274 results about "Domain-specific language" patented technology

A method for directing a domain-specific request to a machine learning (ML) agent of a plurality of ML agents configured to generate domain specific language (DSL) scripts includes, at a computing system: processing a request received from a user to determine a particular domain associated with the request; identifying an ML agent of the plurality of ML agents that is associated with the particular domain; generating, using the ML agent, a DSL script for the particular domain based on the request; executing, using the ML agent, at least one of an API call and a database query based on the DSL script; processing, using the ML agent, a response to the at least one of the API call and the database query; generating, using the ML agent, an output based on the response; and processing the output using at least one other ML agent of the plurality of ML agents.

Behaviour Driven Development (BDD) is used to define test scenarios and to write the test scenarios in code first before writing the application code. Expected behaviours of the new functionality in natural language are defined and converted into test code driven by a Domain Specific Language (DSL) that encapsulates the description of the expected behaviour, after which code for the functionality can start to be written. In certain implementations, artificial intelligence (AI) may be used to first generate the test scenarios and relevant test data, then to produce code that passes all the tests (or iterates until it does) such that the code requires zero or nearly zero human inspection. If generated code passes the test scenarios, it meets the expected behaviour. This saves substantial time investment and reduces the number of steps to completion.

A method for providing a domain-specific language model to facilitate natural language data analytics is disclosed. The method includes aggregating documents from various sources, each of the documents including natural language data; ingesting each of the documents to generate structured data sets that are organized according to a contextual hierarchy; determining prompts that provide domain-specific information for a language model, the domain-specific information including instructions to access the structured data sets; receiving a request via a graphical user interface, the request relating to questions in a natural language format; generating, by using the language model, software codes for the request based on the prompts; and executing each of the software codes to identify results for the request from the structured data sets.

The invention relates to a method and a device for generating software based on a large model technology, a medium and electronic equipment, and relates to the technical field of software generation, and the method comprises the following steps: acquiring demand information of a user for software generation; generating a configuration definition file corresponding to the large model generation demand information through a preset code, wherein the configuration definition file is a configuration file of a domain-specific language definition device; performing regular format reformatting processing on the configuration definition file to obtain a processed file; based on the processed file, determining a service flow logic corresponding to a service function in the to-be-generated software, and based on the service flow logic, generating a target software code corresponding to the to-be-generated software through a code generation large model, the format of the target software code being a configuration file format of the domain-specific language definition device; and based on the target software code, through a preset rendering engine, generating a front-end page and a rear-end page of the software needing to be generated. The method has the effect of improving the software development efficiency.

The invention discloses a domain-specific language compiler optimization method and system based on multi-layer intermediate representation, and the method comprises the steps: S1, defining a DSL to simplify the representation and operation in an MMIR, classifying operators in the MMIR, and enabling all kinds of operators in the MMIR to correspond to keywords in the DSL; s2, analyzing the target MLIR code, extracting input, output and control flow semantics of each operation, mapping an operator in the MLIR code into a corresponding expression in a DSL (Digital Subscriber Line), and converting each optimization strategy into the DSL expression; and S3, generating a DSL code according to the DSL representation, and continuously simulating and evaluating the performance of different optimization strategies by adopting a Monte Carlo tree search algorithm to find an optimal optimization strategy so as to realize compiler optimization. The method has the advantages of being simple in implementation method, low in programming complexity, high in program performance, high in flexibility and the like.

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).

The invention belongs to the field of data query, and particularly discloses a data query method and system based on a large language model, a terminal and a medium. Analyzing the natural language query statement by using a natural language processing technology to obtain query parameters including a query entity, a statement dependency relationship and a user intention; utilizing a pre-trained large language model to generate a logic SQL query statement according to the query parameters; converting the logic SQL query statement into a physical SQL query statement by utilizing a semantic layer technology; the method comprises the following steps of: converting a physical SQL (Structured Query Language) query statement into a domain specific language for Elasticsearch query by utilizing an SQL parser; and executing the Elasticsearch query on the Elasticsearch cluster by using a domain specific language to obtain a query result. A natural language processing technology, a large language model and a semantic layer technology are utilized to convert a natural language query statement into an Elasticsearch query DSL, the data query process is simplified, the data query efficiency and precision of a user are improved, the cost is reduced, and the query requirement is met.

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.

A method includes preparing key actions in a process design document (PDD) from historical PDD documents by tokenizing the PDD with part-of-speech (POS) grammar against key verbs and phrases, extracting automation unit pairs from the historical process documents to map the automation unit pairs with the key verbs and phrases, constructing a set of automation tasks against one or more of the key verbs and phrases, coupling different process models with domain verbs for the phrases to mark one or more of the automation unit pairs as actions against one or more of the key verbs, constructing a tree-like mapping where each key action points to different actions in a target specific automation language, and defining a vocabulary interface of a domain specific language (DSL) by using the key actions and phrases.

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.

The embodiment of the invention provides a large model interaction page rendering method and system, electronic equipment and a storage medium, and belongs to the technical field of front-end development. The method comprises the following steps: acquiring a front-end page processing rule based on a domain-specific language input by a user, and registering the front-end page processing rule into a domain-specific language analyzer; and processing the response message through a front-end page processing rule in the domain-specific language parser to obtain a target code, and executing the target code to render the response message on the front-end interaction page. According to the application, a front-end page processing rule custom function is provided for a user based on a domain-specific language, a custom rule of the user is registered in a domain-specific language parser, and when a response message of a large model is received, a target code for rendering the response message is determined through the domain-specific language parser; custom rendering of the response message is achieved, and the large-model front-end interactive display requirement of a business party is met.

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 provides a code generation method and device, equipment and a storage medium, and relates to the technical field of computers.The method comprises the steps that a target language text corresponding to a target service is obtained, the target language text is compiled through a field specific language DSL, the target language text is analyzed, metadata corresponding to the target language text is obtained, and the metadata are stored in a database; codes of M different programming languages are generated according to the metadata and preset code template files of M different programming languages, M is a positive integer, and the code template file of one programming language comprises a calling structure of the programming language, a grammar structure of the programming language and template variables used for generating code snippets of the programming language. Therefore, the codes of various different programming languages can be generated based on the target language text corresponding to the target business, and the universality and efficiency of automatically generating the codes are improved.

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 embodiment of the invention relates to a method and device for obtaining index data, electronic equipment and a computer program product. The method comprises the steps of generating a second query input by utilizing a language model based on a first query input, and obtaining a first index set, a first dimension set and a first knowledge set from a pre-configured knowledge base based on the second query input; the method further includes determining a second metrics set, a second dimension set, and a second knowledge set using the language model, and generating a domain-specific language DSL code for obtaining metrics data using the language model. In addition, the method further comprises the step of obtaining target index data by using an access service in the index platform based on the DSL code. Therefore, through the embodiment of the invention, the efficiency and the accuracy of index query are improved, and the use experience of the user is remarkably improved.

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.

Various embodiments of the teachings herein include an information processing method. An example method includes: generating a workflow in an OT domain described by using a common information model based on an instruction input by a user, wherein the workflow defines an operation to be performed by a workcell in the OT domain; converting the workflow into a function block program described in a domain specific language; and deploying the function block program described in the domain specific language to runtime of a main controller of the workcell for execution, to control an OT device in the workcell to perform, based on the workflow, the operation.

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 a task execution method based on a domain-specific language and a software development tool chain, and the method comprises the steps: carrying out the analysis and translation of an obtained source code through a domain-specific language compiler, and obtaining a first intermediate representation file obtained through the translation of a plurality of analyzed operators in a parallel mode, performing optimization processing on the first intermediate representation file according to each operator to obtain a second intermediate representation file; and compiling the second intermediate representation file by adopting a reconfigurable computing architecture to obtain a target code to indicate a reconfigurable processor to execute a task. According to the method, the operator in the parallel mode is optimized, and the generated second intermediate representation file is further processed, so that the execution efficiency can be improved, and the resource consumption during operation is reduced. And meanwhile, by using a specific language in the field, the codes are more expressive and intuitive, program errors caused by complex universal languages are reduced, and the readability and maintainability of the codes are 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.

The invention discloses a page rendering method and device, equipment and a storage medium. The method comprises the steps of obtaining a domain specific language DSL file used for describing a target page; the target page comprises a control; based on a preset DSL analysis module, analyzing the obtained DSL file, and creating a control tree structure containing a control instance; rendering the target page according to the created control tree structure; a control instance in the control tree structure comprises a rendering function and a DSL attribute; the value of the DSL attribute comprises DSL data used for describing the control instance to which the DSL attribute belongs; the rendering function is used for determining the current attribute value of the control instance according to the DSL data in the current value of the DSL attribute, and rendering the corresponding control according to the current attribute value of the control instance.

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.

A computer-aided method for generating a computer program is described, which comprises the following steps: a) Providing a functional system model (FM) for the computer program to be created, b) automated execution of a model-to-model transformation (fm2spc) so that a specific system model (SPC) in a domain-specific language (DSL) is generated from the functional system model (FM), c) automated execution of a model-to-text transformation (spc2txt) so that a source code (TXT) for the computer program is created from the specific system model (SPC), d) Implementation of the source code (TXT) into an executable computer program (SUT), e) Generation of a set of executable test cases (TC) based on the functional system model (FM) and / or an optionally underlying original system model (MD), wherein the generation is at least partially automated, as well as f) Verification of the source code (TXT) automatically generated in step c) based on an automated test series of the executable computer program (SUT) using the set of test cases (TC) generated in step e). Furthermore, a computer program product and a development system are specified by carrying out the procedure.

The invention provides a user interface updating method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining a target domain specific language which indicates the characteristics of a target user interface; converting the target domain specific language into a user interface model; and calling a server interface to send the user interface model to a target client, so that the target client performs user interface updating through the user interface model. The dynamic user interface is realized by converting the target domain specific language into the target interface model, so that updating does not need to be performed depending on an installation package, and meanwhile, the user interface model is sent to the target client by calling the server interface; therefore, pushing of user interface updating can be efficiently achieved on the basis that packaging is not needed, and waste of resources is reduced.