubAppInfo,
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steps: agentPlan.steps, // 传入所有步骤，而不仅仅是未执行的步骤
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completionTools,
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completionTools: agentCompletionTools,
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step,
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filesMap,
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subAppsMap
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subAppsMap: agentSubAppsMap
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});
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// Merge response
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@ -513,7 +507,7 @@ export const dispatchRunAgent = async (props: DispatchAgentModuleProps): Promise
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[agentPlanKey]: agentPlan,
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[planMessagesKey]: undefined,
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[replanMessagesKey]: undefined,
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[skillMatchKey]: currentSkillId
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[skillMatchKey]: matchedSkillId
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},
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[DispatchNodeResponseKeyEnum.assistantResponses]: assistantResponses,
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[DispatchNodeResponseKeyEnum.nodeResponse]: {
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@ -260,22 +260,26 @@ export const stepCall = async ({
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usages
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};
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} else if (tool.type === 'workflow' || tool.type === 'toolWorkflow') {
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const fn = tool.type === 'workflow' ? dispatchApp : dispatchPlugin;
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// const fn = tool.type === 'workflow' ? dispatchApp : dispatchPlugin;
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const { response, usages } = await fn({
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...props,
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node,
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workflowStreamResponse: childWorkflowStreamResponse,
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callParams: {
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appId: node.pluginId,
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version: node.version,
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...requestParams
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}
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});
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// const { response, usages } = await fn({
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// ...props,
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// node,
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// workflowStreamResponse: childWorkflowStreamResponse,
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// callParams: {
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// appId: node.pluginId,
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// version: node.version,
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// ...requestParams
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// }
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// });
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// return {
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// response,
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// usages
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// };
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return {
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response,
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usages
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response: 'Can not find the tool',
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usages: []
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};
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} else {
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return {
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@ -5,73 +5,11 @@ import type { ChatCompletionMessageParam, ChatCompletionTool } from '@fastgpt/gl
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import { getLLMModel } from '../../../../ai/model';
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import { getNanoid } from '@fastgpt/global/common/string/tools';
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import { getErrText } from '@fastgpt/global/common/error/utils';
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import { agentSkillToToolRuntime } from './sub/tool/utils';
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import type { SubAppRuntimeType } from './type';
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import type { localeType } from '@fastgpt/global/common/i18n/type';
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import { getSubapps } from './utils';
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import { addLog } from '../../../../../common/system/log';
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/**
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* 构建 Skill Tools 数组
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* 参考 MatcherService.ts 的 match 函数
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*/
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export const buildSkillTools = (skills: AiSkillSchemaType[]) => {
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const skillCompletionTools: ChatCompletionTool[] = [];
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const skillsMap: Record<string, AiSkillSchemaType> = {};
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for (const skill of skills) {
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// 生成唯一函数名
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const functionName = getNanoid(6);
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skill.name = functionName;
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skillsMap[functionName] = skill;
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if (skill.description) {
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skillCompletionTools.push({
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type: 'function',
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function: {
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name: functionName,
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description: skill.description,
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parameters: {
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type: 'object',
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properties: {},
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required: []
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}
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}
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});
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}
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}
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return { skillCompletionTools, skillsMap };
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};
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/**
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* 格式化 Skill 为 SystemPrompt
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* 将匹配到的 skill 格式化为 XML 提示词
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*/
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export const formatSkillAsSystemPrompt = (skill: AiSkillSchemaType): string => {
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const lines = ['<reference_skill>', `**参考技能**: ${skill.name}`, ''];
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if (skill.description) {
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lines.push(`**描述**: ${skill.description}`, '');
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}
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if (skill.steps && skill.steps.trim()) {
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lines.push(`**步骤信息**:`, skill.steps, '');
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}
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lines.push(
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'**说明**:',
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'1. 以上是用户之前保存的类似任务的执行框架',
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'2. 请参考该技能的宏观阶段划分和资源方向',
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'3. 根据当前用户的具体需求，调整和优化框架',
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'4. 保持阶段的逻辑性和方向的清晰性',
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'',
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'</reference_skill>'
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);
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return lines.join('\n');
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};
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/**
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* 主匹配函数
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* 参考 MatcherService.ts 的 match 方法
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|
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@ -107,6 +45,67 @@ export const matchSkillForPlan = async ({
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subAppsMap: Map<string, SubAppRuntimeType>;
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}
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> => {
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/**
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* 构建 Skill Tools 数组
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* 参考 MatcherService.ts 的 match 函数
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*/
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const buildSkillTools = (skills: AiSkillSchemaType[]) => {
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const skillCompletionTools: ChatCompletionTool[] = [];
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const skillsMap: Record<string, AiSkillSchemaType> = {};
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for (const skill of skills) {
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// 生成唯一函数名
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const functionName = getNanoid(6);
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skill.name = functionName;
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skillsMap[functionName] = skill;
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if (skill.description) {
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skillCompletionTools.push({
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type: 'function',
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function: {
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name: functionName,
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description: skill.description,
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parameters: {
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type: 'object',
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properties: {},
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||||
required: []
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
return { skillCompletionTools, skillsMap };
|
||||
};
|
||||
|
||||
/**
|
||||
* 格式化 Skill 为 SystemPrompt
|
||||
* 将匹配到的 skill 格式化为 XML 提示词
|
||||
*/
|
||||
const formatSkillAsSystemPrompt = (skill: AiSkillSchemaType): string => {
|
||||
const lines = ['<reference_skill>', `**参考技能**: ${skill.name}`, ''];
|
||||
|
||||
if (skill.description) {
|
||||
lines.push(`**描述**: ${skill.description}`, '');
|
||||
}
|
||||
|
||||
if (skill.steps && skill.steps.trim()) {
|
||||
lines.push(`**步骤信息**:`, skill.steps, '');
|
||||
}
|
||||
|
||||
lines.push(
|
||||
'**说明**:',
|
||||
'1. 以上是用户之前保存的类似任务的执行框架',
|
||||
'2. 请参考该技能的宏观阶段划分和资源方向',
|
||||
'3. 根据当前用户的具体需求，调整和优化框架',
|
||||
'4. 保持阶段的逻辑性和方向的清晰性',
|
||||
'',
|
||||
'</reference_skill>'
|
||||
);
|
||||
|
||||
return lines.join('\n');
|
||||
};
|
||||
|
||||
addLog.debug('matchSkillForPlan start');
|
||||
const modelData = getLLMModel(model);
|
||||
|
||||
|
|
@ -224,3 +223,26 @@ export const matchSkillForPlan = async ({
|
|||
};
|
||||
}
|
||||
};
|
||||
|
||||
export const matchSkillForId = async ({
|
||||
id,
|
||||
tmbId,
|
||||
lang
|
||||
}: {
|
||||
id: string;
|
||||
tmbId: string;
|
||||
lang?: localeType;
|
||||
}) => {
|
||||
const skill = await MongoAiSkill.findById(id).lean();
|
||||
if (!skill || !skill.tools) return;
|
||||
const { completionTools: skillTools, subAppsMap: skillSubAppsMap } = await getSubapps({
|
||||
tools: skill.tools,
|
||||
tmbId,
|
||||
lang
|
||||
});
|
||||
|
||||
return {
|
||||
skillTools,
|
||||
skillSubAppsMap
|
||||
};
|
||||
};
|
||||
|
|
|
|||
|
|
@ -54,3 +54,15 @@ const MyIconButton = ({
|
|||
};
|
||||
|
||||
export default MyIconButton;
|
||||
|
||||
export const MyDeleteIconButton = ({ onClick, ...props }: Omit<Props, 'icon'>) => {
|
||||
return (
|
||||
<MyIconButton
|
||||
hoverBg="red.50"
|
||||
hoverColor="red.600"
|
||||
onClick={onClick}
|
||||
{...props}
|
||||
icon={'delete'}
|
||||
/>
|
||||
);
|
||||
};
|
||||
|
|
|
|||
|
|
@ -451,7 +451,6 @@
|
|||
"core.dataset.My Dataset": "My Dataset",
|
||||
"core.dataset.Query extension intro": "Enabling the question optimization function can improve the accuracy of Dataset searches during continuous conversations. After enabling this function, when performing Dataset searches, the AI will complete the missing information of the question based on the conversation history.",
|
||||
"core.dataset.Quote Length": "Quote Content Length",
|
||||
"core.dataset.Read Dataset": "View Dataset Details",
|
||||
"core.dataset.Set Website Config": "Start Configuring",
|
||||
"core.dataset.Start export": "Export Started",
|
||||
"core.dataset.Text collection": "Text Dataset",
|
||||
|
|
|
|||
|
|
@ -454,7 +454,6 @@
|
|||
"core.dataset.My Dataset": "我的知识库",
|
||||
"core.dataset.Query extension intro": "开启问题优化功能，可以提高提高连续对话时，知识库搜索的精度。开启该功能后，在进行知识库搜索时，会根据对话记录，利用 AI 补全问题缺失的信息。",
|
||||
"core.dataset.Quote Length": "引用内容长度",
|
||||
"core.dataset.Read Dataset": "查看知识库详情",
|
||||
"core.dataset.Set Website Config": "开始配置",
|
||||
"core.dataset.Start export": "已开始导出",
|
||||
"core.dataset.Text collection": "文本数据集",
|
||||
|
|
|
|||
|
|
@ -450,7 +450,6 @@
|
|||
"core.dataset.My Dataset": "我的知識庫",
|
||||
"core.dataset.Query extension intro": "開啟問題最佳化功能，可以提高連續對話時知識庫搜尋的準確度。開啟此功能後，在進行知識庫搜尋時，系統會根據對話記錄，利用 AI 補充問題中缺少的資訊。",
|
||||
"core.dataset.Quote Length": "引用內容長度",
|
||||
"core.dataset.Read Dataset": "檢視知識庫詳細資料",
|
||||
"core.dataset.Set Website Config": "開始設定",
|
||||
"core.dataset.Start export": "已開始匯出",
|
||||
"core.dataset.Text collection": "文字資料集",
|
||||
|
|
|
|||
|
|
@ -10,9 +10,13 @@ import type {
|
|||
SkillAgentParamsType
|
||||
} from '@fastgpt/global/core/chat/helperBot/skillAgent/type';
|
||||
|
||||
export type HelperBotRefType = {
|
||||
restartChat: () => void;
|
||||
};
|
||||
export type HelperBotProps = {
|
||||
emptyDom?: ReactNode;
|
||||
fileSelectConfig?: AppFileSelectConfigType;
|
||||
ChatBoxRef: React.ForwardedRef<HelperBotRefType>;
|
||||
} & (
|
||||
| {
|
||||
type: typeof HelperBotTypeEnum.topAgent;
|
||||
|
|
@ -29,6 +33,7 @@ type HelperBotContextType = HelperBotProps & {};
|
|||
|
||||
export const HelperBotContext = createContext<HelperBotContextType>({
|
||||
type: HelperBotTypeEnum.topAgent,
|
||||
ChatBoxRef: null,
|
||||
metadata: {
|
||||
role: '',
|
||||
taskObject: '',
|
||||
|
|
|
|||
|
|
@ -1,17 +1,11 @@
|
|||
import React, { useCallback, useRef, useState } from 'react';
|
||||
import React, { forwardRef, useCallback, useImperativeHandle, useRef, useState } from 'react';
|
||||
|
||||
import HelperBotContextProvider, { type HelperBotProps } from './context';
|
||||
import type {
|
||||
AIChatItemValueItemType,
|
||||
ChatItemType,
|
||||
ChatSiteItemType
|
||||
} from '@fastgpt/global/core/chat/type';
|
||||
import HelperBotContextProvider, { type HelperBotRefType, type HelperBotProps } from './context';
|
||||
import type { AIChatItemValueItemType } from '@fastgpt/global/core/chat/type';
|
||||
import { getNanoid } from '@fastgpt/global/common/string/tools';
|
||||
import MyBox from '@fastgpt/web/components/common/MyBox';
|
||||
import { ChatRoleEnum, ChatStatusEnum } from '@fastgpt/global/core/chat/constants';
|
||||
import type { getPaginationRecordsBody } from '@/pages/api/core/chat/getPaginationRecords';
|
||||
import { ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
|
||||
import { useScrollPagination } from '@fastgpt/web/hooks/useScrollPagination';
|
||||
import type { PaginationResponse } from '@fastgpt/web/common/fetch/type';
|
||||
import { Box } from '@chakra-ui/react';
|
||||
import HumanItem from './components/HumanItem';
|
||||
import AIItem from './components/AIItem';
|
||||
|
|
@ -37,7 +31,7 @@ import { streamFetch } from '@/web/common/api/fetch';
|
|||
import type { generatingMessageProps } from '../ChatContainer/type';
|
||||
import { SseResponseEventEnum } from '@fastgpt/global/core/workflow/runtime/constants';
|
||||
|
||||
const ChatBox = ({ type, metadata, onApply, ...props }: HelperBotProps) => {
|
||||
const ChatBox = ({ type, metadata, onApply, ChatBoxRef, ...props }: HelperBotProps) => {
|
||||
const { toast } = useToast();
|
||||
const { t } = useTranslation();
|
||||
|
||||
|
|
@ -59,8 +53,7 @@ const ChatBox = ({ type, metadata, onApply, ...props }: HelperBotProps) => {
|
|||
const requestParams = useMemoEnhance(() => {
|
||||
return {
|
||||
chatId,
|
||||
type,
|
||||
metadata
|
||||
type
|
||||
};
|
||||
}, []);
|
||||
|
||||
|
|
@ -368,6 +361,14 @@ const ChatBox = ({ type, metadata, onApply, ...props }: HelperBotProps) => {
|
|||
setIsChatting(false);
|
||||
});
|
||||
|
||||
useImperativeHandle(ChatBoxRef, () => ({
|
||||
restartChat() {
|
||||
abortRequest();
|
||||
setChatRecords([]);
|
||||
setChatId(getNanoid(12));
|
||||
}
|
||||
}));
|
||||
|
||||
return (
|
||||
<MyBox display={'flex'} flexDirection={'column'} h={'100%'} position={'relative'}>
|
||||
<ScrollData
|
||||
|
|
|
|||
|
|
@ -1,11 +1,14 @@
|
|||
import { Box, Flex, IconButton } from '@chakra-ui/react';
|
||||
import { useTranslation } from 'next-i18next';
|
||||
import React, { useEffect, useMemo } from 'react';
|
||||
import React, { useEffect, useMemo, useRef } from 'react';
|
||||
import MyTooltip from '@fastgpt/web/components/common/MyTooltip';
|
||||
import MyIcon from '@fastgpt/web/components/common/Icon';
|
||||
|
||||
import { useSafeState } from 'ahooks';
|
||||
import type { AppFormEditFormType } from '@fastgpt/global/core/app/formEdit/type';
|
||||
import type {
|
||||
AppFormEditFormType,
|
||||
SelectedToolItemType
|
||||
} from '@fastgpt/global/core/app/formEdit/type';
|
||||
import { useContextSelector } from 'use-context-selector';
|
||||
import { AppContext } from '../../context';
|
||||
import { useChatTest } from '../../useChatTest';
|
||||
|
|
@ -20,10 +23,10 @@ import { ChatTypeEnum } from '@/components/core/chat/ChatContainer/ChatBox/const
|
|||
import type { Form2WorkflowFnType } from '../FormComponent/type';
|
||||
import FillRowTabs from '@fastgpt/web/components/common/Tabs/FillRowTabs';
|
||||
import HelperBot from '@/components/core/chat/HelperBot';
|
||||
import type { HelperBotRefType } from '@/components/core/chat/HelperBot/context';
|
||||
import { HelperBotTypeEnum } from '@fastgpt/global/core/chat/helperBot/type';
|
||||
import { getToolPreviewNode } from '@/web/core/app/api/tool';
|
||||
import type { FlowNodeTemplateType } from '@fastgpt/global/core/workflow/type/node';
|
||||
import { useToast } from '@fastgpt/web/hooks/useToast';
|
||||
import { loadGeneratedTools } from './utils';
|
||||
|
||||
type Props = {
|
||||
appForm: AppFormEditFormType;
|
||||
|
|
@ -36,6 +39,7 @@ const ChatTest = ({ appForm, setAppForm, setRenderEdit, form2WorkflowFn }: Props
|
|||
const { toast } = useToast();
|
||||
|
||||
const [activeTab, setActiveTab] = useSafeState<'helper' | 'chat_debug'>('helper');
|
||||
const HelperBotRef = useRef<HelperBotRefType>(null);
|
||||
|
||||
const { appDetail } = useContextSelector(AppContext, (v) => v);
|
||||
const datasetCiteData = useContextSelector(ChatItemContext, (v) => v.datasetCiteData);
|
||||
|
|
@ -126,7 +130,11 @@ const ChatTest = ({ appForm, setAppForm, setRenderEdit, form2WorkflowFn }: Props
|
|||
aria-label={'delete'}
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
restartChat();
|
||||
if (activeTab === 'helper') {
|
||||
HelperBotRef.current?.restartChat();
|
||||
} else {
|
||||
restartChat();
|
||||
}
|
||||
}}
|
||||
/>
|
||||
</MyTooltip>
|
||||
|
|
@ -134,27 +142,14 @@ const ChatTest = ({ appForm, setAppForm, setRenderEdit, form2WorkflowFn }: Props
|
|||
<Box flex={1}>
|
||||
{activeTab === 'helper' && (
|
||||
<HelperBot
|
||||
ChatBoxRef={HelperBotRef}
|
||||
type={HelperBotTypeEnum.topAgent}
|
||||
metadata={topAgentMetadata}
|
||||
onApply={async (formData) => {
|
||||
const targetToolIds = formData.tools || [];
|
||||
const newTools: FlowNodeTemplateType[] = [];
|
||||
const failedToolIds: string[] = [];
|
||||
|
||||
const results = await Promise.all(
|
||||
targetToolIds.map((toolId: string) =>
|
||||
getToolPreviewNode({ appId: toolId })
|
||||
.then((tool) => ({ status: 'fulfilled' as const, toolId, tool }))
|
||||
.catch((error) => ({ status: 'rejected' as const, toolId, error }))
|
||||
)
|
||||
);
|
||||
|
||||
results.forEach((result) => {
|
||||
if (result.status === 'fulfilled') {
|
||||
newTools.push(result.tool);
|
||||
} else if (result.status === 'rejected') {
|
||||
failedToolIds.push(result.toolId);
|
||||
}
|
||||
const newTools = await loadGeneratedTools({
|
||||
newToolIds: formData.tools || [],
|
||||
existsTools: appForm.selectedTools,
|
||||
fileSelectConfig: appForm.chatConfig.fileSelectConfig
|
||||
});
|
||||
|
||||
setAppForm((prev) => {
|
||||
|
|
|
|||
|
|
@ -32,6 +32,7 @@ import { cardStyles } from '../../constants';
|
|||
import { SmallAddIcon } from '@chakra-ui/icons';
|
||||
import { getAiSkillDetail } from '@/web/core/ai/skill/api';
|
||||
import { getToolConfigStatus } from '@fastgpt/global/core/app/formEdit/utils';
|
||||
import MyIconButton, { MyDeleteIconButton } from '@fastgpt/web/components/common/Icon/button';
|
||||
|
||||
const DatasetSelectModal = dynamic(() => import('@/components/core/app/DatasetSelectModal'));
|
||||
const DatasetParamsModal = dynamic(() => import('@/components/core/app/DatasetParamsModal'));
|
||||
|
|
@ -298,45 +299,69 @@ const EditForm = ({
|
|||
similarity={appForm.dataset.similarity}
|
||||
limit={appForm.dataset.limit}
|
||||
usingReRank={appForm.dataset.usingReRank}
|
||||
datasetSearchUsingExtensionQuery={appForm.dataset.datasetSearchUsingExtensionQuery}
|
||||
usingExtensionQuery={appForm.dataset.datasetSearchUsingExtensionQuery}
|
||||
queryExtensionModel={appForm.dataset.datasetSearchExtensionModel}
|
||||
/>
|
||||
</Box>
|
||||
)}
|
||||
<Grid gridTemplateColumns={'repeat(2, minmax(0, 1fr))'} gridGap={[2, 4]}>
|
||||
{selectDatasets.map((item) => (
|
||||
<MyTooltip key={item.datasetId} label={t('common:core.dataset.Read Dataset')}>
|
||||
<Flex
|
||||
overflow={'hidden'}
|
||||
alignItems={'center'}
|
||||
p={2}
|
||||
bg={'white'}
|
||||
boxShadow={'0 4px 8px -2px rgba(16,24,40,.1),0 2px 4px -2px rgba(16,24,40,.06)'}
|
||||
borderRadius={'md'}
|
||||
border={theme.borders.base}
|
||||
cursor={'pointer'}
|
||||
onClick={() =>
|
||||
router.push({
|
||||
pathname: '/dataset/detail',
|
||||
query: {
|
||||
datasetId: item.datasetId
|
||||
}
|
||||
})
|
||||
<Flex
|
||||
key={item.datasetId}
|
||||
overflow={'hidden'}
|
||||
alignItems={'center'}
|
||||
p={2}
|
||||
bg={'white'}
|
||||
boxShadow={'0 4px 8px -2px rgba(16,24,40,.1),0 2px 4px -2px rgba(16,24,40,.06)'}
|
||||
borderRadius={'md'}
|
||||
border={'base'}
|
||||
_hover={{
|
||||
'& .controler': {
|
||||
display: 'flex'
|
||||
}
|
||||
}}
|
||||
>
|
||||
<Avatar src={item.avatar} w={'1.5rem'} borderRadius={'sm'} />
|
||||
<Box
|
||||
ml={2}
|
||||
flex={'1 0 0'}
|
||||
w={0}
|
||||
className={'textEllipsis'}
|
||||
fontSize={'sm'}
|
||||
color={'myGray.900'}
|
||||
>
|
||||
<Avatar src={item.avatar} w={'1.5rem'} borderRadius={'sm'} />
|
||||
<Box
|
||||
ml={2}
|
||||
flex={'1 0 0'}
|
||||
w={0}
|
||||
className={'textEllipsis'}
|
||||
fontSize={'sm'}
|
||||
color={'myGray.900'}
|
||||
>
|
||||
{item.name}
|
||||
</Box>
|
||||
</Flex>
|
||||
</MyTooltip>
|
||||
{item.name}
|
||||
</Box>
|
||||
|
||||
{/* Icon */}
|
||||
<Box className="controler" display={['flex', 'none']} alignItems={'center'}>
|
||||
<MyIconButton
|
||||
icon={'common/viewLight'}
|
||||
onClick={() =>
|
||||
router.push({
|
||||
pathname: '/dataset/detail',
|
||||
query: {
|
||||
datasetId: item.datasetId
|
||||
}
|
||||
})
|
||||
}
|
||||
/>
|
||||
<MyDeleteIconButton
|
||||
onClick={() => {
|
||||
setAppForm((state) => ({
|
||||
...state,
|
||||
dataset: {
|
||||
...state.dataset,
|
||||
datasets:
|
||||
state.dataset.datasets?.filter(
|
||||
(pre) => pre.datasetId !== item.datasetId
|
||||
) || []
|
||||
}
|
||||
}));
|
||||
}}
|
||||
/>
|
||||
</Box>
|
||||
</Flex>
|
||||
))}
|
||||
</Grid>
|
||||
</Box>
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
import { Box, Flex, IconButton } from '@chakra-ui/react';
|
||||
import { useTranslation } from 'next-i18next';
|
||||
import React, { useMemo } from 'react';
|
||||
import React, { useMemo, useRef } from 'react';
|
||||
import MyTooltip from '@fastgpt/web/components/common/MyTooltip';
|
||||
import MyIcon from '@fastgpt/web/components/common/Icon';
|
||||
import type { SkillEditType, SelectedToolItemType } from '@fastgpt/global/core/app/formEdit/type';
|
||||
|
|
@ -8,11 +8,8 @@ import type { AppFormEditFormType } from '@fastgpt/global/core/app/formEdit/type
|
|||
import MyBox from '@fastgpt/web/components/common/MyBox';
|
||||
import HelperBot from '@/components/core/chat/HelperBot';
|
||||
import { HelperBotTypeEnum } from '@fastgpt/global/core/chat/helperBot/type';
|
||||
import { getToolPreviewNode } from '@/web/core/app/api/tool';
|
||||
import {
|
||||
validateToolConfiguration,
|
||||
getToolConfigStatus
|
||||
} from '@fastgpt/global/core/app/formEdit/utils';
|
||||
import { loadGeneratedTools } from '../utils';
|
||||
import type { HelperBotRefType } from '@/components/core/chat/HelperBot/context';
|
||||
|
||||
type Props = {
|
||||
topAgentSelectedTools?: SelectedToolItemType[];
|
||||
|
|
@ -22,6 +19,7 @@ type Props = {
|
|||
};
|
||||
const ChatTest = ({ topAgentSelectedTools = [], skill, appForm, onAIGenerate }: Props) => {
|
||||
const { t } = useTranslation();
|
||||
const ChatBoxRef = useRef<HelperBotRefType>(null);
|
||||
|
||||
const skillAgentMetadata = useMemo(() => {
|
||||
return {
|
||||
|
|
@ -56,85 +54,40 @@ const ChatTest = ({ topAgentSelectedTools = [], skill, appForm, onAIGenerate }:
|
|||
aria-label={'delete'}
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
ChatBoxRef.current?.restartChat();
|
||||
}}
|
||||
/>
|
||||
</MyTooltip>
|
||||
</Flex>
|
||||
<Box flex={1}>
|
||||
<HelperBot
|
||||
ChatBoxRef={ChatBoxRef}
|
||||
type={HelperBotTypeEnum.skillAgent}
|
||||
metadata={skillAgentMetadata}
|
||||
onApply={async (generatedSkillData) => {
|
||||
console.log(generatedSkillData, 222);
|
||||
|
||||
// 1. 提取所有步骤中的工具 ID（去重，仅保留 type='tool'）
|
||||
const allToolIds = new Set<string>();
|
||||
// 1. 计算新的 tool
|
||||
const newToolIds: string[] = [];
|
||||
generatedSkillData.execution_plan.steps.forEach((step) => {
|
||||
step.expectedTools?.forEach((tool) => {
|
||||
if (tool.type === 'tool') {
|
||||
allToolIds.add(tool.id);
|
||||
const exists = skill.selectedTools.find((t) => t.pluginId === tool.id);
|
||||
if (exists) return;
|
||||
newToolIds.push(tool.id);
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
// 2. 分类工具：已有的和新的
|
||||
const existingTools: SelectedToolItemType[] = [];
|
||||
const newToolIds: string[] = [];
|
||||
|
||||
Array.from(allToolIds).forEach((toolId) => {
|
||||
const existingTool = skill.selectedTools.find((t) => t.pluginId === toolId);
|
||||
if (existingTool) {
|
||||
existingTools.push(existingTool);
|
||||
} else {
|
||||
newToolIds.push(toolId);
|
||||
}
|
||||
});
|
||||
|
||||
// 3. 并行获取新工具详情
|
||||
const newTools: SelectedToolItemType[] = [];
|
||||
const newTools = await loadGeneratedTools({
|
||||
newToolIds,
|
||||
existsTools: skill.selectedTools,
|
||||
topAgentSelectedTools,
|
||||
fileSelectConfig: appForm.chatConfig.fileSelectConfig
|
||||
});
|
||||
|
||||
if (newToolIds.length > 0) {
|
||||
const results = await Promise.all(
|
||||
newToolIds.map((toolId: string) =>
|
||||
getToolPreviewNode({ appId: toolId })
|
||||
.then((tool) => ({ status: 'fulfilled' as const, toolId, tool }))
|
||||
.catch((error) => ({ status: 'rejected' as const, toolId, error }))
|
||||
)
|
||||
);
|
||||
|
||||
results.forEach((result) => {
|
||||
if (result.status !== 'fulfilled') return;
|
||||
const tool = result.tool;
|
||||
// 验证工具配置
|
||||
const toolValid = validateToolConfiguration({
|
||||
toolTemplate: tool,
|
||||
canSelectFile: appForm.chatConfig.fileSelectConfig?.canSelectFile,
|
||||
canSelectImg: appForm.chatConfig.fileSelectConfig?.canSelectImg
|
||||
});
|
||||
|
||||
if (toolValid) {
|
||||
// 添加与 top 相同工具的配置
|
||||
const topTool = topAgentSelectedTools.find(
|
||||
(item) => item.pluginId === tool.pluginId
|
||||
);
|
||||
if (topTool) {
|
||||
tool.inputs.forEach((input) => {
|
||||
const topInput = topTool.inputs.find((topIn) => topIn.key === input.key);
|
||||
if (topInput) {
|
||||
input.value = topInput.value;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
newTools.push({
|
||||
...tool,
|
||||
configStatus: getToolConfigStatus(tool).status
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// 3. 构建 stepsText（保持原有逻辑）
|
||||
// 4. 构建 stepsText
|
||||
const stepsText = generatedSkillData.execution_plan.steps
|
||||
.map((step, index) => {
|
||||
let stepText = `步骤 ${index + 1}: ${step.title}\n${step.description}`;
|
||||
|
|
@ -148,12 +101,12 @@ const ChatTest = ({ topAgentSelectedTools = [], skill, appForm, onAIGenerate }:
|
|||
})
|
||||
.join('\n\n');
|
||||
|
||||
// 4. 应用生成的数据，以 AI 生成的工具列表为准
|
||||
// 5. 应用生成的数据，以 AI 生成的工具列表为准
|
||||
onAIGenerate({
|
||||
name: generatedSkillData.plan_analysis.name || skill.name,
|
||||
description: generatedSkillData.plan_analysis.description || skill.description,
|
||||
stepsText: stepsText,
|
||||
selectedTools: [...existingTools, ...newTools]
|
||||
selectedTools: newTools
|
||||
});
|
||||
}}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -11,6 +11,7 @@ import {
|
|||
IconButton,
|
||||
Textarea
|
||||
} from '@chakra-ui/react';
|
||||
import MyIconButton, { MyDeleteIconButton } from '@fastgpt/web/components/common/Icon/button';
|
||||
import { type AppFileSelectConfigType } from '@fastgpt/global/core/app/type/config';
|
||||
import type { SelectedToolItemType, SkillEditType } from '@fastgpt/global/core/app/formEdit/type';
|
||||
import { useRouter } from 'next/router';
|
||||
|
|
@ -265,38 +266,57 @@ const EditForm = ({
|
|||
</Flex>
|
||||
<Grid gridTemplateColumns={'repeat(2, minmax(0, 1fr))'} gridGap={[2, 4]}>
|
||||
{selectDatasets.map((item) => (
|
||||
<MyTooltip key={item.datasetId} label={t('common:core.dataset.Read Dataset')}>
|
||||
<Flex
|
||||
overflow={'hidden'}
|
||||
alignItems={'center'}
|
||||
p={2}
|
||||
bg={'white'}
|
||||
boxShadow={'0 4px 8px -2px rgba(16,24,40,.1),0 2px 4px -2px rgba(16,24,40,.06)'}
|
||||
borderRadius={'md'}
|
||||
border={theme.borders.base}
|
||||
cursor={'pointer'}
|
||||
onClick={() =>
|
||||
router.push({
|
||||
pathname: '/dataset/detail',
|
||||
query: {
|
||||
datasetId: item.datasetId
|
||||
}
|
||||
})
|
||||
<Flex
|
||||
key={item.datasetId}
|
||||
overflow={'hidden'}
|
||||
alignItems={'center'}
|
||||
p={2}
|
||||
bg={'white'}
|
||||
boxShadow={'0 4px 8px -2px rgba(16,24,40,.1),0 2px 4px -2px rgba(16,24,40,.06)'}
|
||||
borderRadius={'md'}
|
||||
border={'base'}
|
||||
_hover={{
|
||||
'& .controler': {
|
||||
display: 'flex'
|
||||
}
|
||||
}}
|
||||
>
|
||||
<Avatar src={item.avatar} w={'1.5rem'} borderRadius={'sm'} />
|
||||
<Box
|
||||
ml={2}
|
||||
flex={'1 0 0'}
|
||||
w={0}
|
||||
className={'textEllipsis'}
|
||||
fontSize={'sm'}
|
||||
color={'myGray.900'}
|
||||
>
|
||||
<Avatar src={item.avatar} w={'1.5rem'} borderRadius={'sm'} />
|
||||
<Box
|
||||
ml={2}
|
||||
flex={'1 0 0'}
|
||||
w={0}
|
||||
className={'textEllipsis'}
|
||||
fontSize={'sm'}
|
||||
color={'myGray.900'}
|
||||
>
|
||||
{item.name}
|
||||
</Box>
|
||||
</Flex>
|
||||
</MyTooltip>
|
||||
{item.name}
|
||||
</Box>
|
||||
|
||||
{/* Icon */}
|
||||
<Box className="controler" display={['flex', 'none']} alignItems={'center'}>
|
||||
<MyIconButton
|
||||
icon={'common/viewLight'}
|
||||
onClick={() =>
|
||||
router.push({
|
||||
pathname: '/dataset/detail',
|
||||
query: {
|
||||
datasetId: item.datasetId
|
||||
}
|
||||
})
|
||||
}
|
||||
/>
|
||||
<MyDeleteIconButton
|
||||
onClick={() => {
|
||||
setValue(
|
||||
'dataset.list',
|
||||
selectDatasets?.filter((pre) => pre.datasetId !== item.datasetId) || [],
|
||||
{ shouldDirty: true }
|
||||
);
|
||||
}}
|
||||
/>
|
||||
</Box>
|
||||
</Flex>
|
||||
))}
|
||||
</Grid>
|
||||
</Box>
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
import type { SkillEditType } from '@fastgpt/global/core/app/formEdit/type';
|
||||
import type { SelectedToolItemType } from '@fastgpt/global/core/app/formEdit/type';
|
||||
import type { AppChatConfigType } from '@fastgpt/global/core/app/type';
|
||||
import type { AppFormEditFormType } from '@fastgpt/global/core/app/formEdit/type';
|
||||
import type {
|
||||
|
|
@ -28,7 +28,12 @@ import { getDefaultAppForm } from '@fastgpt/global/core/app/utils';
|
|||
import type { FlowNodeInputItemType } from '@fastgpt/global/core/workflow/type/io';
|
||||
import { getAppChatConfig } from '@fastgpt/global/core/workflow/utils';
|
||||
import { Input_Template_File_Link } from '@fastgpt/global/core/workflow/template/input';
|
||||
import { getToolConfigStatus } from '@fastgpt/global/core/app/formEdit/utils';
|
||||
import {
|
||||
getToolConfigStatus,
|
||||
validateToolConfiguration
|
||||
} from '@fastgpt/global/core/app/formEdit/utils';
|
||||
import { getToolPreviewNode } from '@/web/core/app/api/tool';
|
||||
import type { AppFileSelectConfigType } from '@fastgpt/global/core/app/type/config';
|
||||
|
||||
/* format app nodes to edit form */
|
||||
export const appWorkflow2AgentForm = ({
|
||||
|
|
@ -232,3 +237,56 @@ export function agentForm2AppWorkflow(
|
|||
chatConfig: data.chatConfig
|
||||
};
|
||||
}
|
||||
|
||||
export const loadGeneratedTools = async ({
|
||||
newToolIds,
|
||||
existsTools = [],
|
||||
topAgentSelectedTools = [],
|
||||
fileSelectConfig
|
||||
}: {
|
||||
newToolIds: string[]; // 新的，完整的 toolId
|
||||
existsTools?: SelectedToolItemType[];
|
||||
topAgentSelectedTools?: SelectedToolItemType[];
|
||||
fileSelectConfig?: AppFileSelectConfigType;
|
||||
}): Promise<SelectedToolItemType[]> => {
|
||||
const results = (
|
||||
await Promise.all(
|
||||
newToolIds.map<Promise<SelectedToolItemType | undefined>>(async (toolId: string) => {
|
||||
// 已经存在的工具，直接返回
|
||||
const existTool = existsTools.find((tool) => tool.pluginId === toolId);
|
||||
if (existTool) {
|
||||
return existTool;
|
||||
}
|
||||
|
||||
// 新工具，需要与已配置的 tool 进行 input 合并
|
||||
const tool = await getToolPreviewNode({ appId: toolId });
|
||||
// 验证工具配置
|
||||
const toolValid = validateToolConfiguration({
|
||||
toolTemplate: tool,
|
||||
canSelectFile: fileSelectConfig?.canSelectFile,
|
||||
canSelectImg: fileSelectConfig?.canSelectImg
|
||||
});
|
||||
if (!toolValid) {
|
||||
return;
|
||||
}
|
||||
|
||||
const topTool = topAgentSelectedTools.find((item) => item.pluginId === toolId);
|
||||
if (topTool) {
|
||||
tool.inputs.forEach((input) => {
|
||||
const topInput = topTool.inputs.find((topIn) => topIn.key === input.key);
|
||||
if (topInput) {
|
||||
input.value = topInput.value;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
return {
|
||||
...tool,
|
||||
configStatus: getToolConfigStatus(tool).status
|
||||
};
|
||||
})
|
||||
)
|
||||
).filter((item) => item !== undefined);
|
||||
|
||||
return results;
|
||||
};
|
||||
|
|
|
|||
|
|
@ -33,6 +33,7 @@ import { getWebLLMModel } from '@/web/common/system/utils';
|
|||
import ToolSelect from '../FormComponent/ToolSelector/ToolSelect';
|
||||
import OptimizerPopover from '@/components/common/PromptEditor/OptimizerPopover';
|
||||
import { useSystemStore } from '@/web/common/system/useSystemStore';
|
||||
import MyIconButton, { MyDeleteIconButton } from '@fastgpt/web/components/common/Icon/button';
|
||||
|
||||
const DatasetSelectModal = dynamic(() => import('@/components/core/app/DatasetSelectModal'));
|
||||
const DatasetParamsModal = dynamic(() => import('@/components/core/app/DatasetParamsModal'));
|
||||
|
|
@ -289,38 +290,62 @@ const EditForm = ({
|
|||
)}
|
||||
<Grid gridTemplateColumns={'repeat(2, minmax(0, 1fr))'} gridGap={[2, 4]}>
|
||||
{selectDatasets.map((item) => (
|
||||
<MyTooltip key={item.datasetId} label={t('common:core.dataset.Read Dataset')}>
|
||||
<Flex
|
||||
overflow={'hidden'}
|
||||
alignItems={'center'}
|
||||
p={2}
|
||||
bg={'white'}
|
||||
boxShadow={'0 4px 8px -2px rgba(16,24,40,.1),0 2px 4px -2px rgba(16,24,40,.06)'}
|
||||
borderRadius={'md'}
|
||||
border={theme.borders.base}
|
||||
cursor={'pointer'}
|
||||
onClick={() =>
|
||||
router.push({
|
||||
pathname: '/dataset/detail',
|
||||
query: {
|
||||
datasetId: item.datasetId
|
||||
}
|
||||
})
|
||||
<Flex
|
||||
key={item.datasetId}
|
||||
overflow={'hidden'}
|
||||
alignItems={'center'}
|
||||
p={2}
|
||||
bg={'white'}
|
||||
boxShadow={'0 4px 8px -2px rgba(16,24,40,.1),0 2px 4px -2px rgba(16,24,40,.06)'}
|
||||
borderRadius={'md'}
|
||||
border={'base'}
|
||||
_hover={{
|
||||
'& .controler': {
|
||||
display: 'flex'
|
||||
}
|
||||
}}
|
||||
>
|
||||
<Avatar src={item.avatar} w={'1.5rem'} borderRadius={'sm'} />
|
||||
<Box
|
||||
ml={2}
|
||||
flex={'1 0 0'}
|
||||
w={0}
|
||||
className={'textEllipsis'}
|
||||
fontSize={'sm'}
|
||||
color={'myGray.900'}
|
||||
>
|
||||
<Avatar src={item.avatar} w={'1.5rem'} borderRadius={'sm'} />
|
||||
<Box
|
||||
ml={2}
|
||||
flex={'1 0 0'}
|
||||
w={0}
|
||||
className={'textEllipsis'}
|
||||
fontSize={'sm'}
|
||||
color={'myGray.900'}
|
||||
>
|
||||
{item.name}
|
||||
</Box>
|
||||
</Flex>
|
||||
</MyTooltip>
|
||||
{item.name}
|
||||
</Box>
|
||||
|
||||
{/* Icon */}
|
||||
<Box className="controler" display={['flex', 'none']} alignItems={'center'}>
|
||||
<MyIconButton
|
||||
icon={'common/viewLight'}
|
||||
onClick={() =>
|
||||
router.push({
|
||||
pathname: '/dataset/detail',
|
||||
query: {
|
||||
datasetId: item.datasetId
|
||||
}
|
||||
})
|
||||
}
|
||||
/>
|
||||
<MyDeleteIconButton
|
||||
onClick={() => {
|
||||
setAppForm((state) => ({
|
||||
...state,
|
||||
dataset: {
|
||||
...state.dataset,
|
||||
datasets:
|
||||
state.dataset.datasets?.filter(
|
||||
(pre) => pre.datasetId !== item.datasetId
|
||||
) || []
|
||||
}
|
||||
}));
|
||||
}}
|
||||
/>
|
||||
</Box>
|
||||
</Flex>
|
||||
))}
|
||||
</Grid>
|
||||
</Box>
|
||||
|
|
|
|||
|
|
@ -9,13 +9,14 @@ import { MongoChatItem } from '@fastgpt/service/core/chat/chatItemSchema';
|
|||
import { MongoChat } from '@fastgpt/service/core/chat/chatSchema';
|
||||
import { MongoAppChatLog } from '@fastgpt/service/core/app/logs/chatLogsSchema';
|
||||
import { MongoChatItemResponse } from '@fastgpt/service/core/chat/chatItemResponseSchema';
|
||||
import { ChatItemValueTypeEnum, ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
|
||||
import { ChatFileTypeEnum, ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
|
||||
import { FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';
|
||||
import { AppTypeEnum } from '@fastgpt/global/core/app/constants';
|
||||
import { MongoTeamMember } from '@fastgpt/service/support/user/team/teamMemberSchema';
|
||||
import { MongoTeam } from '@fastgpt/service/support/user/team/teamSchema';
|
||||
import { MongoUser } from '@fastgpt/service/support/user/schema';
|
||||
import { TeamMemberRoleEnum } from '@fastgpt/global/support/user/team/constant';
|
||||
import type { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
|
||||
|
||||
const createMockProps = (
|
||||
overrides?: Partial<Props>,
|
||||
|
|
@ -41,7 +42,6 @@ const createMockProps = (
|
|||
obj: ChatRoleEnum.Human,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: {
|
||||
content: 'Hello, how are you?'
|
||||
}
|
||||
|
|
@ -52,7 +52,6 @@ const createMockProps = (
|
|||
obj: ChatRoleEnum.AI,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: {
|
||||
content: 'I am doing well, thank you!'
|
||||
}
|
||||
|
|
@ -142,9 +141,8 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.Human,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.file,
|
||||
file: {
|
||||
type: 'image',
|
||||
type: ChatFileTypeEnum.image,
|
||||
name: 'test.jpg',
|
||||
url: 'https://example.com/test.jpg',
|
||||
key: 'file-key-123'
|
||||
|
|
@ -192,7 +190,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.AI,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Response' }
|
||||
}
|
||||
],
|
||||
|
|
@ -224,7 +221,7 @@ describe('pushChatRecords', () => {
|
|||
});
|
||||
|
||||
it('should handle dataset search node with quoteList', async () => {
|
||||
const quote = {
|
||||
const quote: SearchDataResponseItemType = {
|
||||
id: 'quote-1',
|
||||
chunkIndex: 0,
|
||||
datasetId: 'dataset-1',
|
||||
|
|
@ -242,7 +239,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.AI,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Based on the search results...' }
|
||||
}
|
||||
],
|
||||
|
|
@ -531,7 +527,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.Human,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Hello' }
|
||||
}
|
||||
]
|
||||
|
|
@ -555,7 +550,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.AI,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Hello' }
|
||||
}
|
||||
]
|
||||
|
|
@ -580,7 +574,6 @@ describe('pushChatRecords', () => {
|
|||
dataId: 'data-id-1',
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.interactive,
|
||||
interactive: {
|
||||
type: 'userSelect',
|
||||
params: {
|
||||
|
|
@ -599,7 +592,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.Human,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Option 1' }
|
||||
}
|
||||
]
|
||||
|
|
@ -639,7 +631,6 @@ describe('pushChatRecords', () => {
|
|||
dataId: 'data-id-1',
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.interactive,
|
||||
interactive: {
|
||||
type: 'userInput',
|
||||
params: {
|
||||
|
|
@ -664,7 +655,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.Human,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: JSON.stringify({ username: 'john_doe' }) }
|
||||
}
|
||||
]
|
||||
|
|
@ -705,11 +695,9 @@ describe('pushChatRecords', () => {
|
|||
dataId: 'data-id-1',
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Payment required' }
|
||||
},
|
||||
{
|
||||
type: ChatItemValueTypeEnum.interactive,
|
||||
interactive: {
|
||||
type: 'paymentPause',
|
||||
params: {}
|
||||
|
|
@ -729,8 +717,6 @@ describe('pushChatRecords', () => {
|
|||
});
|
||||
// PaymentPause is removed, and AI response is appended
|
||||
expect(chatItem?.value.length).toBeGreaterThan(0);
|
||||
// The first value should be text, last one should be from AI response
|
||||
expect(chatItem?.value[0].type).toBe(ChatItemValueTypeEnum.text);
|
||||
});
|
||||
|
||||
it('should merge AI response values', async () => {
|
||||
|
|
@ -744,11 +730,9 @@ describe('pushChatRecords', () => {
|
|||
dataId: 'data-id-1',
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'First response' }
|
||||
},
|
||||
{
|
||||
type: ChatItemValueTypeEnum.interactive,
|
||||
interactive: {
|
||||
type: 'userSelect',
|
||||
params: { options: ['A', 'B'] }
|
||||
|
|
@ -763,7 +747,6 @@ describe('pushChatRecords', () => {
|
|||
obj: ChatRoleEnum.AI,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.text,
|
||||
text: { content: 'Second response' }
|
||||
}
|
||||
],
|
||||
|
|
@ -797,7 +780,6 @@ describe('pushChatRecords', () => {
|
|||
durationSeconds: 1.5,
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.interactive,
|
||||
interactive: {
|
||||
type: 'userSelect',
|
||||
params: { options: ['A', 'B'] }
|
||||
|
|
@ -840,7 +822,6 @@ describe('pushChatRecords', () => {
|
|||
dataId: 'data-id-1',
|
||||
value: [
|
||||
{
|
||||
type: ChatItemValueTypeEnum.interactive,
|
||||
interactive: {
|
||||
type: 'userSelect',
|
||||
params: { options: ['A', 'B'] }
|
||||
|
|
|
|||
Loading…
Reference in New Issue