Change embedding (#1463)
* rebuild embedding queue * dataset menu * feat: rebuild data api * feat: ui change embedding model * dataset ui * feat: rebuild index ui * rename collection
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@@ -16,25 +16,47 @@ import PermissionRadio from '@/components/support/permission/Radio';
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import { useSystemStore } from '@/web/common/system/useSystemStore';
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import { useRequest } from '@fastgpt/web/hooks/useRequest';
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import { MongoImageTypeEnum } from '@fastgpt/global/common/file/image/constants';
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import MySelect from '@fastgpt/web/components/common/MySelect';
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import AIModelSelector from '@/components/Select/AIModelSelector';
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import { postRebuildEmbedding } from '@/web/core/dataset/api';
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import { useI18n } from '@/web/context/I18n';
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import type { VectorModelItemType } from '@fastgpt/global/core/ai/model.d';
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import { useContextSelector } from 'use-context-selector';
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import { DatasetPageContext } from '@/web/core/dataset/context/datasetPageContext';
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import MyDivider from '@fastgpt/web/components/common/MyDivider/index';
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const Info = ({ datasetId }: { datasetId: string }) => {
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const { t } = useTranslation();
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const { datasetDetail, loadDatasets, updateDataset } = useDatasetStore();
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const { getValues, setValue, register, handleSubmit } = useForm<DatasetItemType>({
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const { datasetT } = useI18n();
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const { datasetDetail, loadDatasetDetail, loadDatasets, updateDataset } = useDatasetStore();
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const rebuildingCount = useContextSelector(DatasetPageContext, (v) => v.rebuildingCount);
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const trainingCount = useContextSelector(DatasetPageContext, (v) => v.trainingCount);
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const refetchDatasetTraining = useContextSelector(
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DatasetPageContext,
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(v) => v.refetchDatasetTraining
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);
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const { setValue, register, handleSubmit, watch } = useForm<DatasetItemType>({
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defaultValues: datasetDetail
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});
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const avatar = watch('avatar');
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const vectorModel = watch('vectorModel');
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const agentModel = watch('agentModel');
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const permission = watch('permission');
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const { datasetModelList, vectorModelList } = useSystemStore();
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const router = useRouter();
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const [refresh, setRefresh] = useState(false);
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const { openConfirm, ConfirmModal } = useConfirm({
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const { openConfirm: onOpenConfirmDel, ConfirmModal: ConfirmDelModal } = useConfirm({
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content: t('core.dataset.Delete Confirm'),
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type: 'delete'
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});
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const { openConfirm: onOpenConfirmRebuild, ConfirmModal: ConfirmRebuildModal } = useConfirm({
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title: t('common.confirm.Common Tip'),
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content: datasetT('Confirm to rebuild embedding tip'),
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type: 'delete'
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});
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const { File, onOpen: onOpenSelectFile } = useSelectFile({
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fileType: '.jpg,.png',
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@@ -81,13 +103,27 @@ const Info = ({ datasetId }: { datasetId: string }) => {
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onSuccess(src: string | null) {
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if (src) {
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setValue('avatar', src);
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setRefresh((state) => !state);
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}
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},
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errorToast: t('common.avatar.Select Failed')
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});
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const btnLoading = useMemo(() => isDeleting || isSaving, [isDeleting, isSaving]);
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const { mutate: onRebuilding, isLoading: isRebuilding } = useRequest({
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mutationFn: (vectorModel: VectorModelItemType) => {
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return postRebuildEmbedding({
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datasetId,
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vectorModel: vectorModel.model
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});
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},
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onSuccess() {
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refetchDatasetTraining();
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loadDatasetDetail(datasetId, true);
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},
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successToast: datasetT('Rebuild embedding start tip'),
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errorToast: t('common.Update Failed')
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});
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const btnLoading = isSelecting || isDeleting || isSaving || isRebuilding;
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return (
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<Box py={5} px={[5, 10]}>
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@@ -97,6 +133,62 @@ const Info = ({ datasetId }: { datasetId: string }) => {
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</Box>
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<Box flex={1}>{datasetDetail._id}</Box>
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</Flex>
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<Flex mt={8} w={'100%'} alignItems={'center'} flexWrap={'wrap'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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{t('core.ai.model.Vector Model')}
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</Box>
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<Box flex={[1, '0 0 300px']}>
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<AIModelSelector
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w={'100%'}
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value={vectorModel.model}
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disableTip={
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rebuildingCount > 0 || trainingCount > 0
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? datasetT('The knowledge base has indexes that are being trained or being rebuilt')
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: undefined
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}
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list={vectorModelList.map((item) => ({
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label: item.name,
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value: item.model
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}))}
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onchange={(e) => {
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const vectorModel = vectorModelList.find((item) => item.model === e);
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if (!vectorModel) return;
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onOpenConfirmRebuild(() => {
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setValue('vectorModel', vectorModel);
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onRebuilding(vectorModel);
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})();
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}}
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/>
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</Box>
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</Flex>
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<Flex mt={8} w={'100%'} alignItems={'center'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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{t('core.Max Token')}
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</Box>
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<Box flex={[1, '0 0 300px']}>{vectorModel.maxToken}</Box>
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</Flex>
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<Flex mt={6} alignItems={'center'} flexWrap={'wrap'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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{t('core.ai.model.Dataset Agent Model')}
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</Box>
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<Box flex={[1, '0 0 300px']}>
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<AIModelSelector
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w={'100%'}
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value={agentModel.model}
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list={datasetModelList.map((item) => ({
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label: item.name,
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value: item.model
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}))}
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onchange={(e) => {
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const agentModel = datasetModelList.find((item) => item.model === e);
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if (!agentModel) return;
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setValue('agentModel', agentModel);
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}}
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/>
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</Box>
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</Flex>
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<MyDivider my={4} h={'2px'} maxW={'500px'} />
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<Flex mt={5} w={'100%'} alignItems={'center'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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@@ -106,7 +198,7 @@ const Info = ({ datasetId }: { datasetId: string }) => {
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<MyTooltip label={t('common.avatar.Select Avatar')}>
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<Avatar
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m={'auto'}
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src={getValues('avatar')}
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src={avatar}
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w={['32px', '40px']}
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h={['32px', '40px']}
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cursor={'pointer'}
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@@ -121,40 +213,6 @@ const Info = ({ datasetId }: { datasetId: string }) => {
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</Box>
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<Input flex={[1, '0 0 300px']} maxLength={30} {...register('name')} />
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</Flex>
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<Flex mt={8} w={'100%'} alignItems={'center'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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{t('core.ai.model.Vector Model')}
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</Box>
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<Box flex={[1, '0 0 300px']}>{getValues('vectorModel').name}</Box>
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</Flex>
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<Flex mt={8} w={'100%'} alignItems={'center'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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{t('core.Max Token')}
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</Box>
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<Box flex={[1, '0 0 300px']}>{getValues('vectorModel').maxToken}</Box>
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</Flex>
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<Flex mt={6} alignItems={'center'}>
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<Box flex={['0 0 90px', '0 0 160px']} w={0}>
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{t('core.ai.model.Dataset Agent Model')}
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</Box>
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<Box flex={[1, '0 0 300px']}>
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<AIModelSelector
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w={'100%'}
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value={getValues('agentModel').model}
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list={datasetModelList.map((item) => ({
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label: item.name,
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value: item.model
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}))}
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onchange={(e) => {
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const agentModel = datasetModelList.find((item) => item.model === e);
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if (!agentModel) return;
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setValue('agentModel', agentModel);
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setRefresh((state) => !state);
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}}
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/>
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</Box>
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</Flex>
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<Flex mt={8} alignItems={'center'} w={'100%'}>
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<Box flex={['0 0 90px', '0 0 160px']}>{t('common.Intro')}</Box>
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<Textarea flex={[1, '0 0 300px']} {...register('intro')} placeholder={t('common.Intro')} />
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@@ -166,10 +224,9 @@ const Info = ({ datasetId }: { datasetId: string }) => {
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</Box>
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<Box>
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<PermissionRadio
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value={getValues('permission')}
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value={permission}
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onChange={(e) => {
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setValue('permission', e);
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setRefresh(!refresh);
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}}
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/>
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</Box>
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@@ -193,12 +250,14 @@ const Info = ({ datasetId }: { datasetId: string }) => {
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aria-label={''}
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variant={'whiteDanger'}
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size={'smSquare'}
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onClick={openConfirm(onclickDelete)}
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onClick={onOpenConfirmDel(onclickDelete)}
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/>
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)}
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</Flex>
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<File onSelect={onSelectFile} />
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<ConfirmModal />
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<ConfirmDelModal />
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<ConfirmRebuildModal countDown={10} />
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</Box>
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);
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};
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