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refactor(server): job repository (#1382)

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* refactor(server): job repository

* refactor: job repository

* chore: generate open-api

* fix: job panel

* Remove incorrect subtitle

Co-authored-by: Alex Tran <alex.tran1502@gmail.com>
This commit is contained in:
Jason Rasmussen
2023-01-21 23:13:36 -05:00
committed by GitHub
parent f4c90426a5
commit 4cfac47674
34 changed files with 418 additions and 1124 deletions
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244
web/src/lib/components/admin-page/jobs/jobs-panel.svelte
View File

@@ -8,203 +8,97 @@
import { onDestroy, onMount } from 'svelte';
import JobTile from './job-tile.svelte';
let allJobsStatus: AllJobStatusResponseDto;
let setIntervalHandler: NodeJS.Timer;
let jobs: AllJobStatusResponseDto;
let timer: NodeJS.Timer;
const load = async () => {
const { data } = await api.jobApi.getAllJobsStatus();
jobs = data;
};
onMount(async () => {
const { data } = await api.jobApi.getAllJobsStatus();
allJobsStatus = data;
setIntervalHandler = setInterval(async () => {
const { data } = await api.jobApi.getAllJobsStatus();
allJobsStatus = data;
}, 1000);
await load();
timer = setInterval(async () => await load(), 5_000);
});
onDestroy(() => {
clearInterval(setIntervalHandler);
clearInterval(timer);
});
const runThumbnailGeneration = async () => {
const run = async (jobId: JobId, jobName: string, emptyMessage: string) => {
try {
const { data } = await api.jobApi.sendJobCommand(JobId.ThumbnailGeneration, {
command: JobCommand.Start
});
const { data } = await api.jobApi.sendJobCommand(jobId, { command: JobCommand.Start });
if (data) {
notificationController.show({
message: `Thumbnail generation job started for ${data} assets`,
message: `Started ${jobName}`,
type: NotificationType.Info
});
} else {
notificationController.show({
message: `No missing thumbnails found`,
type: NotificationType.Info
});
}
} catch (e) {
console.log('[ERROR] runThumbnailGeneration', e);
notificationController.show({
message: `Error running thumbnail generation job, check console for more detail`,
type: NotificationType.Error
});
}
};
const runExtractEXIF = async () => {
try {
const { data } = await api.jobApi.sendJobCommand(JobId.MetadataExtraction, {
command: JobCommand.Start
});
if (data) {
notificationController.show({
message: `Extract EXIF job started for ${data} assets`,
type: NotificationType.Info
});
} else {
notificationController.show({
message: `No missing EXIF found`,
type: NotificationType.Info
});
}
} catch (e) {
console.log('[ERROR] runExtractEXIF', e);
notificationController.show({
message: `Error running extract EXIF job, check console for more detail`,
type: NotificationType.Error
});
}
};
const runMachineLearning = async () => {
try {
const { data } = await api.jobApi.sendJobCommand(JobId.MachineLearning, {
command: JobCommand.Start
});
if (data) {
notificationController.show({
message: `Object detection job started for ${data} assets`,
type: NotificationType.Info
});
} else {
notificationController.show({
message: `No missing object detection found`,
type: NotificationType.Info
});
notificationController.show({ message: emptyMessage, type: NotificationType.Info });
}
} catch (error) {
handleError(error, `Error running machine learning job, check console for more detail`);
}
};
const runVideoConversion = async () => {
try {
const { data } = await api.jobApi.sendJobCommand(JobId.VideoConversion, {
command: JobCommand.Start
});
if (data) {
notificationController.show({
message: `Video conversion job started for ${data} assets`,
type: NotificationType.Info
});
} else {
notificationController.show({
message: `No videos without an encoded version found`,
type: NotificationType.Info
});
}
} catch (error) {
handleError(error, `Error running video conversion job, check console for more detail`);
}
};
const runTemplateMigration = async () => {
try {
const { data } = await api.jobApi.sendJobCommand(JobId.StorageTemplateMigration, {
command: JobCommand.Start
});
if (data) {
notificationController.show({
message: `Storage migration started`,
type: NotificationType.Info
});
} else {
notificationController.show({
message: `All files have been migrated to the new storage template`,
type: NotificationType.Info
});
}
} catch (e) {
console.log('[ERROR] runTemplateMigration', e);
notificationController.show({
message: `Error running template migration job, check console for more detail`,
type: NotificationType.Error
});
handleError(error, `Unable to start ${jobName}`);
}
};
</script>
<div class="flex flex-col gap-10">
<JobTile
title={'Generate thumbnails'}
subtitle={'Regenerate missing thumbnail (JPEG, WEBP)'}
on:click={runThumbnailGeneration}
jobStatus={allJobsStatus?.isThumbnailGenerationActive}
waitingJobCount={allJobsStatus?.thumbnailGenerationQueueCount.waiting}
activeJobCount={allJobsStatus?.thumbnailGenerationQueueCount.active}
/>
{#if jobs}
<JobTile
title={'Generate thumbnails'}
subtitle={'Regenerate missing thumbnail (JPEG, WEBP)'}
on:click={() =>
run(JobId.ThumbnailGeneration, 'thumbnail generation', 'No missing thumbnails found')}
jobCounts={jobs[JobId.ThumbnailGeneration]}
/>
<JobTile
title={'Extract EXIF'}
subtitle={'Extract missing EXIF information'}
on:click={runExtractEXIF}
jobStatus={allJobsStatus?.isMetadataExtractionActive}
waitingJobCount={allJobsStatus?.metadataExtractionQueueCount.waiting}
activeJobCount={allJobsStatus?.metadataExtractionQueueCount.active}
/>
<JobTile
title={'Extract EXIF'}
subtitle={'Extract missing EXIF information'}
on:click={() => run(JobId.MetadataExtraction, 'extract EXIF', 'No missing EXIF found')}
jobCounts={jobs[JobId.MetadataExtraction]}
/>
<JobTile
title={'Detect objects'}
subtitle={'Run machine learning process to detect and classify objects'}
on:click={runMachineLearning}
jobStatus={allJobsStatus?.isMachineLearningActive}
waitingJobCount={allJobsStatus?.machineLearningQueueCount.waiting}
activeJobCount={allJobsStatus?.machineLearningQueueCount.active}
>
Note that some assets may not have any objects detected, this is normal.
</JobTile>
<JobTile
title={'Video transcoding'}
subtitle={'Run video transcoding process to transcode videos not in the desired format'}
on:click={runVideoConversion}
jobStatus={allJobsStatus?.isVideoConversionActive}
waitingJobCount={allJobsStatus?.videoConversionQueueCount.waiting}
activeJobCount={allJobsStatus?.videoConversionQueueCount.active}
>
Note that some videos won't require transcoding, this is normal.
</JobTile>
<JobTile
title={'Storage migration'}
subtitle={''}
on:click={runTemplateMigration}
jobStatus={allJobsStatus?.isStorageMigrationActive}
waitingJobCount={allJobsStatus?.storageMigrationQueueCount.waiting}
activeJobCount={allJobsStatus?.storageMigrationQueueCount.active}
>
Apply the current
<a
href="/admin/system-settings?open=storage-template"
class="text-immich-primary dark:text-immich-dark-primary">Storage template</a
<JobTile
title={'Detect objects'}
subtitle={'Run machine learning process to detect and classify objects'}
on:click={() =>
run(JobId.MachineLearning, 'object detection', 'No missing object detection found')}
jobCounts={jobs[JobId.MachineLearning]}
>
to previously uploaded assets
</JobTile>
Note that some assets may not have any objects detected, this is normal.
</JobTile>
<JobTile
title={'Video transcoding'}
subtitle={'Run video transcoding process to transcode videos not in the desired format'}
on:click={() =>
run(
JobId.VideoConversion,
'video conversion',
'No videos without an encoded version found'
)}
jobCounts={jobs[JobId.MachineLearning]}
/>
<JobTile
title={'Storage migration'}
subtitle={''}
on:click={() =>
run(
JobId.StorageTemplateMigration,
'storage template migration',
'All files have been migrated to the new storage template'
)}
jobCounts={jobs[JobId.StorageTemplateMigration]}
>
Apply the current
<a
href="/admin/system-settings?open=storage-template"
class="text-immich-primary dark:text-immich-dark-primary">Storage template</a
>
to previously uploaded assets
</JobTile>
{/if}
</div>