f206cb9403
* chore(server): simplify search face query and better clustering * update sql * Use correct syntax for utilizing the index * Update sql
180 lines
6.5 KiB
TypeScript
180 lines
6.5 KiB
TypeScript
import { Embedding, EmbeddingSearch, ISmartInfoRepository } from '@app/domain';
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import { getCLIPModelInfo } from '@app/domain/smart-info/smart-info.constant';
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import { DatabaseLock, RequireLock, asyncLock } from '@app/infra';
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import { AssetEntity, AssetFaceEntity, SmartInfoEntity, SmartSearchEntity } from '@app/infra/entities';
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import { Injectable, Logger } from '@nestjs/common';
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import { InjectRepository } from '@nestjs/typeorm';
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import { Repository } from 'typeorm';
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import { DummyValue, GenerateSql } from '../infra.util';
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import { asVector, isValidInteger } from '../infra.utils';
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@Injectable()
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export class SmartInfoRepository implements ISmartInfoRepository {
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private logger = new Logger(SmartInfoRepository.name);
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private faceColumns: string[];
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constructor(
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@InjectRepository(SmartInfoEntity) private repository: Repository<SmartInfoEntity>,
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@InjectRepository(AssetEntity) private assetRepository: Repository<AssetEntity>,
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@InjectRepository(AssetFaceEntity) private assetFaceRepository: Repository<AssetFaceEntity>,
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@InjectRepository(SmartSearchEntity) private smartSearchRepository: Repository<SmartSearchEntity>,
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) {
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this.faceColumns = this.assetFaceRepository.manager.connection
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.getMetadata(AssetFaceEntity)
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.ownColumns.map((column) => column.propertyName)
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.filter((propertyName) => propertyName !== 'embedding');
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}
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async init(modelName: string): Promise<void> {
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const { dimSize } = getCLIPModelInfo(modelName);
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if (dimSize == null) {
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throw new Error(`Invalid CLIP model name: ${modelName}`);
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}
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const curDimSize = await this.getDimSize();
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this.logger.verbose(`Current database CLIP dimension size is ${curDimSize}`);
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if (dimSize != curDimSize) {
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this.logger.log(`Dimension size of model ${modelName} is ${dimSize}, but database expects ${curDimSize}.`);
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await this.updateDimSize(dimSize);
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}
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}
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@GenerateSql({
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params: [{ ownerId: DummyValue.UUID, embedding: Array.from({ length: 512 }, Math.random), numResults: 100 }],
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})
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async searchCLIP({ ownerId, embedding, numResults }: EmbeddingSearch): Promise<AssetEntity[]> {
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if (!isValidInteger(numResults, { min: 1 })) {
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throw new Error(`Invalid value for 'numResults': ${numResults}`);
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}
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let results: AssetEntity[] = [];
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await this.assetRepository.manager.transaction(async (manager) => {
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await manager.query(`SET LOCAL vectors.k = '${numResults}'`);
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results = await manager
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.createQueryBuilder(AssetEntity, 'a')
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.innerJoin('a.smartSearch', 's')
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.where('a.ownerId = :ownerId')
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.leftJoinAndSelect('a.exifInfo', 'e')
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.orderBy('s.embedding <=> :embedding')
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.setParameters({ ownerId, embedding: asVector(embedding) })
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.limit(numResults)
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.getMany();
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});
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return results;
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}
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@GenerateSql({
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params: [
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{
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ownerId: DummyValue.UUID,
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embedding: Array.from({ length: 512 }, Math.random),
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numResults: 100,
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maxDistance: 0.6,
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},
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],
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})
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async searchFaces({ ownerId, embedding, numResults, maxDistance }: EmbeddingSearch): Promise<AssetFaceEntity[]> {
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if (!isValidInteger(numResults, { min: 1 })) {
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throw new Error(`Invalid value for 'numResults': ${numResults}`);
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}
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let results: AssetFaceEntity[] = [];
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await this.assetRepository.manager.transaction(async (manager) => {
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await manager.query(`SET LOCAL vectors.k = '${numResults}'`);
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const cte = manager
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.createQueryBuilder(AssetFaceEntity, 'faces')
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.select('1 + (faces.embedding <=> :embedding)', 'distance')
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.innerJoin('faces.asset', 'asset')
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.where('asset.ownerId = :ownerId')
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.orderBy('1 + (faces.embedding <=> :embedding)')
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.setParameters({ ownerId, embedding: asVector(embedding) })
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.limit(numResults);
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this.faceColumns.forEach((col) => cte.addSelect(`faces.${col}`, col));
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results = await manager
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.createQueryBuilder()
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.select('res.*')
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.addCommonTableExpression(cte, 'cte')
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.from('cte', 'res')
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.where('res.distance <= :maxDistance', { maxDistance })
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.getRawMany();
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});
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return this.assetFaceRepository.create(results);
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}
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async upsert(smartInfo: Partial<SmartInfoEntity>, embedding?: Embedding): Promise<void> {
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await this.repository.upsert(smartInfo, { conflictPaths: ['assetId'] });
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if (!smartInfo.assetId || !embedding) {
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return;
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}
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await this.upsertEmbedding(smartInfo.assetId, embedding);
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}
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private async upsertEmbedding(assetId: string, embedding: number[]): Promise<void> {
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if (asyncLock.isBusy(DatabaseLock[DatabaseLock.CLIPDimSize])) {
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this.logger.verbose(`Waiting for CLIP dimension size to be updated`);
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await asyncLock.acquire(DatabaseLock[DatabaseLock.CLIPDimSize], () => {});
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}
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await this.smartSearchRepository.upsert(
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{ assetId, embedding: () => asVector(embedding, true) },
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{ conflictPaths: ['assetId'] },
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);
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}
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@RequireLock(DatabaseLock.CLIPDimSize)
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private async updateDimSize(dimSize: number): Promise<void> {
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if (!isValidInteger(dimSize, { min: 1, max: 2 ** 16 })) {
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throw new Error(`Invalid CLIP dimension size: ${dimSize}`);
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}
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const curDimSize = await this.getDimSize();
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if (curDimSize === dimSize) {
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return;
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}
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this.logger.log(`Updating database CLIP dimension size to ${dimSize}.`);
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await this.smartSearchRepository.manager.transaction(async (manager) => {
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await manager.query(`DROP TABLE smart_search`);
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await manager.query(`
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CREATE TABLE smart_search (
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"assetId" uuid PRIMARY KEY REFERENCES assets(id) ON DELETE CASCADE,
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embedding vector(${dimSize}) NOT NULL )`);
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await manager.query(`
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CREATE INDEX clip_index ON smart_search
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USING vectors (embedding cosine_ops) WITH (options = $$
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[indexing.hnsw]
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m = 16
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ef_construction = 300
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$$)`);
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});
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this.logger.log(`Successfully updated database CLIP dimension size from ${curDimSize} to ${dimSize}.`);
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}
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private async getDimSize(): Promise<number> {
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const res = await this.smartSearchRepository.manager.query(`
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SELECT atttypmod as dimsize
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FROM pg_attribute f
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JOIN pg_class c ON c.oid = f.attrelid
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WHERE c.relkind = 'r'::char
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AND f.attnum > 0
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AND c.relname = 'smart_search'
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AND f.attname = 'embedding'`);
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const dimSize = res[0]['dimsize'];
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if (!isValidInteger(dimSize, { min: 1, max: 2 ** 16 })) {
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throw new Error(`Could not retrieve CLIP dimension size`);
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}
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return dimSize;
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}
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}
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