An AI-driven no-code PaaS application development platform

Abstract

The application discloses a kind of based on AI+PaaS's drag-and-drop no-code software development system and method, belong to no-code and artificial intelligence software development technical field.The application discards traditional code development and AI code generation technical route, with standardization JSON configuration file as core intermediate carrier, is combined with AI intelligent generation and visual drag-and-drop dual editing mode, generates JSON development resource file by AI analysis natural language demand or artificial drag-and-drop operation, again by PaaS runtime engine dynamic analysis JSON configuration, automatically completes the architecture building of front and rear separation software, page rendering, business logic execution, realizes software one-key generation, instant running.The application completely solves the industry pain point that traditional software development efficiency is low, existing AI code generation scheme needs secondary editing, cannot be scaled down, without professional coding ability, adapts to the diversified application scene of all industries, substantially reduces software development cost and cycle, with very high universality, expansibility and commercialization promotion value.The application has been carried on DeepPaas platform and landed deployment.

Description

Technical Field

[0001] This invention relates to the fields of no-code, artificial intelligence, and PaaS platform technology, specifically to a no-code software development architecture and automated implementation method that combines AI intelligent generation with drag-and-drop visual editing. Background Technology

[0002] With the widespread adoption of digital transformation, the demand for customized software systems across various industries has exploded. Traditional software development models and existing AI development solutions both have significant technical bottlenecks and cannot meet the needs for large-scale, low-cost, rapid, and low-barrier software delivery.

[0003] Traditional front-end and back-end separation software development models rely on developers manually writing a large amount of front-end page code, back-end interface code, business logic code, and configuration files. This results in long development cycles, high labor costs, and inconsistent coding standards among different developers, making software iteration, maintenance, and migration extremely difficult and unable to quickly respond to diverse and fragmented industry application scenarios.

[0004] Existing AI-assisted development technologies primarily rely on AI-generated complete code. This approach suffers from two major flaws: First, AI-generated code is highly redundant, lacks standardization, and has a high bug rate, requiring professional developers to manually edit, debug, and optimize it, significantly negating the efficiency advantages of AI. Second, code-level generation solutions are highly coupled, meaning that the generated code cannot be reused universally, has low flexibility in adapting to different scenarios, and requires regeneration and modification of code for each change in requirements, making standardization and large-scale deployment impossible. Third, the code compilation and deployment process is cumbersome, preventing the software from being generated and run instantly.

[0005] Existing low-code PaaS platforms only support manual drag-and-drop editing, relying on manual construction of software architecture and configuration of business parameters. They have low levels of intelligence, and complex business scenarios still require manual code addition, resulting in limited improvement in development efficiency and an inability to break free from dependence on professional developers.

[0006] In summary, the industry urgently needs a software development technology solution that combines high efficiency, visual secondary editing, high versatility, and scalability to address industry pain points such as inefficiency in traditional development, difficulty in implementing AI code generation, and insufficient intelligence in low-code platforms. Summary of the Invention

[0007] Purpose of the invention This invention aims to overcome the shortcomings of existing technologies and provide a drag-and-drop no-code software development system and method based on AI+PaaS. It abandons the traditional development logic of code generation and editing, uses JSON configuration files as the core intermediate medium, and combines AI intelligent generation and visual drag-and-drop editing modes to achieve rapid development of front-end and back-end separated software with zero code, visual secondary editing, and instant execution. This significantly improves software development efficiency and enables the large-scale implementation and promotion of AI software development.

[0008] The core innovation of this invention lies in its AI / drag-and-drop generation of standardized JSON development resource files, coupled with dynamic parsing and execution at PaaS runtime, completely bypassing the code-level development and editing process. Unlike traditional code generation solutions, this invention does not generate any compilable source code; it only generates standardized, structured JSON configuration files. All software pages, interfaces, business logic, component parameters, process configurations, permission configurations, IoT development functions, and other development resources are defined through standardized JSON files.

[0009] The platform is equipped with a dedicated PaaS runtime parsing engine that can parse standardized JSON configuration files in real time and dynamically. It automatically completes the front-end and back-end architecture setup, component rendering, business logic execution, and interface scheduling, ultimately generating ready-to-run front-end and back-end separated software. Simultaneously, the platform integrates AI intelligent generation capabilities, supporting the automatic generation of compliant JSON configuration files from natural language input, coupled with manual drag-and-drop visual correction, enabling code-free development across all scenarios and processes.

[0010] The system of this invention is divided into four core modules, which work together to achieve automated software development and operation, as detailed below:

[0011] It includes a built-in general component library, an industry-specific component library, and a business logic template library, encompassing front-end page components, back-end logic components, data connection components, data interaction components, access control components, process configuration components, and interface configuration components. Users can drag and drop to combine various components through a visual interface to customize and build software architectures and business processes. The system collects user drag-and-drop operations, component configuration parameters, and component relationships in real time, automatically encapsulating and generating standardized structured JSON development resource files, eliminating the need for manual coding and configuration.

[0012] Equipped with a dedicated, finely tuned large model, specifically trained for low-code PaaS scenarios, it supports natural language requirement parsing, intelligent scenario matching, and automatic component adaptation. Users input natural language descriptions such as industry scenarios, business requirements, and functional parameters. The AI ​​model automatically identifies the requirement type, matches corresponding component resources and business logic, and automatically generates a complete JSON configuration file that conforms to the platform's parsing specifications. This covers all dimensions of development resources, including data model generation, page layout, interface rules, business processes, data validation, process configuration, and permission configuration, all without manual intervention.

[0013] This is the core execution module of the invention, featuring a built-in JSON standardization parsing engine, a front-end and back-end rendering engine, and a business logic scheduling engine. It can read JSON configuration files generated by AI or through drag-and-drop in real time, dynamically parsing component parameters, architectural relationships, business rules, and data interfaces within the files. It automatically completes real-time front-end page rendering, dynamic back-end service setup, automatic execution of business logic, and data flow scheduling, requiring no compilation or deployment; the software is ready to use immediately upon configuration generation. It also supports incremental parsing and dynamic updates of JSON files, allowing software functionality to be updated in real time simply by modifying the configuration when requirements change.

[0014] It includes built-in templates for various industry scenarios such as government affairs, finance, education, e-commerce, and enterprise office, and supports the reuse, modification, and iteration of JSON configuration files. Compared to code files, JSON configuration files have a concise structure, clear semantics, and are easy to modify, with no code redundancy or syntax errors. It completely avoids the secondary editing and debugging work after traditional AI code generation, supporting rapid software iteration, scenario reuse, and personalized customization.

[0015] The software development method of this invention includes two parallel development modes, and the specific steps are as follows:

[0016] S1. Requirements Input: Users input their software function requirements, application scenarios, and parameter configuration requirements in natural language form through the platform. S2, AI Intelligent Parsing and Generation: AI large model analyzes user needs, matches standardized component resources of the platform, and automatically generates a full-coverage, standardized JSON development resource configuration file; S3, Dynamic Execution at Runtime: The PaaS runtime engine reads JSON files, dynamically parses configuration parameters, automatically builds a front-end and back-end separation architecture, renders pages, schedules interfaces, executes business logic, and generates a software system that can be directly deployed and run online. S4. Iterative Optimization: When requirements change, the user re-enters the natural language requirements, and the AI ​​automatically updates the JSON configuration file. The platform then parses and updates the software functionality in real time.

[0017] S1, AI pre-generated basic configuration: Users input basic scenario requirements, and AI generates a basic JSON configuration file to build the software infrastructure; S2, Manual Visual Fine-Tuning: Users can adjust component layout, modify business logic, and add personalized configurations by dragging and dropping, and the system updates the JSON file in real time; S3, Dynamic Run and Deployment: The PaaS runtime parses the final JSON configuration in real time to generate customized front-end and back-end separation software; S4, Lightweight Iteration: Subsequent feature iterations only require drag-and-drop fine-tuning of configurations, without the need for code modification, enabling rapid software upgrades.

[0018] Compared to existing technologies, this invention possesses three disruptive technological advantages, addressing core pain points in the industry: (1) Completely solve the problem of secondary editing in AI development and achieve zero-code implementation: Abandon the traditional technical route of AI-generated code, take standardized JSON configuration as the core carrier, the AI-generated configuration file has no syntax errors, no redundant content, and is fully compatible with the platform parsing rules. No professional personnel are required to edit, debug, and troubleshoot, completely eliminating the threshold for AI development implementation and having the foundation for large-scale commercial promotion.

[0019] (2) Balancing extreme development efficiency with flexible scenario adaptation: It integrates the dual capabilities of AI fully automatic generation and manual drag-and-drop fine-tuning. Simple scenarios can be generated and launched with one click by AI, while complex scenarios can be customized through human-machine collaboration, adapting to all industries and all types of software application scenarios; JSON configuration is lightweight, reusable, and iterable, greatly shortening the software development cycle and reducing human development costs by more than 80%.

[0020] Leveraging the PaaS runtime dynamic parsing engine, configurations can be generated and run immediately, eliminating the need for code compilation, packaging, and deployment processes. Based on a standardized JSON configuration architecture, it fully realizes front-end and back-end separation, allowing components and configurations to be reused across scenarios and projects, completely solving the problems of high coupling, difficult iteration, and poor reusability in traditional software development.

Claims

1. A drag-and-drop no-code software development system based on AI and PaaS, characterized in that, include: The visual drag-and-drop editing module provides a standardized component library and scene template library. It receives drag-and-drop editing operations from users and automatically generates standardized JSON development resource configuration files based on component combination methods, configuration parameters, and relationships. The AI-powered intelligent JSON generation module receives user natural language requirements, analyzes scenario requirements through specialized fine-tuning of the large model, automatically matches corresponding development components and business logic, and generates a complete JSON development resource configuration file that conforms to the platform's parsing specifications. The PaaS runtime dynamic parsing module has a built-in JSON parsing engine, front-end and back-end rendering engine and business scheduling engine. It is used to read and dynamically parse JSON configuration files generated by AI or drag and drop in real time, automatically complete the front-end and back-end architecture construction, page rendering, business logic execution and interface scheduling, and generate front-end and back-end separated software that can be run directly. The multi-scenario adaptation and iteration module is used to store templates for multiple industry scenarios, enabling the reuse, incremental modification, and dynamic updating of JSON configuration files, and completing lightweight iterative upgrades of the software.

2. The system according to claim 1, characterized in that, The JSON development resource configuration file is the sole development carrier and does not contain any compilable source code. All software functions, architecture, logic, and parameters are defined in a standardized manner through structured JSON fields.

3. The system according to claim 1, characterized in that, The AI-powered intelligent JSON generation module uses a low-code PaaS scenario-specific fine-tuning of a large model, which can accurately parse natural language requirements, automatically adapt component parameters and business rules, and generate JSON configuration files with no syntax errors, requiring no secondary editing, and can be directly parsed and executed by the PaaS runtime module.

4. The system according to claim 1, characterized in that, The PaaS runtime dynamic parsing module supports incremental parsing and real-time updates of JSON files. When the JSON configuration file is modified, there is no need to recompile and deploy; the software functions and architecture can be dynamically and synchronously updated.

5. A drag-and-drop no-code software development method based on AI+PaaS, characterized in that, This includes a fully automated AI generation mode, with the following specific steps: S1. Receive user input of natural language software requirements and scenario parameters; S2. Analyze requirements through AI big data models, match standardized component resources, and automatically generate a fully covered standardized JSON development resource configuration file. S3 and PaaS dynamically parse JSON configuration files at runtime, automatically build a front-end and back-end separated software architecture, render pages, execute business logic, and generate a software system that can be run directly. S4. When requirements are iterated, natural language requirements are re-entered, and AI automatically updates the JSON configuration, and the platform updates software functions in real time.

6. The method according to claim 5, characterized in that, It also includes an AI-assisted drag-and-drop hybrid development mode, with the following steps: S1. AI generates JSON configuration files corresponding to the software infrastructure based on basic requirements; S2. Users can fine-tune component layout, business logic, and configuration parameters through visual drag-and-drop, and the system updates the JSON file in real time. S3 and PaaS runtime parse the final JSON configuration and generate customized front-end and back-end separation software; S4. Lightweight software iteration and scenario reuse are achieved based on JSON configuration.

7. The method according to claim 5, characterized in that, The entire process requires no writing, compiling, or debugging of any source code, completely avoiding the development process of secondary code editing and bug fixing.