mirror of
https://github.com/labring/FastGPT.git
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feat: vector store support oceanbase (#4356)
* feat: vector store support oceanbase * chore(config): Rename pgHNSWEfSearch to hnswEfSearch to work for pg and oceanbase both
This commit is contained in:
@@ -7,7 +7,7 @@ data:
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"vectorMaxProcess": 15,
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"qaMaxProcess": 15,
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"vlmMaxProcess": 15,
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"pgHNSWEfSearch": 100
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"hnswEfSearch": 100
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},
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"llmModels": [
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{
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@@ -25,7 +25,7 @@ weight: 707
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"qaMaxProcess": 15, // 问答拆分线程数量
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"vlmMaxProcess": 15, // 图片理解模型最大处理进程
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"tokenWorkers": 50, // Token 计算线程保持数,会持续占用内存,不能设置太大。
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"pgHNSWEfSearch": 100, // 向量搜索参数。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
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"hnswEfSearch": 100, // 向量搜索参数,仅对 PG 和 OB 生效。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
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"customPdfParse": { // 4.9.0 新增配置
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"url": "", // 自定义 PDF 解析服务地址
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"key": "", // 自定义 PDF 解析服务密钥
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@@ -71,7 +71,7 @@ Mongo 数据库需要注意,需要注意在连接地址中增加 `directConnec
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- `vectorMaxProcess`: 向量生成最大进程,根据数据库和 key 的并发数来决定,通常单个 120 号,2c4g 服务器设置 10~15。
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- `qaMaxProcess`: QA 生成最大进程
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- `vlmMaxProcess`: 图片理解模型最大进程
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- `pgHNSWEfSearch`: PostgreSQL vector 索引参数,越大搜索精度越高但是速度越慢,具体可看 pgvector 官方说明。
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- `hnswEfSearch`: 向量搜索参数,仅对 PG 和 OB 生效,越大搜索精度越高但是速度越慢。
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### 5. 运行
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@@ -302,7 +302,7 @@ OneAPI 的语言识别接口,无法正确的识别其他模型(会始终识
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"vectorMaxProcess": 15, // 向量处理线程数量
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"qaMaxProcess": 15, // 问答拆分线程数量
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"tokenWorkers": 50, // Token 计算线程保持数,会持续占用内存,不能设置太大。
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"pgHNSWEfSearch": 100 // 向量搜索参数。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
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"hnswEfSearch": 100 // 向量搜索参数,仅对 PG 和 OB 生效。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
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},
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"llmModels": [
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{
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@@ -112,7 +112,7 @@ export type SystemEnvType = {
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vectorMaxProcess: number;
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qaMaxProcess: number;
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vlmMaxProcess: number;
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pgHNSWEfSearch: number;
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hnswEfSearch: number;
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tokenWorkers: number; // token count max worker
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oneapiUrl?: string;
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@@ -2,5 +2,6 @@ export const DatasetVectorDbName = 'fastgpt';
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export const DatasetVectorTableName = 'modeldata';
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export const PG_ADDRESS = process.env.PG_URL;
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export const OCEANBASE_ADDRESS = process.env.OCEANBASE_URL;
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export const MILVUS_ADDRESS = process.env.MILVUS_ADDRESS;
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export const MILVUS_TOKEN = process.env.MILVUS_TOKEN;
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@@ -1,13 +1,15 @@
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/* vector crud */
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import { PgVectorCtrl } from './pg/class';
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import { ObVectorCtrl } from './oceanbase/class';
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import { getVectorsByText } from '../../core/ai/embedding';
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import { InsertVectorProps } from './controller.d';
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import { EmbeddingModelItemType } from '@fastgpt/global/core/ai/model.d';
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import { MILVUS_ADDRESS, PG_ADDRESS } from './constants';
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import { MILVUS_ADDRESS, PG_ADDRESS, OCEANBASE_ADDRESS } from './constants';
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import { MilvusCtrl } from './milvus/class';
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const getVectorObj = () => {
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if (PG_ADDRESS) return new PgVectorCtrl();
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if (OCEANBASE_ADDRESS) return new ObVectorCtrl();
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if (MILVUS_ADDRESS) return new MilvusCtrl();
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return new PgVectorCtrl();
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254
packages/service/common/vectorStore/oceanbase/class.ts
Normal file
254
packages/service/common/vectorStore/oceanbase/class.ts
Normal file
@@ -0,0 +1,254 @@
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/* oceanbase 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 { ObClient } from './index';
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import { RowDataPacket, ResultSetHeader } from 'mysql2/promise';
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import {
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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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import { addLog } from '../../system/log';
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export class ObVectorCtrl {
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constructor() {}
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init = async () => {
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try {
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await ObClient.query(`
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CREATE TABLE IF NOT EXISTS ${DatasetVectorTableName} (
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id BIGINT AUTO_INCREMENT 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 ObClient.query(
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`CREATE VECTOR INDEX IF NOT EXISTS vector_index ON ${DatasetVectorTableName}(vector) WITH (distance=inner_product, type=hnsw, m=32, ef_construction=128);`
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);
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await ObClient.query(
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`CREATE INDEX IF NOT EXISTS team_dataset_collection_index ON ${DatasetVectorTableName}(team_id, dataset_id, collection_id);`
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);
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await ObClient.query(
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`CREATE INDEX IF NOT EXISTS create_time_index ON ${DatasetVectorTableName}(createtime);`
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);
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addLog.info('init oceanbase successful');
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} catch (error) {
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addLog.error('init oceanbase error', error);
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}
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};
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insert = async (props: InsertVectorControllerProps): Promise<{ insertId: string }> => {
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const { teamId, datasetId, collectionId, vector, retry = 3 } = props;
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try {
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const { rowCount, rows } = await ObClient.insert(DatasetVectorTableName, {
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values: [
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[
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{ key: 'vector', value: `[${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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if (rowCount === 0) {
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return Promise.reject('insertDatasetData: no insert');
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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 ObClient.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 {
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teamId,
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datasetIds,
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vector,
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limit,
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forbidCollectionIdList,
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filterCollectionIdList,
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retry = 2
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} = props;
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// Get forbid collection
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const formatForbidCollectionIdList = (() => {
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if (!filterCollectionIdList) return forbidCollectionIdList;
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const list = forbidCollectionIdList
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.map((id) => String(id))
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.filter((id) => !filterCollectionIdList.includes(id));
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return list;
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})();
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const forbidCollectionSql =
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formatForbidCollectionIdList.length > 0
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? `AND collection_id NOT IN (${formatForbidCollectionIdList.map((id) => `'${id}'`).join(',')})`
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: '';
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// Filter by collectionId
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const formatFilterCollectionId = (() => {
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if (!filterCollectionIdList) return;
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return filterCollectionIdList
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.map((id) => String(id))
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.filter((id) => !forbidCollectionIdList.includes(id));
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})();
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const filterCollectionIdSql = formatFilterCollectionId
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? `AND collection_id IN (${formatFilterCollectionId.map((id) => `'${id}'`).join(',')})`
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: '';
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// Empty data
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if (formatFilterCollectionId && formatFilterCollectionId.length === 0) {
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return { results: [] };
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}
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try {
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const rows = await ObClient.query<
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({
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id: string;
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collection_id: string;
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score: number;
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} & RowDataPacket)[][]
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>(
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`BEGIN;
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SET ob_hnsw_ef_search = ${global.systemEnv?.hnswEfSearch || 100};
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SELECT id, collection_id, inner_product(vector, [${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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${filterCollectionIdSql}
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${forbidCollectionSql}
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ORDER BY score desc APPROXIMATE LIMIT ${limit};
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COMMIT;`
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).then(([rows]) => rows[2]);
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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
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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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getVectorDataByTime = async (start: Date, end: Date) => {
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const rows = await ObClient.query<
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({
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id: string;
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team_id: string;
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dataset_id: string;
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} & RowDataPacket)[]
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>(
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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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).then(([rows]) => rows);
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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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getVectorCountByTeamId = async (teamId: string) => {
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const total = await ObClient.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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getVectorCountByDatasetId = async (teamId: string, datasetId: string) => {
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const total = await ObClient.count(DatasetVectorTableName, {
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where: [['team_id', String(teamId)], 'and', ['dataset_id', String(datasetId)]]
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});
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return total;
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};
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getVectorCountByCollectionId = async (
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teamId: string,
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datasetId: string,
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collectionId: string
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) => {
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const total = await ObClient.count(DatasetVectorTableName, {
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where: [
|
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['team_id', String(teamId)],
|
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'and',
|
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['dataset_id', String(datasetId)],
|
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'and',
|
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['collection_id', String(collectionId)]
|
||||
]
|
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});
|
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|
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return total;
|
||||
};
|
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}
|
173
packages/service/common/vectorStore/oceanbase/index.ts
Normal file
173
packages/service/common/vectorStore/oceanbase/index.ts
Normal file
@@ -0,0 +1,173 @@
|
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import mysql, { Pool, QueryResult, RowDataPacket, ResultSetHeader } from 'mysql2/promise';
|
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import { addLog } from '../../system/log';
|
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import { OCEANBASE_ADDRESS } from '../constants';
|
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|
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export const getClient = async (): Promise<Pool> => {
|
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if (!OCEANBASE_ADDRESS) {
|
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return Promise.reject('OCEANBASE_ADDRESS is not set');
|
||||
}
|
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|
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if (global.obClient) {
|
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return global.obClient;
|
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}
|
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|
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global.obClient = mysql.createPool({
|
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uri: OCEANBASE_ADDRESS,
|
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waitForConnections: true,
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connectionLimit: Number(process.env.DB_MAX_LINK || 20),
|
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connectTimeout: 20000,
|
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idleTimeout: 60000,
|
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queueLimit: 0,
|
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enableKeepAlive: true,
|
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keepAliveInitialDelay: 0
|
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});
|
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|
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addLog.info(`oceanbase connected`);
|
||||
|
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return global.obClient;
|
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};
|
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|
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type WhereProps = (string | [string, string | number])[];
|
||||
type GetProps = {
|
||||
fields?: string[];
|
||||
where?: WhereProps;
|
||||
order?: { field: string; mode: 'DESC' | 'ASC' | string }[];
|
||||
limit?: number;
|
||||
offset?: number;
|
||||
};
|
||||
|
||||
type DeleteProps = {
|
||||
where: WhereProps;
|
||||
};
|
||||
|
||||
type ValuesProps = { key: string; value?: string | number }[];
|
||||
type UpdateProps = {
|
||||
values: ValuesProps;
|
||||
where: WhereProps;
|
||||
};
|
||||
type InsertProps = {
|
||||
values: ValuesProps[];
|
||||
};
|
||||
|
||||
class ObClass {
|
||||
private getWhereStr(where?: WhereProps) {
|
||||
return where
|
||||
? `WHERE ${where
|
||||
.map((item) => {
|
||||
if (typeof item === 'string') {
|
||||
return item;
|
||||
}
|
||||
const val = typeof item[1] === 'number' ? item[1] : `'${String(item[1])}'`;
|
||||
return `${item[0]}=${val}`;
|
||||
})
|
||||
.join(' ')}`
|
||||
: '';
|
||||
}
|
||||
private getUpdateValStr(values: ValuesProps) {
|
||||
return values
|
||||
.map((item) => {
|
||||
const val =
|
||||
typeof item.value === 'number'
|
||||
? item.value
|
||||
: `'${String(item.value).replace(/\'/g, '"')}'`;
|
||||
|
||||
return `${item.key}=${val}`;
|
||||
})
|
||||
.join(',');
|
||||
}
|
||||
private getInsertValStr(values: ValuesProps[]) {
|
||||
return values
|
||||
.map(
|
||||
(items) =>
|
||||
`(${items
|
||||
.map((item) =>
|
||||
typeof item.value === 'number'
|
||||
? item.value
|
||||
: `'${String(item.value).replace(/\'/g, '"')}'`
|
||||
)
|
||||
.join(',')})`
|
||||
)
|
||||
.join(',');
|
||||
}
|
||||
async select<T extends QueryResult = any>(table: string, props: GetProps) {
|
||||
const sql = `SELECT ${
|
||||
!props.fields || props.fields?.length === 0 ? '*' : props.fields?.join(',')
|
||||
}
|
||||
FROM ${table}
|
||||
${this.getWhereStr(props.where)}
|
||||
${
|
||||
props.order
|
||||
? `ORDER BY ${props.order.map((item) => `${item.field} ${item.mode}`).join(',')}`
|
||||
: ''
|
||||
}
|
||||
LIMIT ${props.limit || 10} OFFSET ${props.offset || 0}
|
||||
`;
|
||||
|
||||
const client = await getClient();
|
||||
return client.query<T>(sql);
|
||||
}
|
||||
async count(table: string, props: GetProps) {
|
||||
const sql = `SELECT COUNT(${props?.fields?.[0] || '*'})
|
||||
FROM ${table}
|
||||
${this.getWhereStr(props.where)}
|
||||
`;
|
||||
|
||||
const client = await getClient();
|
||||
return client
|
||||
.query<({ count: number } & RowDataPacket)[]>(sql)
|
||||
.then(([rows]) => Number(rows[0]?.count || 0));
|
||||
}
|
||||
async delete(table: string, props: DeleteProps) {
|
||||
const sql = `DELETE FROM ${table} ${this.getWhereStr(props.where)}`;
|
||||
const client = await getClient();
|
||||
return client.query(sql);
|
||||
}
|
||||
async update(table: string, props: UpdateProps) {
|
||||
if (props.values.length === 0) {
|
||||
return {
|
||||
rowCount: 0
|
||||
};
|
||||
}
|
||||
|
||||
const sql = `UPDATE ${table} SET ${this.getUpdateValStr(props.values)} ${this.getWhereStr(
|
||||
props.where
|
||||
)}`;
|
||||
const client = await getClient();
|
||||
return client.query(sql);
|
||||
}
|
||||
async insert(table: string, props: InsertProps) {
|
||||
if (props.values.length === 0) {
|
||||
return {
|
||||
rowCount: 0,
|
||||
rows: []
|
||||
};
|
||||
}
|
||||
|
||||
const fields = props.values[0].map((item) => item.key).join(',');
|
||||
const sql = `INSERT INTO ${table} (${fields}) VALUES ${this.getInsertValStr(props.values)}`;
|
||||
|
||||
const client = await getClient();
|
||||
return client.query<ResultSetHeader>(sql).then(([result]) => {
|
||||
return {
|
||||
rowCount: result.affectedRows,
|
||||
rows: [{ id: String(result.insertId) }]
|
||||
};
|
||||
});
|
||||
}
|
||||
async query<T extends QueryResult = any>(sql: string) {
|
||||
const client = await getClient();
|
||||
const start = Date.now();
|
||||
return client.query<T>(sql).then((res) => {
|
||||
const time = Date.now() - start;
|
||||
|
||||
if (time > 300) {
|
||||
addLog.warn(`oceanbase query time: ${time}ms, sql: ${sql}`);
|
||||
}
|
||||
|
||||
return res;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
export const ObClient = new ObClass();
|
||||
export const Oceanbase = global.obClient;
|
@@ -187,7 +187,7 @@ export class PgVectorCtrl {
|
||||
try {
|
||||
const results: any = await PgClient.query(
|
||||
`BEGIN;
|
||||
SET LOCAL hnsw.ef_search = ${global.systemEnv?.pgHNSWEfSearch || 100};
|
||||
SET LOCAL hnsw.ef_search = ${global.systemEnv?.hnswEfSearch || 100};
|
||||
SET LOCAL hnsw.iterative_scan = relaxed_order;
|
||||
WITH relaxed_results AS MATERIALIZED (
|
||||
select id, collection_id, vector <#> '[${vector}]' AS score
|
||||
|
@@ -1,8 +1,10 @@
|
||||
import type { Pool } from 'pg';
|
||||
import { Pool as MysqlPool } from 'mysql2/promise';
|
||||
import { MilvusClient } from '@zilliz/milvus2-sdk-node';
|
||||
|
||||
declare global {
|
||||
var pgClient: Pool | null;
|
||||
var obClient: MysqlPool | null;
|
||||
var milvusClient: MilvusClient | null;
|
||||
}
|
||||
|
||||
|
@@ -26,6 +26,7 @@
|
||||
"mammoth": "^1.6.0",
|
||||
"mongoose": "^8.10.1",
|
||||
"multer": "1.4.5-lts.1",
|
||||
"mysql2": "^3.11.3",
|
||||
"next": "14.2.25",
|
||||
"nextjs-cors": "^2.2.0",
|
||||
"node-cron": "^3.0.3",
|
||||
|
9
pnpm-lock.yaml
generated
9
pnpm-lock.yaml
generated
@@ -220,6 +220,9 @@ importers:
|
||||
multer:
|
||||
specifier: 1.4.5-lts.1
|
||||
version: 1.4.5-lts.1
|
||||
mysql2:
|
||||
specifier: ^3.11.3
|
||||
version: 3.13.0
|
||||
next:
|
||||
specifier: 14.2.25
|
||||
version: 14.2.25(@babel/core@7.26.10)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.85.1)
|
||||
@@ -14607,7 +14610,7 @@ snapshots:
|
||||
eslint: 8.56.0
|
||||
eslint-import-resolver-node: 0.3.9
|
||||
eslint-import-resolver-typescript: 3.9.0(eslint-plugin-import@2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint@8.56.0))(eslint@8.56.0)
|
||||
eslint-plugin-import: 2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint-import-resolver-typescript@3.9.0(eslint-plugin-import@2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint@8.56.0))(eslint@8.56.0))(eslint@8.56.0)
|
||||
eslint-plugin-import: 2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint-import-resolver-typescript@3.9.0)(eslint@8.56.0)
|
||||
eslint-plugin-jsx-a11y: 6.10.2(eslint@8.56.0)
|
||||
eslint-plugin-react: 7.37.4(eslint@8.56.0)
|
||||
eslint-plugin-react-hooks: 5.0.0-canary-7118f5dd7-20230705(eslint@8.56.0)
|
||||
@@ -14637,7 +14640,7 @@ snapshots:
|
||||
stable-hash: 0.0.5
|
||||
tinyglobby: 0.2.12
|
||||
optionalDependencies:
|
||||
eslint-plugin-import: 2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint-import-resolver-typescript@3.9.0(eslint-plugin-import@2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint@8.56.0))(eslint@8.56.0))(eslint@8.56.0)
|
||||
eslint-plugin-import: 2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint-import-resolver-typescript@3.9.0)(eslint@8.56.0)
|
||||
transitivePeerDependencies:
|
||||
- supports-color
|
||||
|
||||
@@ -14652,7 +14655,7 @@ snapshots:
|
||||
transitivePeerDependencies:
|
||||
- supports-color
|
||||
|
||||
eslint-plugin-import@2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint-import-resolver-typescript@3.9.0(eslint-plugin-import@2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint@8.56.0))(eslint@8.56.0))(eslint@8.56.0):
|
||||
eslint-plugin-import@2.31.0(@typescript-eslint/parser@6.21.0(eslint@8.56.0)(typescript@5.8.2))(eslint-import-resolver-typescript@3.9.0)(eslint@8.56.0):
|
||||
dependencies:
|
||||
'@rtsao/scc': 1.1.0
|
||||
array-includes: 3.1.8
|
||||
|
@@ -23,9 +23,11 @@ MULTIPLE_DATA_TO_BASE64=true
|
||||
# mongo 数据库连接参数,本地开发连接远程数据库时,可能需要增加 directConnection=true 参数,才能连接上。
|
||||
MONGODB_URI=mongodb://username:password@0.0.0.0:27017/fastgpt?authSource=admin
|
||||
|
||||
# 向量库优先级: pg > milvus
|
||||
# 向量库优先级: pg > oceanbase > milvus
|
||||
# PG 向量库连接参数
|
||||
PG_URL=postgresql://username:password@host:port/postgres
|
||||
# OceanBase 向量库连接参数
|
||||
OCEANBASE_URL=
|
||||
# milvus 向量库连接参数
|
||||
MILVUS_ADDRESS=
|
||||
MILVUS_TOKEN=
|
||||
|
@@ -8,7 +8,7 @@
|
||||
"qaMaxProcess": 10, // 问答拆分线程数量
|
||||
"vlmMaxProcess": 10, // 图片理解模型最大处理进程
|
||||
"tokenWorkers": 30, // Token 计算线程保持数,会持续占用内存,不能设置太大。
|
||||
"pgHNSWEfSearch": 100, // 向量搜索参数。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
|
||||
"hnswEfSearch": 100, // 向量搜索参数,仅对 PG 和 OB 生效。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
|
||||
"customPdfParse": {
|
||||
"url": "", // 自定义 PDF 解析服务地址
|
||||
"key": "", // 自定义 PDF 解析服务密钥
|
||||
|
@@ -7,7 +7,7 @@
|
||||
"vectorMaxProcess": 15, // 向量处理线程数量
|
||||
"qaMaxProcess": 15, // 问答拆分线程数量
|
||||
"tokenWorkers": 30, // Token 计算线程保持数,会持续占用内存,不能设置太大。
|
||||
"pgHNSWEfSearch": 100 // 向量搜索参数。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
|
||||
"hnswEfSearch": 100 // 向量搜索参数,仅对 PG 和 OB 生效。越大,搜索越精确,但是速度越慢。设置为100,有99%+精度。
|
||||
},
|
||||
"llmModels": [
|
||||
{
|
||||
|
Reference in New Issue
Block a user