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refactor(server): jobs (#2023)

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* refactor: job to domain

* chore: regenerate open api

* chore: tests

* fix: missing breaks

* fix: get asset with missing exif data

---------

Co-authored-by: Alex Tran <alex.tran1502@gmail.com>
This commit is contained in:
Jason Rasmussen
2023-03-20 11:55:28 -04:00
committed by GitHub
parent db6b14361d
commit 386eef046d
68 changed files with 1355 additions and 907 deletions
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57
server/libs/domain/src/smart-info/smart-info.service.ts
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@@ -1,6 +1,7 @@
import { MACHINE_LEARNING_ENABLED } from '@app/common';
import { Inject, Injectable, Logger } from '@nestjs/common';
import { IAssetJob, IJobRepository, JobName } from '../job';
import { IAssetRepository, WithoutProperty } from '../asset';
import { IAssetJob, IBaseJob, IJobRepository, JobName } from '../job';
import { IMachineLearningRepository } from './machine-learning.interface';
import { ISmartInfoRepository } from './smart-info.repository';
@@ -9,26 +10,24 @@ export class SmartInfoService {
private logger = new Logger(SmartInfoService.name);
constructor(
@Inject(IAssetRepository) private assetRepository: IAssetRepository,
@Inject(IJobRepository) private jobRepository: IJobRepository,
@Inject(ISmartInfoRepository) private repository: ISmartInfoRepository,
@Inject(IMachineLearningRepository) private machineLearning: IMachineLearningRepository,
) {}
async handleTagImage(data: IAssetJob) {
const { asset } = data;
if (!MACHINE_LEARNING_ENABLED || !asset.resizePath) {
return;
}
async handleQueueObjectTagging({ force }: IBaseJob) {
try {
const tags = await this.machineLearning.tagImage({ thumbnailPath: asset.resizePath });
if (tags.length > 0) {
await this.repository.upsert({ assetId: asset.id, tags });
await this.jobRepository.queue({ name: JobName.SEARCH_INDEX_ASSET, data: { ids: [asset.id] } });
const assets = force
? await this.assetRepository.getAll()
: await this.assetRepository.getWithout(WithoutProperty.OBJECT_TAGS);
for (const asset of assets) {
await this.jobRepository.queue({ name: JobName.CLASSIFY_IMAGE, data: { asset } });
await this.jobRepository.queue({ name: JobName.DETECT_OBJECTS, data: { asset } });
}
} catch (error: any) {
this.logger.error(`Unable to run image tagging pipeline: ${asset.id}`, error?.stack);
this.logger.error(`Unable to queue object tagging`, error?.stack);
}
}
@@ -50,6 +49,38 @@ export class SmartInfoService {
}
}
async handleClassifyImage(data: IAssetJob) {
const { asset } = data;
if (!MACHINE_LEARNING_ENABLED || !asset.resizePath) {
return;
}
try {
const tags = await this.machineLearning.classifyImage({ thumbnailPath: asset.resizePath });
if (tags.length > 0) {
await this.repository.upsert({ assetId: asset.id, tags });
await this.jobRepository.queue({ name: JobName.SEARCH_INDEX_ASSET, data: { ids: [asset.id] } });
}
} catch (error: any) {
this.logger.error(`Unable to run image tagging pipeline: ${asset.id}`, error?.stack);
}
}
async handleQueueEncodeClip({ force }: IBaseJob) {
try {
const assets = force
? await this.assetRepository.getAll()
: await this.assetRepository.getWithout(WithoutProperty.CLIP_ENCODING);
for (const asset of assets) {
await this.jobRepository.queue({ name: JobName.ENCODE_CLIP, data: { asset } });
}
} catch (error: any) {
this.logger.error(`Unable to queue clip encoding`, error?.stack);
}
}
async handleEncodeClip(data: IAssetJob) {
const { asset } = data;