1343results about "Requirement analysis" patented technology

The invention discloses an ST code generation method based on graph alignment coding large model and multi-agent collaboration, and the method comprises the steps: receiving an ST code programming demand inputted by a user through a demand analysis module, refining and analyzing the demand based on multiple rounds of interactive conversations of the user and insight agents, and generating a standardized ST code programming demand; the retrieval module receives a standardized ST code programming requirement, and retrieves and obtains related knowledge through a retrieval agent in combination with an ST code knowledge base; and the double-agent collaborative self-correction code generation module receives standardized ST code programming requirements and retrieved related knowledge, a graph alignment coding large model constructed based on a graph neural network and a cross-modal alignment technology serves as a coding agent to cooperatively work with a review agent, ST code structure information is injected into the large model, and a final ST code is generated. According to the method, high-accuracy and high-reliability ST code automatic generation can be realized, and the development efficiency of a PLC program in the industrial control field is improved.

Disclosed herein are systems and methods for enabling decentralized, schema-driven interoperability across distributed computing environments through the use of a Standard Knowledge Language (SKL). An Enterprise Mesh Platform (EMP) interprets and executes SKL specifications—such as capabilities, objects, mappings, policies, and workflows—as composable, machine-interpretable contracts that define data structures, logic, and governance protocols. The system supports dynamic versioning, validation, semantic linking, and recursive execution of SKL-defined components. A mesh-wide analytics server coordinates execution, issue detection, and resolution propagation. Capabilities can be orchestrated, remediated, and adapted in real-time based on SKL-defined relationships, while preserving compliance and traceability. The disclosed architecture facilitates federated development, adaptive system integration, and fine-grained policy enforcement across complex digital ecosystems.

A platform for dynamically generating application experiences. The platform comprises a design management system, an agent orchestration system, an analytics system, a model management system, a user management system, and databases for storing design elements and templates. The design management system provides a portal for application owners / designers to create UX / UI designs, allowing them to select design elements from a set of categories or templates. The platform gathers existing websites / applications to identify common design patterns, stored in a design catalogue database, and suggests historical interfaces for design exploration. It enables the generation of templated applications that integrate with legacy systems. The agent orchestration system parses user specifications, selects generative AI systems, and generates UX / UI content based on the specifications. The analytics system collects and analyzes data to provide insights for improving UX / UI design and optimizing website performance. The model management system trains and maintains generative AI models used for content generation.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a page generation method and device based on a natural language, equipment and a medium, and the method comprises the steps: obtaining a demand description in a natural language form, analyzing the demand description based on a preset intention recognition material, and generating a user intention; retrieving in the page feature vector library according to user intention to obtain a page template, performing graphical user interface rendering on the page template to generate a visual component set, injecting associated data into a target component in the visual component set to generate a target page, publishing the target page or publishing and collecting use effect data after modification, and displaying the use effect data. And updating the page feature vector library by using the use effect data. By combining natural language analysis, intention recognition, vector retrieval, graphical rendering and effect data updating, automation from demand input to page generation is realized, manual intervention and development cycle are greatly reduced, and page generation efficiency and quality are improved.

Techniques for leveraging a large language model (LLM) in software development are described. A description of a software development task is received from a user. Data associated with the software system is obtained from a data source. An LLM is prompted to identify at least one aspect of the task which requires clarification from the user, at least partly by providing the obtained data to the LLM and asking the LLM to identify a question for the user which remains unanswered by the obtained data. The question is presented to the user. An answer to the question is received from the user. The LLM is prompted to respond to propose an implementation of the task at least partly based on the data associated with the software system and the answer received from the user. The proposed implementation is received from the LLM and caused to be displayed to the user.

The invention discloses a structured text code generation and review method, which comprises the following steps of: receiving a control task demand input by a user, supporting natural language, structured form or graphical process input, performing deep semantic analysis by utilizing a demand analysis module, identifying control conditions, control actions and constraint factors, and generating and reviewing a structured text code. The task is converted into a plurality of control units through the SCoT chain; the SCoT chain reader generates a semantic vector according to a task demand, the AST reader generates AST representation through a grammar rule structure and a hierarchical relationship, and the decoder predicts a next grammar rule and generates an ST code in combination with the SCoT chain and AST features; and verifying grammar and logic of the ST code through an interactive automatic review and repair mechanism, if compiling errors occur, analyzing errors by the teacher model and providing repair suggestions, and performing code repair by the student model according to guidance until the code conforms to an expected function and passes compiling.

The embodiment of the invention provides an RPA process generation method and device based on a large model, a medium and a product. The method comprises the following steps: receiving business demand information in a natural language form input by a user; based on a preset large model and a business capability knowledge base, analyzing the business demand information, and determining a business operation sequence matched with the business scene; based on a robot process automation (RPA) component knowledge base and a preset multi-modal visual understanding model, analyzing the service operation sequence into a single-step executable atomic operation sequence; and according to the atomic operation sequence and the large model, generating an executable code of the target RPA component. According to the scheme, a user is supported to input business process requirements in a natural language form, the requirements are automatically converted into the business process operation sequence based on a large model, and the corresponding RPA code is generated and executed, so that the understanding cost of the user is greatly reduced, the execution efficiency of the business process is improved, and the labor cost is reduced.

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 disclosed technology provides for an improved approach to AI code generation. In various embodiments, the disclosed technology provides for an AI agent architecture platform for generating, revising, testing, and debugging code using a customizable team of agents with specific tasks.

The invention relates to the technical field of front ends, can be applied to the field of science and technology finance / digital medical treatment, and discloses an activity landing page intelligent building method and device, electronic equipment and a storage medium. The method comprises the following steps: analyzing activity demand data through a large language model, and matching the activity demand data with features of components in a component library according to an analysis result to obtain candidate components; determining a target component and component attributes according to the user operation instruction to generate an initial page structure; configuring a business association rule between the target components based on the rule engine, and converting the natural language description of the business rule into a form which can be recognized by the rule engine through a large language model; generating a preview page of the activity landing page according to the initial page structure and the business association rule, and updating the page structure and the business association rule according to the adjustment instruction; and compiling and packaging the updated page structure and the business association rule. According to the method, intelligent construction of the landing page from demand to deployment is realized, and the efficiency and normalization are improved.

The invention discloses a software requirement modeling method and device based on a natural language, equipment and a medium, and relates to the field of software requirement modeling. According to the software demand modeling method and device based on the natural language, the equipment and the medium, through automatic demand analysis and model generation, the manual workload is greatly reduced, and meanwhile, errors caused by manual understanding deviation are reduced; close connection among the steps is ensured by sharing intermediate representation and a unified data model, output of the previous step provides structured information for input of the next step, and information loss or distortion is avoided; a demand provider is allowed to participate in a model confirmation process through an iterative demand acquisition and modeling framework of man-machine cooperation, and the quality of a demand model is continuously improved; by means of the model consistency analysis technology based on the data flow dependency relationship, the problem of inconsistency between the requirement specification and the software model can be automatically detected, and the software product quality is improved.

The invention provides a script preservation method which can be applied to the technical field of artificial intelligence. The script preservation method comprises the following steps: carrying out semantic understanding on demand related files by utilizing a large model, extracting core elements, and generating a structured demand change list; analyzing to obtain an abstract syntax tree of an existing script code, and constructing a mapping relationship between the software automation test element and a script code block; dynamically comparing the structured demand change list with an existing script code structure tree based on a mapping relation between software automation test elements and script code blocks, identifying a script range influenced by demand change, and outputting a change influence matrix; and based on the change influence matrix, generating an automatic script code snippet needing to be updated, and realizing preservation of the automatic script. The invention further provides a script preservation device and equipment, a storage medium and a program product.

Implementations relate to generating a plurality of training instances to train a generative model in performing tasks using external tool(s) / service(s) accessible via corresponding API(s). The plurality of training instances each includes a synthetic natural language user instruction and execution step(s) to perform a task (e.g., a single-API task or a multi-API task) specified in the synthetic natural language user instruction. The synthetic natural language user instructions selected for the synthetic training data can be generated based on processing textual prompt(s) using a first LLM, where the textual prompt(s) can each include a list of APIs and associated API documents, one or more seed examples, and a request to synthesize a natural language user instruction. The one or more execution steps for a corresponding synthetic natural language user instruction can be generated based on parsing the corresponding synthetic natural language user instruction using the first LLM or a second LLM.

The invention provides a multi-agent construction method and device and related equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: according to a first target instruction input by a first user, obtaining a plurality of sub-tasks corresponding to the first target instruction and a logic relation between the sub-tasks; obtaining at least one target agent from an agent capability library based on the first target instruction, wherein the target agent is an agent matched with the subtask in the agent capability library; determining a behavior tree structure according to the plurality of subtasks and the logical relationship, wherein the behavior tree structure is used for mapping a connection relationship between the at least one target agent; and adjusting a connection relationship between the at least one target agent based on the behavior tree structure to obtain a target multi-agent. The ability to understand complex business contexts and user intentions is enhanced, and accurate construction of a multi-agent system is realized.

The present disclosure provides systems and methods performed in a central system. An initial entity model comprising a plurality of artefacts is formed. A runtime engine determines a plurality of available agent engagements based on the initial entity model. Responsive to an input selecting one of the available agent engagements, a notification is sent to an external autonomous agent. An indication of an action to be performed is received from the external autonomous agent. Responsive thereto, a message is sent to an external service indicating the action, thereby causing the action to be performed. The entity model is updated with a new artefact corresponding to the performed action, and a further plurality of agent actions is determined based on the updated entity model.

The invention discloses a method and system for establishing a software code and demand tracking relation, and relates to the computer and software engineering technology, and the method comprises the steps: translating a Chinese demand and a code annotation into English, and separating a code logic from an annotation text based on a specified rule; word embedding is carried out on the preprocessed Chinese requirements, the code logic and the annotation text to obtain embedded semantic vector representation; performing hierarchical mixed matching based on the obtained semantic vector representation so as to associate the demand with the code; and fusing the association results through configurable decision logic to determine a final matching result. According to the method provided by the embodiment of the invention, based on a multi-modal semantic alignment technology of the pre-training model, high-precision and robust tracking relation identification is realized by combining deep semantic association of the modeling demand text and the code snippets.

The invention discloses a code generation and restoration method and device based on multi-round feedback of a large language model, and the method comprises the following steps: 1, converting problem description into a structured tetrad (target, input, output and constraint) through a two-stage task demand deconstruction mechanism, and generating a pseudo-code frame according to the structured tetrad; 2, generating a plurality of candidate code schemes in parallel based on different implementation strategies; 3, selecting an optimal code implementation scheme through multi-dimensional evaluation; 4, generating an extended test case through boundary condition analysis and public test reasoning, and expanding a verification range; 5, classifying error types in combination with static analysis and dynamic execution information, and applying a special repair strategy; 6, providing detailed repair reasons and ideas by an interpretable repair mechanism; and 7, establishing a multi-round feedback repair verification iteration mechanism composed of testing, analysis, repair and verification. According to the method, the performance of an existing large language model in processing a complex programming task is effectively improved.

The invention relates to the technical field of artificial intelligence, in particular to a visual large screen development method and system based on a multi-modal large model, and the method comprises the following steps: a demand analysis step, an intelligent generation step, a visual arrangement step, a configuration management step and an operation support step. The method has the beneficial effects that the system can synchronously analyze natural language instructions, business data parameters and visual reference examples through a multi-modal semantic alignment engine, and a design scheme with both function completeness and aesthetic consistency is generated. In scenes of smart city situation awareness, industrial equipment real-time monitoring and the like, a user only needs to input demand descriptions of'displaying energy consumption trends and abnormal point locations of all regions in recent half a year 'and the like, a complete large screen scheme including a thermodynamic map, a time sequence broken line graph and a 3D alarm mark can be automatically generated, and the development period is shortened by more than 70% compared with a traditional mode.

The invention discloses an agent development arrangement scheduling method and system based on a natural language, and belongs to the technical field of agent development creation, and the agent development arrangement scheduling method based on the natural language comprises the following steps: S100, obtaining a user demand and a demand constraint condition according to a natural language instruction input by a user; according to the user demand and the demand constraint condition, decomposing the user demand to form a plurality of sub-targets; according to each sub-target, generating a sub-target cue word template corresponding to each sub-target, and further obtaining a plurality of sub-target cue word templates; and S200, obtaining a plurality of tools corresponding to the plurality of sub-targets, analyzing the tool capability, evaluating the matching degree of the tools and the plurality of sub-targets, and obtaining an optimal tool list. According to the method, user demand analysis, task decomposition and tool scheduling are completed through a natural language processing technology, manual intervention is greatly reduced, and the efficiency of agent development is improved.

According to the automatic software development method and device and the computer program, intelligent demand analysis is achieved through a natural language processing technology, dynamic task arrangement is conducted through a finite state automaton, collaborative development is completed by means of a multi-specialized role agent, intelligent verification is implemented based on a template matching mechanism, and the development efficiency is improved. And a complete automatic closed loop from demand to delivery is constructed. According to the scheme, full-process automation is realized, manual intervention is greatly reduced, and the development efficiency is remarkably improved; through division and cooperation of multiple agents, the professionality and decision-making quality of each link are ensured, and the capability limitation of a single agent is overcome; flexible and reliable process control is provided based on state machine management, and development state changes are dynamically adapted; and the standard consistency of the delivery result is ensured by combining template verification. According to the method, the problems of long development period, large quality fluctuation and the like caused by chain splitting, low intelligent level and excessive dependence on manpower of an existing development tool are effectively solved, and a feasible path is provided for comprehensive intelligence of software development.

Systems / techniques that facilitate automatic product support systems and methods via generative artificial intelligence (GAI) and customer interactions are provided. In various embodiments, a system can access an electronic interaction record pertaining to a software product. In various aspects, the system can synthesize, via execution of GAI on the electronic interaction record, first text that describes a problem afflicting the software product. In various instances, the system can determine, based on executing the GAI on the first text, whether there is an available software feature in an available software feature repository that addresses or solves the problem. In various cases, the system can, in response to a determination that there is no available software feature that addresses or solves the problem, synthesize, via execution of the GAI on the first text, a recommended design alteration to the software product that would address or solve the problem.

The invention provides a 3D application generation method and device and electronic equipment, and relates to the technical field of computers.The method comprises the steps that natural language information input by a user is analyzed through a large language model, and structured scene description information is generated; generating interactive three-dimensional scene preview according to the scene description information; receiving an operation instruction sent by a user for the scene description information based on the three-dimensional scene preview, and determining a final scene configuration parameter according to the operation instruction; and according to the final scene configuration parameters, constructing the 3D application in stages, and after at least one stage is completed, providing a runnable 3D application intermediate version for the user. According to the method, the natural language understanding ability of the large language model is deeply fused with a visual interaction guide mechanism, so that low-threshold and high-efficiency 3D application creation is realized, a user with zero programming basis can quickly and accurately convert the creation into a high-quality immersive application, and the flexibility of 3D application creation is improved.

The invention discloses a code generation method and device based on a natural language and a medium. The method comprises the following steps: obtaining candidate functions provided by a user based on a target system, and determining function demand information described by a natural language; determining target information from the feature information according to the function demand information; wherein the feature information is determined in advance according to candidate functions; and generating a cue word according to the function demand information and the target information, inputting the cue word into the large language model to generate a code module for executing the function demand information, and integrating the code module into the target system. According to the method, the feature metadata corresponding to the candidate functions of the target system is combined with the natural language information of the user to guide and generate the code module for executing the user-defined function requirements, so that the user is allowed to generate the code module which can be integrated into the target system through the natural language on the scene site; and the processing efficiency of the user function requirements is improved.

An integrated development environment (IDE) leverages a generative AI model to generate industrial control code in accordance with specified functional requirements, which can be provided to the industrial IDE system as intuitive natural language spoken or written text. The industrial IDE can also analyze written code in response to natural language prompts submitted against the code, generate answers to user-submitted questions about the code, and offer recommendations for improving the code in response to specific questions or requests submitted by the user.

The invention discloses a software requirement specification document automatic generation method based on a large language model, and the method comprises the steps: text preprocessing: carrying out the category labeling of sentences in software requirement customer opinion data, and dividing a data set into a training set and a verification set; training a demand classifier: classifying texts in the application data set, designing and training a BERT-GCN model, and summarizing different categories of information into different dimensions of software demands; a text multi-classification task: inputting a to-be-processed customer opinion data text into the trained demand classifier for demand text classification, and outputting a classified tagged text; and generating a standard requirement document: inputting the classified tagged text into a large language model, designing a corresponding output prompt template, and guiding the large language model to generate a standardized software requirement specification document. The problems that an existing method for generating the software requirement specification document is low in efficiency and prone to making mistakes are solved.

The invention discloses an automatic page generation method of a software construction platform based on a large language model, which comprises the following steps of: extracting a scene, a page and constraint description from a natural language demand, and generating JSON (JavaScript Object Notation) content containing a data model, a query condition, a table column and static data through the large language model; according to component type constraints and verification rules, the JSON is mapped to components and combinations of buttons, labels, texts, pictures, pull-down selection, multi-choice, single choice, tables, dates and the like of the code-free construction platform; and automatically filling a component set based on the upper and lower partition templates, and injecting static data and verification logic. Through industry knowledge adaptation, component semantic binding and dynamic constraint, it is ensured that the page conforms to field specifications and interaction logic, the learning cost is reduced, manual intervention is reduced, and the method is suitable for the fields of smart cities, natural resources, urban and rural residence construction, emergency management, enterprise digital transformation and the like.

Methods, systems, and apparatus, including computer-readable storage media for validation of Infrastructure-as-Code (IaC) configurations with added context, using a language model. A validation system can receive a request to validate an IaC configuration file. The request can include the IaC configuration file to be validated, as well as identifiers for identifying the policy from which validation requirements should be used for validating the IaC configuration file. Pre-trained machine learning models for generating natural language and / or structured code output may be fine-tuned to reduce or eliminate hallucinations, vague. or incorrect output, using training examples of syntactically correct IaC configuration files. An embedding repository of syntactically correct IaC configuration files and a repository of policy documents can be queried for augmenting the prompt to the language model.

The invention provides an end-to-end intelligent system development method and system based on an AI large model. The method comprises the following steps: S1, receiving a system demand described by a user through a natural language; s2, analyzing the requirements through an AI large model and converting the requirements into formalized specifications; s3, automatically generating a system architecture and dividing components; s4, generating each component code in a recursive manner; s5, dynamically detecting and repairing the generated code problem; s6, automatically integrating all components to form a complete system; and S7, continuously optimizing the system based on system feedback or user feedback. According to the method, work of multiple stages such as demand analysis, architecture design, module division, code writing and testing is automatically completed, distributed integration and smart contract are performed, distributed integration verification is performed through a block chain smart contract and a graph database, data consistency, interface matching and security among components are ensured, the integration process is optimized, and the integration efficiency is improved. Cross-domain cooperation is achieved, and the development efficiency is high.

The invention discloses a financial digital intelligent management system, and relates to the technical field of computers, and the system comprises an atomic power unit ACU, a side effect metadata management module which is used for decomposing a financial process into ACU and defining the structured side effect metadata of the ACU, and the structured side effect metadata comprises an influence object, a type, a condition, a range, a preset risk level and the importance of an associated data object; the dynamic process arrangement engine module is used for generating candidate execution paths according to the process definition and the ACU side effect metadata, and selecting a final execution plan by taking the score minimization as an optimization target; and the execution control and risk relief module selectively performs influence domain sandbox rehearsal before actual execution of the ACU according to a risk assessment result, and executes conditional rollback or compensation when execution fails or unacceptable side effects are generated. According to the invention, through prospective side effect management and intelligent risk avoidance and control, the stability, reliability, auditing performance and combinable innovation capability of a financial automation process are significantly improved.

The invention relates to the technical field of artificial intelligence, and discloses a workflow-based agent implementation method, platform and equipment and a storage medium. The method comprises the following steps: constructing a plurality of business components according to a business scene and a predefined unified metadata structure standard, and constructing a target execution engine; the metadata structure standard comprises an execution link which is a service component to be executed subsequently after the current service component is executed; selecting at least one target component; determining a dependency relationship between the target components based on the execution link, constructing a target workflow, and setting trigger conditions and priorities corresponding to the target components; and in the process of executing the target workflow, obtaining related execution information of the target component, and writing the related execution information into the corresponding message channel. According to the invention, the service component is constructed according to the unified metadata structure standard, so that the user can construct the workflow according to different service scenes, and asynchronous transmission and distribution of related execution information are realized by using the message channel.