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README.md

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## Roadmap
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### When will version 1.0 be released
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Versions before 1.0 are beta versions, not recommended for production use, and interface compatibility is not guaranteed. There is no planned release date yet. It will be released after the following features are completed:
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- Comprehensive unit test and integration test coverage
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- Complete version management method, easy to roll back to previous versions
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- Comprehensive unit test, integration test, and effectiveness test coverage
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- Code quality optimization, many details still need to be polished
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- Support for degradation and timeout configuration
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- Complete version management method, easy to roll back to previous versions
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- Metric monitoring system improvement
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- C++ model serving
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- Validate model training effectiveness on public datasets
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### Future Feature Planning
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- Frontend UI for viewing current execution DAG, SQL code, statistics, etc.
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- Support for more external data sources, such as JDBC, MongoDB, etc.
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- Tensorboard visualization of model training process
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- GPU training and inference support
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- Support for authentication and authorization
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- Best practice tutorials, including search, recommendation, etc.

README_zh.md

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## 路线图
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### 1.0版本什么时候发布
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1.0之前版本都是beta版本,不建议线上使用,不保证接口兼容性。目前无规划发布时间,将在下述功能完善后发布:
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- 完善的单元测试、集成测试覆盖
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- 完善的版本管理方法,可以方便回滚到之前的版本
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- 完善的单元测试、集成测试、效果测试覆盖
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- 优化代码质量,目前仍很多细节要打磨
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- 支持降级和超时配置
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- 完善的版本管理方法,可以方便回滚到之前的版本
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- metric监控系统完善
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- c++模型serving
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- 在公开数据集上验证模型训练的有效性
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### 后续功能规划
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- 前端UI,用于查看当前执行DAG、SQL代码、统计信息等
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- 支持更多的外部数据源,比如JDBC、MongoDB等
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- Tensorboard可视化模型训练过程
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- GPU训练、推理支持
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- 支持认证、鉴权
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- 最佳实践教程,包括搜索、推荐等

docs/docs/intro.md

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1.0 之前版本都是 beta 版本,不建议线上使用,不保证接口兼容性。目前无规划发布时间,将在下述功能完善后发布:
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- 完善的单元测试、集成测试覆盖
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- 完善的版本管理方法,可以方便回滚到之前的版本
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- 完善的单元测试、集成测试、效果测试覆盖
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- 优化代码质量,目前仍很多细节要打磨
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- 支持降级和超时配置
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- 完善的版本管理方法,可以方便回滚到之前的版本
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- Metric 监控系统完善
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- C++ 模型 Serving
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- 在公开数据集上验证模型训练的有效性
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### 后续功能规划
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- 支持更多的外部数据源,比如 JDBC、MongoDB 等
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- Tensorboard 可视化模型训练过程
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- GPU 训练、推理支持
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- 支持认证、鉴权
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- 最佳实践教程,包括搜索、推荐等

docs/en/docs/intro.md

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Versions before 1.0 are beta versions, not recommended for production use, and do not guarantee interface compatibility. There is no planned release date yet; it will be released after the following features are completed:
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- Comprehensive unit test and integration test coverage
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- Comprehensive unit test, integration test, and effectiveness test coverage
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- Code quality optimization, many details still need refinement
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- Support for degradation and timeout configuration
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- Complete version management methods for easy rollback to previous versions
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- Optimize code quality, many details still need refinement
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- Improve metric monitoring system
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- Optimize metric monitoring system
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- C++ model serving
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- Validate model training effectiveness on public datasets
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### Future Feature Plans
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- Support for more external data sources, such as JDBC, MongoDB, etc.
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- Tensorboard visualization of model training process
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- GPU training and inference support
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- Support for authentication and authorization
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- Best practice tutorials, including search, recommendation, etc.

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