733 results about "Code development" patented technology

Some embodiments engineer a prompt for submission to a language model, such as a software development large language model. Some embodiments ascertain a relationship between code development information and potential context. Code development information includes static analysis results, project settings, development tool history or status data, and other software development data which augments training data previously embedded in the language model. Some embodiments compute a prompt inclusion score of the potential context, based on at least the relationship, and use the inclusion score to determine whether to include the potential context in the language model prompt. In some scenarios, an embodiment determines where to place the context in the prompt. Scoring is performed by a formula, statistical scoring model, or machine learning scoring model. Some embodiments reduce context inclusion false positives and false negatives that were based on the use of embedding similarity scores alone.

The invention discloses an intelligent low-code development method and system based on deep learning model optimization, and relates to the technical field of deep learning. A multi-dimensional domain knowledge graph is constructed, a three-dimensional space-time fusion training sample set is constructed based on the domain knowledge graph, and cross-modal feature alignment is performed on the training sample set, so that the multi-dimensional domain knowledge graph is constructed; the method comprises the following steps: generating an executable logic flow template, encoding the executable logic flow template into a Markov decision process, and performing joint strategy optimization on an optimization target of logic flow by integrating a feature importance index generated by a gradient back propagation path and a multi-target reinforcement learning framework of a Pareto leading edge analysis module. Extracting a strategy parameterization sequence after joint strategy optimization, injecting the strategy parameterization sequence into a dynamic verification sandbox environment, and performing abnormal mode detection and feedback type parameter distillation iteration on an execution track through an online variational auto-encoder to complete dynamic adjustment of the strategy; and the elasticity, the stability and the expandability of the low-code platform are improved.

The invention discloses a low-code development automatic generation method based on a large language model, which comprises the following steps: collecting natural language description information input by a user, and preprocessing; inputting the standardized demand corpus set into a large language model, and executing semantic understanding and context modeling; matching the low-code component library based on the structured semantic representation to generate component assembly description information; generating and verifying an engineering skeleton according to the assembly description information, and outputting an executable low-code application initial version; running the executable low-code application initial version, and monitoring and analyzing execution difference to generate an increment adjustment instruction; and inputting the increment adjustment instruction into the large language model, performing reconstruction and adaptive optimization, and outputting an executable low-code application final version. According to the method, large language model semantic understanding and adaptive optimization technologies are fused, automatic generation and continuous optimization of low-code applications are realized, and the method has the advantages of intelligence, high precision and engineering reliability.

The invention provides an interactive integration method and system for an AI large model and a low-code platform, and relates to the technical field of interaction of the AI large model and the low-code platform, and the method comprises the steps: obtaining a task demand input by a user, analyzing the task demand into a structured task instruction, automatically matching an optimal AI model, and dynamically generating an adaptive API call parameter, according to the method, the AI large model and the low-code platform can be deeply integrated, the technical problems of integration complexity, interaction mode solidification, updating lag and the like are solved, and the method has the advantages that the method is simple and convenient to operate, and the method is suitable for popularization and application. According to the method, a user can call a complex model without AI professional knowledge, the low-code development efficiency is improved by more than 50%, and the security in a data processing process is enhanced by introducing a security verification mechanism, so that the integration efficiency of a low-code platform and an AI large model is greatly improved.

The invention provides a modular construction method of a low-code visual interaction system, and relates to the technical field of low-code development. The method comprises the following steps: constructing an edge cognitive topology network, packaging each node into a reconfigurable meta-module, analyzing a user operation track by using an intention perception interface to generate a meta-intention vector, and carrying out context correlation analysis through a semantic behavior chain to generate a potential behavior sequence. And establishing an asymmetric coupling relationship based on an implicit context mapper, forming a dynamic semantic resonance field, triggering distributed intention resonance and activating a matching element module, and generating a collaborative logic cluster under the constraint of edge computing node resources. And dynamically adjusting an interaction rule and a resource allocation strategy of the logic unit. According to the method, automatic construction and high-precision intention adaptation of complex business logic are realized, the elastic expansion capability and the real-time response efficiency of the system in an edge computing scene are improved, and the risk of logic fault and resource scrambling caused by node isomerism is reduced.

The invention discloses an AI low-code development component automatic generation method based on a knowledge graph, and relates to the technical field of AI low-code development, and the method comprises the following specific steps: constructing an AI development knowledge graph: constructing a knowledge graph containing a five-layer structure, collecting and preprocessing multi-source data, and extracting various entities and association relationships, so as to obtain an AI development knowledge graph; constructing an ontology structure, importing the ontology structure into a database, and forming a final knowledge graph through manual auditing and machine reasoning optimization; according to the method, the multi-dimensional AI development knowledge graph is constructed, user requirements are analyzed in combination with the optimized natural language processing model, the component configuration scheme is generated by introducing the multi-level reasoning mechanism, and finally the standardized low-code component is automatically generated, so that full-automatic conversion from the user requirements to the low-code component is realized, and the user experience is improved. The defect that an existing low-code platform depends on manual component configuration is overcome, the development period is greatly shortened, and the development cost and the technical threshold are reduced.

Provided in the present application is a code generation method, comprising: a code development platform receives input information by a user in a first code file, extracts context information of the input information according to a data warehouse to which the first code file belongs, and retrieves a business knowledge base corresponding to the data warehouse according to the input information so as to obtain target business knowledge; then the code development platform combines the input information, the context information and the target business knowledge according to a prompt template, so as to obtain prompt information; and then the code development platform inputs the prompt information into a large language model (LLM) for reasoning, and presents to the user a code segment reasoned by the LLM. Thus, using the prompt information from the same data source in different processes for prompting the LLM can achieve complete sharing and complete alignment of the prompt information, thereby improving the accuracy of generating code in single time. Furthermore, using a unified prompt template to combine the context information and the business knowledge can make a code segment generated by the LLM more accurate, thereby improving the code acceptance rate in professional domains.

The invention discloses a zero-code development platform and method, electronic equipment and a medium, and belongs to the field of software development. The zero code development platform comprises a data protocol layer, an equipment layer, an operator and module library, a business logic layer and an application layer, the data protocol layer manages an industrial control protocol and a database system; the equipment layer accesses and manages hardware resources; the operator and module library provides a function operator, a resource component operator and an HMI module for calling; the business logic layer calls operators and modules in a module library in a graphical mode through a designer to construct a business task process; and the application layer provides a running environment for the business process and executes the process. According to the zero-code development platform, the development method, the electronic equipment and the medium provided by the invention, efficient development and management of complex industrial automation applications can be realized through a multi-layer architecture design, the overall performance of a system and the development experience of a user are improved, the development process is simplified, and the development period is shortened.

Systems and methods described herein enable adaptive, threshold-based modification of node maps representing ontologies, knowledge graphs, or code development pipelines using generative artificial intelligence. The disclosed platform can retrieve a node map and generate one or more candidate perturbations that modify nodes or relationships within the node map. The disclosed platform can evaluate the effect of the perturbations by comparing respective outputs against ground-truth data. Perturbations can be automatically determined based on changes in external datasets, compliance policies, or operational requirements. The perturbations can be implemented when a computed perturbation quality value satisfies a threshold quality criterion. As such, the system enables efficient, policy-compliant evolution of relational system architectures in dynamic environments.

The invention discloses a software development method and device based on artificial intelligence, equipment and a medium, and the method comprises the steps: receiving a development demand of a user through a natural language interaction interface, and capturing context state information of a current development environment; and a historical solution of the development demand is retrieved based on the dynamic knowledge graph through the product agent. And when the historical solution based on the development demand is retrieved, generating an executable code by encoding according to the hierarchical code generation strategy based on the historical solution through the architect agent. And performing grammar verification, operation verification and demand conformity detection on the executable code by combining the context state information based on a hierarchical verification mechanism through a test agent to obtain a verification result. And when the test agent judges that the verification result meets the development requirement, summarizing the executable code into a final code implementation scheme through the summarizing agent, and pushing the final code implementation scheme to a user. And the reuse rate and the quality control capability of code development are improved.

The invention provides an industrial PLC code generation system and method based on artificial intelligence, and the system comprises an input module, a model optimization module, a code generation module and a deployment module, the input module is used for receiving and analyzing a natural language, a flow chart and an I / O configuration table, and generating a structured logic constraint; the model optimization module is used for supporting low-precision reasoning and dynamic expert network load balancing by adopting an artificial intelligence model of industrial control field data fine tuning; the code generation module is used for outputting PLC codes meeting industrial standards and supporting simulation verification and error correction; and the deployment module is used for downloading the generated code to target PLC equipment or integrating the generated code to engineering software. According to the industrial PLC code generation system and method based on the artificial intelligence, a tool for generating the PLC code based on the natural language of the artificial intelligence is provided, the code development efficiency is improved, and the error rate is reduced.

The invention discloses an intelligent file service system generation method based on a low-code development mode. The method comprises the following steps: constructing a file service core data model, defining file metadata fields, a storage structure and an association relationship, and forming a standardized data architecture. According to the method, the core data model, the visual page component library and the drag-and-drop workflow template are constructed, linkage binding of data-component-process is achieved in combination with a low-code engine, and the efficiency bottleneck of a traditional development mode is broken through; through a three-way real-time synchronization mechanism, real-time hot repair and dynamic branch judgment, page layout and flow rule adjustment can take effect immediately through visual configuration, and the problem of dynamic demand response lag is solved; through the intelligent resource scheduling logic compiled through environment adaptation, a differentiation scheme is generated for different deployment environments, the configuration difference influence under a private cloud and server mixed deployment scene is remarkably reduced, the deployment failure rate is greatly reduced, and the system online stability is improved.

The invention relates to a platform management method and system based on low code development, and the method comprises the steps: obtaining a plurality of heterogeneous data sources, extracting first data from the plurality of heterogeneous data sources, and carrying out the preprocessing of the first data, and obtaining standard data used for constructing a knowledge graph; and acquiring a plurality of different entities and entity relationships among the different entities from the standard data, and constructing the knowledge graph according to the plurality of different entities and the entity relationships among the different entities. And mapping entity nodes in the knowledge graph and entity relationships among different entity nodes to a low-dimensional space through a graph embedding model to perform vector representation so as to extract global knowledge including the entity relationships among different entity nodes and a network topology structure. And acquiring a predefined business process and a plurality of corresponding decision points when the business process is executed, and evaluating an execution result of the business process by executing global knowledge and a current business process variable to obtain a corresponding guidance decision.

The invention provides a knowledge graph construction method based on a low-code development platform, and belongs to the technical field of knowledge graph construction. The method comprises the following steps: counting and carding metadata and business entity structures in a low-code development platform, and formulating a mapping specification for mapping from a relational database to semantic data; obtaining a target relational database in the configuration file, extracting table data and column data in the target relational database, and converting the table data and the column data into entity class parameters and attribute class parameters in the knowledge graph based on a mapping specification; extracting an unstructured data source related to the target business from the low-code development platform, and converting the unstructured data source into structured data; and associating the structured data with the entity class parameters and the attribute class parameters, and storing the associated data in the knowledge graph. Automatic mapping and storage from the relational database to the knowledge graph are realized, so that the data utilization rate and the business intelligence level are improved.

The invention discloses an AI semantic understanding-based zero-code multi-terminal application automatic construction method, which comprises the following steps of: receiving a UI design draft image and layer metadata uploaded by a user, respectively extracting visual features and structural features through a double-branch feature extractor based on an AI semantic understanding technology, and establishing an AI semantic understanding model; a cross-modal attention module and a cavity space pyramid pooling module are combined to generate an enhanced feature graph, and a high-precision UI component mask and an interaction dependency graph are generated; according to target end equipment parameters, dynamic weights are generated through a multi-layer perceptron, layout constraints of the interaction dependency graph are adjusted, a layout target function is optimized, and component overlapping and visual unbalance are minimized; based on the predefined control library and the mapping rule, the UI component is mapped into the atomic control of the target platform, the interaction logic is converted into the event-action chain, and the target platform code is generated, and the automation degree and the cross-platform consistency of zero code development are improved through dynamic adaptation of the target end equipment and automatic code generation.

The present application discloses a test code repairing method applied to a code development platform. The method comprises: obtaining a test code corresponding to a source code, and then executing the test code to obtain execution information of the test code, wherein the execution information comprises abnormal stack tracking information output during execution of the test code; on the basis of the execution information, performing fault localization on the test code to obtain location information of a faulty code; on the basis of the location information of the faulty code, extracting context information, wherein the context information comprises at least one of a faulty test case, a fault description, or the faulty content; and inputting a prompt constructed on the basis of the context information into a language model and performing inference, so as to obtain a first repaired code. The method is used to perform fault localization in light of the execution information, extract the context information on the basis of the location information of the faulty code, and, on the basis of the context information, generate accurate and complex repaired code via an advanced language model, thereby adapting to various complex fault scenarios and improving repair efficiency and accuracy.

The invention discloses a low-code development platform event arrangement method and device based on native JS, and relates to the technical field of visual programming, and the method comprises the steps: responding to an event arrangement request sent by a user through a visual development interface, calling a visual framework, and presenting an event arrangement canvas in the visual development interface; configuring event nodes and event process connections in the event arrangement canvas; generating event flow configuration data based on the event node and the event flow connection; converting the event flow configuration data into a native JavaScript code, calling a rendering engine, and rendering a page style and page data of the visual development interface according to the native JavaScript code; and in response to an interactive operation of a user on the visual development interface, triggering the corresponding native JavaScript code to execute a corresponding event process. The development efficiency can be effectively improved, and the development period is shortened.

The invention discloses a programming assistant framework, a programming assisting method, equipment, a medium and a product, and relates to the technical field of artificial intelligence, and the programming assistant framework comprises a DevOps platform integration module, a DevOps platform integration module, a DevOps platform integration module, a DevOps platform integration module, a DevOps platform integration module and a DevOps platform integration module, wherein the DevOps platform integration module is used for receiving input information sent by any link in links for code development and maintenance; the input information is sent to a code completion and dialogue function module; the code completion and dialogue function module is used for acquiring code related problems in input information, reading source codes in a project code library, and performing abstract syntax tree analysis on the source codes to obtain an abstract syntax tree; and the RAG retrieval enhancement generation module is used for performing semantic recognition on code related problems to obtain a user intention, traversing the abstract syntax tree according to the user intention, determining code context information, obtaining retrieval information according to the user intention and the code context information, and outputting code suggestions generated according to the retrieval information. The overall development efficiency in the development process is improved.

The invention relates to the technical field of multi-source data synchronization, in particular to a cross-library data real-time synchronization method based on a CDC technology. Data change is synchronized to a target system in real time through code-free graphical configuration, so that synchronization from a source database to a data warehouse, a data analysis platform or other business systems is realized, secondary code development is not needed, business personnel with low technical threshold and non-technical background can realize cross-database real-time synchronization of data through interface configuration, and the data synchronization efficiency is improved. Communication and cooperation among different departments are enhanced, and the working efficiency is improved.

The invention relates to the technical field of code pre-configuration, in particular to a demand-oriented code pre-configuration method, system and equipment and a storage medium. Matching a plurality of performance function number sequences from the code function library according to the function requirements of the target scene; performing function demand sample frequent mining on the target scene to obtain a function demand input parameter and a function demand output identifier set; inputting the function demand input parameters into a plurality of function number sequences to obtain a plurality of function demand prediction outputs; traversing the plurality of function demand prediction outputs for outlier analysis to obtain a plurality of output prediction outlier factors; traversing the plurality of performance function number sequences to carry out calculation power demand prediction to obtain a plurality of expected calculation power; and based on the plurality of expected computing power and the plurality of output prediction outlier factors, sorting the plurality of performance function number sequences to obtain a target performance function number sequence, and executing code pre-configuration. The code development efficiency is improved, and the code practicability is enhanced.

The invention provides an intelligent low-code platform development system based on a large model, and the system comprises a data processing and storage module which is used for collecting and processing business demand data; the low-code development module is used for visually arranging page layout and business logic to generate configuration metadata and supporting a user to operate based on a dialogue mode; the test module is used for generating, executing and feeding back a test case and ensuring the quality of the developed application program; and the artificial intelligence and reasoning module is used for providing capability based on machine learning and natural language processing and supporting intelligent data processing, content generation and reasoning. And the interaction and agent module is used for supporting a user to interact with the system based on a dialogue mode and realizing automatic task execution. According to the system provided by the invention, the code development efficiency and the application program quality can be remarkably improved, and meanwhile, the development cost is reduced.

The invention provides a sandbox isolation style debugging method and equipment based on a generative AI technology, and belongs to the technical field of low-code development, and the method specifically comprises the following steps: creating an isolated sandbox rendering environment, loading a user-defined style, and establishing an accurate corresponding relation between a preprocessed code and a final CSS; the custom style is injected into the last position of a head area of a sandbox environment through a created stack label to provide a real-time preview interface, so that when a user modifies the style in a style editor, a page in a sandbox updates and displays a modification effect; receiving a modification operation of a user on the style through the style editor or the style editor, and injecting a sandbox environment to trigger interface updating; and storing the final custom style file. By creating the isolated sandbox rendering environment, the style debugging process is limited in an independent space, the influence of style conflicts on the whole page is effectively avoided, and the debugging safety and stability are improved.

The embodiment of the invention discloses a contract generation method and device based on a low-code platform and a medium, and relates to the technical field of low-code development, and the method comprises the steps: obtaining a contract creation demand form inputted by a user through a form interface corresponding to the low-code platform, the contract creation demand form comprises contract dynamic data and contract attribute information; based on the contract attribute information, a corresponding contract template file is loaded on a front-end page through a preset plug-in, contract configuration information corresponding to the contract template file is determined, and the contract configuration information comprises form fields and business logic rules; and according to the contract configuration information, performing front-end and back-end verification on the contract dynamic data, and when the cooperative verification is passed, performing dynamic matching on the contract dynamic data and the contract template file to generate a target contract file.

The invention discloses a code generation method and device of a front-end component and a computer program product. Relates to the field of front-end development, and comprises the following steps: responding to a dragging instruction of a user, dragging a front-end component to a visual interface, responding to a configuration instruction of the user, configuring attributes, styles and events for the front-end component, and obtaining a configured front-end component, the front-end component comprising at least one of a button, a textbox, a card and a table; determining a first target data model of the configured front-end component, and generating a front-end code of the first target data model based on the component knowledge base and the code generator; responding to a natural language instruction for describing the business logic of the front-end component by the user, and inputting the natural language instruction into the large language model to obtain a front-end logic code of the front-end component; and determining the front-end code and the front-end logic code as target codes of the front-end component. Through the method and the device, the problem of low code development efficiency of the front-end component in related technologies is solved.

The invention discloses an automatic interface docking method and system, a medium and a low-code development platform, and relates to the field of Internet information services, and the method comprises the steps: determining a target interface as a docking target in an interface database according to an interface docking request of a user; obtaining an interface configuration file of the target interface, wherein the interface configuration file comprises a service port, an interface transmission protocol and interface authentication setting; generating a calling code template based on the service port, the interface transmission protocol and the interface authentication setting; generating an interface calling code based on parameter setting of a user on the calling code template; and when the interface configuration file of the target interface changes, updating the interface calling code. According to the invention, the interface docking efficiency can be improved.

There are provided systems and methods for dynamic user interfaces and content with reduced code development using an intelligent scenario simulation engine. A service provider, such as an online transaction processor, may provide computing services to users, such as electronic transaction processing, which may be facilitated and / or assisted by agents of the service provider. To provide dynamic user interfaces and content tailored to a user experience and based on different simulated scenarios of the user experience, the service provider may utilize a simulation engine to simulate permutations of user interfaces and content from combinations of the user and / or agents data and service states of available services that may be accessed and used through the user interfaces. This may utilize a large language model and / or generative AI to simulate such scenarios, as well as computing code for the user interfaces and calls to provide content via the services.

The invention discloses a solution for intelligent low-code construction and automatic deployment of a multi-terminal application full stack, belongs to the technical field of software development, and solves the problems that an existing low-code development platform is high in use threshold, does not support customized development and is disjunction in application construction and application use. The invention provides an intelligent low-code construction platform. The intelligent low-code construction platform comprises a low-code construction platform, an application rendering unit, an application deployment unit and a display interaction unit, the low-code construction platform is used for constructing a plurality of application pages according to the developer personalized configuration information, and associating the plurality of application pages according to set association logic information among the plurality of application pages to obtain an application program; generating application data according to the application program, and storing the application data; the page cross-end rendering unit is used for performing Web end and App end rendering on the application program according to a defined page rendering protocol to obtain a Web end application and an App end application; and the display interaction unit is used for displaying the interaction function and the application logic of the Web end application and the App end application.

Disclosed in the present application is a code generation method, which is applied to a code development platform. The code development platform comprises a main plug-in and a plurality of extension plug-ins, wherein the main plug-in is used for providing an actual value of a basic variable of a prompt, and the plurality of extension plug-ins are used for extending the prompt in terms of a programming language, scenario or development framework. The method comprises: a main plug-in receiving a code generation instruction, and then determining, in response to the code generation instruction, at least one extension plug-in corresponding to the code generation instruction from among a plurality of extension plug-ins; the main plug-in receiving a prompt returned by the at least one extension plug-in, wherein the prompt is obtained by means of the at least one extension plug-in extracting an actual value of an extension variable on the basis of extraction logic and replacing an extension variable in a prompt template with the actual value of the extension variable; the main plug-in performing inference by means of a language model and on the basis of the prompt, so as to obtain a second code segment. In the method, a prompt of a specific code generation task and the implementation of prompt engineering is entrusted to corresponding extension plug-ins, thereby realizing flexible extension of prompts.

Disclosed in the present application is a code generation method. The method comprises: a code development platform receiving input information from a user for a first code file in a project; acquiring in-file context and first cross-file context on the basis of a static structure of the project; acquiring second cross-file context on the basis of behavior characteristics of the user when developing the project; acquiring third cross-file context on the basis of the degree of evolution coupling between at least one second code file in a code warehouse of the project and the first code file; generating prompt information on the basis of the input information, the in-file context, the first cross-file context, the second cross-file context and the third cross-file context; inputting the prompt information into a code generation model for reasoning, so as to obtain at least one group of generated codes; and presenting to the user the at least one group of generated codes in parallel. The method takes multi-dimensional project-level context and a user input as inputs of a code generation model, thereby improving the capability of the code generation model using cross-file context during code generation, and improving the code generation performance.

The invention provides a data acquisition and monitoring analysis system based on an MES platform, and relates to an industrial software application system. Comprising a low-code development module, a factory modeling module, a monitoring module and a data acquisition module, the low-code development module realizes cross-device linkage development and control program generation through combination of a dragging interface and a device API library in an MES platform integration environment, and guarantees efficient communication control of the device, the factory modeling module integrates two production modes, and the monitoring module is connected with the monitoring module. The monitoring module is used for realizing dynamic modeling and optimizing a production process according to multi-dimensional parameters, the monitoring module is used for realizing ultra-low-delay transmission processing and real-time monitoring of data under high concurrency by applying a dual-cache and message middleware mechanism, and the data acquisition module is used for realizing real-time monitoring of the data based on a machine learning algorithm and a complex event processing technology. Dynamically adjusting the acquisition frequency precision based on the production state; the system aims at improving the efficiency, quality and management level of industrial production, and has wide application prospects and important industrial software application value.