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* perf: system toolset & mcp (#5200) * feat: support system toolset * fix: type * fix: system tool config * chore: mcptool config migrate * refactor: mcp toolset * fix: fe type error * fix: type error * fix: show version * chore: support extract tool's secretInputConfig out of inputs * chore: compatible with old version mcp * chore: adjust * deps: update dependency @fastgpt-skd/plugin * fix: version * fix: some bug (#5316) * chore: compatible with old version mcp * fix: version * fix: compatible bug * fix: mcp object params * fix: type error * chore: update test cases * chore: remove log * fix: toolset node name * optimize app logs sort (#5310) * log keys config modal * multiple select * api * fontsize * code * chatid * fix build * fix * fix component * change name * log keys config * fix * delete unused * fix * perf: log code * perf: send auth code modal enter press * fix log (#5328) * perf: mcp toolset comment * perf: log ui * remove log (#5347) * doc * fix: action * remove log * fix: Table Optimization (#5319) * feat: table test: 1 * feat: table test: 2 * feat: table test: 3 * feat: table test: 4 * feat: table test : 5 把maxSize改回chunkSize * feat: table test : 6 都删了,只看maxSize * feat: table test : 7 恢复初始,接下来删除标签功能 * feat: table test : 8 删除标签功能 * feat: table test : 9 删除标签功能成功 * feat: table test : 10 继续调试,修改trainingStates * feat: table test : 11 修改第一步 * feat: table test : 12 修改第二步 * feat: table test : 13 修改了HtmlTable2Md * feat: table test : 14 修改表头分块规则 * feat: table test : 15 前面表格分的太细了 * feat: table test : 16 改着改着表头又不加了 * feat: table test : 17 用CUSTOM_SPLIT_SIGN不行,重新改 * feat: table test : 18 表头仍然还会多加,但现在分块搞的合理了终于 * feat: table test : 19 还是需要搞好表头问题,先保存一下调试情况 * feat: table test : 20 调试结束,看一下replace有没有问题,没问题就pr * feat: table test : 21 先把注释删了 * feat: table test : 21 注释replace都改了,下面切main分支看看情况 * feat: table test : 22 修改旧文件 * feat: table test : 23 修改测试文件 * feat: table test : 24 xlsx表格处理 * feat: table test : 25 刚才没保存先com了 * feat: table test : 26 fix * feat: table test : 27 先com一版调试 * feat: table test : 28 试试放format2csv里 * feat: table test : 29 xlsx解决 * feat: table test : 30 tablesplit解决 * feat: table test : 31 * feat: table test : 32 * perf: table split * perf: mcp old version compatibility (#5342) * fix: system-tool secret inputs * fix: rewrite runtime node i18n for system tool * perf: mcp old version compatibility * fix: splitPluginId * fix: old mcp toolId * fix: filter secret key * feat: support system toolset activation * chore: remove log * perf: mcp update * perf: rewrite toolset * fix:delete variable id (#5335) * perf: variable update * fix: multiple select ui * perf: model config move to plugin * fix: var conflit * perf: variable checker * Avoid empty number * update doc time * fix: test * fix: mcp object * update count app * update count app --------- Co-authored-by: Finley Ge <32237950+FinleyGe@users.noreply.github.com> Co-authored-by: heheer <heheer@sealos.io> Co-authored-by: heheer <zhiyu44@qq.com> Co-authored-by: colnii <1286949794@qq.com> Co-authored-by: dreamer6680 <1468683855@qq.com>
246 lines
8.3 KiB
TypeScript
246 lines
8.3 KiB
TypeScript
import { type SystemModelItemType } from '../type';
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import { ModelTypeEnum } from '@fastgpt/global/core/ai/model';
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import { MongoSystemModel } from './schema';
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import {
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type LLMModelItemType,
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type EmbeddingModelItemType,
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type TTSModelType,
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type STTModelType,
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type RerankModelItemType
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} from '@fastgpt/global/core/ai/model.d';
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import { debounce } from 'lodash';
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import { getModelProvider } from '@fastgpt/global/core/ai/provider';
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import { findModelFromAlldata } from '../model';
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import {
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reloadFastGPTConfigBuffer,
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updateFastGPTConfigBuffer
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} from '../../../common/system/config/controller';
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import { delay } from '@fastgpt/global/common/system/utils';
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import { pluginClient } from '../../../thirdProvider/fastgptPlugin';
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import { setCron } from '../../../common/system/cron';
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export const loadSystemModels = async (init = false) => {
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const pushModel = (model: SystemModelItemType) => {
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global.systemModelList.push(model);
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// Add default value
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if (model.type === ModelTypeEnum.llm) {
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model.datasetProcess = model.datasetProcess ?? true;
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model.usedInClassify = model.usedInClassify ?? true;
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model.usedInExtractFields = model.usedInExtractFields ?? true;
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model.usedInToolCall = model.usedInToolCall ?? true;
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model.useInEvaluation = model.useInEvaluation ?? true;
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}
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if (model.isActive) {
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global.systemActiveModelList.push(model);
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if (model.type === ModelTypeEnum.llm) {
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global.llmModelMap.set(model.model, model);
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global.llmModelMap.set(model.name, model);
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if (model.isDefault) {
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global.systemDefaultModel.llm = model;
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}
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if (model.isDefaultDatasetTextModel) {
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global.systemDefaultModel.datasetTextLLM = model;
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}
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if (model.isDefaultDatasetImageModel) {
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global.systemDefaultModel.datasetImageLLM = model;
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}
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} else if (model.type === ModelTypeEnum.embedding) {
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global.embeddingModelMap.set(model.model, model);
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global.embeddingModelMap.set(model.name, model);
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if (model.isDefault) {
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global.systemDefaultModel.embedding = model;
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}
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} else if (model.type === ModelTypeEnum.tts) {
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global.ttsModelMap.set(model.model, model);
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global.ttsModelMap.set(model.name, model);
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if (model.isDefault) {
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global.systemDefaultModel.tts = model;
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}
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} else if (model.type === ModelTypeEnum.stt) {
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global.sttModelMap.set(model.model, model);
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global.sttModelMap.set(model.name, model);
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if (model.isDefault) {
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global.systemDefaultModel.stt = model;
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}
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} else if (model.type === ModelTypeEnum.rerank) {
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global.reRankModelMap.set(model.model, model);
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global.reRankModelMap.set(model.name, model);
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if (model.isDefault) {
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global.systemDefaultModel.rerank = model;
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}
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}
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}
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};
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if (!init && global.systemModelList) return;
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global.systemModelList = [];
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global.systemActiveModelList = [];
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global.llmModelMap = new Map<string, LLMModelItemType>();
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global.embeddingModelMap = new Map<string, EmbeddingModelItemType>();
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global.ttsModelMap = new Map<string, TTSModelType>();
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global.sttModelMap = new Map<string, STTModelType>();
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global.reRankModelMap = new Map<string, RerankModelItemType>();
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// @ts-ignore
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global.systemDefaultModel = {};
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try {
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// Get model from db and plugin
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const [dbModels, systemModels] = await Promise.all([
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MongoSystemModel.find({}).lean(),
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pluginClient.model.list().then((res) => {
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if (res.status === 200) return res.body;
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console.error('Get fastGPT plugin model error');
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return [];
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})
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]);
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// Load system model from local
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await Promise.all(
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systemModels.map(async (model) => {
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const mergeObject = (obj1: any, obj2: any) => {
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if (!obj1 && !obj2) return undefined;
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const formatObj1 = typeof obj1 === 'object' ? obj1 : {};
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const formatObj2 = typeof obj2 === 'object' ? obj2 : {};
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return { ...formatObj1, ...formatObj2 };
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};
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const dbModel = dbModels.find((item) => item.model === model.model);
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const modelData: any = {
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...model,
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...dbModel?.metadata,
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// @ts-ignore
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defaultConfig: mergeObject(model.defaultConfig, dbModel?.metadata?.defaultConfig),
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// @ts-ignore
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fieldMap: mergeObject(model.fieldMap, dbModel?.metadata?.fieldMap),
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provider: getModelProvider(dbModel?.metadata?.provider || (model.provider as any)).id,
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type: dbModel?.metadata?.type || model.type,
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isCustom: false
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};
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pushModel(modelData);
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})
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);
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// Custom model(Not in system config)
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dbModels.forEach((dbModel) => {
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if (global.systemModelList.find((item) => item.model === dbModel.model)) return;
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pushModel({
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...dbModel.metadata,
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isCustom: true
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});
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});
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// Default model check
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if (!global.systemDefaultModel.llm) {
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global.systemDefaultModel.llm = Array.from(global.llmModelMap.values())[0];
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}
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if (!global.systemDefaultModel.datasetTextLLM) {
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global.systemDefaultModel.datasetTextLLM = Array.from(global.llmModelMap.values()).find(
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(item) => item.datasetProcess
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);
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}
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if (!global.systemDefaultModel.datasetImageLLM) {
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global.systemDefaultModel.datasetImageLLM = Array.from(global.llmModelMap.values()).find(
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(item) => item.vision
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);
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}
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if (!global.systemDefaultModel.embedding) {
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global.systemDefaultModel.embedding = Array.from(global.embeddingModelMap.values())[0];
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}
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if (!global.systemDefaultModel.tts) {
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global.systemDefaultModel.tts = Array.from(global.ttsModelMap.values())[0];
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}
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if (!global.systemDefaultModel.stt) {
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global.systemDefaultModel.stt = Array.from(global.sttModelMap.values())[0];
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}
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if (!global.systemDefaultModel.rerank) {
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global.systemDefaultModel.rerank = Array.from(global.reRankModelMap.values())[0];
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}
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// Sort model list
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global.systemActiveModelList.sort((a, b) => {
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const providerA = getModelProvider(a.provider);
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const providerB = getModelProvider(b.provider);
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return providerA.order - providerB.order;
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});
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console.log(
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`Load models success, total: ${global.systemModelList.length}, active: ${global.systemActiveModelList.length}`,
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JSON.stringify(
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global.systemActiveModelList.map((item) => ({
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provider: item.provider,
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model: item.model,
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name: item.name
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})),
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null,
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2
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)
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);
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} catch (error) {
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console.error('Load models error', error);
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// @ts-ignore
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global.systemModelList = undefined;
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return Promise.reject(error);
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}
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};
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export const getSystemModelConfig = async (model: string): Promise<SystemModelItemType> => {
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const modelData = findModelFromAlldata(model);
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if (!modelData) return Promise.reject('Model is not found');
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if (modelData.isCustom) return Promise.reject('Custom model not data');
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// Read file
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const modelDefaulConfig = await pluginClient.model.list().then((res) => {
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if (res.status === 200) {
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return res.body.find((item) => item.model === model) as SystemModelItemType;
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}
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return Promise.reject('Can not get model config from plugin');
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});
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return {
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...modelDefaulConfig,
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provider: modelData.provider,
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isCustom: false
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};
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};
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export const watchSystemModelUpdate = () => {
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const changeStream = MongoSystemModel.watch();
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changeStream.on(
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'change',
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debounce(async () => {
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try {
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// Main node will reload twice
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await loadSystemModels(true);
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// All node reaload buffer
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await reloadFastGPTConfigBuffer();
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} catch (error) {}
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}, 500)
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);
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};
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// 更新完模型后,需要重载缓存
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export const updatedReloadSystemModel = async () => {
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// 1. 更新模型(所有节点都会触发)
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await loadSystemModels(true);
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// 2. 更新缓存(仅主节点触发)
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await updateFastGPTConfigBuffer();
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// 3. 延迟1秒,等待其他节点刷新
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await delay(1000);
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};
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export const cronRefreshModels = async () => {
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setCron('*/5 * * * *', async () => {
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// 1. 更新模型(所有节点都会触发)
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await loadSystemModels(true);
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// 2. 更新缓存(仅主节点触发)
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await updateFastGPTConfigBuffer();
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});
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};
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