Add tests for filterSafeProps function in Markdown utils test suite

Update dataset.md (#4927 )
feat: text collecion auto save for a txt file (#4924 )
2025-05-29 16:12:14 +00:00 · 2025-05-29 18:25:59 +08:00 · 2025-05-29 17:57:27 +08:00 · 2025-05-29 14:29:28 +08:00 · 2025-05-29 13:37:59 +08:00 · 2025-05-28 22:11:40 +08:00
55 changed files with 805 additions and 849 deletions
--- a/deploy/docker/docker-compose-milvus.yml
+++ b/deploy/docker/docker-compose-milvus.yml
@@ -132,15 +132,15 @@ services:
  # fastgpt
  sandbox:
    container_name: sandbox
-    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10-fix2 # 阿里云
    networks:
      - fastgpt
    restart: always
  fastgpt-mcp-server:
    container_name: fastgpt-mcp-server
-    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10-fix2 # 阿里云
    ports:
      - 3005:3000
    networks:
@@ -150,8 +150,8 @@ services:
      - FASTGPT_ENDPOINT=http://fastgpt:3000
  fastgpt:
    container_name: fastgpt
-    image: ghcr.io/labring/fastgpt:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10-fix2 # 阿里云
    ports:
      - 3000:3000
    networks:
--- a/deploy/docker/docker-compose-oceanbase/docker-compose.yml
+++ b/deploy/docker/docker-compose-oceanbase/docker-compose.yml
@@ -109,15 +109,15 @@ services:
  # fastgpt
  sandbox:
    container_name: sandbox
-    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10-fix2 # 阿里云
    networks:
      - fastgpt
    restart: always
  fastgpt-mcp-server:
    container_name: fastgpt-mcp-server
-    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10-fix2 # 阿里云
    ports:
      - 3005:3000
    networks:
@@ -127,8 +127,8 @@ services:
      - FASTGPT_ENDPOINT=http://fastgpt:3000
  fastgpt:
    container_name: fastgpt
-    image: ghcr.io/labring/fastgpt:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10-fix2 # 阿里云
    ports:
      - 3000:3000
    networks:
--- a/deploy/docker/docker-compose-opengauss.yml
+++ b/deploy/docker/docker-compose-opengauss.yml
@@ -1,218 +0,0 @@
-# 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:
--- a/deploy/docker/docker-compose-pgvector.yml
+++ b/deploy/docker/docker-compose-pgvector.yml
@@ -96,15 +96,15 @@ services:
  # fastgpt
  sandbox:
    container_name: sandbox
-    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10-fix2 # 阿里云
    networks:
      - fastgpt
    restart: always
  fastgpt-mcp-server:
    container_name: fastgpt-mcp-server
-    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10-fix2 # 阿里云
    ports:
      - 3005:3000
    networks:
@@ -114,8 +114,8 @@ services:
      - FASTGPT_ENDPOINT=http://fastgpt:3000
  fastgpt:
    container_name: fastgpt
-    image: ghcr.io/labring/fastgpt:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10-fix2 # 阿里云
    ports:
      - 3000:3000
    networks:
--- a/deploy/docker/docker-compose-zilliz.yml
+++ b/deploy/docker/docker-compose-zilliz.yml
@@ -72,15 +72,15 @@ services:

  sandbox:
    container_name: sandbox
-    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-sandbox:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:v4.9.10-fix2 # 阿里云
    networks:
      - fastgpt
    restart: always
  fastgpt-mcp-server:
    container_name: fastgpt-mcp-server
-    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt-mcp_server:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-mcp_server:v4.9.10-fix2 # 阿里云
    ports:
      - 3005:3000
    networks:
@@ -90,8 +90,8 @@ services:
      - FASTGPT_ENDPOINT=http://fastgpt:3000
  fastgpt:
    container_name: fastgpt
-    image: ghcr.io/labring/fastgpt:v4.9.10 # git
-    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10 # 阿里云
+    image: ghcr.io/labring/fastgpt:v4.9.10-fix2 # git
+    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.9.10-fix2 # 阿里云
    ports:
      - 3000:3000
    networks:
--- a/docSite/content/zh-cn/docs/development/openapi/dataset.md
+++ b/docSite/content/zh-cn/docs/development/openapi/dataset.md
@@ -645,7 +645,7 @@ data 为集合的 ID。
 {{< /tab >}}
 {{< /tabs >}}

-### 创建一个外部文件库集合（商业版）
+### 创建一个外部文件库集合（弃用）

 {{< tabs tabTotal="3" >}}
 {{< tab tabName="请求示例" >}}
--- a/docSite/content/zh-cn/docs/development/upgrading/4910.md
+++ b/docSite/content/zh-cn/docs/development/upgrading/4910.md
@@ -15,8 +15,8 @@ weight: 790

 ### 2. 更新镜像 tag

- 更新 FastGPT 镜像 tag: v4.9.10
- 更新 FastGPT 商业版镜像 tag: v4.9.10
+- 更新 FastGPT 镜像 tag: v4.9.10-fix2
+- 更新 FastGPT 商业版镜像 tag: v4.9.10-fix2
 - mcp_server 无需更新
 - Sandbox 无需更新
 - AIProxy 无需更新
--- a/docSite/content/zh-cn/docs/development/upgrading/4911.md
+++ b/docSite/content/zh-cn/docs/development/upgrading/4911.md
@@ -10,12 +10,16 @@ weight: 789

 ## 🚀 新增内容

-1. 工作流中，子流程版本控制，可选择“保持最新版本”，无需手动更新。
+1. 工作流中增加节点搜索功能。
+2. 工作流中，子流程版本控制，可选择“保持最新版本”，无需手动更新。

 ## ⚙️ 优化

-
+1. 原文缓存改用 gridfs 存储，提高上限。

 ## 🐛 修复

-1. 工作流中，管理员声明的全局系统工具，无法进行版本管理。
+1. 工作流中，管理员声明的全局系统工具，无法进行版本管理。
+2. 工具调用节点前，有交互节点时，上下文异常。
+3. 修复备份导入，小于 1000 字时，无法分块问题。
+4. 自定义 PDF 解析，无法保存 base64 图片。
--- a/env.d.ts
+++ b/env.d.ts
@@ -15,7 +15,6 @@ declare global {
      MONGODB_LOG_URI?: string;
      PG_URL: string;
      OCEANBASE_URL: string;
-      OPENGAUSS_URL: string;
      MILVUS_ADDRESS: string;
      MILVUS_TOKEN: string;
      SANDBOX_URL: string;
--- a/packages/global/core/dataset/api.d.ts
+++ b/packages/global/core/dataset/api.d.ts
@@ -124,13 +124,6 @@ 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
--- a/packages/global/core/dataset/utils.ts
+++ b/packages/global/core/dataset/utils.ts
@@ -40,5 +40,6 @@ export function getSourceNameIcon({
 export const predictDataLimitLength = (mode: TrainingModeEnum, data: any[]) => {
  if (mode === TrainingModeEnum.qa) return data.length * 20;
  if (mode === TrainingModeEnum.auto) return data.length * 5;
+  if (mode === TrainingModeEnum.image) return data.length * 2;
  return data.length;
 };
--- a/packages/global/core/workflow/type/node.d.ts
+++ b/packages/global/core/workflow/type/node.d.ts
@@ -125,6 +125,7 @@ export type FlowNodeItemType = FlowNodeTemplateType & {
  nodeId: string;
  parentNodeId?: string;
  isError?: boolean;
+  searchedText?: string;
  debugResult?: {
    status: 'running' | 'success' | 'skipped' | 'failed';
    message?: string;
--- a/packages/service/common/buffer/rawText/controller.ts
+++ b/packages/service/common/buffer/rawText/controller.ts
@@ -0,0 +1,178 @@
+import { retryFn } from '@fastgpt/global/common/system/utils';
+import { connectionMongo } from '../../mongo';
+import { MongoRawTextBufferSchema, bucketName } from './schema';
+import { addLog } from '../../system/log';
+import { setCron } from '../../system/cron';
+import { checkTimerLock } from '../../system/timerLock/utils';
+import { TimerIdEnum } from '../../system/timerLock/constants';
+
+const getGridBucket = () => {
+  return new connectionMongo.mongo.GridFSBucket(connectionMongo.connection.db!, {
+    bucketName: bucketName
+  });
+};
+
+export const addRawTextBuffer = async ({
+  sourceId,
+  sourceName,
+  text,
+  expiredTime
+}: {
+  sourceId: string;
+  sourceName: string;
+  text: string;
+  expiredTime: Date;
+}) => {
+  const gridBucket = getGridBucket();
+  const metadata = {
+    sourceId,
+    sourceName,
+    expiredTime
+  };
+
+  const buffer = Buffer.from(text);
+
+  const fileSize = buffer.length;
+  // 单块大小：尽可能大，但不超过 14MB，不小于128KB
+  const chunkSizeBytes = (() => {
+    // 计算理想块大小：文件大小 ÷ 目标块数(10)。 并且每个块需要小于 14MB
+    const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
+
+    // 确保块大小至少为128KB
+    const minChunkSize = 128 * 1024; // 128KB
+
+    // 取理想块大小和最小块大小中的较大值
+    let chunkSize = Math.max(idealChunkSize, minChunkSize);
+
+    // 将块大小向上取整到最接近的64KB的倍数，使其更整齐
+    chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
+
+    return chunkSize;
+  })();
+
+  const uploadStream = gridBucket.openUploadStream(sourceId, {
+    metadata,
+    chunkSizeBytes
+  });
+
+  return retryFn(async () => {
+    return new Promise((resolve, reject) => {
+      uploadStream.end(buffer);
+      uploadStream.on('finish', () => {
+        resolve(uploadStream.id);
+      });
+      uploadStream.on('error', (error) => {
+        addLog.error('addRawTextBuffer error', error);
+        resolve('');
+      });
+    });
+  });
+};
+
+export const getRawTextBuffer = async (sourceId: string) => {
+  const gridBucket = getGridBucket();
+
+  return retryFn(async () => {
+    const bufferData = await MongoRawTextBufferSchema.findOne(
+      {
+        'metadata.sourceId': sourceId
+      },
+      '_id metadata'
+    ).lean();
+    if (!bufferData) {
+      return null;
+    }
+
+    // Read file content
+    const downloadStream = gridBucket.openDownloadStream(bufferData._id);
+    const chunks: Buffer[] = [];
+
+    return new Promise<{
+      text: string;
+      sourceName: string;
+    } | null>((resolve, reject) => {
+      downloadStream.on('data', (chunk) => {
+        chunks.push(chunk);
+      });
+
+      downloadStream.on('end', () => {
+        const buffer = Buffer.concat(chunks);
+        const text = buffer.toString('utf8');
+        resolve({
+          text,
+          sourceName: bufferData.metadata?.sourceName || ''
+        });
+      });
+
+      downloadStream.on('error', (error) => {
+        addLog.error('getRawTextBuffer error', error);
+        resolve(null);
+      });
+    });
+  });
+};
+
+export const deleteRawTextBuffer = async (sourceId: string): Promise<boolean> => {
+  const gridBucket = getGridBucket();
+
+  return retryFn(async () => {
+    const buffer = await MongoRawTextBufferSchema.findOne({ 'metadata.sourceId': sourceId });
+    if (!buffer) {
+      return false;
+    }
+
+    await gridBucket.delete(buffer._id);
+    return true;
+  });
+};
+
+export const updateRawTextBufferExpiredTime = async ({
+  sourceId,
+  expiredTime
+}: {
+  sourceId: string;
+  expiredTime: Date;
+}) => {
+  return retryFn(async () => {
+    return MongoRawTextBufferSchema.updateOne(
+      { 'metadata.sourceId': sourceId },
+      { $set: { 'metadata.expiredTime': expiredTime } }
+    );
+  });
+};
+
+export const clearExpiredRawTextBufferCron = async () => {
+  const clearExpiredRawTextBuffer = async () => {
+    addLog.debug('Clear expired raw text buffer start');
+    const gridBucket = getGridBucket();
+
+    return retryFn(async () => {
+      const data = await MongoRawTextBufferSchema.find(
+        {
+          'metadata.expiredTime': { $lt: new Date() }
+        },
+        '_id'
+      ).lean();
+
+      for (const item of data) {
+        await gridBucket.delete(item._id);
+      }
+      addLog.debug('Clear expired raw text buffer end');
+    });
+  };
+
+  setCron('*/10 * * * *', async () => {
+    if (
+      await checkTimerLock({
+        timerId: TimerIdEnum.clearExpiredRawTextBuffer,
+        lockMinuted: 9
+      })
+    ) {
+      try {
+        await clearExpiredRawTextBuffer();
+      } catch (error) {
+        addLog.error('clearExpiredRawTextBufferCron error', error);
+      }
+    }
+  });
+};
--- a/packages/service/common/buffer/rawText/schema.ts
+++ b/packages/service/common/buffer/rawText/schema.ts
@@ -1,33 +1,22 @@
-import { getMongoModel, Schema } from '../../mongo';
-import { type RawTextBufferSchemaType } from './type';
+import { getMongoModel, type Types, Schema } from '../../mongo';

-export const collectionName = 'buffer_rawtexts';
+export const bucketName = 'buffer_rawtext';

 const RawTextBufferSchema = new Schema({
-  sourceId: {
-    type: String,
-    required: true
-  },
-  rawText: {
-    type: String,
-    default: ''
-  },
-  createTime: {
-    type: Date,
-    default: () => new Date()
-  },
-  metadata: Object
+  metadata: {
+    sourceId: { type: String, required: true },
+    sourceName: { type: String, required: true },
+    expiredTime: { type: Date, required: true }
+  }
 });
+RawTextBufferSchema.index({ 'metadata.sourceId': 'hashed' });
+RawTextBufferSchema.index({ 'metadata.expiredTime': -1 });

-try {
-  RawTextBufferSchema.index({ sourceId: 1 });
-  //  20 minutes
-  RawTextBufferSchema.index({ createTime: 1 }, { expireAfterSeconds: 20 * 60 });
-} catch (error) {
-  console.log(error);
-}
-
-export const MongoRawTextBuffer = getMongoModel<RawTextBufferSchemaType>(
-  collectionName,
-  RawTextBufferSchema
-);
+export const MongoRawTextBufferSchema = getMongoModel<{
+  _id: Types.ObjectId;
+  metadata: {
+    sourceId: string;
+    sourceName: string;
+    expiredTime: Date;
+  };
+}>(`${bucketName}.files`, RawTextBufferSchema);
--- a/packages/service/common/buffer/rawText/type.d.ts
+++ b/packages/service/common/buffer/rawText/type.d.ts
@@ -1,8 +0,0 @@
-export type RawTextBufferSchemaType = {
-  sourceId: string;
-  rawText: string;
-  createTime: Date;
-  metadata?: {
-    filename: string;
-  };
-};
--- a/packages/service/common/file/gridfs/controller.ts
+++ b/packages/service/common/file/gridfs/controller.ts
@@ -6,13 +6,13 @@ import { type DatasetFileSchema } from '@fastgpt/global/core/dataset/type';
 import { MongoChatFileSchema, MongoDatasetFileSchema } from './schema';
 import { detectFileEncoding, detectFileEncodingByPath } from '@fastgpt/global/common/file/tools';
 import { CommonErrEnum } from '@fastgpt/global/common/error/code/common';
-import { MongoRawTextBuffer } from '../../buffer/rawText/schema';
 import { readRawContentByFileBuffer } from '../read/utils';
 import { gridFsStream2Buffer, stream2Encoding } from './utils';
 import { addLog } from '../../system/log';
-import { readFromSecondary } from '../../mongo/utils';
 import { parseFileExtensionFromUrl } from '@fastgpt/global/common/string/tools';
 import { Readable } from 'stream';
+import { addRawTextBuffer, getRawTextBuffer } from '../../buffer/rawText/controller';
+import { addMinutes } from 'date-fns';

 export function getGFSCollection(bucket: `${BucketNameEnum}`) {
  MongoDatasetFileSchema;
@@ -223,15 +223,13 @@ export const readFileContentFromMongo = async ({
  rawText: string;
  filename: string;
 }> => {
-  const bufferId = `${fileId}-${customPdfParse}`;
+  const bufferId = `${String(fileId)}-${customPdfParse}`;
  // read buffer
-  const fileBuffer = await MongoRawTextBuffer.findOne({ sourceId: bufferId }, undefined, {
-    ...readFromSecondary
-  }).lean();
+  const fileBuffer = await getRawTextBuffer(bufferId);
  if (fileBuffer) {
    return {
-      rawText: fileBuffer.rawText,
-      filename: fileBuffer.metadata?.filename || ''
+      rawText: fileBuffer.text,
+      filename: fileBuffer?.sourceName
    };
  }

@@ -265,16 +263,13 @@ export const readFileContentFromMongo = async ({
    }
  });

-  // < 14M
-  if (fileBuffers.length < 14 * 1024 * 1024 && rawText.trim()) {
-    MongoRawTextBuffer.create({
-      sourceId: bufferId,
-      rawText,
-      metadata: {
-        filename: file.filename
-      }
-    });
-  }
+  // Add buffer
+  addRawTextBuffer({
+    sourceId: bufferId,
+    sourceName: file.filename,
+    text: rawText,
+    expiredTime: addMinutes(new Date(), 20)
+  });

  return {
    rawText,
--- a/packages/service/common/file/gridfs/schema.ts
+++ b/packages/service/common/file/gridfs/schema.ts
@@ -1,16 +1,16 @@
 import { Schema, getMongoModel } from '../../mongo';

-const DatasetFileSchema = new Schema({});
-const ChatFileSchema = new Schema({});
+const DatasetFileSchema = new Schema({
+  metadata: Object
+});
+const ChatFileSchema = new Schema({
+  metadata: Object
+});

-try {
-  DatasetFileSchema.index({ uploadDate: -1 });
+DatasetFileSchema.index({ uploadDate: -1 });

-  ChatFileSchema.index({ uploadDate: -1 });
-  ChatFileSchema.index({ 'metadata.chatId': 1 });
-} catch (error) {
-  console.log(error);
-}
+ChatFileSchema.index({ uploadDate: -1 });
+ChatFileSchema.index({ 'metadata.chatId': 1 });

 export const MongoDatasetFileSchema = getMongoModel('dataset.files', DatasetFileSchema);
 export const MongoChatFileSchema = getMongoModel('chat.files', ChatFileSchema);
--- a/packages/service/common/file/gridfs/utils.ts
+++ b/packages/service/common/file/gridfs/utils.ts
@@ -1,5 +1,57 @@
 import { detectFileEncoding } from '@fastgpt/global/common/file/tools';
 import { PassThrough } from 'stream';
+import { getGridBucket } from './controller';
+import { type BucketNameEnum } from '@fastgpt/global/common/file/constants';
+import { retryFn } from '@fastgpt/global/common/system/utils';
+
+export const createFileFromText = async ({
+  bucket,
+  filename,
+  text,
+  metadata
+}: {
+  bucket: `${BucketNameEnum}`;
+  filename: string;
+  text: string;
+  metadata: Record<string, any>;
+}) => {
+  const gridBucket = getGridBucket(bucket);
+
+  const buffer = Buffer.from(text);
+
+  const fileSize = buffer.length;
+  // 单块大小：尽可能大，但不超过 14MB，不小于128KB
+  const chunkSizeBytes = (() => {
+    // 计算理想块大小：文件大小 ÷ 目标块数(10)。 并且每个块需要小于 14MB
+    const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
+
+    // 确保块大小至少为128KB
+    const minChunkSize = 128 * 1024; // 128KB
+
+    // 取理想块大小和最小块大小中的较大值
+    let chunkSize = Math.max(idealChunkSize, minChunkSize);
+
+    // 将块大小向上取整到最接近的64KB的倍数，使其更整齐
+    chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
+
+    return chunkSize;
+  })();
+
+  const uploadStream = gridBucket.openUploadStream(filename, {
+    metadata,
+    chunkSizeBytes
+  });
+
+  return retryFn(async () => {
+    return new Promise<{ fileId: string }>((resolve, reject) => {
+      uploadStream.end(buffer);
+      uploadStream.on('finish', () => {
+        resolve({ fileId: String(uploadStream.id) });
+      });
+      uploadStream.on('error', reject);
+    });
+  });
+};

 export const gridFsStream2Buffer = (stream: NodeJS.ReadableStream) => {
  return new Promise<Buffer>((resolve, reject) => {
--- a/packages/service/common/file/read/utils.ts
+++ b/packages/service/common/file/read/utils.ts
@@ -110,7 +110,7 @@ export const readRawContentByFileBuffer = async ({

    return {
      rawText: text,
-      formatText: rawText,
+      formatText: text,
      imageList
    };
  };
--- a/packages/service/common/system/timerLock/constants.ts
+++ b/packages/service/common/system/timerLock/constants.ts
@@ -5,7 +5,8 @@ export enum TimerIdEnum {
  clearExpiredSubPlan = 'clearExpiredSubPlan',
  updateStandardPlan = 'updateStandardPlan',
  scheduleTriggerApp = 'scheduleTriggerApp',
-  notification = 'notification'
+  notification = 'notification',
+  clearExpiredRawTextBuffer = 'clearExpiredRawTextBuffer'
 }

 export enum LockNotificationEnum {
--- a/packages/service/common/vectorDB/constants.ts
+++ b/packages/service/common/vectorDB/constants.ts
@@ -3,6 +3,5 @@ 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;
--- a/packages/service/common/vectorDB/controller.ts
+++ b/packages/service/common/vectorDB/controller.ts
@@ -1,11 +1,10 @@
 /* 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, OPENGAUSS_ADDRESS } from './constants';
+import { MILVUS_ADDRESS, PG_ADDRESS, OCEANBASE_ADDRESS } from './constants';
 import { MilvusCtrl } from './milvus';
 import { setRedisCache, getRedisCache, delRedisCache, CacheKeyEnum } from '../redis/cache';
 import { throttle } from 'lodash';
@@ -15,7 +14,6 @@ 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();
 };
--- a/packages/service/common/vectorDB/opengauss/controller.ts
+++ b/packages/service/common/vectorDB/opengauss/controller.ts
@@ -1,188 +0,0 @@
-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;
--- a/packages/service/common/vectorDB/opengauss/index.ts
+++ b/packages/service/common/vectorDB/opengauss/index.ts
@@ -1,253 +0,0 @@
-/* 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;
-  };
-}
--- a/packages/service/common/vectorDB/type.d.ts
+++ b/packages/service/common/vectorDB/type.d.ts
@@ -6,7 +6,6 @@ declare global {
  var pgClient: Pool | null;
  var obClient: MysqlPool | null;
  var milvusClient: MilvusClient | null;
-  var gsClient: Pool | null;
 }

 export type EmbeddingRecallItemType = {
--- a/packages/service/core/dataset/collection/controller.ts
+++ b/packages/service/core/dataset/collection/controller.ts
@@ -77,7 +77,10 @@ export const createCollectionAndInsertData = async ({
  const chunkSplitter = computeChunkSplitter(createCollectionParams);
  const paragraphChunkDeep = computeParagraphChunkDeep(createCollectionParams);

-  if (trainingType === DatasetCollectionDataProcessModeEnum.qa) {
+  if (
+    trainingType === DatasetCollectionDataProcessModeEnum.qa ||
+    trainingType === DatasetCollectionDataProcessModeEnum.backup
+  ) {
    delete createCollectionParams.chunkTriggerType;
    delete createCollectionParams.chunkTriggerMinSize;
    delete createCollectionParams.dataEnhanceCollectionName;
--- a/packages/service/core/dataset/read.ts
+++ b/packages/service/core/dataset/read.ts
@@ -218,6 +218,10 @@ export const rawText2Chunks = ({
    };
  };

+  if (backupParse) {
+    return parseDatasetBackup2Chunks(rawText).chunks;
+  }
+
  // Chunk condition
  // 1. 选择最大值条件，只有超过了最大值(默认为模型的最大值*0.7），才会触发分块
  if (chunkTriggerType === ChunkTriggerConfigTypeEnum.maxSize) {
@@ -240,10 +244,6 @@ export const rawText2Chunks = ({
    }
  }

-  if (backupParse) {
-    return parseDatasetBackup2Chunks(rawText).chunks;
-  }
-
  const { chunks } = splitText2Chunks({
    text: rawText,
    chunkSize,
--- a/packages/service/core/workflow/dispatch/agent/runTool/index.ts
+++ b/packages/service/core/workflow/dispatch/agent/runTool/index.ts
@@ -86,7 +86,6 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
    });

  // Check interactive entry
-  const interactiveResponse = lastInteractive;
  props.node.isEntry = false;
  const hasReadFilesTool = toolNodes.some(
    (item) => item.flowNodeType === FlowNodeTypeEnum.readFiles
@@ -143,7 +142,7 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
        })
      }
    ];
-    if (interactiveResponse) {
+    if (lastInteractive && isEntry) {
      return value.slice(0, -2);
    }
    return value;
@@ -183,7 +182,7 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
        toolModel,
        maxRunToolTimes: 30,
        messages: adaptMessages,
-        interactiveEntryToolParams: interactiveResponse?.toolParams
+        interactiveEntryToolParams: lastInteractive?.toolParams
      });
    }
    if (toolModel.functionCall) {
@@ -194,7 +193,7 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
        toolNodes,
        toolModel,
        messages: adaptMessages,
-        interactiveEntryToolParams: interactiveResponse?.toolParams
+        interactiveEntryToolParams: lastInteractive?.toolParams
      });
    }

@@ -224,7 +223,7 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
      toolNodes,
      toolModel,
      messages: adaptMessages,
-      interactiveEntryToolParams: interactiveResponse?.toolParams
+      interactiveEntryToolParams: lastInteractive?.toolParams
    });
  })();

--- a/packages/service/core/workflow/dispatch/index.ts
+++ b/packages/service/core/workflow/dispatch/index.ts
@@ -11,7 +11,6 @@ import type {
  SystemVariablesType
 } from '@fastgpt/global/core/workflow/runtime/type';
 import type { RuntimeNodeItemType } from '@fastgpt/global/core/workflow/runtime/type.d';
-import type { FlowNodeOutputItemType } from '@fastgpt/global/core/workflow/type/io.d';
 import type {
  AIChatItemValueItemType,
  ChatHistoryItemResType,
--- a/packages/service/core/workflow/dispatch/plugin/run.ts
+++ b/packages/service/core/workflow/dispatch/plugin/run.ts
@@ -17,6 +17,7 @@ import { chatValue2RuntimePrompt } from '@fastgpt/global/core/chat/adapt';
 import { getPluginRunUserQuery } from '@fastgpt/global/core/workflow/utils';
 import { getPluginInputsFromStoreNodes } from '@fastgpt/global/core/app/plugin/utils';
 import type { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
+import { getUserChatInfoAndAuthTeamPoints } from '../../../../support/permission/auth/team';

 type RunPluginProps = ModuleDispatchProps<{
  [NodeInputKeyEnum.forbidStream]?: boolean;
@@ -73,9 +74,11 @@ export const dispatchRunPlugin = async (props: RunPluginProps): Promise<RunPlugi
    };
  });

+  const { externalProvider } = await getUserChatInfoAndAuthTeamPoints(runningAppInfo.tmbId);
  const runtimeVariables = {
    ...filterSystemVariables(props.variables),
-    appId: String(plugin.id)
+    appId: String(plugin.id),
+    ...(externalProvider ? externalProvider.externalWorkflowVariables : {})
  };
  const { flowResponses, flowUsages, assistantResponses, runTimes } = await dispatchWorkFlow({
    ...props,
--- a/packages/service/core/workflow/dispatch/plugin/runApp.ts
+++ b/packages/service/core/workflow/dispatch/plugin/runApp.ts
@@ -20,6 +20,7 @@ import { ReadPermissionVal } from '@fastgpt/global/support/permission/constant';
 import { getAppVersionById } from '../../../app/version/controller';
 import { parseUrlToFileType } from '@fastgpt/global/common/file/tools';
 import { type ChildrenInteractive } from '@fastgpt/global/core/workflow/template/system/interactive/type';
+import { getUserChatInfoAndAuthTeamPoints } from '../../../../support/permission/auth/team';

 type Props = ModuleDispatchProps<{
  [NodeInputKeyEnum.userChatInput]: string;
@@ -97,11 +98,13 @@ export const dispatchRunAppNode = async (props: Props): Promise<Response> => {

  // Rewrite children app variables
  const systemVariables = filterSystemVariables(variables);
+  const { externalProvider } = await getUserChatInfoAndAuthTeamPoints(appData.tmbId);
  const childrenRunVariables = {
    ...systemVariables,
    ...childrenAppVariables,
    histories: chatHistories,
-    appId: String(appData._id)
+    appId: String(appData._id),
+    ...(externalProvider ? externalProvider.externalWorkflowVariables : {})
  };

  const childrenInteractive =
--- a/packages/service/core/workflow/dispatch/tools/readFiles.ts
+++ b/packages/service/core/workflow/dispatch/tools/readFiles.ts
@@ -5,8 +5,6 @@ import { NodeOutputKeyEnum } from '@fastgpt/global/core/workflow/constants';
 import { type DispatchNodeResultType } from '@fastgpt/global/core/workflow/runtime/type';
 import axios from 'axios';
 import { serverRequestBaseUrl } from '../../../../common/api/serverRequest';
-import { MongoRawTextBuffer } from '../../../../common/buffer/rawText/schema';
-import { readFromSecondary } from '../../../../common/mongo/utils';
 import { getErrText } from '@fastgpt/global/common/error/utils';
 import { detectFileEncoding, parseUrlToFileType } from '@fastgpt/global/common/file/tools';
 import { readRawContentByFileBuffer } from '../../../../common/file/read/utils';
@@ -14,6 +12,8 @@ import { ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
 import { type ChatItemType, type UserChatItemValueItemType } from '@fastgpt/global/core/chat/type';
 import { parseFileExtensionFromUrl } from '@fastgpt/global/common/string/tools';
 import { addLog } from '../../../../common/system/log';
+import { addRawTextBuffer, getRawTextBuffer } from '../../../../common/buffer/rawText/controller';
+import { addMinutes } from 'date-fns';

 type Props = ModuleDispatchProps<{
  [NodeInputKeyEnum.fileUrlList]: string[];
@@ -158,14 +158,12 @@ export const getFileContentFromLinks = async ({
    parseUrlList
      .map(async (url) => {
        // Get from buffer
-        const fileBuffer = await MongoRawTextBuffer.findOne({ sourceId: url }, undefined, {
-          ...readFromSecondary
-        }).lean();
+        const fileBuffer = await getRawTextBuffer(url);
        if (fileBuffer) {
          return formatResponseObject({
-            filename: fileBuffer.metadata?.filename || url,
+            filename: fileBuffer.sourceName || url,
            url,
-            content: fileBuffer.rawText
+            content: fileBuffer.text
          });
        }

@@ -220,17 +218,12 @@ export const getFileContentFromLinks = async ({
          });

          // Add to buffer
-          try {
-            if (buffer.length < 14 * 1024 * 1024 && rawText.trim()) {
-              MongoRawTextBuffer.create({
-                sourceId: url,
-                rawText,
-                metadata: {
-                  filename: filename
-                }
-              });
-            }
-          } catch (error) {}
+          addRawTextBuffer({
+            sourceId: url,
+            sourceName: filename,
+            text: rawText,
+            expiredTime: addMinutes(new Date(), 20)
+          });

          return formatResponseObject({ filename, url, content: rawText });
        } catch (error) {
--- a/packages/web/components/common/String/HighlightText.tsx
+++ b/packages/web/components/common/String/HighlightText.tsx
@@ -1,17 +1,26 @@
 import { Box } from '@chakra-ui/react';
-import React from 'react';
+import React, { useMemo } from 'react';

 const HighlightText = ({
  rawText,
  matchText,
-  color = 'primary.600'
+  color = 'primary.600',
+  mode = 'text'
 }: {
  rawText: string;
  matchText: string;
  color?: string;
+  mode?: 'text' | 'bg';
 }) => {
-  const regex = new RegExp(`(${matchText})`, 'gi');
-  const parts = rawText.split(regex);
+  const { parts } = useMemo(() => {
+    const regx = new RegExp(`(${matchText})`, 'gi');
+    const parts = rawText.split(regx);
+
+    return {
+      regx,
+      parts
+    };
+  }, [rawText, matchText]);

  return (
    <Box>
@@ -28,7 +37,17 @@ const HighlightText = ({
        }

        return (
-          <Box as="span" key={index} color={highLight ? color : 'inherit'}>
+          <Box
+            as="span"
+            key={index}
+            {...(mode === 'bg'
+              ? {
+                  bg: highLight ? color : 'transparent'
+                }
+              : {
+                  color: highLight ? color : 'inherit'
+                })}
+          >
            {part}
          </Box>
        );
@@ -37,4 +56,4 @@ const HighlightText = ({
  );
 };

-export default HighlightText;
+export default React.memo(HighlightText);
--- a/packages/web/hooks/useSystem.ts
+++ b/packages/web/hooks/useSystem.ts
@@ -3,6 +3,8 @@ import { useContextSelector } from 'use-context-selector';

 export const useSystem = () => {
  const isPc = useContextSelector(useSystemStoreContext, (state) => state.isPc);
+  const isMac =
+    typeof window !== 'undefined' && window.navigator.userAgent.toLocaleLowerCase().includes('mac');

-  return { isPc };
+  return { isPc, isMac };
 };
--- a/packages/web/i18n/en/workflow.json
+++ b/packages/web/i18n/en/workflow.json
@@ -63,6 +63,8 @@
  "field_required": "Required",
  "field_used_as_tool_input": "Used as Tool Call Parameter",
  "filter_description": "Currently supports filtering by tags and creation time. Fill in the format as follows:\n{\n  \"tags\": {\n    \"$and\": [\"Tag 1\",\"Tag 2\"],\n    \"$or\": [\"When there are $and tags, and is effective, or is not effective\"]\n  },\n  \"createTime\": {\n      \"$gte\": \"YYYY-MM-DD HH:mm format, collection creation time greater than this time\",\n      \"$lte\": \"YYYY-MM-DD HH:mm format, collection creation time less than this time, can be used with $gte\"\n  }\n}",
+  "find_tip": "Find node ctrl f",
+  "find_tip_mac": "Find node ⌘ f",
  "foldAll": "Collapse all",
  "form_input_result": "User complete input result",
  "form_input_result_tip": "an object containing the complete result",
@@ -123,18 +125,23 @@
  "max_tokens": "Maximum Tokens",
  "mouse_priority": "Mouse first\n- Press the left button to drag the canvas\n- Hold down shift and left click to select batches",
  "new_context": "New Context",
+  "next": "Next",
+  "no_match_node": "No results",
+  "no_node_found": "No node was not found",
  "not_contains": "Does Not Contain",
  "only_the_reference_type_is_supported": "Only reference type is supported",
  "optional_value_type": "Optional Value Type",
  "optional_value_type_tip": "You can specify one or more data types. When dynamically adding fields, users can only select the configured types.",
  "pan_priority": "Touchpad first\n- Click to batch select\n- Move the canvas with two fingers",
  "pass_returned_object_as_output_to_next_nodes": "Pass the object returned in the code as output to the next nodes. The variable name needs to correspond to the return key.",
+  "please_enter_node_name": "Enter the node name",
  "plugin.Instruction_Tip": "You can configure an instruction to explain the purpose of the plugin. This instruction will be displayed each time the plugin is used. Supports standard Markdown syntax.",
  "plugin.Instructions": "Instructions",
  "plugin.global_file_input": "File links (deprecated)",
  "plugin_file_abandon_tip": "Plugin global file upload has been deprecated, please adjust it as soon as possible. \nRelated functions can be achieved through plug-in input and adding image type input.",
  "plugin_input": "Plugin Input",
  "plugin_output_tool": "When the plug-in is executed as a tool, whether this field responds as a result of the tool",
+  "previous": "Previous",
  "question_classification": "Classify",
  "question_optimization": "Query extension",
  "quote_content_placeholder": "The structure of the reference content can be customized to better suit different scenarios. \nSome variables can be used for template configuration\n\n{{q}} - main content\n\n{{a}} - auxiliary data\n\n{{source}} - source name\n\n{{sourceId}} - source ID\n\n{{index}} - nth reference",
@@ -177,9 +184,9 @@
  "text_content_extraction": "Text Extract",
  "text_to_extract": "Text to Extract",
  "these_variables_will_be_input_parameters_for_code_execution": "These variables will be input parameters for code execution",
-  "tool.tool_result": "Tool operation results",
  "to_add_node": "to add",
  "to_connect_node": "to connect",
+  "tool.tool_result": "Tool operation results",
  "tool_call_termination": "Stop ToolCall",
  "tool_custom_field": "Custom Tool",
  "tool_field": " Tool Field Parameter Configuration",
--- a/packages/web/i18n/zh-CN/workflow.json
+++ b/packages/web/i18n/zh-CN/workflow.json
@@ -63,6 +63,8 @@
  "field_required": "必填",
  "field_used_as_tool_input": "作为工具调用参数",
  "filter_description": "目前支持标签和创建时间过滤，需按照以下格式填写：\n{\n  \"tags\": {\n    \"$and\": [\"标签 1\",\"标签 2\"],\n    \"$or\": [\"有 $and 标签时，and 生效，or 不生效\"]\n  },\n  \"createTime\": {\n      \"$gte\": \"YYYY-MM-DD HH:mm 格式即可，集合的创建时间大于该时间\",\n      \"$lte\": \"YYYY-MM-DD HH:mm 格式即可，集合的创建时间小于该时间,可和 $gte 共同使用\"\n  }\n}",
+  "find_tip": "查找节点 ctrl f",
+  "find_tip_mac": "查找节点  ⌘  f",
  "foldAll": "全部折叠",
  "form_input_result": "用户完整输入结果",
  "form_input_result_tip": "一个包含完整结果的对象",
@@ -123,18 +125,23 @@
  "max_tokens": "最大 Tokens",
  "mouse_priority": "鼠标优先\n- 左键按下后可拖动画布\n- 按住 shift 后左键可批量选择",
  "new_context": "新的上下文",
+  "next": "下一个",
+  "no_match_node": "无结果",
+  "no_node_found": "未搜索到节点",
  "not_contains": "不包含",
  "only_the_reference_type_is_supported": "仅支持引用类型",
  "optional_value_type": "可选的数据类型",
  "optional_value_type_tip": "可以指定 1 个或多个数据类型，用户在动态添加字段时，仅可选择配置的类型",
  "pan_priority": "触摸板优先\n- 单击批量选择\n- 双指移动画布",
  "pass_returned_object_as_output_to_next_nodes": "将代码中 return 的对象作为输出，传递给后续的节点。变量名需要对应 return 的 key",
+  "please_enter_node_name": "请输入节点名称",
  "plugin.Instruction_Tip": "可以配置一段说明，以解释该插件的用途。每次使用插件前，会显示该段说明。支持标准 Markdown 语法。",
  "plugin.Instructions": "使用说明",
  "plugin.global_file_input": "文件链接(弃用)",
  "plugin_file_abandon_tip": "插件全局文件上传已弃用，请尽快调整。可以通过插件输入，添加图片类型输入来实现相关功能。",
  "plugin_input": "插件输入",
  "plugin_output_tool": "插件作为工具执行时，该字段是否作为工具响应结果",
+  "previous": "上一个",
  "question_classification": "问题分类",
  "question_optimization": "问题优化",
  "quote_content_placeholder": "可以自定义引用内容的结构，以更好的适配不同场景。可以使用一些变量来进行模板配置\n{{q}} - 主要内容\n{{a}} - 辅助数据\n{{source}} - 来源名\n{{sourceId}} - 来源ID\n{{index}} - 第 n 个引用",
--- a/packages/web/i18n/zh-Hant/workflow.json
+++ b/packages/web/i18n/zh-Hant/workflow.json
@@ -63,6 +63,8 @@
  "field_required": "必填",
  "field_used_as_tool_input": "作為工具呼叫參數",
  "filter_description": "目前支援標籤和建立時間篩選，需按照以下格式填寫：\n{\n  \"tags\": {\n    \"$and\": [\"標籤 1\",\"標籤 2\"],\n    \"$or\": [\"當有 $and 標籤時，$and 才會生效，$or 不會生效\"]\n  },\n  \"createTime\": {\n      \"$gte\": \"YYYY-MM-DD HH:mm 格式，資料集的建立時間大於這個時間\",\n      \"$lte\": \"YYYY-MM-DD HH:mm 格式，資料集的建立時間小於這個時間，可以和 $gte 一起使用\"\n  }\n}",
+  "find_tip": "查找節點 ctrl f",
+  "find_tip_mac": "查找節點 ⌘ f",
  "foldAll": "全部折疊",
  "form_input_result": "使用者完整輸入結果",
  "form_input_result_tip": "一個包含完整結果的物件",
@@ -123,18 +125,23 @@
  "max_tokens": "最大 Token 數",
  "mouse_priority": "滑鼠優先\n- 按下左鍵拖曳畫布\n- 按住 Shift 鍵並點選左鍵可批次選取",
  "new_context": "新的脈絡",
+  "next": "下一個",
+  "no_match_node": "無結果",
+  "no_node_found": "未搜索到節點",
  "not_contains": "不包含",
  "only_the_reference_type_is_supported": "僅支援引用類型",
  "optional_value_type": "可選的資料類型",
  "optional_value_type_tip": "可以指定一或多個資料類型，使用者在動態新增欄位時，只能選擇已設定的類型",
  "pan_priority": "觸控板優先\n- 點選可批次選取\n- 使用兩指移動畫布",
  "pass_returned_object_as_output_to_next_nodes": "將程式碼中 return 的物件作為輸出，傳遞給後續的節點。變數名稱需要對應 return 的鍵值",
+  "please_enter_node_name": "請輸入節點名稱",
  "plugin.Instruction_Tip": "您可以設定一段說明來解釋這個外掛程式的用途。每次使用外掛程式前，都會顯示這段說明。支援標準 Markdown 語法。",
  "plugin.Instructions": "使用說明",
  "plugin.global_file_input": "檔案連結（已淘汰）",
  "plugin_file_abandon_tip": "外掛程式全域檔案上傳功能已淘汰，請儘速調整。您可以透過外掛程式輸入，新增圖片類型輸入來達成相關功能。",
  "plugin_input": "外掛程式輸入",
  "plugin_output_tool": "外掛程式作為工具執行時，這個欄位是否作為工具的回應結果",
+  "previous": "上一個",
  "question_classification": "問題分類",
  "question_optimization": "問題最佳化",
  "quote_content_placeholder": "可以自訂引用內容的結構，以便更好地適應不同場景。可以使用一些變數來設定範本\n{{q}} - 主要內容\n{{a}} - 輔助資料\n{{source}} - 來源名稱\n{{sourceId}} - 來源 ID\n{{index}} - 第 n 個引用",
@@ -177,9 +184,9 @@
  "text_content_extraction": "文字內容擷取",
  "text_to_extract": "要擷取的文字",
  "these_variables_will_be_input_parameters_for_code_execution": "這些變數會作為程式碼執行的輸入參數",
-  "tool.tool_result": "工具運行結果",
  "to_add_node": "添加節點",
  "to_connect_node": "連接節點",
+  "tool.tool_result": "工具運行結果",
  "tool_call_termination": "工具呼叫終止",
  "tool_custom_field": "自訂工具變數",
  "tool_field": "工具參數設定",
--- a/projects/app/.env.template
+++ b/projects/app/.env.template
@@ -29,8 +29,6 @@ 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=
--- a/projects/app/src/instrumentation.ts
+++ b/projects/app/src/instrumentation.ts
@@ -39,6 +39,12 @@ export async function register() {
      systemStartCb();
      initGlobalVariables();

+      try {
+        await preLoadWorker();
+      } catch (error) {
+        console.error('Preload worker error', error);
+      }
+
      // Connect to MongoDB
      await connectMongo(connectionMongo, MONGO_URL);
      connectMongo(connectionLogMongo, MONGO_LOG_URL);
@@ -54,12 +60,6 @@ export async function register() {
      startCron();
      startTrainingQueue(true);

-      try {
-        await preLoadWorker();
-      } catch (error) {
-        console.error('Preload worker error', error);
-      }
-
      console.log('Init system success');
    }
  } catch (error) {
--- a/projects/app/src/pageComponents/app/detail/Plugin/Header.tsx
+++ b/projects/app/src/pageComponents/app/detail/Plugin/Header.tsx
@@ -25,16 +25,20 @@ import MyModal from '@fastgpt/web/components/common/MyModal';
 import { formatTime2YMDHMS } from '@fastgpt/global/common/string/time';
 import { useToast } from '@fastgpt/web/hooks/useToast';
 import { useSystemStore } from '@/web/common/system/useSystemStore';
-import SaveButton from '../Workflow/components/SaveButton';
 import PublishHistories from '../PublishHistoriesSlider';
 import { WorkflowEventContext } from '../WorkflowComponents/context/workflowEventContext';
 import { WorkflowStatusContext } from '../WorkflowComponents/context/workflowStatusContext';
+import SaveButton from '../Workflow/components/SaveButton';

 const Header = () => {
  const { t } = useTranslation();
  const { isPc } = useSystem();
  const router = useRouter();
-  const { toast } = useToast();
+  const { toast: backSaveToast } = useToast({
+    containerStyle: {
+      mt: '60px'
+    }
+  });

  const { appDetail, onSaveApp, currentTab } = useContextSelector(AppContext, (v) => v);
  const isV2Workflow = appDetail?.version === 'v2';
@@ -183,6 +187,7 @@ const Header = () => {
                size={'sm'}
                leftIcon={<MyIcon name={'core/workflow/debug'} w={['14px', '16px']} />}
                variant={'whitePrimary'}
+                flexShrink={0}
                onClick={() => {
                  const data = flowData2StoreDataAndCheck();
                  if (data) {
@@ -211,12 +216,12 @@ const Header = () => {
    onBack,
    onOpenBackConfirm,
    isV2Workflow,
-    showHistoryModal,
    t,
+    showHistoryModal,
    loading,
    onClickSave,
-    flowData2StoreDataAndCheck,
    setShowHistoryModal,
+    flowData2StoreDataAndCheck,
    setWorkflowTestData
  ]);

@@ -229,10 +234,11 @@ const Header = () => {
            setShowHistoryModal(false);
          }}
          past={past}
-          onSwitchTmpVersion={onSwitchTmpVersion}
          onSwitchCloudVersion={onSwitchCloudVersion}
+          onSwitchTmpVersion={onSwitchTmpVersion}
        />
      )}
+
      <MyModal
        isOpen={isOpenBackConfirm}
        onClose={onCloseBackConfirm}
@@ -254,7 +260,7 @@ const Header = () => {
                await onClickSave({});
                onCloseBackConfirm();
                onBack();
-                toast({
+                backSaveToast({
                  status: 'success',
                  title: t('app:saved_success'),
                  position: 'top-right'
--- a/projects/app/src/pageComponents/app/detail/Workflow/Header.tsx
+++ b/projects/app/src/pageComponents/app/detail/Workflow/Header.tsx
@@ -13,7 +13,7 @@ import { useTranslation } from 'next-i18next';

 import MyIcon from '@fastgpt/web/components/common/Icon';
 import { useContextSelector } from 'use-context-selector';
-import { WorkflowContext } from '../WorkflowComponents/context';
+import { WorkflowContext, type WorkflowSnapshotsType } from '../WorkflowComponents/context';
 import { AppContext, TabEnum } from '../context';
 import RouteTab from '../RouteTab';
 import { useRouter } from 'next/router';
@@ -25,10 +25,10 @@ import MyModal from '@fastgpt/web/components/common/MyModal';
 import { formatTime2YMDHMS } from '@fastgpt/global/common/string/time';
 import { useToast } from '@fastgpt/web/hooks/useToast';
 import { useSystemStore } from '@/web/common/system/useSystemStore';
-import SaveButton from './components/SaveButton';
 import PublishHistories from '../PublishHistoriesSlider';
 import { WorkflowEventContext } from '../WorkflowComponents/context/workflowEventContext';
 import { WorkflowStatusContext } from '../WorkflowComponents/context/workflowStatusContext';
+import SaveButton from '../Workflow/components/SaveButton';

 const Header = () => {
  const { t } = useTranslation();
@@ -187,6 +187,7 @@ const Header = () => {
                size={'sm'}
                leftIcon={<MyIcon name={'core/workflow/debug'} w={['14px', '16px']} />}
                variant={'whitePrimary'}
+                flexShrink={0}
                onClick={() => {
                  const data = flowData2StoreDataAndCheck();
                  if (data) {
@@ -215,12 +216,12 @@ const Header = () => {
    onBack,
    onOpenBackConfirm,
    isV2Workflow,
-    showHistoryModal,
    t,
+    showHistoryModal,
    loading,
    onClickSave,
-    flowData2StoreDataAndCheck,
    setShowHistoryModal,
+    flowData2StoreDataAndCheck,
    setWorkflowTestData
  ]);

@@ -228,7 +229,7 @@ const Header = () => {
    <>
      {Render}
      {showHistoryModal && isV2Workflow && currentTab === TabEnum.appEdit && (
-        <PublishHistories
+        <PublishHistories<WorkflowSnapshotsType>
          onClose={() => {
            setShowHistoryModal(false);
          }}
--- a/projects/app/src/pageComponents/app/detail/Workflow/components/SaveButton.tsx
+++ b/projects/app/src/pageComponents/app/detail/Workflow/components/SaveButton.tsx
@@ -43,6 +43,7 @@ const SaveButton = ({
      Trigger={
        <Button
          size={'sm'}
+          flexShrink={0}
          rightIcon={
            <MyIcon
              name={isSave ? 'core/chat/chevronUp' : 'core/chat/chevronDown'}
--- a/projects/app/src/pageComponents/app/detail/Workflow/components/SearchButton.tsx
+++ b/projects/app/src/pageComponents/app/detail/Workflow/components/SearchButton.tsx
@@ -0,0 +1,220 @@
+import React, { useState, useCallback } from 'react';
+import { Box, Flex, Button, IconButton, type ButtonProps, Input } from '@chakra-ui/react';
+import { useTranslation } from 'next-i18next';
+import { useContextSelector } from 'use-context-selector';
+import { WorkflowNodeEdgeContext } from '../../WorkflowComponents/context/workflowInitContext';
+import { useReactFlow } from 'reactflow';
+import { useKeyPress, useThrottleEffect } from 'ahooks';
+import MyIcon from '@fastgpt/web/components/common/Icon';
+import MyTooltip from '@fastgpt/web/components/common/MyTooltip';
+import { useSystem } from '@fastgpt/web/hooks/useSystem';
+
+const SearchButton = (props: ButtonProps) => {
+  const { t } = useTranslation();
+  const setNodes = useContextSelector(WorkflowNodeEdgeContext, (state) => state.setNodes);
+  const { fitView } = useReactFlow();
+  const { isMac } = useSystem();
+
+  const [keyword, setKeyword] = useState<string>();
+  const [searchIndex, setSearchIndex] = useState<number>(0);
+  const [searchedNodeCount, setSearchedNodeCount] = useState(0);
+
+  useKeyPress(['ctrl.f', 'meta.f'], (e) => {
+    e.preventDefault();
+    e.stopPropagation();
+    setKeyword('');
+  });
+  useKeyPress(['esc'], (e) => {
+    e.preventDefault();
+    e.stopPropagation();
+    setKeyword(undefined);
+  });
+
+  const onSearch = useCallback(() => {
+    setNodes((nodes) => {
+      if (!keyword) {
+        setSearchIndex(0);
+        setSearchedNodeCount(0);
+        return nodes.map((node) => ({
+          ...node,
+          data: {
+            ...node.data,
+            searchedText: undefined
+          }
+        }));
+      }
+
+      const searchResult = nodes.filter((node) => {
+        const nodeName = t(node.data.name as any);
+        return nodeName.toLowerCase().includes(keyword.toLowerCase());
+      });
+
+      if (searchResult.length === 0) {
+        return nodes.map((node) => ({
+          ...node,
+          data: {
+            ...node.data,
+            searchedText: undefined
+          }
+        }));
+      }
+
+      setSearchedNodeCount(searchResult.length);
+
+      const searchedNode = searchResult[searchIndex] ?? searchResult[0];
+
+      if (searchedNode) {
+        fitView({ nodes: [searchedNode], padding: 0.4 });
+      }
+
+      return nodes.map((node) => ({
+        ...node,
+        selected: node.id === searchedNode.id,
+        data: {
+          ...node.data,
+          searchedText: searchResult.find((item) => item.id === node.id) ? keyword : undefined
+        }
+      }));
+    });
+  }, [keyword, searchIndex]);
+
+  useThrottleEffect(
+    () => {
+      onSearch();
+    },
+    [onSearch],
+    {
+      wait: 500
+    }
+  );
+
+  const goToNextMatch = useCallback(() => {
+    if (searchIndex === searchedNodeCount - 1) {
+      setSearchIndex(0);
+    } else {
+      setSearchIndex(searchIndex + 1);
+    }
+  }, [searchIndex, searchedNodeCount]);
+
+  const goToPreviousMatch = useCallback(() => {
+    if (searchIndex === 0) {
+      setSearchIndex(searchedNodeCount - 1);
+    } else {
+      setSearchIndex(searchIndex - 1);
+    }
+  }, [searchIndex, searchedNodeCount]);
+
+  const clearSearch = useCallback(() => {
+    setKeyword(undefined);
+    setSearchIndex(0);
+    setSearchedNodeCount(0);
+  }, []);
+
+  if (keyword === undefined) {
+    return (
+      <Box position={'absolute'} top={'72px'} left={6} zIndex={1}>
+        <MyTooltip label={isMac ? t('workflow:find_tip_mac') : t('workflow:find_tip')}>
+          <IconButton
+            icon={<MyIcon name="common/searchLight" w="20px" color={'#8A95A7'} />}
+            aria-label=""
+            variant="whitePrimary"
+            size={'mdSquare'}
+            borderRadius={'50%'}
+            bg={'white'}
+            _hover={{ bg: 'white', borderColor: 'primary.300' }}
+            boxShadow={'0px 4px 10px 0px rgba(19, 51, 107, 0.20)'}
+            {...props}
+            onClick={() => setKeyword('')}
+          />
+        </MyTooltip>
+      </Box>
+    );
+  }
+
+  return (
+    <Flex
+      position="absolute"
+      top={3}
+      left="50%"
+      transform="translateX(-50%)"
+      pl={5}
+      pr={4}
+      py={4}
+      zIndex={1}
+      borderRadius={'lg'}
+      bg={'white'}
+      alignItems={'center'}
+      boxShadow={
+        '0px 20px 24px -8px rgba(19, 51, 107, 0.15), 0px 0px 1px 0px rgba(19, 51, 107, 0.15)'
+      }
+      border={'0.5px solid rgba(0, 0, 0, 0.13)'}
+      maxW={['90vw', '550px']}
+      w={'100%'}
+    >
+      <Input
+        flex="1 0 0"
+        h={8}
+        border={'none'}
+        px={0}
+        _focus={{
+          border: 'none',
+          boxShadow: 'none'
+        }}
+        fontSize={'16px'}
+        value={keyword}
+        placeholder={t('workflow:please_enter_node_name')}
+        autoFocus
+        onFocus={onSearch}
+        onChange={(e) => setKeyword(e.target.value)}
+        onKeyDown={(e) => {
+          if (e.key === 'Enter') {
+            e.preventDefault();
+            e.stopPropagation();
+            goToNextMatch();
+          }
+        }}
+      />
+
+      <Box fontSize="sm" color="myGray.600" whiteSpace={'nowrap'} userSelect={'none'}>
+        {searchedNodeCount > 0
+          ? `${searchIndex + 1} / ${searchedNodeCount}`
+          : t('workflow:no_match_node')}
+      </Box>
+
+      {/* Border */}
+      <Box h={5} w={'1px'} bg={'myGray.250'} ml={3} mr={2} />
+
+      <Button
+        size="xs"
+        variant="grayGhost"
+        px={2}
+        isDisabled={searchedNodeCount <= 1}
+        onClick={goToPreviousMatch}
+      >
+        {t('workflow:previous')}
+      </Button>
+      <Button
+        size="xs"
+        variant="grayGhost"
+        px={2}
+        isDisabled={searchedNodeCount <= 1}
+        onClick={goToNextMatch}
+      >
+        {t('workflow:next')}
+      </Button>
+
+      <Flex
+        ml={2}
+        borderRadius="sm"
+        _hover={{ bg: 'myGray.100' }}
+        p={'1'}
+        cursor="pointer"
+        onClick={clearSearch}
+      >
+        <MyIcon name="common/closeLight" w="1.2rem" />
+      </Flex>
+    </Flex>
+  );
+};
+
+export default React.memo(SearchButton);
--- a/projects/app/src/pageComponents/app/detail/WorkflowComponents/Flow/index.tsx
+++ b/projects/app/src/pageComponents/app/detail/WorkflowComponents/Flow/index.tsx
@@ -1,7 +1,6 @@
 import React from 'react';
 import ReactFlow, { type NodeProps, SelectionMode } from 'reactflow';
 import { Box, IconButton, useDisclosure } from '@chakra-ui/react';
-import { SmallCloseIcon } from '@chakra-ui/icons';
 import { EDGE_TYPE, FlowNodeTypeEnum } from '@fastgpt/global/core/workflow/node/constant';

 import dynamic from 'next/dynamic';
@@ -20,6 +19,8 @@ import ContextMenu from './components/ContextMenu';
 import { WorkflowNodeEdgeContext, WorkflowInitContext } from '../context/workflowInitContext';
 import { WorkflowEventContext } from '../context/workflowEventContext';
 import NodeTemplatesPopover from './NodeTemplatesPopover';
+import SearchButton from '../../Workflow/components/SearchButton';
+import MyIcon from '@fastgpt/web/components/common/Icon';

 const NodeSimple = dynamic(() => import('./nodes/NodeSimple'));
 const nodeTypes: Record<FlowNodeTypeEnum, any> = {
@@ -113,20 +114,22 @@ const Workflow = () => {
        <>
          <IconButton
            position={'absolute'}
-            top={5}
-            left={5}
+            top={6}
+            left={6}
            size={'mdSquare'}
            borderRadius={'50%'}
-            icon={<SmallCloseIcon fontSize={'26px'} />}
-            transform={isOpenTemplate ? '' : 'rotate(135deg)'}
+            icon={<MyIcon name="common/addLight" w={'26px'} />}
            transition={'0.2s ease'}
            aria-label={''}
            zIndex={1}
-            boxShadow={'2px 2px 6px #85b1ff'}
+            boxShadow={
+              '0px 4px 10px 0px rgba(19, 51, 107, 0.20), 0px 0px 1px 0px rgba(19, 51, 107, 0.50)'
+            }
            onClick={() => {
              isOpenTemplate ? onCloseTemplate() : onOpenTemplate();
            }}
          />
+          <SearchButton />
          <NodeTemplatesModal isOpen={isOpenTemplate} onClose={onCloseTemplate} />
          <NodeTemplatesPopover />
        </>
--- a/projects/app/src/pageComponents/app/detail/WorkflowComponents/Flow/nodes/render/NodeCard.tsx
+++ b/projects/app/src/pageComponents/app/detail/WorkflowComponents/Flow/nodes/render/NodeCard.tsx
@@ -36,6 +36,7 @@ import MyTag from '@fastgpt/web/components/common/Tag/index';
 import MySelect from '@fastgpt/web/components/common/MySelect';
 import { useCreation } from 'ahooks';
 import { formatToolError } from '@fastgpt/global/core/app/utils';
+import HighlightText from '@fastgpt/web/components/common/String/HighlightText';

 type Props = FlowNodeItemType & {
  children?: React.ReactNode | React.ReactNode[] | string;
@@ -45,6 +46,7 @@ type Props = FlowNodeItemType & {
  w?: string | number;
  h?: string | number;
  selected?: boolean;
+  searchedText?: string;
  menuForbid?: {
    debug?: boolean;
    copy?: boolean;
@@ -70,6 +72,7 @@ const NodeCard = (props: Props) => {
    h = 'full',
    nodeId,
    selected,
+    searchedText,
    menuForbid,
    isTool = false,
    isError = false,
@@ -187,7 +190,12 @@ const NodeCard = (props: Props) => {
                h={'24px'}
              />
              <Box ml={2} fontSize={'18px'} fontWeight={'medium'} color={'myGray.900'}>
-                {t(name as any)}
+                <HighlightText
+                  rawText={t(name as any)}
+                  matchText={searchedText ?? ''}
+                  mode={'bg'}
+                  color={'#ffe82d'}
+                />
              </Box>
              <Button
                display={'none'}
@@ -280,6 +288,7 @@ const NodeCard = (props: Props) => {
    nodeId,
    isFolded,
    avatar,
+    searchedText,
    t,
    name,
    showVersion,
--- a/projects/app/src/pageComponents/dataset/detail/Import/diffSource/FileCustomText.tsx
+++ b/projects/app/src/pageComponents/dataset/detail/Import/diffSource/FileCustomText.tsx
@@ -49,7 +49,7 @@ const CustomTextInput = () => {
          createStatus: 'waiting',
          rawText: data.value,
          sourceName: data.name,
-          icon: 'file/fill/manual'
+          icon: 'file/fill/txt'
        }
      ]);
      goToNext();
--- a/projects/app/src/pages/api/core/app/list.ts
+++ b/projects/app/src/pages/api/core/app/list.ts
@@ -138,18 +138,20 @@ async function handler(req: ApiRequestProps<ListAppBody>): Promise<AppListItemTy
  })();
  const limit = (() => {
    if (getRecentlyChat) return 15;
-    if (searchKey) return 20;
-    return 1000;
+    if (searchKey) return 50;
+    return;
  })();

  const myApps = await MongoApp.find(
    findAppsQuery,
-    '_id parentId avatar type name intro tmbId updateTime pluginData inheritPermission'
+    '_id parentId avatar type name intro tmbId updateTime pluginData inheritPermission',
+    {
+      limit: limit
+    }
  )
    .sort({
      updateTime: -1
    })
-    .limit(limit)
    .lean();

  // Add app permission and filter apps by read permission
--- a/projects/app/src/pages/api/core/dataset/collection/create/fileId.ts
+++ b/projects/app/src/pages/api/core/dataset/collection/create/fileId.ts
@@ -4,11 +4,11 @@ import { type FileIdCreateDatasetCollectionParams } from '@fastgpt/global/core/d
 import { createCollectionAndInsertData } from '@fastgpt/service/core/dataset/collection/controller';
 import { DatasetCollectionTypeEnum } from '@fastgpt/global/core/dataset/constants';
 import { BucketNameEnum } from '@fastgpt/global/common/file/constants';
-import { MongoRawTextBuffer } from '@fastgpt/service/common/buffer/rawText/schema';
 import { NextAPI } from '@/service/middleware/entry';
 import { type ApiRequestProps } from '@fastgpt/service/type/next';
 import { WritePermissionVal } from '@fastgpt/global/support/permission/constant';
 import { type CreateCollectionResponse } from '@/global/core/dataset/api';
+import { deleteRawTextBuffer } from '@fastgpt/service/common/buffer/rawText/controller';

 async function handler(
  req: ApiRequestProps<FileIdCreateDatasetCollectionParams>
@@ -52,7 +52,7 @@ async function handler(
  });

  // remove buffer
-  await MongoRawTextBuffer.deleteOne({ sourceId: fileId });
+  await deleteRawTextBuffer(fileId);

  return {
    collectionId,
--- a/projects/app/src/pages/api/core/dataset/collection/create/text.ts
+++ b/projects/app/src/pages/api/core/dataset/collection/create/text.ts
@@ -6,6 +6,7 @@ import { DatasetCollectionTypeEnum } from '@fastgpt/global/core/dataset/constant
 import { NextAPI } from '@/service/middleware/entry';
 import { WritePermissionVal } from '@fastgpt/global/support/permission/constant';
 import { type CreateCollectionResponse } from '@/global/core/dataset/api';
+import { createFileFromText } from '@fastgpt/service/common/file/gridfs/utils';

 async function handler(req: NextApiRequest): CreateCollectionResponse {
  const { name, text, ...body } = req.body as TextCreateDatasetCollectionParams;
@@ -18,6 +19,18 @@ async function handler(req: NextApiRequest): CreateCollectionResponse {
    per: WritePermissionVal
  });

+  // 1. Create file from text
+  const filename = `${name}.txt`;
+  const { fileId } = await createFileFromText({
+    bucket: 'dataset',
+    filename,
+    text,
+    metadata: {
+      teamId,
+      uid: tmbId
+    }
+  });
+
  const { collectionId, insertResults } = await createCollectionAndInsertData({
    dataset,
    rawText: text,
@@ -25,9 +38,9 @@ async function handler(req: NextApiRequest): CreateCollectionResponse {
      ...body,
      teamId,
      tmbId,
-      type: DatasetCollectionTypeEnum.virtual,
-
-      name
+      type: DatasetCollectionTypeEnum.file,
+      fileId,
+      name: filename
    }
  });

--- a/projects/app/src/service/common/system/cron.ts
+++ b/projects/app/src/service/common/system/cron.ts
@@ -11,6 +11,7 @@ import { checkTimerLock } from '@fastgpt/service/common/system/timerLock/utils';
 import { TimerIdEnum } from '@fastgpt/service/common/system/timerLock/constants';
 import { addHours } from 'date-fns';
 import { getScheduleTriggerApp } from '@/service/core/app/utils';
+import { clearExpiredRawTextBufferCron } from '@fastgpt/service/common/buffer/rawText/controller';

 // Try to run train every minute
 const setTrainingQueueCron = () => {
@@ -83,4 +84,5 @@ export const startCron = () => {
  setClearTmpUploadFilesCron();
  clearInvalidDataCron();
  scheduleTriggerAppCron();
+  clearExpiredRawTextBufferCron();
 };
--- a/projects/app/src/service/core/dataset/queues/generateQA.ts
+++ b/projects/app/src/service/core/dataset/queues/generateQA.ts
@@ -2,7 +2,7 @@ import { MongoDatasetTraining } from '@fastgpt/service/core/dataset/training/sch
 import { pushQAUsage } from '@/service/support/wallet/usage/push';
 import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
 import { createChatCompletion } from '@fastgpt/service/core/ai/config';
-import type { ChatCompletionMessageParam, StreamChatType } from '@fastgpt/global/core/ai/type.d';
+import type { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type.d';
 import { addLog } from '@fastgpt/service/common/system/log';
 import { splitText2Chunks } from '@fastgpt/global/common/string/textSplitter';
 import { replaceVariable } from '@fastgpt/global/common/string/tools';
--- a/projects/app/src/service/core/dataset/queues/generateVector.ts
+++ b/projects/app/src/service/core/dataset/queues/generateVector.ts
--- a/projects/app/src/service/core/dataset/queues/utils.ts
+++ b/projects/app/src/service/core/dataset/queues/utils.ts
@@ -1,6 +1,6 @@
 import { TeamErrEnum } from '@fastgpt/global/common/error/code/team';
 import { checkTeamAIPoints } from '@fastgpt/service/support/permission/teamLimit';
-import { sendOneInform } from '../support/user/inform/api';
+import { sendOneInform } from '../../../support/user/inform/api';
 import { lockTrainingDataByTeamId } from '@fastgpt/service/core/dataset/training/controller';
 import { InformLevelEnum } from '@fastgpt/global/support/user/inform/constants';

@@ -18,7 +18,7 @@ export const checkTeamAiPointsAndLock = async (teamId: string) => {
          templateParam: {},
          teamId
        });
-        console.log('余额不足，暂停【向量】生成任务');
+        console.log('余额不足，暂停训练生成任务');
        await lockTrainingDataByTeamId(teamId);
      } catch (error) {}
    }
--- a/projects/app/src/service/core/dataset/training/utils.ts
+++ b/projects/app/src/service/core/dataset/training/utils.ts
@@ -1,5 +1,5 @@
-import { generateQA } from '@/service/events/generateQA';
-import { generateVector } from '@/service/events/generateVector';
+import { generateQA } from '@/service/core/dataset/queues/generateQA';
+import { generateVector } from '@/service/core/dataset/queues/generateVector';
 import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
 import { type DatasetTrainingSchemaType } from '@fastgpt/global/core/dataset/type';
 import { MongoDatasetTraining } from '@fastgpt/service/core/dataset/training/schema';
--- a/test/cases/components/Markdown/utils.test.ts
+++ b/test/cases/components/Markdown/utils.test.ts
@@ -1,5 +1,5 @@
 import { describe, it, expect } from 'vitest';
-import { mdTextFormat, CodeClassNameEnum } from '@/components/Markdown/utils';
+import { mdTextFormat, CodeClassNameEnum, filterSafeProps } from '@/components/Markdown/utils';

 describe('Markdown utils', () => {
  describe('mdTextFormat', () => {
@@ -56,4 +56,121 @@ describe('Markdown utils', () => {
      expect(CodeClassNameEnum.audio).toBe('audio');
    });
  });
+
+  describe('filterSafeProps', () => {
+    const allowedAttrs = new Set(['class', 'style', 'title', 'id']);
+
+    it('should filter out non-whitelisted attributes', () => {
+      const props = {
+        class: 'test',
+        nonexistent: 'value',
+        title: 'title'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'test',
+        title: 'title'
+      });
+    });
+
+    it('should filter out dangerous event handlers', () => {
+      const props = {
+        class: 'test',
+        onClick: () => {},
+        onMouseover: () => {}
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'test'
+      });
+    });
+
+    it('should filter out dangerous protocols', () => {
+      const props = {
+        title: 'javascript:alert(1)',
+        id: 'vbscript:alert(1)',
+        class: 'safe'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'safe'
+      });
+    });
+
+    it('should handle encoded malicious content', () => {
+      const props = {
+        title: '&#106;&#97;&#118;&#97;&#115;&#99;&#114;&#105;&#112;&#116;&#58;alert(1)',
+        id: '%6A%61%76%61%73%63%72%69%70%74%3Aalert(1)',
+        class: 'safe'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'safe'
+      });
+    });
+
+    it('should filter style objects', () => {
+      const props = {
+        style: {
+          color: 'red',
+          background: 'javascript:alert(1)'
+        },
+        class: 'test'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'test'
+      });
+    });
+
+    it('should handle empty and null values', () => {
+      const props = {
+        class: '',
+        title: null,
+        style: null
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: '',
+        title: null,
+        style: null
+      });
+    });
+
+    it('should filter nested objects except style', () => {
+      const props = {
+        data: { key: 'value' },
+        style: { color: 'red' },
+        class: 'test'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        style: { color: 'red' },
+        class: 'test'
+      });
+    });
+
+    it('should handle multiple iterations of encoded content', () => {
+      const props = {
+        title: encodeURIComponent(encodeURIComponent('javascript:alert(1)')),
+        class: 'safe'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'safe'
+      });
+    });
+
+    it('should filter suspicious content patterns', () => {
+      const props = {
+        title: 'Function("alert(1)")',
+        id: 'eval("alert(1)")',
+        class: 'test'
+      };
+      const result = filterSafeProps(props, allowedAttrs);
+      expect(result).toEqual({
+        class: 'test'
+      });
+    });
+  });
 });
Author	SHA1	Message	Date
gru-agent[bot]	1066ea62e3	Add tests for filterSafeProps function in Markdown utils test suite	2025-05-29 16:12:14 +00:00
Archer	8ed35ffe7e	Update dataset.md (#4927 )	2025-05-29 18:25:59 +08:00
Archer	0f866fc552	feat: text collecion auto save for a txt file (#4924 )	2025-05-29 17:57:27 +08:00
Archer	05c7ba4483	feat: Workflow node search (#4920 ) * add node find (#4902) * add node find * plugin header * fix * fix * remove * type * add searched status * optimize * perf: search nodes --------- Co-authored-by: heheer <heheer@sealos.io>	2025-05-29 14:29:28 +08:00
heheer	fa80ce3a77	fix child app external variables (#4919 )	2025-05-29 13:37:59 +08:00
Archer	830358aa72	remove invalid code (#4915 )	2025-05-28 22:11:40 +08:00
Archer	02b214b3ec	feat: remove buffer;fix: custom pdf parse (#4914 ) * fix: doc * fix: remove buffer * fix: pdf parse	2025-05-28 21:48:10 +08:00
Archer	a171c7b11c	perf: buffer;fix: back up split (#4913 ) * perf: buffer * fix: back up split * fix: app limit * doc	2025-05-28 18:18:25 +08:00
heheer	802de11363	fix runtool empty message (#4911 ) * fix runtool empty message * del unused code * fix	2025-05-28 17:48:30 +08:00