177 results about "Domain-specific language" patented technology

Techniques for grammar powered retrieval augmented generation for domain specific languages are disclosed. In some embodiments, a system, a process, and / or a computer program product for grammar powered retrieval augmented generation for domain specific languages includes automatically generating a seed dataset for a domain specific language (DSL) (e.g., a resource query language (RQL), and wherein the RQL is generated for RQL for multi-domain security applications); expanding the seed dataset for the DSL using a Large Language Model (LLM); and validating the seed dataset for the DSL, wherein the seed dataset for the DSL is input to the LLM for fine tune training of the LLM (e.g., fine-tuned for a cloud security application).

A cloud deployment automation system consisting of: a deployment automation device housed in a rack-mountable enclosure, the device comprising: a multi-core orchestration processor configured to execute deployment logic as compiled execution graphs; a storage module operatively coupled to the orchestration processor, the storage storing a set of deployment templates, real-time execution states, telemetry logs, and policy configurations; a secure credential management processing unit embedded in the device, configured to generate, store, and rotate cloud access tokens, API keys, and user-specific credentials, and to provide encrypted access to those credentials during deployment execution; an in-memory workflow execution engine executed by the orchestration processor, configured to analyze a user-defined deployment configuration that includes a declarative specification of infrastructure resources and compile that configuration into a directed acyclic graph (DAG) that represents the resource deployment order, dependency mapping, and rollback relationships, a cloud provider interface subsystem communicatively connected to multiple heterogeneous cloud platforms via appropriate API adapters, the subsystem enabling the orchestration processor to send provisioning requests and receive status events from the platforms; a customizable workflow compiler unit configured to convert graphical workflow definitions or domain-specific language (DSL) scripts into execution sequences that can be used by the workflow execution engine, where the workflow compiler unit supports conditional branching, asynchronous operations, and runtime variable resolution; and A policy enforcement control unit integrated into the deployment automation device, with the policy engine configured to apply organization-specific compliance rules, tagging conventions, security group configurations, and runtime resource limits to all deployment actions in a context-aware manner prior to execution.

The invention discloses a multi-agent task arrangement method and system, and relates to the technical field of artificial intelligence. In the method, firstly, a task demand is obtained, key information and intention of the task demand are extracted, and task semantics are obtained; secondly, based on the task semantics and the business standard process template, obtaining a business standard process template matched with the task demand; then, according to the matched business standard process template and task semantics, a task context is constructed, and a domain specific language DSL is generated through reasoning according to the task context; thirdly, the DSL is analyzed, a task dependency graph is constructed according to the DSL analysis result, and the task dependency graph is converted into BPMN process model data; and finally, sub-task scheduling and execution of the sub-agents are carried out according to the BPMN process model data. According to the method provided by the invention, the dependence on professional developers or process engineers can be reduced, the response and planning time of complex tasks can be shortened, the result predictability can be improved, and the reasoning cost can be obviously reduced.

Systems, devices, and techniques are disclosed for network security policy generation and distribution. A security policy written using a Domain Specific Language (DSL) for network security may be received. The security policy may be associated with a service owner and a control plane. A representation of the security policy may be generated from the security policy. A configuration bundle of the service owner may be updated with the representation of the security policy. The security policy may be determined to be approved. A rule set may be generated from the representation of the security policy. A differential between the rule set and a current rule set may be determined. A security component associated with the control plane based on the differential may be configured.

The embodiment of the invention provides a multi-agent arrangement method and device based on a service grid and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the following steps: generating corresponding domain-specific language description information based on workflow information of a plurality of agents; and based on the domain-specific language description information, generating routing information corresponding to the workflow information of the plurality of agents, the routing information being used for defining a calling relationship of the plurality of agents in the service grid. According to the scheme, the labor cost is reduced, and the arrangement efficiency is improved.

The invention relates to a low-code visualization optimization method and system for power credential development, and the method comprises the following steps: S1, obtaining data in a credential environment, recognizing the interface difference and performance bottleneck points between components through a compatibility test matrix, and building a standardized adaptive interface specification; s2, obtaining a standardized business object model based on the standardized adaptive interface specification; based on the business object model, defining attributes, relationships and constraint rules of each business entity, and forming a data dictionary and an interface specification special for the electric power field; s3, on the basis of the data dictionary and the interface specification special for the power field, constructing a DSL (field specific language) of power visualization; s4, a dragging type interactive design is adopted, and the visual operation is converted into a DSL configuration file; and S5, automatically converting the DSL configuration into a React or Vue component code through a code generation engine, and carrying out compatibility optimization on the kernel of the creative browser. According to the invention, the power credential development efficiency is effectively improved.

Disclosed is a computer-implemented method for constructing a domain-specific language learning model (LLM). The computer-implemented method includes a step of ingesting, from a server, a domain-focused dataset. The computer-implemented method includes a step of assimilating, from a search engine database, a real-time digital data stream. The computer-implemented method includes a step of integrating the domain-focused dataset, and the real-time digital data stream within an application logic layer to obtain an integrated dataset. The computer-implemented method includes a step of employing, by a processor, a transformer algorithm on the integrated dataset to extract a plurality of domain-specific textual insights. The computer-implemented method includes a step of utilizing, by the processor, said domain-specific textual insights to execute one or more business tasks. The computer-implemented method includes a step of presenting both the domain-specific textual insights and the executed business tasks on a user interface.

A method of extracting meta-data from a document includes capturing style attributes from the document, identifying cell-wise location coordinates for text characters using page segmentation and border table extraction, and finding relationship between nearby cells using surrounding embedding by determining shortest distant text cell in top, left, right, and bottom direction. The method further includes applying Graph Convolution Network with Informative Attention (GCN-IA) for providing more attention to informative nodes for generating better representation of surrounding embedding and capturing a deep contextual meaning from text cells. A domain specific language model is utilized and improved by a domain aware tokenizer. The method includes capturing a complex visual layout of the document using the domain specific visual model, determining meta-data information, representing linguistic and visual contexts of the document, and correcting the extracted output by applying advanced-post processing on the extracted output from advanced language-visual model.

The embodiment of the invention discloses a code conversion method and device based on a domain-specific language and a medium, and relates to the technical field of code conversion, the method comprises the steps that a DSL file and a target conversion language input by a user are received, the DSL file comprises at least one class definition, and the class definition comprises a class name, a field declaration and a method signature declaration; the DSL file is analyzed to extract a plurality of class annotations marked in the class definition, and the class annotations comprise target language identification information, unique class identification information, construction mode identification information and array access mode identification information; and according to the target language identification information in the target conversion language and the class annotations, a matched specified class annotation set is extracted from the class annotations, a code file conforming to the grammar of the target conversion language is generated based on the specified class annotation set, and the specified class annotation set comprises the class annotations, field annotations and method annotations.

The invention discloses a data exception attribution method and device, equipment, a storage medium and a program product, and relates to the technical field of data exception detection.The method comprises the steps that to-be-detected target data is obtained; identifying abnormal points of the target data, and generating an abnormal detection result; converting an anomaly detection result into a domain-specific language description; the domain specific language description is analyzed, and related events corresponding to the abnormal points are determined; and analyzing the correlation between the related event and the abnormal point, and generating an attribution result corresponding to the abnormal point. According to the technical scheme, automation from anomaly detection to attribution result generation is achieved, the problem of anomaly detection and attribution separation is solved, and the attribution analysis effect of data anomaly is improved.

The invention discloses a large language model structured generation system and method, and relates to the technical field of artificial intelligence, and the system comprises a front end which is used for receiving a domain-specific language input by a user, and converting the domain-specific language into a back-end recognizable language; the back end is used for receiving the back end recognizable language and converting the back end recognizable language into basic operators, and the basic operators comprise a wait operator, a write operator and operators evolved based on the wait operator and the write operator; the reasoning framework is used for receiving a domain-specific language input by a user and converting the domain-specific language into a lexical ID state machine; the lexical ID state machine is used for constraining the large language model generation content based on the basic operator corresponding to the lexical ID state machine so as to ensure that the large language model generation content conforms to the corresponding grammar structure, the problem that in the prior art, the requirement for efficient and accurate processing of the complex large model structuring cannot be achieved is solved, and the large language model structuring efficiency is improved. And the problems of high time complexity, weak structured demand description capability and high use threshold exist.

The invention relates to the technical field of data compliance. According to the AI-driven data compliance rule intelligent method, device and equipment and the medium, the method comprises the steps that natural language input of a user is obtained, and user demand description is obtained; performing multi-dimensional semantic analysis on the user demand description through a pre-trained large language model, and generating a structured semantic framework comprising an intention vector, an entity relation graph and a constraint condition set; performing compliance correction on the structured semantic framework to generate an optimized semantic framework; performing logic conflict detection and performance simulation test on the domain-specific language rule to generate an executable compliance rule; and deploying the executable compliance rule to the target data governance platform so as to achieve the technical effects of reducing the learning threshold and the manual error rate generated by the domain specific language rule, improving the semantic adaptation capability in a complex business scene and optimizing the operation stability of the rule on the data governance platform.

The invention discloses a data analysis method and device, equipment and a storage medium, and relates to the technical field of data analysis, and the method comprises the steps: analyzing a user analysis demand according to a data big model and prompt word information corresponding to a preset grammar rule, and obtaining a demand operation type and a data processing sequence; performing instruction generation according to a preset grammar rule, the demand operation type and the data processing sequence to obtain a domain-specific language; and analyzing the to-be-analyzed data according to the domain-specific language and the data analysis engine to obtain a target data analysis result. Complex data analysis and visualization requirements of a user are expressed in a concise language description through a set grammar rule, a large model only needs to generate a domain-specific language, and then the domain-specific language is analyzed by an analysis engine, so that the use cost of the large model is reduced, and meanwhile, the data analysis efficiency is improved.

The invention relates to the technical field of financial report data processing, in particular to a financial report data processing system based on a domain-specific language. According to the method, calculation and verification of financial report subjects are completed through an integrated pipeline of DSL, AST / IR, DAG and parallelization / vectorization / caching / JIT; through an STRICT / ZERO / SKIP strategy machine and assertion type verification, the robustness and audibility are ensured; under expression-level and execution-level multi-optimization, considerable throughput and stability improvement are realized. According to the method, the financial report formula can be flexibly defined through the DSL, automatic analysis and calculation execution can be realized, and unified processing of dynamic balance verification can be realized, so that the processing efficiency and accuracy can be comprehensively improved.

Adaptable data warehousing computing systems and methods are disclosed for improved and flexible declarative control for programmatic modeling and database building, including in compute intense environments. A declarative scripting engine executes computing commands defined in a domain specific language (DSL), which is configured to programmatically configure a conceptual data model defining business object(s). A logical data model may be generated based on a declarative command defining the conceptual data model. A physical data model may be generated based on the logical data model, where the physical data model defines stage, core layer, and / or a data mart layers that may be deployed to a target database or data warehouse, and where the stage, core layer, and / or a data mart layers are the same or similar to those of the logical data model.

The invention provides a website construction method and device based on a large model, electronic equipment and a readable storage medium, and relates to the technical field of artificial intelligence such as natural language processing, deep learning and large models. The website construction method based on the large model comprises the steps that user request information is input into the large model, and construction demand information is obtained; the construction demand information is input into the large model, a front-end planning information set is obtained, and the front-end planning information set comprises front-end planning information corresponding to each website page; the front-end planning information set is input into the large model, a DSL description information set is obtained, and the DSL description information set comprises DSL description information corresponding to each website page; and performing page rendering according to the DSL description information set, and obtaining a target website corresponding to the construction demand information according to a rendering result. The website construction steps can be simplified, and the website construction efficiency can be improved.

The invention relates to a cross-platform software development method and related equipment. The method is applied to the electronic equipment providing a low-code tool chain, and the low-code tool chain comprises a low-code development platform and a compiler. Based on the configuration of the meta model of the vehicle-mounted resource, the low-code development platform generates an automobile domain specific language VDSL file for describing the vehicle-mounted software function; the compiler obtains the VDSL file, compiles the VDSL file into running program codes running in different controllers and sends the running program codes to a cloud server, and the cloud server is used for sending the running program codes to the different controllers. According to the method and the device, the running program codes corresponding to different controllers are generated through the unified VDSL, so that cross-platform running software programs can be conveniently developed in the same platform, the software development efficiency is improved, and the development cost is reduced.

The invention discloses a sheet metal part manufacturability reasoning method based on space-semantic map alignment, and relates to the field of manufacturing-oriented design evaluation and industrial knowledge reasoning, and the method comprises the following steps: carrying out geometric analysis on a CAD geometric model of a sheet metal part to be evaluated; abstracting the geometric features and the topological / metric spatial relationship thereof into a computable spatial semantic graph; performing semantic analysis on the process specification described by a natural language, converting the process rule into formalized logic check expression by using a large language model through context learning, and generating an executable domain-specific language check script; executing the script on a spatial semantic graph, realizing deterministic reasoning through graph matching and attribute verification, and completing accurate mapping and violation detection of text rules and geometric features; and outputting an interpretable diagnosis result containing violation feature positioning, triggering rules and numerical evidence. In order to solve the problems that a process rule'natural language-geometric model 'has a semantic gap, a traditional rule system is poor in adaptability, and an end-to-end learning method is high in data dependence and cannot be explained, a new rule can be quickly adapted under the condition that a large amount of data does not need to be labeled and a model does not need to be retrained; the method can accurately identify the violation of the micro-size and spatial relationship, and has reasoning preciseness, interpretability and engineering availability.

The invention discloses a dynamic self-verification method based on service flow-test flow homologous heterogeneous execution. The method comprises the following steps: uniformly describing service logic and a corresponding interface test contract through a strong type of domain specific language (DSL); the method comprises the following steps: simultaneously compiling homologous DSL descriptions into stateful business workflows executed by a process engine and stateless and combinable atomic test contract sets called by a test executor by utilizing a double-path compiling engine; during operation, loose coupling synchronous triggering and execution of a service flow and a test flow are realized based on a high-throughput event bus, and real-time and high-fidelity contract verification, performance monitoring and chaos probe testing are performed on cross-system interface calling in a production environment. According to the invention, the traditional post-event and off-line integration test is converted into the in-event, on-line and continuous system endogenous capability, and the industrial problems that the complex enterprise system group integration test is difficult and the operation and maintenance monitoring is passive are effectively solved.

Techniques are provided for processing rules expressed in a domain-specific language. A computing system may receive a rule including an entity identifier, a property of the entity, and one or more logical operators delimited by syntactic tokens of the language. The rule is parsed into an abstract syntax tree (AST) representation that structurally represents entities, properties, and conditional logic, and the AST is transformed into an executable function configured to evaluate input data objects defined according to a machine-readable data model. Execution of the function on input data produces a logical outcome along with intermediate results corresponding to evaluations of individual conditions and logical operators. The computing system generates an execution trace comprising the logical outcome and the intermediate results, the trace being stored in a structured log retrievable to provide evidence of how outcomes were determined.

Techniques for fast smart contract processing and validation. A C3N smart contract may be written in a high-level programming language such as Go rather than a domain-specific language (DSL) for smart contracts that is difficult to learn and utilize correctly. The smart contract may support a predefined list of C3N libraries, including APIs for accessing components within a C3N containerized environment. The smart contract may natively support access to oracles and data external to the C3N blockchain. The C3N smart contact may be deployed as source code or executable code for one or more target architectures. Such executable code may be run directly on the target architectures without additional compilation or interpretation. Validator nodes can verify correct execution of C3N smart contracts through unit tests.

A computer-implemented method, computer system, and computer program product for generating a calculation model. An input natural language text prompt describing a calculation in a particular domain is received. Using a large language model, a domain-specific language (DSL) version of the input text prompt is generated and the DSL version of the prompt is converted to a JavaScript Object Notation (JSON) form that represents a model of the calculation, resulting in a calculation model, which is output to a user.

In one aspect, an example method can be used with a system comprising a set of domain specific language (DSL)-compatible modules. The method can include: (i) designing a template for an interactive media object, wherein the template includes one or more fixed portions and one or more variable portions; (ii) curating the designed template by at least using received input to modify the one or more variable portions of the designed template; (iii) modifying the curated template by replacing a content placeholder of the curated template with a corresponding content item, thereby automatically converting the curated template into an interactive media object definition file; and (iv) using the interactive media object definition file to render and present, via a media selection menu of a presentation device, an interactive media object defined by the interactive media object definition file.

The invention provides a multi-industry supply chain plan configuration method, which comprises the following steps of: converting time series data of a multi-industry supply chain service into an event-driven grammar structure, and constructing a uniform data analysis layer through a domain-specific language; the method comprises the following steps: decomposing a cross-industry business rule into configurable DSL semantic units to form an atomization rule discrimination module; analyzing and executing the DSL semantic unit in real time through a dynamic rule engine; interaction between the business rules and the execution engine is realized based on a DSL compiler, and supply chain plan configuration results adaptive to different industries are generated; and carrying out dynamic aggregation, impact reduction and prediction error analysis on the supply chain data through a time sequence calculation framework, and generating a real-time business guidance index. According to the scheme, business rules are unified and abstracted through DSL, cross-industry rapid adaptation is achieved, rule dynamic configuration supports millisecond-level effectiveness, a visual DSL editor reduces coding requirements, and a time sequence calculation framework is combined with complex aggregation and loop detection.

The invention relates to the technical field of block chain technology and education data management, and discloses an education data management system and method based on a block chain, and the method comprises the steps: constructing an education business field specific language, and training an education business intention understanding model; applying a constraint solving algorithm to solve the smart contract parameters meeting various constraint conditions, and generating a smart contract code meeting multi-objective optimization; performing multi-level formalized verification on the generated intelligent contract code; constructing an educational policy and regulation knowledge base and calculating a contract policy compliance score; implementing a hierarchical transition strategy; the system is constructed based on a domestic Feiteng processor and a Kylin operating system, and stable operation and data security in an extreme environment are ensured; the technical problems of difficulty in intelligent contract development, difficulty in policy compliance evaluation and complexity in contract evolution upgrading in education data management are solved, and reliable storage, safe sharing and effective management of education data are realized.

The embodiment of the invention provides a database statement processing method and device and a data management system.The database statement processing method is applied to the data management system, the data management system is configured with multiple databases, and the method comprises the steps that a to-be-rewritten database statement associated with a target database in the multiple databases is obtained, generating a source syntax tree based on the to-be-rewritten database statement; selecting a target rewriting rule associated with the target database from preset domain-specific language rewriting rules, and determining a statement rewriting type of the to-be-rewritten database statement; updating the source syntax tree according to the statement rewriting type and the target rewriting rule to obtain a target syntax tree matched with the target database; and generating a target database statement based on the target syntax tree, and executing a data processing operation corresponding to the target database statement in the target database.

The invention provides a cross-modal content generation method, system, equipment and program product based on domain-specific language model driving, which are applied to the field of artificial intelligence content generation, and the method comprises the following steps: initializing a domain-specific language DSL file, calling a service module to process commodity information to generate first content data, writing the first content data into the DSL file, and writing the first content data into the DSL file; according to the scheme, the problems that the page making process depends on manpower, and collaboration is low in efficiency can be solved, end-to-end automatic generation of the marketing page is achieved, and the content generation efficiency is improved.

Provided in the present disclosure are a method and apparatus for visual debugging, and a computing device, a computer-readable storage medium and a computer program product. The method comprises: on the basis of a code in an integrated development environment, generating a domain-specific language file associated with at least one graph in the code, wherein each graph represents a workflow in the code; on the basis of the domain-specific language file, acquiring node information and edge information of a graph corresponding to a workflow to be debugged; and on the basis of the node information and the edge information, generating a visual graphical representation of the graph.

The invention relates to a water system upstream and downstream relation modeling and graph database automatic mapping method based on a domain-specific language. The method comprises the steps that nodes of a water system network are converted into DSL texts according to the pre-designed domain-specific language; performing automatic completion on the DSL text; performing automatic verification on the DSL text after automatic completion; performing relation analysis and data structuring on the DSL text after automatic verification so as to produce nodes and a relation data table; importing the nodes and the relational data table into a graph database; and visualizing the data in the graph database. According to the method, the abstract and verification of the grammar level can be carried out aiming at the water system structure relation characteristics, so that the high self-adaption of the business layer is realized, and the modeling efficiency, accuracy and automation level are greatly improved.

The invention relates to a method and device for application development, computing equipment, a computer readable storage medium and a computer program product. The method comprises the steps of generating a first domain-specific language file associated with a zero-low-code platform based on a workflow of a visual application arranged on the zero-low-code platform; generating a first executable code of the application based on the first domain-specific language file; and using the first executable code in an integrated development environment for development of the application.