论文标题
一种用于使用自然语言创建业务自动化的无代码低代码范式
A No-Code Low-Code Paradigm for Authoring Business Automations Using Natural Language
论文作者
论文摘要
大多数业务流程自动化仍然使用传统的自动化技术（例如工作流引擎）开发。这些系统提供了特定的特定语言，需要商业知识和编程技能才能有效使用。因此，企业用户通常缺乏足够的编程技能来充分利用这些面向代码的环境。我们提出了一个使用自然语言来构建业务自动化的范式。该方法采用大型语言模型将自然语言中描述的业务规则和自动化转化为商业规则引擎可解释的特定领域语言。我们比较了各个目标域上各种语言模型配置的性能，并探索使用受限的解码以确保句法正确生成输出。
Most business process automation is still developed using traditional automation technologies such as workflow engines. These systems provide domain specific languages that require both business knowledge and programming skills to effectively use. As such, business users often lack adequate programming skills to fully leverage these code oriented environments. We propose a paradigm for the construction of business automations using natural language. The approach applies a large language model to translate business rules and automations described in natural language, into a domain specific language interpretable by a business rule engine. We compare the performance of various language model configurations, across various target domains, and explore the use of constrained decoding to ensure syntactically correct generation of output.
