224 results about "Interpreter" patented technology

The invention provides a power grid field table data reasoning and question answering method based on a code enhancement framework, and the method comprises the steps: building the code enhancement framework, processing the reasoning and question answering tasks of power project WBS table data through a large language model, and firstly carrying out the structure self-interpretation of the power project WBS table data; the method comprises the steps that firstly, the understanding ability of a model for a complex WBS table hierarchical structure and a task decomposition relation is improved, then based on table structure description and natural language questions formed by work content description proposed by a user, executable codes are automatically generated, related task information and resource configuration data in WBS table data are extracted, and the task configuration information is extracted; executing the code through an external code interpreter to obtain a result, and finally combining the code execution result and the reasoning ability of the model to generate a natural language answer about the number of human resources required for completing the specific work content; according to the method, the understanding, reasoning and people number estimation capabilities of the large language model during processing of complex WBS table data in the power grid operation and maintenance process can be effectively improved.

A system for returning synthetic database query results. The system may include a memory unit for storing instructions, and a processor configured to execute the instructions to perform operations comprising: receiving a query input by a user at a user interface; determining, based on natural language processing, a type of the query input; determining, based on the received query input and a database language interpreter, an output data format; returning, based on a generation model and the output data format, a result of the query input; providing, to a plurality of training models and based on the determined query type, the query input and the result; and training the training models, based on the query input and the result.

The invention provides a graphical programming education system, which comprises a database used for storing coding information and drawing data; the scheduler is connected with the database and used for managing data flow between the database and the interpreter; the interpreter is connected with the scheduler and is used for analyzing the coding information and generating a task in an intermediate representation form which can be understood by the system; the judgment module is connected with the interpreter and is used for carrying out logic judgment on the task and providing a control signal for the operation module; the operation module is connected with the judgment module and is used for executing the task according to the control signal and transmitting the output to the output module; and the output module is used for displaying the result transmitted by the operation module. The system is used for realizing bidirectional mapping and real-time synchronization between the coded information and the graphical representation, and realizing dynamic visualization of the coded information logic based on the data flow.

Provided is an architecture for facilitating creation and enforcement of policy templates. The architecture includes a policy template designer, a script generator, a policy enforcement engine, and a plurality of technology-specific interpreters. The policy template designer records, for creating a policy template, selection of a set of technologies. The script generator generates a policy template script indicative the set of technologies. The policy enforcement engine generates a set of provisioning scripts indicative of a set of resources to be provisioned by the set of technologies. The policy enforcement engine communicates the set of provisioning scripts to a set of technology-specific interpreters of the plurality of technology-specific interpreters. The set of technology-specific interpreters communicate with the set of technologies to provision the set of resources.

The invention relates to the field of three-dimensional modeling and artificial intelligence control systems, in particular to a large language model driving type FMT automatic modeling method supporting an MCP protocol. According to the method, a Python interpreter is embedded into FMT modeling software, a core modeling operation function is registered as a Python callable script, a remote instruction format defined by an MCP (Model Control Protocol) protocol is matched, and a user describes a modeling intention through a natural language; then decomposing a natural language input by a user according to intentions by using a large language model, generating a complete FMT modeling program, and automatically manipulating the FMT to complete modeling operation; and finally, a full-chain closed loop of natural language-script instruction-software operation behavior-real-time feedback is realized, a large language model is supported to directly control an actual software modeling process, and the automatic modeling capability is greatly improved.

The invention belongs to the technical field of mathematical solving, and provides a mathematical application question solving method and system based on data synthesis, and the method comprises the steps: obtaining a to-be-solved mathematical application question; constructing a reasoning chain of the mathematical application questions based on a large language model; judging whether the constructed reasoning chain is converted into a program auxiliary chain or not according to the prompt judgment word; if conversion is needed, the large language model generates an inference chain and a program auxiliary chain, the program auxiliary chain is executed by using a code interpreter, and solving of the mathematical application question is completed; otherwise, solving the mathematical application problem directly according to the reasoning chain.

The invention relates to the technical field of computers, in particular to a method for optimizing the processing speed of a user mode program under an NUMA architecture. The method comprises the steps that in response to the optimization requirement of a user for the processing speed of an original file, first mark information representing the optimization requirement is added in the original file, a target file is generated, and the original file is a user mode program file; registering an interpreter corresponding to the target file; when a starting request corresponding to a target file is received and the starting request is scheduled to the non-uniform memory access node, calling an interpreter to process the target file to obtain a file copy; loading the file copy to a cache space of the non-uniform memory access node; according to the scheme, when the target file is executed, local access can be directly performed, so that delay and performance overhead caused by cross-node access are avoided, and the reading speed and the processing efficiency of the file copy are improved; and while the function complexity is reduced, the system stability is improved, and the system is easier to maintain and manage.

Large Language Model (LLM) driven proactive scheduling may be provided. First, a proactive feedback module may be used that gathers user requests and device feedback. Next, an instructive interpreter module may be used that receives the user requests and the device feedback and produces instructive prompts based on the user requests and the device feedback. Then a user-reinforced scheduling optimization module may be used that receives responses to the instructive prompts and continuously enhances bandwidth scheduling based on the receives responses.

The invention relates to the technical field of computer data processing and mode recognition, and discloses an intelligent handwriting record analysis system supporting translation process traceability and capability assessment, which comprises the following steps: collecting multi-dimensional handwriting data generated when a user translates by using an intelligent pen; the Hidden Markov model decodes the handwriting into translation behavior primitive sequences such as smooth writing, hesitant pause and the like; automatically dividing semantic regions such as a main translation region and a draft region by a density clustering algorithm; performing space-time fusion attribution to generate a space-time attribution log for accurately recording behaviors, time and positions; and establishing a multi-dimensional capability index system containing translation efficiency, quality and strategies based on the log, and carrying out quantitative calculation and generating a visual user capability portrait. According to the method, the invisible translation cognition process is converted into traceable and quantifiable objective data, deep insight and comprehensive evaluation of the translation process are achieved, and a scientific and efficient analysis tool is provided for translation teaching and interpreter ability evaluation.

The invention provides a Python algorithm development debugging system and method based on a simulation platform, the system comprises a TonderPy simulation engine service, a platform interface dynamic library file TonderPy.pyd, a Python interpreter and a Python algorithm model, the TonderPy simulation engine service is used for establishing communication connection with the simulation platform, driving the Python algorithm model, and dynamically optimizing an interface calling time sequence based on a collaborative scheduling algorithm; the platform interface dynamic library file TonderPy.pyd packages an interactive interface of the simulation platform and is used for obtaining situation information of the simulation platform, transmitting the situation information to the Python algorithm model and sending a task instruction to the simulation platform; the Python interpreter is arranged in a TonderPy simulation engine service and is used for loading and executing a Python algorithm source file; the Python algorithm model generates a task instruction according to the situation information; according to the system, standardized calling of a simulation platform interface is realized, and the algorithm development complexity is reduced; the data interaction efficiency between the algorithm and the platform is improved; a real-time closed-loop verification mechanism is constructed, the debugging period is shortened, and the utilization rate of system resources is improved.

A system for standardizing units of measure, comprising: a database comprising standardized units, unit text variations, unit context information, and interpreter standards; a neural network configured to process at least one of: unit text input, unit context input, and interpreter input to generate suggested standardized unit mappings; a nearest unit search component configured to match neural network outputs to permitted standardized units from the database; and an output component configured to provide a standardized unit based on the matched neural network outputs.

Systems and methods are provided for providing a vulnerability applicability module, wherein a context detector, a context detection output interpreter module and / or an executable may be included in a catalog of known vulnerabilities. An IHS remote access controller may detect publication of a catalog of known vulnerabilities and execute the context detector, the context detection output interpreter module and / or the executable included in the catalog. This causes the remote controller to identify configurations for one or more of the plurality of hardware components of the IHS, determine whether any of the one or more of the hardware component configurations are identified as vulnerable in the catalog of known vulnerabilities, and generate comprehensive applicability determination module, which upon execution by the IHS, determines configuration vulnerabilities in the catalog of known vulnerabilities that are present on the IHS for remediation.

Example solutions for providing an artificial intelligence (AI) exception interpreter are disclosed. An exception interpreter receives an exception report from a software application, evaluates it (using AI), and generates a first exception handling response. This provides the benefit of learning over a large amount of exception handling data, which offers super performance over trial-and-error tactics by programmers who are either less experienced or unfamiliar with exceptions from third party resources. Some examples sanitize exception reports of sensitive information. Some examples track an exception event history, so that when the same exception is seen multiple times (meaning a prior response was not effective), a different exception handling response may be provided.

A system implements an interpreter for extensible markup language (XML) to validate XML produced by large language models (LLMs). The system uses an LLM to generate a first set of XML instructions to perform a first task in an environment communicatively coupled to the system. The system executes the first set of XML instructions and observes a result of the execution. Based on the observed result, the system either uses the LLM to generate a second set of XML instructions to perform a second task, or detects an error in the first set of XML instructions. When an error is detected, the system uses the LLM to modify the first set of XML instructions to correct the error.

Disclosed herein are methods, systems, servers, and computer-readable media for interpreting computer code with a multimodal machine learning model. In an embodiment, this comprises: receiving, an input comprising at least one of a text prompt, file prompt, or data object, determining, using a multimodal machine learning model, that the input requires implementing computer code, and in response to determining the input requires implementing computer code: generating computer code based on the input, executing the generated computer code using a code interpreter, and providing, through an interface, an output based on the generated computer code.

The invention discloses an adjustment method for an SAAS platform service rule and an interpreter system. The invention relates to the technical field of a multi-tenant software as a service (Software as a Service) platform. Starting a rule definition interface; and receiving an interface edited by a user in a graphical manner or calling a template in the rule template library, and automatically defining and constructing a business rule. Meanwhile, format check and grammar verification are carried out on the service rules; and if the rule has a problem, returning error information to the user interface. A business rule passing verification is analyzed through an RETE algorithm interpreter module and converted into executable rule logic (rule program); according to the technical scheme of the invention, the tenants can quickly define and adjust the rules according to own business requirements without waiting for the support of a development team, so that the flexibility and response speed of the business are greatly improved. The tenants can flexibly define and adjust the business rules, and personalized requirements are met.

One example described herein can involve a system that receives, from a user, a structured document that describes one or more conditions selected by the user to customize one or more electronic data structures. The system can also query a database to retrieve data from the database. The system can then execute an interpreter program, which can ingest the structured document and the data, identify a subset of the data that satisfies the condition(s), and generate the one or more electronic data structures based on the subset of the data. The electronic data structure(s) can include the identified subset of the data and exclude a remainder of the data. The system can compact the electronic data structure(s) by removing empty fields therein. The system can then provide the compacted data structure(s) to the user.

The present disclosure provides an interpreter of a reconfigurable cryptographic algorithm based on customized high-level C language, in the field of information security. The interpreter includes an input program of cryptographic algorithm customized language, a compilation optimization module, an intermediate file and data flow graph generation module, a mapping module and an array generation configuration code module. The disclosure provides an automatic mapping tool for the reconfigurable processor, which can take customized high-level C language as input, and the interpreter arranges and connects computing units like operators according to the input high-level C program, to complete the mapping of the whole computing function. This can shorten the development cycle of the reconfigurable system, reduce the hardware mastery requirements for users, map the computing units of different parts to the reconfigurable processor in a more optimized way, and effectively enhance the performance of the reconfigurable processor.

The invention discloses a method for dynamically constructing a UDF based on a large model. The method comprises the following steps: S1, constructing a multi-dimensional requirement cue word of a user-defined function according to characteristics and use requirements of a target platform; s2, the multi-dimensional requirement cue words are input into a pre-trained large language model for code generation, the large language model is subjected to multi-round iteration based on the multi-dimensional requirement cue words, and an optimal code sequence for achieving the user-defined function is output; s3, code style standardization is carried out on the optimal code sequence, and a compiler or an interpreter and a static analysis tool are respectively called to carry out grammar check and static analysis on the optimal code sequence, and constructing an optimization cue word according to an error log output by the compiler or the interpreter and a static analysis result output by the static analysis tool, and inputting the optimization cue word into the large language model to carry out iterative optimization on the optimal code sequence.

The invention discloses a multi-source complex table-oriented trusted question and answer agent construction method and system, a question and answer agent is constructed based on a ReAct framework, at least a code interpreter tool and a document reading tool are used in the ReAct framework, and the multi-source complex table-oriented trusted question and answer agent construction method comprises the following steps: constructing a multi-mode complex table analysis tool; the analysis module is used for analyzing a non-editable unstructured table file into an editable structured table text; constructing a single-mode complex table cleaning tool for performing abstract modeling, identification extraction and structure reconstruction on a complex data structure of the structured table text to generate a normalized table which is simpler than an original table in structure; and constructing an illusion detection and repair tool for performing real-time illusion verification on the output content of the question and answer agent, and triggering a fallback regeneration mechanism when illusion is detected. According to the invention, through tool set expansion and multi-tool cooperation, an efficient and credible table question and answer agent is constructed.

The invention provides a Python bytecode obfuscation method and system based on dynamic screening and random replacement, and the method comprises the steps: calculating a plurality of safety indexes and a comprehensive safety index SDI of bytecode files, and screening out the bytecode files which have high safety requirements and need to be obfuscated; a linear congruence generator is constructed, a pseudo-random number sequence is provided for obfuscation operation of byte codes, and operation code dynamic replacement obfuscation operation is performed in byte code instructions by generating random seeds, constructing random dynamic operation code mapping tables and applying the independent operation code mapping tables to different byte code files needing to be obfuscated; and performing obfuscation state detection on the obfuscated bytecode file, if the detection result is the obfuscated bytecode file, modifying bytecode analysis and instruction scheduling logic, increasing a runtime de-obfuscation process, embedding an Opcode reflection mechanism, re-compiling to generate a customized Python interpreter supporting the execution of the obfuscated bytecode, and executing the obfuscated bytecode file. According to the invention, byte codes can be confused.

Various techniques for providing a privacy-aware dynamic path explainer are disclosed. In some embodiments, a system, a process, and / or a computer program product for a privacy-aware dynamic path explainer includes receiving a graph of a network that includes one or more vulnerabilities and / or one or more risk findings (e.g., the graph can also include one or more systems and / or one or more misconfigurations); contextualizing the graph of the network; generating one or more prompts and inputting the contextualized graph to a Large-Language Model (LLM); and generating an output that summarizes the contextualized graph using the LLM.

Disclosed herein are methods, systems, servers, and computer-readable media for interpreting computer code with a multimodal machine learning model. In an embodiment, this comprises: receiving, an input comprising at least one of a text prompt, file prompt, or data object, determining, using a multimodal machine learning model, that the input requires implementing computer code, and in response to determining the input requires implementing computer code: generating computer code based on the input, executing the generated computer code using a code interpreter, and providing, through an interface, an output based on the generated computer code.

The invention discloses an index system early warning method and device, equipment, a storage medium and a program product, and relates to the technical field of operation and maintaining.The method comprises the steps that a logic expression input by a user in a similar natural language form is analyzed, an abstract syntax tree is generated, recursion processing is conducted through a recursion decline interpreter, and an executable rule object is obtained; scheduling the executable rule object according to a preset priority weight to obtain a total scheduling result, the preset priority weight being a weight allocated for the priority of each early warning rule; and when the early warning rule is triggered, carrying out early warning on the abnormal indexes in the logic expression. According to the method, the logic expression is introduced to dynamically define the index, then the logic expression is analyzed into the abstract syntax tree, and dynamic compiling of the abstract syntax tree is realized by using the recursive decline interpreter, so that the flexibility of index early warning can be improved through the introduced logic expression in a complex monitoring scene, and the early warning efficiency is improved. Therefore, the efficiency of index operation and maintenance response is improved.

The present application discloses an intelligent contract execution engine, an intelligent contract execution method, and related devices. The execution engine includes: an interface call unit for calling a specified intelligent contract according to interface parameters; a contract reading unit for obtaining target contract content; an interpretation execution unit for detecting the target contract content, interpreting the target contract content that passes the detection as machine code, and executing the machine code; and a data management unit for performing database operations on the world state to be persisted through a pre-encapsulated PHP constraint class and operating on the environment information during runtime. Since the PHP interpreter is an execution engine widely supported and optimized by the community and has relatively stable execution capabilities; at the same time, since the PHP execution process reads and writes variables based on the register method, it can maintain higher execution performance compared to the Ethereum virtual machine that reads and writes variables based on the stack, and better supports high-frequency blockchain business scenarios.

The invention relates to the technical field of national cryptographic algorithm acceleration, and discloses a national cryptographic algorithm acceleration system based on a Numba just-in-time compiling technology. The numerical calculation mode reconstruction module is used for performing numerical calculation mode reconstruction on SM2 elliptic curve scalar multiplication, SM3 message extension round function, SM4 nonlinear transformation and ZUC flow generation logic contained in the national cryptographic algorithm core calculation module by utilizing an LLVM compiling chain of Numba, and converting an interpretively executed Python code into an optimized machine code adaptive to hardware; key function compiling acceleration is achieved through a (at) njit decorator, hot spot operation is dynamically recognized through compiling scheduling, and a differential instruction optimization strategy is loaded; the platform shows multiple technical advantages: on the development efficiency level, by presetting a standardized acceleration module library and an automatic compiling tool chain, the integration complexity of a national cryptographic algorithm is greatly reduced; in the aspect of operation performance, the compilation optimization depth is better than that of a general interpreter acceleration scheme; in the aspect of safety controllability, the mathematical theory basis of the national cryptographic algorithm is completely reserved, and hidden risks possibly introduced by black box type hardware acceleration are avoided.

A stored program interpreter or virtual machine with a reduced or simple instruction set that implements a Sequencer which allows the programming of time-dependent behavior of controlled loads or circuits such as Electronic Circuit Breaker Units (ECBUs). Programs can be dynamically loaded or modified at run-time, allowing ensemble behavior of controlled loads, such as wig-wag or de-ice heat cycling, to be implemented without a change to the embedded firmware application code.

The invention relates to an ESG questionnaire scoring method, device and system based on an interpreter. The method comprises the steps of obtaining enterprise label information filled by an enterprise user; according to the enterprise label information, taking a plurality of ESG indexes matched with the enterprise user in an index library as target indexes, and obtaining a target index set; according to the target index set, generating questionnaires, and sending the obtained questionnaires to the user side; analyzing the assignment logic pseudo code bound with the target index set through an interpreter to generate a target list; and obtaining answer sheet information filled by the enterprise user for the questionnaire, executing the pseudo-code scoring script in the target list through an interpreter to score the answer sheet, and obtaining the score of each ESG index in the target index set. Through the dynamic configuration mode of the pseudo codes and the use of the interpreter, the adjustment of the scoring logic is separated from the system development, and the dependence on professional developers is reduced, so that the development and maintenance cost of the system is effectively reduced.