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V4.6.9-first commit (#899)
* perf: insert mongo dataset data session * perf: dataset data index * remove delay * rename bill schema * rename bill record * perf: bill table * perf: prompt * perf: sub plan * change the usage count * feat: usage bill * publish usages * doc * 新增团队聊天功能 (#20) * perf: doc * feat 添加标签部分 feat 信息团队标签配置 feat 新增团队同步管理 feat team分享页面 feat 完成team分享页面 feat 实现模糊搜索 style 格式化 fix 修复迷糊匹配 style 样式修改 fix 团队标签功能修复 * fix 修复鉴权功能 * merge 合并代码 * fix 修复引用错误 * fix 修复pr问题 * fix 修复ts格式问题 --------- Co-authored-by: archer <545436317@qq.com> Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> * update extra plan * fix: ts * format * perf: bill field * feat: standard plan * fix: ts * feat 个人账号页面修改 (#22) * feat 添加标签部分 feat 信息团队标签配置 feat 新增团队同步管理 feat team分享页面 feat 完成team分享页面 feat 实现模糊搜索 style 格式化 fix 修复迷糊匹配 style 样式修改 fix 团队标签功能修复 * fix 修复鉴权功能 * merge 合并代码 * fix 修复引用错误 * fix 修复pr问题 * fix 修复ts格式问题 * feat 修改个人账号页 --------- Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> * sub plan page (#23) * fix chunk index; error page text * feat: dataset process Integral prediction * feat: stand plan field * feat: sub plan limit * perf: index * query extension * perf: share link push app name * perf: plan point unit * perf: get sub plan * perf: account page * feat 新增套餐详情弹窗代码 (#24) * merge 合并代码 * fix 新增套餐详情弹框 * fix 修复pr问题 * feat: change http node input to prompt editor (#21) * feat: change http node input to prompt editor * fix * split PromptEditor to HttpInput * Team plans (#25) * perf: pay check * perf: team plan test * plan limit check * replace sensitive text * perf: fix some null * collection null check * perf: plans modal * perf: http module * pacakge (#26) * individuation page and pay modal amount (#27) * feat: individuation page * team chat config * pay modal * plan count and replace invalid chars (#29) * fix: user oneapi * fix: training queue * fix: qa queue * perf: remove space chars * replace invalid chars * change httpinput dropdown menu (#28) * perf: http * reseet free plan * perf: plan code to packages * remove llm config to package * perf: code * perf: faq * fix: get team plan --------- Co-authored-by: yst <77910600+yu-and-liu@users.noreply.github.com> Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> Co-authored-by: heheer <71265218+newfish-cmyk@users.noreply.github.com>
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Archer
@@ -11,7 +11,7 @@ import { simpleText } from '@fastgpt/global/common/string/tools';
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import { countPromptTokens } from '@fastgpt/global/common/string/tiktoken';
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import type { VectorModelItemType, LLMModelItemType } from '@fastgpt/global/core/ai/model.d';
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export const lockTrainingDataByTeamId = async (teamId: string, retry = 3): Promise<any> => {
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export const lockTrainingDataByTeamId = async (teamId: string): Promise<any> => {
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try {
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await MongoDatasetTraining.updateMany(
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{
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@@ -21,13 +21,7 @@ export const lockTrainingDataByTeamId = async (teamId: string, retry = 3): Promi
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lockTime: new Date('2999/5/5')
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}
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);
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} catch (error) {
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if (retry > 0) {
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await delay(1000);
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return lockTrainingDataByTeamId(teamId, retry - 1);
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}
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return Promise.reject(error);
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}
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} catch (error) {}
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};
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export async function pushDataListToTrainingQueue({
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@@ -51,17 +45,15 @@ export async function pushDataListToTrainingQueue({
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datasetId: { _id: datasetId, vectorModel, agentModel }
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} = await getCollectionWithDataset(collectionId);
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const checkModelValid = async ({ collectionId }: { collectionId: string }) => {
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if (!collectionId) return Promise.reject(`CollectionId is empty`);
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const checkModelValid = async () => {
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if (trainingMode === TrainingModeEnum.chunk) {
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const vectorModelData = vectorModelList?.find((item) => item.model === vectorModel);
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if (!vectorModelData) {
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return Promise.reject(`Model ${vectorModel} is inValid`);
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return Promise.reject(`File model ${vectorModel} is inValid`);
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}
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return {
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maxToken: vectorModelData.maxToken * 1.5,
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maxToken: vectorModelData.maxToken * 1.3,
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model: vectorModelData.model,
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weight: vectorModelData.weight
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};
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@@ -70,7 +62,7 @@ export async function pushDataListToTrainingQueue({
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if (trainingMode === TrainingModeEnum.qa) {
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const qaModelData = datasetModelList?.find((item) => item.model === agentModel);
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if (!qaModelData) {
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return Promise.reject(`Model ${agentModel} is inValid`);
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return Promise.reject(`Vector model ${agentModel} is inValid`);
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}
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return {
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maxToken: qaModelData.maxContext * 0.8,
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@@ -81,9 +73,7 @@ export async function pushDataListToTrainingQueue({
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return Promise.reject(`Training mode "${trainingMode}" is inValid`);
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};
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const { model, maxToken, weight } = await checkModelValid({
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collectionId
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});
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const { model, maxToken, weight } = await checkModelValid();
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// format q and a, remove empty char
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data.forEach((item) => {
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