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feat(server): separate face search relation (#10371)

Browse source 
* wip

* various fixes

* new migration

* fix test

* add face search entity, update sql

* update e2e

* set storage to external
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Mert 2024-06-16 15:25:27 -04:00 • committed by GitHub
parent 0fe152b1ef
commit 6b1b5054f8
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12 changed files with 130 additions and 47 deletions
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54
server/src/migrations/1718486162779-AddFaceSearchRelation.ts Normal file
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import { getVectorExtension } from 'src/database.config';
import { DatabaseExtension } from 'src/interfaces/database.interface';
import { MigrationInterface, QueryRunner } from 'typeorm';
export class AddFaceSearchRelation1718486162779 implements MigrationInterface {
public async up(queryRunner: QueryRunner): Promise<void> {
if (getVectorExtension() === DatabaseExtension.VECTORS) {
await queryRunner.query(`SET search_path TO "$user", public, vectors`);
await queryRunner.query(`SET vectors.pgvector_compatibility=on`);
}
await queryRunner.query(`
CREATE TABLE face_search (
"faceId" uuid PRIMARY KEY REFERENCES asset_faces(id) ON DELETE CASCADE,
embedding vector(512) NOT NULL )`);
await queryRunner.query(`ALTER TABLE face_search ALTER COLUMN embedding SET STORAGE EXTERNAL`);
await queryRunner.query(`ALTER TABLE smart_search ALTER COLUMN embedding SET STORAGE EXTERNAL`);
await queryRunner.query(`
INSERT INTO face_search("faceId", embedding)
SELECT id, embedding
FROM asset_faces faces`);
await queryRunner.query(`ALTER TABLE asset_faces DROP COLUMN "embedding"`);
await queryRunner.query(`
CREATE INDEX face_index ON face_search
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
}
public async down(queryRunner: QueryRunner): Promise<void> {
if (getVectorExtension() === DatabaseExtension.VECTORS) {
await queryRunner.query(`SET search_path TO "$user", public, vectors`);
await queryRunner.query(`SET vectors.pgvector_compatibility=on`);
}
await queryRunner.query(`ALTER TABLE asset_faces ADD COLUMN "embedding" vector(512)`);
await queryRunner.query(`ALTER TABLE face_search ALTER COLUMN embedding SET STORAGE DEFAULT`);
await queryRunner.query(`ALTER TABLE smart_search ALTER COLUMN embedding SET STORAGE DEFAULT`);
await queryRunner.query(`
UPDATE asset_faces
SET embedding = fs.embedding
FROM face_search fs
WHERE id = fs."faceId"`);
await queryRunner.query(`DROP TABLE face_search`);
await queryRunner.query(`
CREATE INDEX face_index ON asset_faces
USING hnsw (embedding vector_cosine_ops)
WITH (ef_construction = 300, m = 16)`);
}
}