mirror of
https://github.com/labring/FastGPT.git
synced 2025-10-14 23:22:22 +00:00
support openGauss vector store (#4819)
This commit is contained in:
218
deploy/docker/docker-compose-opengauss.yml
Normal file
218
deploy/docker/docker-compose-opengauss.yml
Normal file
@@ -0,0 +1,218 @@
|
||||
# 数据库的默认账号和密码仅首次运行时设置有效
|
||||
# 如果修改了账号密码,记得改数据库和项目连接参数,别只改一处~
|
||||
# 该配置文件只是给快速启动,测试使用。正式使用,记得务必修改账号密码,以及调整合适的知识库参数,共享内存等。
|
||||
# 如何无法访问 dockerhub 和 git,可以用阿里云(阿里云没有arm包)
|
||||
|
||||
version: '3.3'
|
||||
services:
|
||||
# db
|
||||
gs:
|
||||
image: opengauss/opengauss:7.0.0-RC1 # docker hub
|
||||
container_name: gs
|
||||
restart: always
|
||||
# ports: # 生产环境建议不要暴露
|
||||
# - 5432:5432
|
||||
networks:
|
||||
- fastgpt
|
||||
environment:
|
||||
# 这里的配置只有首次运行生效。修改后,重启镜像是不会生效的。需要把持久化数据删除再重启,才有效果
|
||||
- GS_USER=username
|
||||
- GS_PASSWORD=password
|
||||
- GS_DB=postgres
|
||||
volumes:
|
||||
- ./opengauss/data:/var/lib/opengauss/data
|
||||
healthcheck:
|
||||
test: ['CMD-SHELL', 'netstat -lntp | grep tcp6 > /dev/null 2>&1']
|
||||
interval: 10s
|
||||
timeout: 10s
|
||||
retries: 10
|
||||
mongo:
|
||||
image: mongo:5.0.18 # dockerhub
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/mongo:5.0.18 # 阿里云
|
||||
# image: mongo:4.4.29 # cpu不支持AVX时候使用
|
||||
container_name: mongo
|
||||
restart: always
|
||||
# ports:
|
||||
# - 27017:27017
|
||||
networks:
|
||||
- fastgpt
|
||||
command: mongod --keyFile /data/mongodb.key --replSet rs0
|
||||
environment:
|
||||
- MONGO_INITDB_ROOT_USERNAME=myusername
|
||||
- MONGO_INITDB_ROOT_PASSWORD=mypassword
|
||||
volumes:
|
||||
- ./mongo/data:/data/db
|
||||
entrypoint:
|
||||
- bash
|
||||
- -c
|
||||
- |
|
||||
openssl rand -base64 128 > /data/mongodb.key
|
||||
chmod 400 /data/mongodb.key
|
||||
chown 999:999 /data/mongodb.key
|
||||
echo 'const isInited = rs.status().ok === 1
|
||||
if(!isInited){
|
||||
rs.initiate({
|
||||
_id: "rs0",
|
||||
members: [
|
||||
{ _id: 0, host: "mongo:27017" }
|
||||
]
|
||||
})
|
||||
}' > /data/initReplicaSet.js
|
||||
# 启动MongoDB服务
|
||||
exec docker-entrypoint.sh "$$@" &
|
||||
|
||||
# 等待MongoDB服务启动
|
||||
until mongo -u myusername -p mypassword --authenticationDatabase admin --eval "print('waited for connection')"; do
|
||||
echo "Waiting for MongoDB to start..."
|
||||
sleep 2
|
||||
done
|
||||
|
||||
# 执行初始化副本集的脚本
|
||||
mongo -u myusername -p mypassword --authenticationDatabase admin /data/initReplicaSet.js
|
||||
|
||||
# 等待docker-entrypoint.sh脚本执行的MongoDB服务进程
|
||||
wait $$!
|
||||
|
||||
redis:
|
||||
image: redis:7.2-alpine
|
||||
container_name: redis
|
||||
# ports:
|
||||
# - 6379:6379
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
command: |
|
||||
redis-server --requirepass mypassword --loglevel warning --maxclients 10000 --appendonly yes --save 60 10 --maxmemory 4gb --maxmemory-policy noeviction
|
||||
healthcheck:
|
||||
test: ['CMD', 'redis-cli', '-a', 'mypassword', 'ping']
|
||||
interval: 10s
|
||||
timeout: 3s
|
||||
retries: 3
|
||||
start_period: 30s
|
||||
volumes:
|
||||
- ./redis/data:/data
|
||||
|
||||
# fastgpt
|
||||
sandbox:
|
||||
container_name: sandbox
|
||||
image: ghcr.io/labring/fastgpt-sandbox:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.7-fix2 # 阿里云
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
fastgpt-mcp-server:
|
||||
container_name: fastgpt-mcp-server
|
||||
image: ghcr.io/labring/fastgpt-mcp_server:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.7-fix2 # 阿里云
|
||||
ports:
|
||||
- 3005:3000
|
||||
networks:
|
||||
- fastgpt
|
||||
restart: always
|
||||
environment:
|
||||
- FASTGPT_ENDPOINT=http://fastgpt:3000
|
||||
fastgpt:
|
||||
container_name: fastgpt
|
||||
image: ghcr.io/labring/fastgpt:v4.9.7-fix2 # git
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.7-fix2 # 阿里云
|
||||
# image: swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/labring/fastgpt:v4.8.4-linuxarm64 # openGauss在arm架构上性能更好
|
||||
ports:
|
||||
- 3000:3000
|
||||
networks:
|
||||
- fastgpt
|
||||
depends_on:
|
||||
- mongo
|
||||
- gs
|
||||
- sandbox
|
||||
restart: always
|
||||
environment:
|
||||
# 前端外部可访问的地址,用于自动补全文件资源路径。例如 https:fastgpt.cn,不能填 localhost。这个值可以不填,不填则发给模型的图片会是一个相对路径,而不是全路径,模型可能伪造Host。
|
||||
- FE_DOMAIN=
|
||||
# root 密码,用户名为: root。如果需要修改 root 密码,直接修改这个环境变量,并重启即可。
|
||||
- DEFAULT_ROOT_PSW=1234
|
||||
# AI Proxy 的地址,如果配了该地址,优先使用
|
||||
- AIPROXY_API_ENDPOINT=http://aiproxy:3000
|
||||
# AI Proxy 的 Admin Token,与 AI Proxy 中的环境变量 ADMIN_KEY
|
||||
- AIPROXY_API_TOKEN=aiproxy
|
||||
# 数据库最大连接数
|
||||
- DB_MAX_LINK=30
|
||||
# 登录凭证密钥
|
||||
- TOKEN_KEY=any
|
||||
# root的密钥,常用于升级时候的初始化请求
|
||||
- ROOT_KEY=root_key
|
||||
# 文件阅读加密
|
||||
- FILE_TOKEN_KEY=filetoken
|
||||
# MongoDB 连接参数. 用户名myusername,密码mypassword。
|
||||
- MONGODB_URI=mongodb://myusername:mypassword@mongo:27017/fastgpt?authSource=admin
|
||||
# openGauss 连接参数
|
||||
- OPENGAUSS_URL=opengauss://gaussdb:Huawei12%23%24@gs:9999/test
|
||||
# Redis 连接参数
|
||||
- REDIS_URL=redis://default:mypassword@redis:6379
|
||||
# sandbox 地址
|
||||
- SANDBOX_URL=http://sandbox:3000
|
||||
# 日志等级: debug, info, warn, error
|
||||
- LOG_LEVEL=info
|
||||
- STORE_LOG_LEVEL=warn
|
||||
# 工作流最大运行次数
|
||||
- WORKFLOW_MAX_RUN_TIMES=1000
|
||||
# 批量执行节点,最大输入长度
|
||||
- WORKFLOW_MAX_LOOP_TIMES=100
|
||||
# 自定义跨域,不配置时,默认都允许跨域(多个域名通过逗号分割)
|
||||
- ALLOWED_ORIGINS=
|
||||
# 是否开启IP限制,默认不开启
|
||||
- USE_IP_LIMIT=false
|
||||
# 对话文件过期天数
|
||||
- CHAT_FILE_EXPIRE_TIME=7
|
||||
volumes:
|
||||
- ./config.json:/app/data/config.json
|
||||
|
||||
# AI Proxy
|
||||
aiproxy:
|
||||
image: ghcr.io/labring/aiproxy:v0.1.7
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/labring/aiproxy:v0.1.7 # 阿里云
|
||||
container_name: aiproxy
|
||||
restart: unless-stopped
|
||||
depends_on:
|
||||
aiproxy_pg:
|
||||
condition: service_healthy
|
||||
networks:
|
||||
- fastgpt
|
||||
environment:
|
||||
# 对应 fastgpt 里的AIPROXY_API_TOKEN
|
||||
- ADMIN_KEY=aiproxy
|
||||
# 错误日志详情保存时间(小时)
|
||||
- LOG_DETAIL_STORAGE_HOURS=1
|
||||
# 数据库连接地址
|
||||
- SQL_DSN=postgres://postgres:aiproxy@aiproxy_pg:5432/aiproxy
|
||||
# 最大重试次数
|
||||
- RETRY_TIMES=3
|
||||
# 不需要计费
|
||||
- BILLING_ENABLED=false
|
||||
# 不需要严格检测模型
|
||||
- DISABLE_MODEL_CONFIG=true
|
||||
healthcheck:
|
||||
test: ['CMD', 'curl', '-f', 'http://localhost:3000/api/status']
|
||||
interval: 5s
|
||||
timeout: 5s
|
||||
retries: 10
|
||||
aiproxy_pg:
|
||||
image: pgvector/pgvector:0.8.0-pg15 # docker hub
|
||||
# image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.8.0-pg15 # 阿里云
|
||||
restart: unless-stopped
|
||||
container_name: aiproxy_pg
|
||||
volumes:
|
||||
- ./aiproxy_pg:/var/lib/postgresql/data
|
||||
networks:
|
||||
- fastgpt
|
||||
environment:
|
||||
TZ: Asia/Shanghai
|
||||
POSTGRES_USER: postgres
|
||||
POSTGRES_DB: aiproxy
|
||||
POSTGRES_PASSWORD: aiproxy
|
||||
healthcheck:
|
||||
test: ['CMD', 'pg_isready', '-U', 'postgres', '-d', 'aiproxy']
|
||||
interval: 5s
|
||||
timeout: 5s
|
||||
retries: 10
|
||||
networks:
|
||||
fastgpt:
|
1
env.d.ts
vendored
1
env.d.ts
vendored
@@ -15,6 +15,7 @@ declare global {
|
||||
MONGODB_LOG_URI?: string;
|
||||
PG_URL: string;
|
||||
OCEANBASE_URL: string;
|
||||
OPENGAUSS_URL: string;
|
||||
MILVUS_ADDRESS: string;
|
||||
MILVUS_TOKEN: string;
|
||||
SANDBOX_URL: string;
|
||||
|
7
packages/global/core/dataset/api.d.ts
vendored
7
packages/global/core/dataset/api.d.ts
vendored
@@ -124,6 +124,13 @@ export type PgSearchRawType = {
|
||||
collection_id: string;
|
||||
score: number;
|
||||
};
|
||||
|
||||
export type GsSearchRawType = {
|
||||
id: string;
|
||||
collection_id: string;
|
||||
score: number;
|
||||
};
|
||||
|
||||
export type PushDatasetDataChunkProps = {
|
||||
q: string; // embedding content
|
||||
a?: string; // bonus content
|
||||
|
@@ -3,5 +3,6 @@ export const DatasetVectorTableName = 'modeldata';
|
||||
|
||||
export const PG_ADDRESS = process.env.PG_URL;
|
||||
export const OCEANBASE_ADDRESS = process.env.OCEANBASE_URL;
|
||||
export const OPENGAUSS_ADDRESS = process.env.OPENGAUSS_URL;
|
||||
export const MILVUS_ADDRESS = process.env.MILVUS_ADDRESS;
|
||||
export const MILVUS_TOKEN = process.env.MILVUS_TOKEN;
|
||||
|
@@ -1,10 +1,11 @@
|
||||
/* vector crud */
|
||||
import { PgVectorCtrl } from './pg';
|
||||
import { ObVectorCtrl } from './oceanbase';
|
||||
import { GsVectorCtrl } from './opengauss';
|
||||
import { getVectorsByText } from '../../core/ai/embedding';
|
||||
import { type DelDatasetVectorCtrlProps, type InsertVectorProps } from './controller.d';
|
||||
import { type EmbeddingModelItemType } from '@fastgpt/global/core/ai/model.d';
|
||||
import { MILVUS_ADDRESS, PG_ADDRESS, OCEANBASE_ADDRESS } from './constants';
|
||||
import { MILVUS_ADDRESS, PG_ADDRESS, OCEANBASE_ADDRESS, OPENGAUSS_ADDRESS } from './constants';
|
||||
import { MilvusCtrl } from './milvus';
|
||||
import { setRedisCache, getRedisCache, delRedisCache, CacheKeyEnum } from '../redis/cache';
|
||||
import { throttle } from 'lodash';
|
||||
@@ -14,6 +15,7 @@ const getVectorObj = () => {
|
||||
if (PG_ADDRESS) return new PgVectorCtrl();
|
||||
if (OCEANBASE_ADDRESS) return new ObVectorCtrl();
|
||||
if (MILVUS_ADDRESS) return new MilvusCtrl();
|
||||
if (OPENGAUSS_ADDRESS) return new GsVectorCtrl();
|
||||
|
||||
return new PgVectorCtrl();
|
||||
};
|
||||
|
188
packages/service/common/vectorDB/opengauss/controller.ts
Normal file
188
packages/service/common/vectorDB/opengauss/controller.ts
Normal file
@@ -0,0 +1,188 @@
|
||||
import { delay } from '@fastgpt/global/common/system/utils';
|
||||
import { addLog } from '../../system/log';
|
||||
import { Pool } from 'pg';
|
||||
import type { QueryResultRow } from 'pg';
|
||||
import { OPENGAUSS_ADDRESS } from '../constants';
|
||||
|
||||
export const connectGs = async (): Promise<Pool> => {
|
||||
if (global.gsClient) {
|
||||
return global.gsClient;
|
||||
}
|
||||
|
||||
global.gsClient = new Pool({
|
||||
connectionString: OPENGAUSS_ADDRESS,
|
||||
max: Number(process.env.DB_MAX_LINK || 20),
|
||||
min: 10,
|
||||
keepAlive: true,
|
||||
idleTimeoutMillis: 600000,
|
||||
connectionTimeoutMillis: 20000,
|
||||
query_timeout: 30000,
|
||||
statement_timeout: 40000,
|
||||
idle_in_transaction_session_timeout: 60000
|
||||
});
|
||||
|
||||
global.gsClient.on('error', async (err) => {
|
||||
addLog.error(`openGauss error`, err);
|
||||
global.gsClient?.end();
|
||||
global.gsClient = null;
|
||||
|
||||
await delay(1000);
|
||||
addLog.info(`Retry connect openGauss`);
|
||||
connectGs();
|
||||
});
|
||||
|
||||
try {
|
||||
await global.gsClient.connect();
|
||||
console.log('openGauss connected');
|
||||
return global.gsClient;
|
||||
} catch (error) {
|
||||
addLog.error(`openGauss connect error`, error);
|
||||
global.gsClient?.end();
|
||||
global.gsClient = null;
|
||||
|
||||
await delay(1000);
|
||||
addLog.info(`Retry connect openGauss`);
|
||||
|
||||
return connectGs();
|
||||
}
|
||||
};
|
||||
|
||||
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 GsClass {
|
||||
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 QueryResultRow = 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 ${props.offset || 0}
|
||||
`;
|
||||
|
||||
const gs = await connectGs();
|
||||
return gs.query<T>(sql);
|
||||
}
|
||||
async count(table: string, props: GetProps) {
|
||||
const sql = `SELECT COUNT(${props?.fields?.[0] || '*'})
|
||||
FROM ${table}
|
||||
${this.getWhereStr(props.where)}
|
||||
`;
|
||||
|
||||
const gs = await connectGs();
|
||||
return gs.query(sql).then((res) => Number(res.rows[0]?.count || 0));
|
||||
}
|
||||
async delete(table: string, props: DeleteProps) {
|
||||
const sql = `DELETE FROM ${table} ${this.getWhereStr(props.where)}`;
|
||||
const gs = await connectGs();
|
||||
return gs.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 gs = await connectGs();
|
||||
return gs.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
|
||||
)} RETURNING id`;
|
||||
|
||||
const gs = await connectGs();
|
||||
return gs.query<{ id: string }>(sql);
|
||||
}
|
||||
async query<T extends QueryResultRow = any>(sql: string) {
|
||||
const gs = await connectGs();
|
||||
const start = Date.now();
|
||||
return gs.query<T>(sql).then((res) => {
|
||||
const time = Date.now() - start;
|
||||
|
||||
if (time > 300) {
|
||||
addLog.warn(`gs query time: ${time}ms, sql: ${sql}`);
|
||||
}
|
||||
|
||||
return res;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
export const GsClient = new GsClass();
|
||||
export const Gs = global.gsClient;
|
253
packages/service/common/vectorDB/opengauss/index.ts
Normal file
253
packages/service/common/vectorDB/opengauss/index.ts
Normal file
@@ -0,0 +1,253 @@
|
||||
/* pg vector crud */
|
||||
import { DatasetVectorTableName } from '../constants';
|
||||
import { delay } from '@fastgpt/global/common/system/utils';
|
||||
import { GsClient, connectGs } from './controller';
|
||||
import { GsSearchRawType } from '@fastgpt/global/core/dataset/api';
|
||||
import type {
|
||||
DelDatasetVectorCtrlProps,
|
||||
EmbeddingRecallCtrlProps,
|
||||
EmbeddingRecallResponse,
|
||||
InsertVectorControllerProps
|
||||
} from '../controller.d';
|
||||
import dayjs from 'dayjs';
|
||||
import { addLog } from '../../system/log';
|
||||
|
||||
export class GsVectorCtrl {
|
||||
constructor() {}
|
||||
init = async () => {
|
||||
try {
|
||||
await connectGs();
|
||||
await GsClient.query(`
|
||||
CREATE EXTENSION IF NOT EXISTS vector;
|
||||
CREATE TABLE IF NOT EXISTS ${DatasetVectorTableName} (
|
||||
id BIGSERIAL PRIMARY KEY,
|
||||
vector VECTOR(1536) NOT NULL,
|
||||
team_id VARCHAR(50) NOT NULL,
|
||||
dataset_id VARCHAR(50) NOT NULL,
|
||||
collection_id VARCHAR(50) NOT NULL,
|
||||
createtime TIMESTAMP DEFAULT CURRENT_TIMESTAMP
|
||||
);
|
||||
`);
|
||||
|
||||
await GsClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS vector_index ON ${DatasetVectorTableName} USING hnsw (vector vector_ip_ops) WITH (m = 32, ef_construction = 128);`
|
||||
);
|
||||
await GsClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS team_dataset_collection_index ON ${DatasetVectorTableName} USING btree(team_id, dataset_id, collection_id);`
|
||||
);
|
||||
await GsClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS create_time_index ON ${DatasetVectorTableName} USING btree(createtime);`
|
||||
);
|
||||
|
||||
addLog.info('init pg successful');
|
||||
} catch (error) {
|
||||
addLog.error('init pg error', error);
|
||||
}
|
||||
};
|
||||
insert = async (props: InsertVectorControllerProps): Promise<{ insertId: string }> => {
|
||||
const { teamId, datasetId, collectionId, vector, retry = 3 } = props;
|
||||
|
||||
try {
|
||||
const { rowCount, rows } = await GsClient.insert(DatasetVectorTableName, {
|
||||
values: [
|
||||
[
|
||||
{ key: 'vector', value: `[${vector}]` },
|
||||
{ key: 'team_id', value: String(teamId) },
|
||||
{ key: 'dataset_id', value: String(datasetId) },
|
||||
{ key: 'collection_id', value: String(collectionId) }
|
||||
]
|
||||
]
|
||||
});
|
||||
|
||||
if (rowCount === 0) {
|
||||
return Promise.reject('insertDatasetData: no insert');
|
||||
}
|
||||
|
||||
return {
|
||||
insertId: rows[0].id
|
||||
};
|
||||
} catch (error) {
|
||||
if (retry <= 0) {
|
||||
return Promise.reject(error);
|
||||
}
|
||||
await delay(500);
|
||||
return this.insert({
|
||||
...props,
|
||||
retry: retry - 1
|
||||
});
|
||||
}
|
||||
};
|
||||
delete = async (props: DelDatasetVectorCtrlProps): Promise<any> => {
|
||||
const { teamId, retry = 2 } = props;
|
||||
|
||||
const teamIdWhere = `team_id='${String(teamId)}' AND`;
|
||||
|
||||
const where = await (() => {
|
||||
if ('id' in props && props.id) return `${teamIdWhere} id=${props.id}`;
|
||||
|
||||
if ('datasetIds' in props && props.datasetIds) {
|
||||
const datasetIdWhere = `dataset_id IN (${props.datasetIds
|
||||
.map((id) => `'${String(id)}'`)
|
||||
.join(',')})`;
|
||||
|
||||
if ('collectionIds' in props && props.collectionIds) {
|
||||
return `${teamIdWhere} ${datasetIdWhere} AND collection_id IN (${props.collectionIds
|
||||
.map((id) => `'${String(id)}'`)
|
||||
.join(',')})`;
|
||||
}
|
||||
|
||||
return `${teamIdWhere} ${datasetIdWhere}`;
|
||||
}
|
||||
|
||||
if ('idList' in props && Array.isArray(props.idList)) {
|
||||
if (props.idList.length === 0) return;
|
||||
return `${teamIdWhere} id IN (${props.idList.map((id) => String(id)).join(',')})`;
|
||||
}
|
||||
return Promise.reject('deleteDatasetData: no where');
|
||||
})();
|
||||
|
||||
if (!where) return;
|
||||
|
||||
try {
|
||||
await GsClient.delete(DatasetVectorTableName, {
|
||||
where: [where]
|
||||
});
|
||||
} catch (error) {
|
||||
if (retry <= 0) {
|
||||
return Promise.reject(error);
|
||||
}
|
||||
await delay(500);
|
||||
return this.delete({
|
||||
...props,
|
||||
retry: retry - 1
|
||||
});
|
||||
}
|
||||
};
|
||||
embRecall = async (props: EmbeddingRecallCtrlProps): Promise<EmbeddingRecallResponse> => {
|
||||
const {
|
||||
teamId,
|
||||
datasetIds,
|
||||
vector,
|
||||
limit,
|
||||
forbidCollectionIdList,
|
||||
filterCollectionIdList,
|
||||
retry = 2
|
||||
} = props;
|
||||
|
||||
// Get forbid collection
|
||||
const formatForbidCollectionIdList = (() => {
|
||||
if (!filterCollectionIdList) return forbidCollectionIdList;
|
||||
const list = forbidCollectionIdList
|
||||
.map((id) => String(id))
|
||||
.filter((id) => !filterCollectionIdList.includes(id));
|
||||
return list;
|
||||
})();
|
||||
const forbidCollectionSql =
|
||||
formatForbidCollectionIdList.length > 0
|
||||
? `AND collection_id NOT IN (${formatForbidCollectionIdList.map((id) => `'${id}'`).join(',')})`
|
||||
: '';
|
||||
|
||||
// Filter by collectionId
|
||||
const formatFilterCollectionId = (() => {
|
||||
if (!filterCollectionIdList) return;
|
||||
|
||||
return filterCollectionIdList
|
||||
.map((id) => String(id))
|
||||
.filter((id) => !forbidCollectionIdList.includes(id));
|
||||
})();
|
||||
const filterCollectionIdSql = formatFilterCollectionId
|
||||
? `AND collection_id IN (${formatFilterCollectionId.map((id) => `'${id}'`).join(',')})`
|
||||
: '';
|
||||
// Empty data
|
||||
if (formatFilterCollectionId && formatFilterCollectionId.length === 0) {
|
||||
return { results: [] };
|
||||
}
|
||||
|
||||
try {
|
||||
const results: any = await GsClient.query(
|
||||
`BEGIN;
|
||||
SET ob_hnsw_ef_search = ${global.systemEnv?.hnswEfSearch || 100};
|
||||
SELECT id, collection_id, inner_product(vector, [${vector}]) AS score
|
||||
FROM ${DatasetVectorTableName}
|
||||
WHERE team_id='${teamId}'
|
||||
AND dataset_id IN (${datasetIds.map((id) => `'${String(id)}'`).join(',')})
|
||||
${filterCollectionIdSql}
|
||||
${forbidCollectionSql}
|
||||
ORDER BY score desc APPROXIMATE LIMIT ${limit};
|
||||
COMMIT;`
|
||||
);
|
||||
const rows = results?.[3]?.rows as GsSearchRawType[];
|
||||
|
||||
if (!Array.isArray(rows)) {
|
||||
return {
|
||||
results: []
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
results: rows.map((item) => ({
|
||||
id: String(item.id),
|
||||
collectionId: item.collection_id,
|
||||
score: item.score * -1
|
||||
}))
|
||||
};
|
||||
} catch (error) {
|
||||
if (retry <= 0) {
|
||||
return Promise.reject(error);
|
||||
}
|
||||
return this.embRecall({
|
||||
...props,
|
||||
retry: retry - 1
|
||||
});
|
||||
}
|
||||
};
|
||||
getVectorDataByTime = async (start: Date, end: Date) => {
|
||||
const { rows } = await GsClient.query<{
|
||||
id: string;
|
||||
team_id: string;
|
||||
dataset_id: string;
|
||||
}>(`SELECT id, team_id, dataset_id
|
||||
FROM ${DatasetVectorTableName}
|
||||
WHERE createtime BETWEEN '${dayjs(start).format('YYYY-MM-DD HH:mm:ss')}' AND '${dayjs(
|
||||
end
|
||||
).format('YYYY-MM-DD HH:mm:ss')}';
|
||||
`);
|
||||
|
||||
return rows.map((item) => ({
|
||||
id: String(item.id),
|
||||
teamId: item.team_id,
|
||||
datasetId: item.dataset_id
|
||||
}));
|
||||
};
|
||||
getVectorCountByTeamId = async (teamId: string) => {
|
||||
const total = await GsClient.count(DatasetVectorTableName, {
|
||||
where: [['team_id', String(teamId)]]
|
||||
});
|
||||
|
||||
return total;
|
||||
};
|
||||
getVectorCountByDatasetId = async (teamId: string, datasetId: string) => {
|
||||
const total = await GsClient.count(DatasetVectorTableName, {
|
||||
where: [['team_id', String(teamId)], 'and', ['dataset_id', String(datasetId)]]
|
||||
});
|
||||
|
||||
return total;
|
||||
};
|
||||
getVectorCountByCollectionId = async (
|
||||
teamId: string,
|
||||
datasetId: string,
|
||||
collectionId: string
|
||||
) => {
|
||||
const total = await GsClient.count(DatasetVectorTableName, {
|
||||
where: [
|
||||
['team_id', String(teamId)],
|
||||
'and',
|
||||
['dataset_id', String(datasetId)],
|
||||
'and',
|
||||
['collection_id', String(collectionId)]
|
||||
]
|
||||
});
|
||||
|
||||
return total;
|
||||
};
|
||||
}
|
1
packages/service/common/vectorDB/type.d.ts
vendored
1
packages/service/common/vectorDB/type.d.ts
vendored
@@ -6,6 +6,7 @@ declare global {
|
||||
var pgClient: Pool | null;
|
||||
var obClient: MysqlPool | null;
|
||||
var milvusClient: MilvusClient | null;
|
||||
var gsClient: Pool | null;
|
||||
}
|
||||
|
||||
export type EmbeddingRecallItemType = {
|
||||
|
@@ -29,6 +29,8 @@ MONGODB_LOG_URI=mongodb://username:password@0.0.0.0:27017/fastgpt?authSource=adm
|
||||
PG_URL=postgresql://username:password@host:port/postgres
|
||||
# OceanBase 向量库连接参数
|
||||
OCEANBASE_URL=
|
||||
# openGauss 向量库连接参数
|
||||
OPENGAUSS_URL=
|
||||
# milvus 向量库连接参数
|
||||
MILVUS_ADDRESS=
|
||||
MILVUS_TOKEN=
|
||||
|
Reference in New Issue
Block a user