Jerry Yan
cc6415c4d9
问题描述： 在数据管理的数据集编辑中，如果之前设置了关联数据集，编辑时选择不关联数据集后保存不会生效。 根本原因： MyBatis-Plus 的 updateById 方法默认使用 FieldStrategy.NOT_NULL 策略， 只有当字段值为非 null 时才会更新到数据库。 当 parentDatasetId 从有值变为 null 时，默认情况下不会更新到数据库。 修复方案： 在 Dataset.java 的 parentDatasetId 字段上添加 @TableField(updateStrategy = FieldStrategy.IGNORED) 注解， 表示即使值为 null 也需要更新到数据库。 配合前端修改（恢复发送空字符串），现在可以正确清除关联数据集： 1. 前端发送空字符串表示"无关联数据集" 2. 后端 handleParentChange 通过 normalizeParentId 将空字符串转为 null 3. dataset.setParentDatasetId(null) 设置为 null 4. 由于添加了 IGNORED 策略，即使为 null 也会更新到数据库
DataMate All-in-One Data Work Platform
DataMate is an enterprise-level data processing platform for model fine-tuning and RAG retrieval, supporting core functions such as data collection, data management, operator marketplace, data cleaning, data synthesis, data annotation, data evaluation, and knowledge generation.
If you like this project, please give it a Star⭐️!
🌟 Core Features
- Core Modules: Data Collection, Data Management, Operator Marketplace, Data Cleaning, Data Synthesis, Data Annotation, Data Evaluation, Knowledge Generation.
- Visual Orchestration: Drag-and-drop data processing workflow design.
- Operator Ecosystem: Rich built-in operators and support for custom operators.
🚀 Quick Start
Prerequisites
- Git (for pulling source code)
- Make (for building and installing)
- Docker (for building images and deploying services)
- Docker-Compose (for service deployment - Docker method)
- Kubernetes (for service deployment - k8s method)
- Helm (for service deployment - k8s method)
This project supports deployment via two methods: docker-compose and helm. After executing the command, please enter the corresponding number for the deployment method. The command echo is as follows:
Choose a deployment method:
1. Docker/Docker-Compose
2. Kubernetes/Helm
Enter choice:
Clone the Code
git clone git@github.com:ModelEngine-Group/DataMate.git
cd DataMate
Deploy the basic services
make install
If the machine you are using does not have make installed, please run the following command to deploy it:
# Windows
set REGISTRY=ghcr.io/modelengine-group/
docker compose -f ./deployment/docker/datamate/docker-compose.yml up -d
docker compose -f ./deployment/docker/milvus/docker-compose.yml up -d
# Linux/Mac
export REGISTRY=ghcr.io/modelengine-group/
docker compose -f ./deployment/docker/datamate/docker-compose.yml up -d
docker compose -f ./deployment/docker/milvus/docker-compose.yml up -d
Once the container is running, access http://localhost:30000 in a browser to view the front-end interface.
To list all available Make targets, flags and help text, run:
make help
Build and deploy Mineru Enhanced PDF Processing
make build-mineru
make install-mineru
Deploy the DeerFlow service
make install-deer-flow
Local Development and Deployment
After modifying the local code, please execute the following commands to build the image and deploy using the local image.
make build
make install dev=true
Uninstall
make uninstall
When running make uninstall, the installer will prompt once whether to delete volumes; that single choice is applied to all components. The uninstall order is: milvus -> label-studio -> datamate, which ensures the datamate network is removed cleanly after services that use it have stopped.
🤝 Contribution Guidelines
Thank you for your interest in this project! We warmly welcome contributions from the community. Whether it's submitting bug reports, suggesting new features, or directly participating in code development, all forms of help make the project better.
• 📮 GitHub Issues: Submit bugs or feature suggestions.
• 🔧 GitHub Pull Requests: Contribute code improvements.
📄 License
DataMate is open source under the MIT license. You are free to use, modify, and distribute the code of this project in compliance with the license terms.