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4.8.3 (#1654)
* Milvus (#1644) * feat: support regx * 4.8.3 test and fix (#1648) * perf: version tip * feat: sandbox support log * fix: debug component render * fix: share page header * fix: input guide auth * fix: iso viewport * remove file * fix: route url * feat: add debug timout * perf: reference select support trigger * perf: session code * perf: theme * perf: load milvus
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@@ -1,18 +1,180 @@
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/* pg vector crud */
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import { DatasetVectorTableName } from '../constants';
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import { delay } from '@fastgpt/global/common/system/utils';
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import { PgClient, connectPg } from './index';
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import { PgSearchRawType } from '@fastgpt/global/core/dataset/api';
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import {
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initPg,
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insertDatasetDataVector,
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deleteDatasetDataVector,
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embeddingRecall,
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getVectorDataByTime,
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getVectorCountByTeamId
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} from './controller';
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DelDatasetVectorCtrlProps,
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EmbeddingRecallCtrlProps,
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EmbeddingRecallResponse,
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InsertVectorControllerProps
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} from '../controller.d';
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import dayjs from 'dayjs';
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export class PgVector {
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export class PgVectorCtrl {
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constructor() {}
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init = initPg;
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insert = insertDatasetDataVector;
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delete = deleteDatasetDataVector;
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recall = embeddingRecall;
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getVectorCountByTeamId = getVectorCountByTeamId;
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getVectorDataByTime = getVectorDataByTime;
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init = async () => {
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try {
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await connectPg();
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await PgClient.query(`
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CREATE EXTENSION IF NOT EXISTS vector;
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CREATE TABLE IF NOT EXISTS ${DatasetVectorTableName} (
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id BIGSERIAL PRIMARY KEY,
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vector VECTOR(1536) NOT NULL,
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team_id VARCHAR(50) NOT NULL,
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dataset_id VARCHAR(50) NOT NULL,
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collection_id VARCHAR(50) NOT NULL,
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createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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);
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`);
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await PgClient.query(
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`CREATE INDEX CONCURRENTLY IF NOT EXISTS vector_index ON ${DatasetVectorTableName} USING hnsw (vector vector_ip_ops) WITH (m = 32, ef_construction = 128);`
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);
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await PgClient.query(
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`CREATE INDEX CONCURRENTLY IF NOT EXISTS team_dataset_collection_index ON ${DatasetVectorTableName} USING btree(team_id, dataset_id, collection_id);`
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);
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await PgClient.query(
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`CREATE INDEX CONCURRENTLY IF NOT EXISTS create_time_index ON ${DatasetVectorTableName} USING btree(createtime);`
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);
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console.log('init pg successful');
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} catch (error) {
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console.log('init pg error', error);
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}
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};
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insert = async (props: InsertVectorControllerProps): Promise<{ insertId: string }> => {
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const { teamId, datasetId, collectionId, vector, retry = 3 } = props;
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try {
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const { rows } = await PgClient.insert(DatasetVectorTableName, {
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values: [
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[
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{ key: 'vector', value: `[${vector}]` },
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{ key: 'team_id', value: String(teamId) },
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{ key: 'dataset_id', value: String(datasetId) },
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{ key: 'collection_id', value: String(collectionId) }
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]
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]
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});
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return {
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insertId: rows[0].id
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};
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} catch (error) {
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if (retry <= 0) {
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return Promise.reject(error);
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}
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await delay(500);
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return this.insert({
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...props,
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retry: retry - 1
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});
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}
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};
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delete = async (props: DelDatasetVectorCtrlProps): Promise<any> => {
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const { teamId, retry = 2 } = props;
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const teamIdWhere = `team_id='${String(teamId)}' AND`;
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const where = await (() => {
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if ('id' in props && props.id) return `${teamIdWhere} id=${props.id}`;
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if ('datasetIds' in props && props.datasetIds) {
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const datasetIdWhere = `dataset_id IN (${props.datasetIds
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.map((id) => `'${String(id)}'`)
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.join(',')})`;
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if ('collectionIds' in props && props.collectionIds) {
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return `${teamIdWhere} ${datasetIdWhere} AND collection_id IN (${props.collectionIds
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.map((id) => `'${String(id)}'`)
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.join(',')})`;
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}
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return `${teamIdWhere} ${datasetIdWhere}`;
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}
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if ('idList' in props && Array.isArray(props.idList)) {
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if (props.idList.length === 0) return;
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return `${teamIdWhere} id IN (${props.idList.map((id) => String(id)).join(',')})`;
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}
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return Promise.reject('deleteDatasetData: no where');
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})();
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if (!where) return;
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try {
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await PgClient.delete(DatasetVectorTableName, {
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where: [where]
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});
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} catch (error) {
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if (retry <= 0) {
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return Promise.reject(error);
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}
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await delay(500);
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return this.delete({
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...props,
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retry: retry - 1
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});
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}
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};
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embRecall = async (props: EmbeddingRecallCtrlProps): Promise<EmbeddingRecallResponse> => {
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const { teamId, datasetIds, vector, limit, retry = 2 } = props;
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try {
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const results: any = await PgClient.query(
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`
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BEGIN;
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SET LOCAL hnsw.ef_search = ${global.systemEnv?.pgHNSWEfSearch || 100};
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select id, collection_id, vector <#> '[${vector}]' AS score
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from ${DatasetVectorTableName}
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where team_id='${teamId}'
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AND dataset_id IN (${datasetIds.map((id) => `'${String(id)}'`).join(',')})
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order by score limit ${limit};
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COMMIT;`
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);
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const rows = results?.[2]?.rows as PgSearchRawType[];
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return {
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results: rows.map((item) => ({
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id: String(item.id),
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collectionId: item.collection_id,
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score: item.score * -1
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}))
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};
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} catch (error) {
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if (retry <= 0) {
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return Promise.reject(error);
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}
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return this.embRecall({
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...props,
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retry: retry - 1
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});
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}
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};
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getVectorCountByTeamId = async (teamId: string) => {
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const total = await PgClient.count(DatasetVectorTableName, {
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where: [['team_id', String(teamId)]]
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});
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return total;
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};
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getVectorDataByTime = async (start: Date, end: Date) => {
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const { rows } = await PgClient.query<{
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id: string;
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team_id: string;
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dataset_id: string;
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}>(`SELECT id, team_id, dataset_id
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FROM ${DatasetVectorTableName}
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WHERE createtime BETWEEN '${dayjs(start).format('YYYY-MM-DD HH:mm:ss')}' AND '${dayjs(
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end
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).format('YYYY-MM-DD HH:mm:ss')}';
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`);
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return rows.map((item) => ({
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id: String(item.id),
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teamId: item.team_id,
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datasetId: item.dataset_id
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}));
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};
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}
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