3833 results about "Programming language" patented technology

The invention discloses a report chart automatic generation method based on natural language analysis and data query, which comprises the following steps: acquiring a natural language text, and constructing a slot set and an initial semantic fragment; executing consistency verification and ambiguity identification, and constructing a semantic framework; executing field standardization and mode alignment, generating a data query statement and establishing a traceability chain identifier; querying a target database to obtain an original data set, completing data quality self-correction, and generating a cleaned data set; calling an improved Mamba model to construct a constraint judgment matrix and outputting a target chart subset; generating a chart description grammar and an image annotation template, and executing image rendering, feature point recognition and image sidebar construction; and performing layout optimization and double compilation, and outputting a structured report file. According to the method, the chart generation automation level and the report compiling efficiency are improved, and the accuracy, traceability and specialty of the output content are ensured.

Techniques for generating an executable API call for an LLM-generated request, where the executable API call is usable to cause a component to generate a potential response to a user input, are described. In some embodiments, the system receives a user input and uses a language model to generate a request for a component to provide a potential response to the user input. The system uses the request, an API description corresponding to the component, and other information not available to the language model during processing to generate an executable API call corresponding to the request. The system can execute the executable API calls (in a system-determined order or concurrently) to cause the corresponding components to generate potential responses to the user input.

The invention discloses an MCP generation and calling method and device in a low-code platform, equipment and a medium, and relates to the field of artificial intelligence low-code, and the method comprises the steps: carrying out the semantic analysis and structure standardization of initial metadata generated in the application development process of the low-code platform, and obtaining target metadata; converting the target metadata into an MCP description file, converting a business description corresponding to the MCP service in the initial metadata into a natural language description which can be understood by a large model, and integrating the natural language description into the MCP description file to obtain a target MCP description file; constructing a standardized MCP warehouse, and managing the MCP service corresponding to the target MCP description file by using the MCP warehouse; and acquiring a user request by utilizing the large model, and performing MCP calling on the MCP service by utilizing the large model based on the current running state data in the application running process, so that the large model responds to the user request. According to the method, deep fusion of low codes and large models is promoted.

Embodiments of the disclosed technologies are capable of generating natural language queries. The embodiments describe generating a training natural language query of a training structured search query using a first LLM and a first prompt. The embodiments further describe fine-tuning a second LLM using the training natural language query of the training structured search query and the training structured search query. The fine-tuned second LLM generates a structured version of a natural language query. The embodiments further describe generating the structured version of a received natural language query using the fine-tuned second LLM and a second prompt.

A structured query language statement generation method, executed by an electronic device, and comprising: determining a natural language text representing a query task, and determining a preset database, the preset database comprising at least one data table, and each data table comprising at least one field (101); on the basis of the natural language text, determining, from the preset database, at least one task-associated field and at least one task-associated data table which are associated with the natural language text (102); rewriting the natural language text on the basis of the task-associated field to obtain a rewritten natural language text (103); acquiring prompt information for the rewritten natural language text, the prompt information being used for guiding a query statement generation model in generating a structured query language statement (104); performing question classification on the rewritten natural language text to obtain question type information of the rewritten natural language text (105); and generating the structured query language statement of the rewritten natural language text by means of the query statement generation model on the basis of the task-associated field, the task-associated data table, the prompt information, and the question type information (106).

A bank of a memory device may be divided into column planes. Each column plane may be associated with column selects. In some examples, a portion of a column plane associated with one column select may be used to store metadata associated with data of the remaining column selects. In some examples, the metadata may be mapped to the data based on a portion of a column address. In some examples, whether the memory device provides metadata responsive to a column address may be based on a value stored in a mode register. In some examples, the portion of the column plane associated with the one column select associated with metadata may also store error correction code data associated with the data of the remaining column selects.

The invention provides a method and system based on NLP file analysis, and relates to the technical field of natural language processing. According to the method, time and identifier unification and format and character set standardization are carried out on the multi-source file, layout segmentation, table structure extraction, reference analysis, term standardization and anaphora resolution are combined, semantic representation is constructed, a hierarchical index and a unique traceability identifier are generated, intention recognition, retrieval sorting, incremental updating and consistency verification are supported, and the method is suitable for large-scale popularization and application. Unification, semantization and traceability of the file analysis process are achieved, and the processing efficiency and accuracy are improved.

The invention discloses a digital back-end full-process script design method, and relates to the field of digital integrated circuit design, and the method comprises the steps: receiving an RTL behavior level netlist, a process library file and a constraint file as input, and generating a library configuration file valeeb.tcl; a gate-level netlist and a corresponding comprehensive report are generated by using a library configuration file valerib.tcl; performing logic synthesis according to the behavior level netlist and the make syn to generate a gate level netlist, and generating layout and wiring data through make out; according to the layout and wiring data, antenna inspection is carried out through a make ant command, design rule inspection is carried out through a make drc command, and comparison inspection of a generated layout and a schematic diagram is carried out through a make lvs command; performing power consumption analysis according to the layout and wiring data; and performing IR analysis according to the parasitic parameters. Aiming at the problem that the chip digital back-end design process is low in efficiency in the prior art, the design efficiency is improved.

A bank of a memory device is divided into column planes. Each column plane is associated with column selects. A portion of a column plane associated with one column select used to store metadata associated with data of the remaining column selects. Both the metadata and the data are provided to an error correction code circuit as a combined code word that provides error correction for both the data and the metadata.

The invention relates to an automatic program repairing method of a dynamic information enhanced large language model. According to the method, key information (such as a variable state, an execution path and the like) in the execution process of a defect program is collected and structurally integrated into an input prompt of an LLM, so that the LLM can deeply understand an execution behavior and a fault occurrence mechanism of a defect code. Meanwhile, dynamic semantic information in the error patch execution process is captured, and LLM is helped to analyze repair failure reasons and optimize subsequent repair strategies. According to the method, structured dynamic debugging information is introduced, so that an iterative repair mechanism similar to'execution-observation-debugging 'of a human developer is realized, the method is closer to a real software maintenance and debugging process, a cognitive reasoning process of the human developer in an actual debugging process is effectively simulated, and the debugging efficiency is improved. Therefore, the potential of the LLM in the program repair task is fully released.

The invention provides a low-code application logic generation method and system based on a large language model, and the method comprises the steps: obtaining a natural language demand and an operation environment snapshot of a user, and constructing a prompt project context of the large language model based on the natural language demand and the operation environment snapshot; based on the context of the prompt project, performing retrieval by utilizing a large language model to obtain a logic component; processing the logic component based on a pre-constructed agent to generate a logic DSL text; analyzing and rendering the logic DSL text to obtain a visual logic flow graph, and updating the logic DSL text in response to a modification operation of a user on the visual logic flow graph; based on the logic DSL text, verifying application logic corresponding to the logic DSL text in the sandbox environment, and deploying the application logic to the current application after verification is passed. According to the invention, complex business requirements can be met, and logic development thresholds are reduced.

The invention provides an intelligent instruction execution method, system and device and a medium. The intelligent instruction execution method comprises the steps that current environment state information of a robot and a natural language task instruction input by a user are obtained; generating cue words at least based on the environment state information, the task instruction, a predefined standardized function interface document and a thinking chain example, and inputting the generated cue words into a large language model; the method comprises the following steps: decomposing a task instruction into sub-task sequences by utilizing a large language model, and organizing the decomposed sub-task sequences into complete executable code blocks; performing static logic verification on the code blocks before code execution; if verification is not passed, error description is generated and fed back to the large language model for code correction; and in a code execution stage, if abnormal information is returned after the code is executed, the abnormal information is returned to the large language model, so that the large language model regenerates a correction code according to an abnormal reason. The autonomous decision-making level and the task execution success rate of the robot are improved.

A natural language-based no-code test automation system is provided. The test automation system includes natural language-based test cases and an app description file including a natural language description of a particular test application run on test devices. An intelligent test execution engine includes an orchestrator configured to convert the natural language-based test cases into actions to be performed for testing the test application on the test devices using the app description file and a large language model subsystem implementing large language models. The orchestrator maps each of the actions to a corresponding test application interface call in the test automation system using one or more of the large language models, and automatically tests the test application by iteratively executing each of the actions via the corresponding test application interface call.

A system and method for inspecting multiple instances across cloud computing environments for a cybersecurity issue is configured to detect a code object in a configuration code file, the code object utilized to deploy a virtual instance in a cloud computing environment; generate in a security graph a code object node representing the code object; generate in the security graph a resource node representing a virtual instance deployed in a first cloud computing environment based on the code object, wherein the resource node is connected to the code object node; detect a cybersecurity issue on the virtual instance; and generate an instruction to inspect a second virtual instance deployed in a second cloud computing environment based on the code object, the second virtual instance represented by a second resource node connected to the code object node.

The invention provides a business processing method and device for an online transaction scene and electronic equipment. Comprising the following steps: acquiring business data, defining a logic arrangement keyword based on an online transaction execution language, arranging the business data according to the logic arrangement keyword to obtain DSL arrangement data, constructing a grammar verification analyzer, and performing grammar verification processing on the DSL arrangement data by adopting the grammar verification analyzer to obtain the DSL arrangement data. An abstract syntax tree is constructed based on the verified DSL arrangement data, the abstract syntax tree comprises root nodes and leaf nodes, the root nodes represent arrangement rules and scheduling logic, and the leaf nodes represent actually called atomic transactions in the service data; and traversing each node in the abstract syntax tree by adopting an execution engine, and calling a node processor corresponding to each node to process the service data. The problem that an existing rule arrangement engine is poor in business reliability when being applied to banking businesses is solved.

The embodiment of the invention provides a method and device for generating a text by using a large language model. The method comprises the steps of obtaining a to-be-matched target sub-sequence from a current lexical element sequence, wherein the current lexical element sequence comprises an input lexical element sequence and a generated lexical element sequence generated by a large language model; the generated lexical element sequence comprises a plurality of special lexical elements used for identifying the beginning of the interval, and the plurality of special lexical elements comprise a first special lexical element closest to the tail of the sequence; from a target word list in a word list library, determining a word element combination matched with the target sub-sequence as a draft word element sequence for speculative decoding; wherein the vocabulary library comprises a plurality of vocabulary corresponding to the plurality of intervals, and the target vocabulary is the vocabulary, corresponding to the interval represented by the first special lexical element, in the plurality of vocabulary; and verifying the draft lexical element sequence by using a large language model to determine a subsequent generated lexical element sequence. And the reasoning speed of the large language model can be effectively improved.

The invention relates to the technical field of software architecture design, and discloses a software architecture design method based on intelligent bionic implementation of a large model group. The method comprises the steps of obtaining software design requirement input; performing multi-level semantic analysis on software design requirement input to generate an initial component set and context environment description; based on the context environment description, candidate component knowledge related to the initial component set is retrieved from a distributed knowledge base; performing consistency verification on the candidate component knowledge and the initial component set by utilizing a dynamic inference engine to generate a verified component map; according to the verified component atlas, candidate software architectures are generated through an architecture template matching algorithm; and performing iterative adjustment on the candidate software architecture by adopting an optimization strategy, and outputting a target software architecture design. Through collaborative analysis and intelligent reasoning of the large model group, automation and intelligence of software architecture design are achieved, and the efficiency and quality of software design are improved.

The invention relates to the technical field of large language models, in particular to an official document content generation and compliance verification system based on a large language model. Comprising an official document extraction module used for analyzing a model essay by using a large language model, extracting a writing style and a fixed sentence pattern, constructing a knowledge graph, storing format specifications, common expressions and logic structures, mining and constructing a core intention library, and storing typical intention prototype vectors; the content generation module is used for generating paragraphs through context sensing, expanding and writing keywords, analyzing behavior data, predicting writing intention vectors and performing condition control; the compliance verification module is used for warning improper words in real time, retrieving policy verification logic and verification formats, and performing pre-verification based on intention vectors; and the writing auxiliary module is used for providing real-time modification suggestions and forward-looking prompts based on writing intention vectors. According to the technical scheme, document writing efficiency and quality can be improved.

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.

A system and method for inspecting multiple instances across cloud computing environments for a cybersecurity issue is presented. The system is configured to: detect a code object in a configuration code file, the code object utilized to deploy a virtual instance in a cloud computing environment; generate in a security graph a code object node representing the code object; generate in the security graph a resource node representing a virtual instance deployed in a first cloud computing environment based on the code object, wherein the resource node is connected to the code object node; detect a cybersecurity issue on the virtual instance; and generate an instruction to inspect a second virtual instance deployed in a second cloud computing environment based on the code object, the second virtual instance represented by a second resource node connected to the code object node.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a large language model to generate computer code executable to generate a series of calendar events for completing a target objective. Furthermore, the disclosed systems provide a catalyst calendar interface which includes a chat window and an integrated calendar window to interface to display the series of calendar events. For instance, the disclosed systems utilize the large language model to generate a task curriculum which includes a set of executable tasks whose completion accomplishes the target objective. Furthermore, the disclosed systems can generate computer code executable by a calendar application to generate the series of calendar events corresponding to the set of executable tasks. The disclosed systems can interact with the chat window to provide the series of calendar events incorporating an integrated view of the calendar application, via the integrated calendar window, using rich calendar content.

The invention provides a layout generation method, a constraint file editor, a layout generator and a terminal.The layout generation method comprises the steps that firstly, device parameters of a target fixed circuit structure are converted into device parameters of a corresponding layout structure based on a configuration file; and determining the arrangement type, array number, spacing and other structural layouts of the device according to the layout rule. And generating a constraint file of bottom design through preset process parameters, and finally generating a layout result of the target fixed circuit structure based on the structural layout of the device and the constraint file. According to the scheme, full-automatic layout and wiring of the analog circuit layout can be realized, the design efficiency is remarkably improved, and the dependence on a specific process and a professional threshold of a layout engineer is reduced. Meanwhile, through parameterization constraint and symmetrical layout control on a fixed circuit structure, high symmetry of the layout is ensured, and the stability and reliability of circuit performance are effectively improved.

The invention provides an intelligent analysis method, system, equipment and program product for automatic code review, which are applied to the field of computer software engineering and development tools, and the method comprises the following steps: obtaining code difference data, preprocessing to generate a semantic code unit, constructing a structured cue word and inputting the structured cue word into a large language model, according to the scheme, the problems that in existing code review, semantic understanding is insufficient, and efficiency is low can be solved, automatic risk identification and analysis of code changes are achieved, and review efficiency and accuracy are improved.

Embodiments of the disclosed technologies are capable of generating natural language queries. The embodiments describe generating a training natural language query of a training structured search query using a first LLM and a first prompt. The embodiments further describe fine-tuning a second LLM using the training natural language query of the training structured search query and the training structured search query. The fine-tuned second LLM generates a structured version of a natural language query. The embodiments further describe generating the structured version of a received natural language query using the fine-tuned second LLM and a second prompt.

A communications session with a user may be automated using a language model. The language model may be instructed to select a next action to be performed where the next action may include transmitting a responsive communication to the user or performing an API call. The prompt used to query the language model may include one or more of the following: a representation of text of the communications session, a list of available API calls, instructions to select a next action, a representation of API calls performed, or a representation of API call responses received. The language model may be sequentially queried to continue the communications session by transmitting responsive communications or performing API calls. In some implementations, a prompt template may be used to generate the prompt and a prompt template may be selected using text of the communications session.

The invention provides a data analysis method and device, equipment, a readable storage medium and a program product. The scheme comprises the steps of obtaining data analysis target information in a natural language form of a user; then, the data analysis target information is input into a first large language model, first task sequence information obtained by splitting the data analysis target information through the first large language model is obtained, and the first task sequence information comprises multiple pieces of task information and task execution logic information of the multiple pieces of task information; then calling a plurality of agents to execute the plurality of pieces of task information according to the task execution logic information to obtain a plurality of pieces of task result information generated by the plurality of agents; and finally, based on the multiple pieces of task result information, determining a data analysis result corresponding to the data analysis target information.

The invention belongs to the technical field of large language models, and discloses a time sequence card generation method and device based on a large language model, and the method comprises the steps: receiving a card creation instruction, and obtaining a card data type in the card creation instruction; extracting target text data in a dialog box of the large language model based on the card data type; converting the target text data into target card data corresponding to the card data type; generating a card title corresponding to the target card data according to the target text data; combining the target card data and the corresponding card titles to obtain time sequence cards; and putting the time sequence card into a tool window adjacent to the dialog box for displaying. According to the method, the manual operation of the user can be reduced, and the co-creation work efficiency and convenience of the large language model and the user are improved.

The embodiment of the invention provides an interface verification method and device based on a dynamic rule, a medium and a program product, and relates to the technical field of parameter verification. The method comprises the following steps: before calling interface processing, acquiring a user-defined annotation associated with an interface; determining a to-be-verified field and corresponding rule index information based on the user-defined annotation; acquiring a corresponding target verification rule from a rule cache list based on the rule index information; wherein the rule cache list is loaded and cached on the basis of a dynamic rule base under the condition of compiling initialization or rule change; and verifying the corresponding field to be verified based on the target verification rule. According to the embodiment of the invention, a cache rule-oriented verification mode is adopted to dynamically adapt to the business change of the rule base, so that the interface verification efficiency in a dynamic business scene can be effectively improved, and the maintenance cost can be reduced.

The invention relates to a multi-modal interaction-oriented automatic operation backtracking and digital person continuous talking control method and system, and the system comprises an operation snapshot module which records operation nodes through a semantic anchor point marking technology, such as an interface XPath page number and a PPT page number; the interruption detection module is used for capturing a user interruption instruction in real time; the progress prediction engine dynamically adjusts a follow-up demonstration path based on a program; and the continuous talk controller is used for coordinating RPA operation execution, digital human rendering and voice synthesis through a three-level priority thread pool. The problems of inaccurate operation flow backtracking and multi-modal thread conflict after demonstration interruption are solved, the breakpoint continuous talk error is obviously lower than that of a traditional scheme, and the method is suitable for PPT demonstration, cockpit explanation, business system training, course explanation and 3D modeling guidance scenes.

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.