Low-code platform-based application model generation method, equipment and medium

Abstract

The invention discloses an application model generation method and device based on a low-code platform and a medium, and relates to the technical field of low-code application models. The method comprises the steps that user service data are collected, the service data are stored through forms, and the forms comprise a main form and sub-forms; the relation between the main form and the sub-form is identified, model elements are obtained, and the model elements comprise business entities, sub-entities, entity relations, value objects and aggregation roots; an external dictionary is introduced, model elements are expressed through JSON, and a visual script model is generated; packaging the script model to obtain a deployment package, and dynamically publishing the deployment package to a database; and when the database exports the deployment package, storing the deployment package as a JSON file, and compressing and encrypting the JSON file. According to the method, after the form is abstracted into the model, higher-degree reuse can be achieved, the workload of repeated model design and application and form development is reduced, and the development process is faster.

Description

Technical Field

[0001] The present application relates to the technical field of low-code application models, and in particular to a method, device and medium for generating an application model based on a low-code platform. Background Art

[0002] When generating complex business application models, traditional low-code platforms often require developers to manually write a large amount of configuration code or perform cumbersome drag-and-drop operations, which greatly prolongs the development cycle; as business needs continue to change, business application models need to be iterated frequently, however, existing technologies often find it difficult to respond quickly to these changes, resulting in delayed model updates and affecting business efficiency; existing technologies are often difficult to deeply integrate with the company's existing IT systems, databases, and applications, resulting in a lot of time and effort required for data migration and system docking during model building; when displaying complex business application models, traditional low-code platforms often find it difficult to provide an intuitive and easy-to-use visual interface, affecting user understanding and use; the lack of multi-client real-time communication capabilities limits team collaboration and model discussions, and it is often easy to form data islands.

[0003] Through the above analysis, the problems and defects of the prior art are as follows: Existing technologies cannot efficiently, flexibly and securely generate, manage, deploy and display complex business application models on low-code platforms. Summary of the invention

[0004] The embodiments of the present application provide a method, device and medium for generating an application model based on a low-code platform, which solves the problem in the prior art that complex business application models cannot be generated, managed, deployed and displayed on a low-code platform efficiently, flexibly and securely.

[0005] In the first aspect, an embodiment of the present application provides a method for generating an application model based on a low-code platform, characterized in that the method includes: collecting user business data and storing the business data through a form, the form including a main form and a sub-form; identifying the relationship between the main form and the sub-form to obtain model elements, the model elements including business entities, sub-entities and entity relationships, as well as value objects and aggregate roots; introducing an external dictionary, and expressing the model elements through JSON to generate a visual script model; packaging the script model to obtain a deployment package, and dynamically publishing the deployment package to the database; when the database exports the deployment package, the deployment package is saved as a JSON file, and compressed and encrypted.

[0006] In one implementation of the present application, the relationship between the main form and the sub-form is identified to obtain model elements, specifically including: using autonomous learning technology to perform unsupervised learning on the form to extract business data features; combining representation learning in deep learning to map the features to a high-dimensional space to form a unified representation vector; and identifying business entities and sub-entities through cluster analysis.

[0007] In one implementation of the present application, the script model is packaged and published to the database, specifically including: interacting with the Minio object storage service through the Rest API to dynamically upload the deployment package to the storage bucket; generating a unique identifier and version label for the deployment package, and providing a permission-based access control mechanism and preview.

[0008] In one implementation of the present application, the deployment package is dynamically uploaded to the bucket by interacting with the Minio object storage service through the Rest API, specifically including: when the user chooses to customize, a user interface is provided to allow the user to enter or select the name of the bucket; when the user does not choose to customize, the corresponding bucket is searched according to the model element.

[0009] In one implementation of the present application, an external dictionary is introduced and model elements are expressed through JSON, specifically including: based on the external dictionary including key-value pairs for matching, a string similarity algorithm is used to match model elements with key-value pairs, and the successfully matched key-value pairs are associated with corresponding model elements; a canvas is created, business entities, sub-entities, entity relationships, value objects and aggregate roots, as well as key-value pairs are mapped to type nodes on the canvas, and updated according to the matching results of the external dictionary.

[0010] In one implementation of the present application, the method further includes: adding connections to type nodes and assigning an identifier and a listener to each connection; and using a WebSocket library to establish a real-time communication connection to enable multiple clients to communicate in real time.

[0011] In one implementation of the present application, when the database exports the deployment package, the deployment package is saved as a JSON file, and after compression and encryption, the method also includes: decompressing and decrypting the imported JSON file; selecting components through intelligent algorithms and low-code platforms based on the context of the JSON file and user history; displaying the script model through the component, and determining the field type, label, and default value in the form based on the business entities, sub-entities, and entity relationships in the script model.

[0012] In one implementation of the present application, the method further includes: when business data is updated, searching for an identifier and a version tag in a database; after the data update operation is completed and submitted, a version tag increment mechanism is automatically triggered.

[0013] In the second aspect, an embodiment of the present application also provides an application model generation device based on a low-code platform, the device comprising at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: collect user business data and store the business data through forms, the forms comprising a main form and a sub-form; identify the relationship between the main form and the sub-form, and obtain model elements, the model elements comprising business entities, sub-entities and entity relationships, as well as value objects and aggregate roots; introduce an external dictionary, and express the model elements through JSON to generate a visual script model; package the script model, obtain a deployment package, and dynamically publish the deployment package to the database; when the database exports the deployment package, save the deployment package as a JSON file, and compress and encrypt it.

[0014] On the third aspect, the embodiment of the present application also provides a non-volatile computer storage medium generated based on a low-code platform application model, storing computer executable instructions, and the computer executable instructions are set to: collect user business data and store the business data through forms, the forms include main forms and sub-forms; identify the relationship between the main form and the sub-form, and obtain model elements, the model elements include business entities, sub-entities and entity relationships, as well as value objects and aggregate roots; introduce external dictionaries, and express model elements through JSON to generate a visual script model; package the script model to obtain a deployment package, and dynamically publish the deployment package to the database; when the database exports the deployment package, save the deployment package as a JSON file, and compress and encrypt it.

[0015] The embodiment of the present application provides a method, device and medium for generating an application model based on a low-code platform, which promotes the low-code development platform: after the form is abstracted into a model, a higher degree of reuse can be achieved, reducing the workload of repeated model design and application and form development, and the visual interactive design reduces the dependence on professional developers, making the development process faster. The introduction of entity models and visual design tools clearly presents the complex business form logic, which is convenient for application developers to quickly start operations; the promotion effect on enterprises: platform users can quickly create and modify business forms, flexibly respond to changes in market demand, significantly shorten the business launch cycle, and improve business agility. Through the abstraction capability of the low-code platform, high-quality business form development can be completed with less manpower and resources, reducing application development costs. The abstract method of the entity model makes the enterprise form data and business rules more standardized, which is convenient for subsequent data analysis and process optimization to enhance the enterprise data governance capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A flow chart of a method for generating an application model based on a low-code platform provided in an embodiment of the present application; Figure 2 A schematic diagram of the internal structure of a device based on a low-code platform application model generation embodiment provided in the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0018] The embodiments of the present application provide a method, device and medium for generating an application model based on a low-code platform, which solves the problem in the prior art that complex business application models cannot be generated, managed, deployed and displayed on a low-code platform efficiently, flexibly and securely.

[0019] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0020] Figure 1 A flow chart of a method for generating an application model based on a low-code platform is provided in an embodiment of the present application. Figure 1 As shown, the embodiment of the present application provides a method for generating an application model based on a low-code platform, which specifically includes the following steps: Step 10: Collect user business data and store it through forms. The forms include main forms and subforms.

[0021] In this step, we collect user and enterprise requirements, and then design the main form and subforms based on the collected requirements. The main form is usually used to store core business data, such as customer information and order details, and the subform is used to store detailed information associated with the main form data, such as the list of items in the order and the customer's contact information.

[0022] Step 20: Identify the relationship between the main form and the subform, and obtain the model elements. The model elements include business entities, subentities and entity relationships, as well as value objects and aggregate roots.

[0023] In the embodiment of the present application, the form fields are mapped to entity attributes in the model, which is determined by the complexity of the low-code platform form. The application form is the expansion of the real business, including ordinary forms, process forms, aggregate forms, and subforms. These are all form relationships. There are display components and field components in the form. The display components are for better display of the form but cannot be converted into entity attributes. The field components carry business data and can be abstracted as entity attributes. The field definition includes: basic field information: field name, type (string, number, date, etc.), default value; field constraints: length limit, whether it is required, whether it is unique, and other verification rules; domain meaning: the business semantics of the field, which is convenient for future expansion or integration into a larger domain model.

[0024] Applications store user data through forms, and express the relationships of real business through the relationships between forms. Usually, the relationships between forms corresponding to complex businesses are also relatively complex, so forms are abstracted. The relationships between forms can be represented in the model as aggregation relationships or references between entities: One-to-one relationship: A direct relationship between one form and another form (such as a user form and a user details form) can be achieved through reference. One-to-many relationship (subform): The relationship between the main form and the subform can be modeled using aggregate roots and subentities. For example: the order form (aggregate root) contains the order details form (subentity); many-to-many relationship: represented by an intermediate form, such as the "student form" and the "course form" are associated through the "course selection form".

[0025] As an optional embodiment, identifying the relationship between the main form and the sub-form to obtain the model elements may specifically include: Step 21: using autonomous learning technology to perform unsupervised learning on the form to extract business data features; Step 22: combining representation learning in deep learning to map the features to a high-dimensional space to form a unified representation vector; Step 23: identifying business entities and sub-entities through cluster analysis.

[0026] In this step, according to the characteristics and requirements of the representation vector, a suitable clustering algorithm, such as K-means and DBSCAN, is selected to perform cluster analysis on the generated representation vector, and similar vectors are classified into one category. Each category represents a business entity or sub-entity. Based on the clustering results, business entities and sub-entities are identified, and the relationship between entities, master-slave relationship or inclusion relationship, is analyzed.

[0027] Step 30: Introduce an external dictionary and express model elements through JSON (JavaScript Object Notation) to generate a visual script model; In this step, the external dictionary (such as data dictionary, classification label) can be regarded as a service or external resource in the domain model. As a value object, this scenario is suitable for external dictionaries with small data volume. The value of the external dictionary is directly referenced in the form field (such as the status field references the value in the "status dictionary"); as an external service: this scenario is suitable for dictionaries with large data volume. It is difficult to use the dictionary as a model value object. The dictionary value is dynamically loaded through the external service interface to facilitate real-time updates.

[0028] As an optional embodiment, an external dictionary is introduced and model elements are expressed through JSON, which may specifically include: Step 301: Based on the key-value pairs included in the external dictionary for matching, the model elements are matched with the key-value pairs using a string similarity algorithm, and the successfully matched key-value pairs are associated with the corresponding model elements; Step 302: A canvas is created, business entities, sub-entities, entity relationships, value objects and aggregate roots, as well as key-value pairs are mapped to type nodes on the canvas, and updated according to the matching results of the external dictionary.

[0029] In this step, create a canvas. As the carrier of the node, the canvas is the basis of visualization. Entities and value objects are mapped to different types of nodes on the canvas, and lines are added. Nodes are associated through Edge. User operations can be recorded through the history module of AntV X6 to facilitate subsequent undo and redo by users.

[0030] As an optional embodiment, the method may further include: step 303: adding a connection to the type node, and assigning an identifier and a listener to each connection; step 304: using the WebSocket library to establish a real-time communication connection to enable multiple clients to communicate in real time.

[0031] Step 40: Pack the script model to obtain a deployment package, and dynamically publish the deployment package to the database; As an optional embodiment, packaging the script model and publishing it to the database may specifically include: Step 401: interacting with the Minio object storage service through the Rest API to obtain a deployment package, and dynamically uploading the deployment package to the storage bucket; In this step, when publishing the model, the model of the current canvas is saved to the object storage system MinIO. The model is stored in JSON format with version information. The version number is generated using an incremental strategy. The published script interacts with Minio through the Rest API. The system generates a storage path for each script, such as " / model / {model_name} / {version}", to facilitate subsequent quick access and dynamic loading. The upload process includes script compression, encryption (optional) and the addition of metadata (version number, creation time, etc.).

[0032] As an optional embodiment, interacting with the Minio object storage service through the Rest API to dynamically upload the deployment package to the bucket can specifically include: Step 4011: When the user chooses to customize, a user interface is provided to allow the user to enter or select the name of the bucket; Step 4012: When the user does not choose to customize, the corresponding bucket is searched according to the model element.

[0033] In this step, if the bucket does not exist, you can generate a new bucket name, following the naming conventions of the storage service, which is usually a combination of letters, numbers, hyphens, and underscores. You can use some strategies to generate a unique bucket name, such as combining a timestamp, a random number, or a specific identifier.

[0034] Step 402: Generate a unique identifier and version label for the deployment package, and provide a permission-based access control mechanism and preview.

[0035] Step 50: When the database exports the deployment package, save the deployment package as a JSON file and compress and encrypt it.

[0036] In this step, each model is saved independently as a JSON file, including the complete structure of the model (fields, validation rules, associations, dictionaries). The JSON generated from the abstract model is encrypted and compressed using a compression tool to ensure data security during file transfer.

[0037] As an optional embodiment, when the database exports the deployment package, the deployment package is saved as a JSON file, and after compression and encryption, the method may also include: Step 60: decompressing and decrypting the imported JSON file; Step 70: selecting components through intelligent algorithms and low-code platforms based on the context of the JSON file and user history.

[0038] In this step, the user's operation history on the platform, current project context (and component usage habits) are captured.

[0039] Step 80: Display the script model through the component, and determine the field type, label, and default value in the form based on the business entities, sub-entities, and entity relationships in the script model.

[0040] In this step, model file import is a reverse engineering. By decompressing the encrypted JSON file, it is converted into an application entity model. Like the model visualization technology mentioned in the previous chapter, the imported application entity model is displayed to the user through the canvas. At the same time, the user is allowed to actively adjust the model and publish the model version through the visual model editor according to the actual business. The process of converting the model to the form needs to be mapped to the low-code platform system component or custom component according to the data type in the model. The mapping relationship of the system component is maintained by the platform. The specific mapping relationship is shown in the following table: Table 1 Mapping relationship

[0041] In addition, the low-code platform allows users to customize components through the component factory. The mapping relationship between fields and custom components is open to users, and supports users to customize the mapping relationship between model fields and custom components. After completing the mapping relationship between the model and the component, the user's selected components can be added to the form designer according to the relationship order. Users can adjust the component layout again through the layout component according to business needs to complete the form design.

[0042] As an optional embodiment, the method may further include: when business data is updated, searching for an identifier and a version tag in a database; after the data update operation is completed and submitted, automatically triggering a version tag increment mechanism.

[0043] In this step, the system records the version update log, including update time, updater, comparison of old and new version numbers, and other information, so as to facilitate subsequent version tracking, auditing, or rollback operations.

[0044] In summary, low-code platform applications are the basic units for solving real-world business problems, and are also the solution spaces corresponding to the real-world business problem spaces. They digitize real-world business problems through forms, processes, web pages, reports, and dashboards, and visualize data assets. When users create applications on the low-code platform, they design application forms by dragging and dropping, abstracting the application forms into entity models, including modeling of form fields, validation rules, and association relationships, and then visually displaying the models through canvas. Users can edit models intuitively through interactive methods such as dragging and dropping, and support the release and management of model versions, including version saving, comparison, and rollback operations. The present invention realizes the rapid creation of forms based on models through the abstraction and management of models, application model export and import, meets business needs, and speeds up market response.

[0045] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, this application embodiment also provides a low-code platform application model generation device, whose structure is as follows: Figure 2 shown.

[0046] Figure 2A schematic diagram of the internal structure of a device based on a low-code platform application model generation device is provided in an embodiment of the present application. Figure 2 As shown, the device includes: at least one processor 201; and, a memory 202 communicatively connected to the at least one processor; Among them, the memory 202 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 201 so that at least one processor 201 can: collect user business data and store the business data through forms, and the forms include a main form and a sub-form; identify the relationship between the main form and the sub-form, and obtain model elements, and the model elements include business entities, sub-entities and entity relationships, as well as value objects and aggregate roots; introduce external dictionaries, and express model elements through JSON to generate a visual script model; package the script model to obtain a deployment package, and dynamically publish the deployment package to the database; when the database exports the deployment package, save the deployment package as a JSON file, and compress and encrypt it.

[0047] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium generated based on a low-code platform application model, storing computer executable instructions, wherein the computer executable instructions are set to: collect user business data and store the business data through forms, wherein the forms include a main form and a subform; identify the relationship between the main form and the subform, and obtain model elements, wherein the model elements include business entities, subentities and entity relationships, as well as value objects and aggregate roots; introduce an external dictionary, and express the model elements through JSON to generate a visual script model; package the script model to obtain a deployment package, and dynamically publish the deployment package to a database; when the database exports the deployment package, save the deployment package as a JSON file, and compress and encrypt it.

[0048] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the IoT device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0049] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0050] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0051] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0052] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0053] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0054] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0055] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0056] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0057] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0058] The above is only the embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for generating an application model based on a low-code platform, characterized in that: The method comprises: Collect user business data and store the business data through a form, wherein the form includes a main form and a subform; Identify the relationship between the main form and the subform, and obtain model elements, wherein the model elements include business entities, subentities and entity relationships, as well as value objects and aggregate roots; Introduce an external dictionary and express the model elements through JSON to generate a visual script model; Packaging the script model to obtain a deployment package, and dynamically publishing the deployment package to a database; When the database exports the deployment package, the deployment package is saved as a JSON file and compressed and encrypted.

2. According to the method for generating an application model based on a low-code platform according to claim 1, it is characterized in that: Identify the relationship between the main form and the subform, and obtain model elements, including: Using autonomous learning technology to perform unsupervised learning on the form to extract business data features; Combined with representation learning in deep learning, the features are mapped to a high-dimensional space to form a unified representation vector; Business entities and sub-entities are identified through cluster analysis.

3. According to a method for generating an application model based on a low-code platform according to claim 1, it is characterized in that: Packaging the script model to obtain a deployment package, and publishing the deployment package to a database, specifically includes: Interact with the Minio object storage service through the Rest API and dynamically upload the deployment package to the storage bucket; A unique identifier and version label are generated for the deployment package, and a permission-based access control mechanism and preview are provided.

4. The method for generating an application model based on a low-code platform according to claim 3, characterized in that: The interaction with the Minio object storage service through the Rest API to dynamically upload the deployment package to the storage bucket specifically includes: If the user selects custom, a user interface is provided to allow the user to enter or select a name for the bucket; When the user does not select customization, the corresponding storage bucket is searched according to the model element.

5. According to the method for generating an application model based on a low-code platform according to claim 4, it is characterized in that: The introduction of the external dictionary and the expression of the model elements through JSON specifically include: Based on the key-value pairs included in the external dictionary for matching, the model elements are matched with the key-value pairs using a string similarity algorithm, and the successfully matched key-value pairs are associated with the corresponding model elements; A canvas is created, the business entities, sub-entities, entity relationships, value objects and aggregate roots, and the key-value pairs are mapped to type nodes on the canvas, and updated according to the matching results of the external dictionary.

6. A method for generating an application model based on a low-code platform according to claim 5, characterized in that: The method further comprises: Adding connections to the nodes of the type, and assigning an identifier and a listener to each connection; Use the WebSocket library to establish a real-time communication connection to enable multiple clients to communicate in real time.

7. The method for generating an application model based on a low-code platform according to claim 1, characterized in that: When the database exports the deployment package, after the deployment package is saved as a JSON file and compressed and encrypted, the method further includes: Unzip and decrypt the imported JSON file; Select components through intelligent algorithms and low-code platforms based on the context of the JSON file and user history; The script model is displayed through the component, and the field type, label, and default value in the form are determined according to the business entities, sub-entities, and entity relationships in the script model.

8. The method for generating an application model based on a low-code platform according to claim 6, characterized in that: The method further comprises: When the business data is updated, searching the database for the identifier and version tag; After the data is updated and submitted, the version tag increment mechanism is automatically triggered.

9. A device for generating an application model based on a low-code platform, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: Collect user business data and store the business data through a form, wherein the form includes a main form and a subform; Identify the relationship between the main form and the subform, and obtain model elements, wherein the model elements include business entities, subentities and entity relationships, as well as value objects and aggregate roots; Introduce an external dictionary and express the model elements through JSON to generate a visual script model; Packaging the script model to obtain a deployment package, and dynamically publishing the deployment package to a database; When the database exports the deployment package, the deployment package is saved as a JSON file and compressed and encrypted.

10. A non-volatile computer storage medium generated based on a low-code platform application model, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Collect user business data and store the business data through a form, wherein the form includes a main form and a subform; Identify the relationship between the main form and the subform, and obtain model elements, wherein the model elements include business entities, subentities and entity relationships, as well as value objects and aggregate roots; Introduce an external dictionary and express the model elements through JSON to generate a visual script model; Packaging the script model to obtain a deployment package, and dynamically publishing the deployment package to a database; When the database exports the deployment package, the deployment package is saved as a JSON file and compressed and encrypted.

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