144 results about "Toolchain" patented technology

The invention provides a dynamic tool integration method and system for an intention-driven AI dialogue system, and the method comprises the steps: S5, extracting resource occupation information from a transaction log according to a state persistence record, carrying out the resource release and temporary context cleaning of each heterogeneous component, and obtaining a released resource list; s6, searching a breakpoint state snapshot and a transaction log from the distributed database according to the released resource list, and reconstructing a tool chain execution flow historical state to obtain a fault context analysis result; and S8, according to the context recovery state and the semantic feature vector, updating a tool chain execution stream, and reallocating computing resources through a heterogeneous component coordination mechanism to obtain a task continuity confirmation result. According to the method, the recovery efficiency and the resource utilization rate of the tool chain in an abnormal scene are remarkably improved, and the task continuity and the system robustness in a high-concurrency environment are guaranteed.

The invention discloses a large model calling system and method based on an MCP tool chain, and the method comprises the steps: receiving user input, and carrying out the preliminary matching of tools: querying whether the user input contains an entity in an entity database or not through a fuzzy matching technology, and carrying out the preliminary screening of a plurality of candidate tools based on a matching result, so as to obtain limited to-be-selected tools; user input is converted into semantic vectors, semantic matching is conducted in a vector database, and semantic similarities of all tools to be selected are ranked through a similarity calculation method; extracting key information in user input; abstracting the user input into a specified format; and matching the specified format with the historical workflow template, and if the historical workflow template is matched, replacing the key information to a corresponding position of the historical workflow template by adopting a structure-preserving parameter replacement algorithm to realize workflow reuse. According to the method and the device, a complete technical link from accurate tool screening to intelligent workflow multiplexing can be realized.

The invention discloses a lightweight cross-platform PLC (Programmable Logic Controller) multi-language code generation method, which relates to the field of industrial process control, and firstly provides a unified intermediate data model, and on the basis, a module for converting each PLC language into the unified intermediate data model is realized; on the basis of a standardized JSON data structure, a modularized unified intermediate language conversion chain is further supported, an analyzer and a generator communicate through a JSON interface, a cross-platform conversion path is supported, and unified intermediate language conversion from PLC to JSON to XML to ST to C is completed; the method comprises the following steps of: integrating an open source compiler and runtime, constructing an open and pluggable automatic execution framework, compiling a generated C code into a platform executable file by using an adaptive GCC tool chain aiming at different target platforms, and deploying a program generated by compiling to a soft PLC runtime system supporting multiple platforms. According to the method, a JSON intermediate data structure which is light in weight, unrelated to languages and uniform in structure and a matched conversion framework of the JSON intermediate data structure are constructed.

The invention provides a script language-oriented seismic batch processing job editing method and device, and the method comprises the steps: obtaining a to-be-processed seismic job demand, and determining a seismic job project and database information; initializing each module object in a pre-established seismic batch processing operation framework, wherein the framework is a scripting language framework comprising a preset core library, a module library and a tool chain; determining a standard type parameter corresponding to each module object; initializing an operation topological structure of the seismic batch processing operation framework; selecting a target module object and adding the target module object to the target operation based on the earthquake operation project and the database information; and outputting the topological graph of the module according to the debugging requirement, and generating a target operation corresponding to the seismic operation requirement by calling the XML format file. According to the method, seamless connection of job editing and code editing is realized through a script language-oriented seismic batch processing job framework, so that the method is more flexible and efficient; and diversified requirements of a user for job editing by using a script programming language are met.

A method and a system for compiling a neural network, a computer storage medium, and a compilation device are provided. The method for compiling the neural network comprises: translating a network file into an intermediate representation file; optimizing the intermediate representation file to obtain an optimized intermediate representation file, based on a performance analysis, single-node optimization, and collaborated optimization; generating a network template file based on hardware interfaces through the optimized intermediate representation file; compiling the network template file into an executable inference application. The present disclosure aims to design and implement an automated compilation toolchain framework. This framework adjusts parameters, generates code, creates intermediate representations (IRs), and applies optimization algorithms based on software and hardware information. When this compilation toolchain operates on a target chip, it ensures consistent network output results, achieves higher computation rates within shorter optimization times, reduces computation delays, and facilitates user debugging and tuning.

The invention discloses a smart home control method and system based on a multi-modal large model, and the method comprises the steps: carrying out the cross-modal feature extraction and semantic alignment processing of voice, image and sensor data through an improved multi-modal large model, and achieving the semantic space mapping of multi-source data based on a context sharing mechanism and reasoning logic; the method comprises the following steps: abstracting local smart home equipment into a standardized resource entity by using an MCP technology, defining an equipment function feature set through a protocol interface, and packaging the equipment function feature set into a callable tool chain; constructing a real-time data fusion model, and generating a control instruction sequence through the multi-modal large model based on the real-time data fusion model; and calling a corresponding tool in the tool chain according to the control instruction sequence to execute equipment control. The problems that an existing system depends on single-mode data and is easily interfered by the environment, the access cost of new equipment is high due to the fact that a unified data fusion framework does not exist, a control strategy is difficult to adapt to user behavior changes, equipment communication protocols are different, and the user requirement matching degree is low are solved.

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 an agent and tool chain collaborative data processing method and device and a medium, and relates to the technical field of agent application. The method comprises the steps of receiving a data processing task target and related configuration parameters input by a user, and initializing task context data based on the task target and the configuration parameters; executing a circular processing process by an agent based on a ReAct framework, and dynamically adjusting a task strategy by iteratively executing a thinking stage, an action stage and an observation stage until a task completion condition is met; in the circular processing process, based on standardized tool calling instruction data generated by the intelligent agent, cooperatively calling the MCP tool chain and a plurality of tools in the external tool adaptation layer to execute a data processing task; performing aggregation processing and data verification on the multi-source result data returned by the tool execution to generate integrated analysis result data; and displaying task execution process data and a final analysis result in real time through a front-end interaction interface, and dynamically adjusting a task execution process based on user intervention instruction data.

The invention discloses an AI dialogue flow control method, system and device supporting real-time interruption of a user, a medium and a program product. The method comprises the steps that a user request is received, and a flow session is established; based on the stream session, requesting LLM increment generation, receiving fragments generated by increment, returning the fragments, and pushing the fragments to the client; when a click stop request of a user is received, an STOP signal is sent; when the STOP signal is monitored, sending a mark termination request; after a mark termination request is received, a subsequent generation termination request is sent to the LLM, a STREAMTERMINATED semantic event is published and broadcasted, and generated content and a termination mark are returned to the client; terminating subsequent generation comprises stopping untriggered subsequent reasoning and tool chain calling; discarding the tail cache which is not sent; and recording the output token count, and terminating the offset. The AI dialogue flow control method supports real-time interruption of the user, is low in delay, clear in semantics and recoverable, and further has the advantages of saving resources, being high in stability, capable of being universally expanded, gaining behavior analysis and the like.

A system and method for a protocol parser that has native support for parsing TLVs and flag-fields and allow users to code in a language convenient to them and leverage standard tool chains and tools. The same parser source can be compiled to arbitrary software and hardware targets without code change and provide the highest performance possible given its capabilities.

The invention relates to the technical field of embedded system software development and continuous integration, in particular to a docker-based AGV (automatic guided vehicle) cross compiling method, which comprises the following steps of: constructing an ARM (advanced RISC machines) root file system on an x86 development host by using a virtualization tool, configuring a header file and a dependency library, and packaging and compressing to obtain an ARM root file system mirror image; pulling the basic mirror image from the public warehouse to create an x86 Docker container, copying the ARM mirror image to a specific path of the container and mounting the ARM mirror image to prepare a Docker mirror image special for AGV cross compiling; writing a CMake cross tool chain file in the container, introducing an ARM mounting path, setting a dependency path and appointing a tool chain; then integrating the commands, automatically updating the container through mirror image ID comparison, and constructing operation commands such as Makefile packaging and compiling and the like at the same time; and finally, calling an integration command to start cross compiling, and generating a program capable of running on an ARM board card of the AGV. According to the method, unified and efficient multiplexing of the AGV cross compiling environment can be realized, the development efficiency is improved, the maintenance cost is reduced, and the method is adaptive to an AGV project needing cross compiling.

The invention discloses a resource optimization method and system based on demand driving, belongs to the technical field of software product development, and aims to solve the technical problems that resource allocation in software product life cycle management depends on artificial experience, is low in efficiency, subjective in allocation standard and difficult to dynamically adapt to project changes. Comprising the following steps: acquiring demand characteristics, and endowing the demand characteristics with weights; the method comprises the following steps: modeling available resources of a project to form a resource constraint model, defining attributes and constraint conditions of the resources through the resource constraint model, and collecting state information of the resources in real time; on the basis of the weights of the demand features, the state information of the resources and the attributes and constraint conditions of the resources, the resources are allocated through a multi-objective optimization algorithm, and an optimal resource allocation scheme is formed; issuing the resource allocation scheme to an execution end through tool chain integration; and optimizing the weight of the demand feature and the optimal resource allocation scheme based on a machine learning method.

The invention provides a collaborative management system and method for an EDA all-in-one machine, the collaborative management system comprises a business layer, an application layer, a platform layer and a hardware layer, the hardware layer is used for providing hardware resources and deploying container instances; the platform layer is used for performing instance management, resource quota allocation and instance life cycle control of container instances on the hardware resources provided by the hardware layer; the application layer is used for running the EDA tool of the corresponding version in the container instance; and the business layer is used for carrying out resource planning, template configuration, task scheduling and result management on the chip design whole process of the EDA all-in-one machine. According to the scheme, the whole process of chip design is integrated through the business layer, scattered project information, resource requirements and result management are incorporated into a unified framework, the tool chain information barrier is broken, and the manual coordination cost is reduced. And meanwhile, the predictability and traceability of task execution are improved, and an efficient and ordered collaborative management scheme is provided for the EDA all-in-one machine.

This invention discloses a method and system for constructing an AI-native operating system based on ecosystem collaboration, belonging to the field of operating system technology. The invention first acquires and decomposes target requirements to form a set of functional and non-functional requirements, constraints, and priority lists. Based on this, it generates an operating system architecture description including kernel configuration and subsystem division. Then, it generates and completes multi-dimensional checks on module code and configuration files, and compiles, links, and packages them through a toolchain to generate an operating system image. This invention employs a three-layer AI model to realize requirement reasoning, system construction, and test optimization, forming a complete automated closed loop from requirement input to runnable image output. Simultaneously, it establishes a unified ecosystem collaboration mechanism to support multi-vendor collaborative development. This invention effectively reduces errors and repetitive work caused by manual intervention, shortens the development cycle, improves system stability and adaptability, and promotes the collaborative evolution and improvement of the AI-native operating system ecosystem.

The application discloses a circuit input sensitivity analysis method based on Undef SAT, which comprises five steps of netlist analysis and input division, two groups of CNF clause construction, S set assignment and initial solving, first group of solution increment SAT processing and termination and result output. The method uses the incremental SAT processing mode to gradually determine the final assignment of the input variables of the L set, effectively avoids full space search, significantly reduces the search space, and improves the analysis and determination efficiency. The method constructs two groups of CNF clauses supporting irrelevant item propagation, directly processes the irrelevant input variables of the S set by using the Undef SAT solver, reduces the number of logic propagation, and thus reduces the operation time. The integrated process of the circuit input sensitivity analysis formed by the method is suitable for mainstream EDA tool chains, has good engineering applicability, and is suitable for different scenes such as logic synthesis stage, formal verification, functional equivalence checking and loop oscillation detection.

The application provides a script language-oriented seismic batch processing job editing method and device, including obtaining seismic job requirements to be processed, determining seismic job items and database information; initializing each module object in a previously established seismic batch processing job framework, the framework being a script language framework including a preset core library, a module library and a tool chain; determining standard type parameters corresponding to each module object; initializing a job topology structure of the seismic batch processing job framework; based on the seismic job items and the database information, selecting target module objects and adding them to target jobs; outputting a topology graph of a module according to debugging needs, and generating target jobs corresponding to seismic job requirements by calling an XML format file. The application edits a seismic batch processing job framework by facing a script language, realizes seamless connection between job editing and code editing, is more flexible and efficient, and meets diversified needs of users in editing jobs by using a script programming language.

The invention provides an automatic testing method and system for tool chain database file analysis and mapping, and belongs to the technical field of automatic testing. The method comprises the steps that a source file is obtained, and first configuration data is obtained through analysis; obtaining a vehicle control operation system configuration file generated after the tool chain performs analysis and mapping processing on the source file, and performing analysis to obtain second configuration data; calling a mapping rule according to a to-be-tested configuration parameter object, and performing mapping processing on the first configuration data to obtain target configuration data; and performing automatic data comparison on the second configuration data and the target configuration data to generate a test report. The method has the beneficial effects that special verification is performed on the correctness of the configuration file of the vehicle control operation system mapped by the source file through tool chain analysis in the design and configuration stage, so that the configuration error of the tool chain caused by the file analysis and mapping error is found in time, the error is prevented from being left in the downstream code generation, integration and function test stage, and the operation efficiency is improved. And the later-stage troubleshooting, debugging and repairing cost is reduced.

The invention provides a real-time kernel-oriented program real-time compiling method and device and a storage medium. The method comprises the following steps: constructing and running an operating system containing real-time kernel capability on a target hardware platform, and determining a real-time interface library and a real-time equipment driving model of the operating system as dependence of compiling and linking; real-time transformation is carried out on the high-level language compiler and the runtime key library to generate a transformed tool chain, and the real-time transformation comprises the steps that a real-time interface library is introduced into construction and link configuration of the runtime key library, an interface and a data structure of a real-time equipment driving model are included in a visible range of the runtime key library, and the real-time interface library and the real-time equipment driving model are constructed. Real-time constraints are set for a concurrent scheduling and timer mechanism; and compiling an application program source code by utilizing the transformed tool chain, and introducing a real-time interface library in a linking stage to obtain a real-time application program running on an operating system. According to the method, real-time compilation without change of the source code, uniform interface adaptation, cross-architecture multiplexing and deterministic operation can be realized.

This invention relates to the field of vehicle communication technology, providing a method and system for converting Excel to ARXML format. The method pre-defines an Excel conversion template, specifying that different worksheets correspond to different top-level containers in the ARXML document, and pre-defined mapping rules between Excel column names and ARXML element attributes or child nodes. Based on these mapping rules, the method automatically converts data rows in the Excel worksheet into corresponding ARXML element nodes, and performs reference relationship parsing on the generated nodes, replacing reference path placeholders with reference nodes conforming to the AUTOSAR standard. Finally, it integrates all ARXML element nodes that have undergone reference parsing and updates, generating a compliant ARXML file that can be directly used in the AUTOSAR toolchain. This invention transforms complex manual coding into parameterized table configuration, effectively improving the efficiency, consistency, and compliance of vehicle communication configuration file creation through end-to-end rule mapping and automated processing.

The application discloses a kind of UVM verification platform automatic generation system and method based on generative artificial intelligence, the system includes generative AI dynamic anchoring module, LLM-VCS self-feedback verification module and conflict detection correction module;The generative AI dynamic anchoring module is used to solve the context window limit problem on large language model, by the key component in UVM platform is marked as anchor file and generates subsequent file based on dependency relationship priority;LLM-VCS self-feedback verification module cooperates with large language model and EDA tool chain, forms closed loop system from specification input to UVM platform generation, simulation and debugging;The conflict detection correction module is used to detect and correct the interface inconsistency and logic error between generated files.The application can adapt to the verification needs of different RTL designs, effectively solve the interface consistency problem of high coupling between UVM modules, flexibly generate UVM platform of different structures, significantly improve the verification efficiency and quality.

The invention provides an automatic network protocol program de-randomization method, and belongs to the technical field of fuzzy testing. The method comprises the following steps: a code analysis stage: analyzing a target network protocol program by constructing a prompt guide large language model, identifying random problems and classifying the random problems; an adaptive query generation stage: dynamically generating an adaptive query for each class of deterministic problems so as to locate random codes involved by the random problems; in the deterministic transformation stage, a deterministic patch containing deterministic constraints is generated according to the random codes; in the patch verification stage, the validity of the deterministic patch is verified by executing path consistency detection and fuzzy test efficiency evaluation; and a tool chain integration stage: integrating the generated deterministic patch into a fuzzy test framework so as to carry out continuous verification and subsequent optimization. According to the method, the randomness problem in the program can be identified and eliminated, and the stability and effectiveness of the fuzzy test are remarkably improved.

The embodiment of the invention relates to the technical field of software development, and discloses a platform compiling method and device adaptive to various cross tool chains, equipment and a storage medium, the method comprises the following steps: executing a compiling script, and displaying a tool chain list; the tool chain list comprises a plurality of available cross tool chains, and each cross tool chain has a predefined configuration file and an adaptive script which are independently stored in an independent subdirectory of a tool chain configuration directory; in response to a selection instruction of a user, calling a configuration file and an adaptive script of a target tool chain from the tool chain configuration directory, and configuring a construction environment of the target tool chain; the target tool chain is a cross tool chain in a tool chain list selected by the user; and compiling in the configured construction environment. By means of the technical scheme, the problems that in the prior art, due to the fact that using configurations of cross tool chains provided by all platforms are different, cross-platform compiling of the same set of codes becomes difficult, and the development efficiency is low can be solved.

The invention relates to the technical field, and discloses an intelligent software development auxiliary platform fusing multi-modal information, which comprises a multi-modal information acquisition module, a multi-modal fusion module, an interaction and auxiliary generation module, an atlas construction module, a collaborative management module and a feedback closed loop module. According to the method, information of different forms such as requirement documents, design drafts, codes and operation and maintenance data is automatically understood and associated, a unified project knowledge graph is constructed, 'information isolated island 'in a traditional development tool chain is broken, complete and traceable contexts are provided for developers, manual switching and information splicing among multiple tools are not needed, and the development efficiency is improved. And the cognitive load and the context switching cost are obviously reduced. The high-quality code can be directly generated according to the natural language description or the design manuscript, and repeated work is liberated.

The invention discloses an agent cooperation method based on an intervening tool chain, and belongs to the field of computer task scheduling, and the method comprises the steps: generating tool chain description data corresponding to a demand description text according to the demand description text used for representing an agent scheduling behavior; according to the tool chain description data, generating an execution tool chain for achieving a proxy scheduling behavior; and executing the proxy scheduling behavior based on the execution tool chain. According to the method, by introducing an intervening tool chain structure and a semantic-driven tool chain generation mechanism, system response delay and resource waste caused by process stiffness or tool calling failure are reduced, and the problem that the stability and expansibility of the tool calling process are insufficient is solved.

The invention discloses an embedded software construction method and device, electronic equipment and a storage medium, and belongs to the technical field of software development, the method comprises the steps that construction parameters configured by a user are provided, and the construction parameters comprise a hardware identifier used for specifying a target embedded hardware platform type; calling a corresponding configuration file from a preset configuration library according to the hardware identifier, wherein the configuration file is used for providing a compiler tool chain path and default compiling options related to the platform; generating a compiling rule frame based on the configuration file, wherein the compiling rule frame comprises a to-be-compiled file list, a final compiling option and a target generation rule; and executing compiling operation according to the compiling rule framework to generate a target output file. According to the method, the preset configuration file is automatically matched through the hardware identifier, so that manual configuration redundancy is greatly reduced; dynamic switching of tool chain configuration during cross-platform construction is realized, and zero modification of platform migration is ensured.

1. Name of the product in this design: Graphical User Interface for Wind Farm Wind Resource Assessment Toolchain for Electronic Equipment. 2. Purpose of this design product: an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: Main view of Design 1. 5. Designate Design 1 as the base design. 6. Purpose of the graphical user interface: Designs 1 to 3 show the graphical user interface for wind farm planning and design. In the main views of Design 1 and Design 2, the left side of the interface displays specific project information, the middle area displays the location of each project on the map, and the user can select any project on the left. The selected project will display more information in the information box on the left, and the corresponding location of the project on the map will be enlarged. The circle is the user location display style. Design 3 serves the same purpose as Design 1 and Design 2, except that Design 3 additionally displays layer information when the layer button on the right is selected. 7. Other situations requiring explanation: Design 1 and Design 3 request color protection.

A method for constructing an openEuler embedded file system based on an SPARC framework comprises the steps that firstly, according to build root source codes, a proper kernel header version is selected, a cross compiling tool chain of the SPARC framework is compiled, then a binary inclusion set is compiled through the cross compiling tool chain and the build root source codes, and finally the binary inclusion set is packaged to form the file system. According to the method, all source code packets are compiled and compressed into file system packets through a sparc cross compiling tool chain.

The invention discloses a two-way communication method for a digital twin system and PLC (Programmable Logic Controller) equipment in a Linux environment, which comprises the following steps of: establishing a secure communication channel based on TCP (Transmission Control Protocol) and TLS (Transport Layer Server) encryption and two-way authentication, defining an application layer message structure, and finishing initial secure link connection; developing, integrating and packaging a UE5 plug-in with a communication function, and providing visual blueprint nodes to configure PLC equipment parameters and process message serialization; based on a secure communication channel and a UE5 plug-in, real-time bidirectional data interaction is executed between the digital twin system and PLC equipment, and connection is maintained through heartbeat detection and automatic reconnection; and constructing the UE5 project containing the plug-in into a Linux executable file through a cross compiling tool chain, and deploying and configuring the Linux executable file. According to the invention, a safe, real-time and easy-to-use complete solution for bidirectional communication between the digital twin system and the PLC equipment in the Linux environment with good expansibility is formed while the requirements of localization and autonomous controllability are met.

The invention provides a training method, device and equipment for a tool chain generation model. The training method comprises the steps of obtaining first question information of a user; inputting the first problem information into an initial tool chain generation model to obtain a corresponding first sequence data set; according to the first sequence data set, performing first-stage training on the initial tool chain generation model to obtain a trained first tool chain generation model; acquiring second question information of the user, and inputting the second question information into the first tool chain generation model to obtain a corresponding second sequence data set; acquiring a preset data quality detection standard; determining a third sequence data set meeting a data quality detection standard according to the second sequence data set; according to the third sequence data set, a group relative strategy optimization method is adopted, second-stage training is conducted on the first tool chain generation model, a trained target tool chain generation model is obtained, and the technical effect of improving the model training efficiency and accuracy is achieved.

The invention provides a multi-dimensional self-adaptive large model inference engine method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting hardware identification information of calculation hardware, and calling a hardware fingerprint database for matching to generate a hardware type result and a hardware characteristic parameter; constructing a hardware abstraction layer, loading a hardware abstraction driving plug-in according to a hardware type result, and virtualizing computing hardware into a unified logic computing power unit through a hardware abstraction interface; when a large model reasoning task is triggered, dynamically routing to a back-end executor according to a hardware type result by querying a back-end registry; on the basis of hardware characteristic parameters and a hardware abstract interface, a hardware compiling tool chain is called through a rear-end executor, graph optimization and operator fusion are executed on a large model calculation graph, and therefore self-adaptive deployment and efficient reasoning of a large model on heterogeneous hardware can be achieved; the problems that in the prior art, heterogeneous hardware is insufficient in compatibility, configuration is tedious and rigid, and compilation optimization barriers and performance losses are caused during model cross-platform migration are solved.