60 results about "YAML" patented technology

The invention provides a semantic-based migration and consistency verification method, system and device and a medium, and relates to the technical field of databases. The method comprises the following steps: performing metadata topology scanning analysis by obtaining metadata, including generating an abstract syntax tree and constructing a semantic graph; according to a metadata topology scanning analysis result, performing data mapping and conversion, including loading a YAML rule and generating corresponding type mapping and constraint conversion; data migration is carried out through primary key fragmentation parallel migration, batch writing optimization and real-time double-writing verification; through structure-data-business three-layer verification, simulation business SQL comparison and automatic difference repair, the integrity of migrated data and business compliance are ensured, the semantic gap problem in heterogeneous database migration is solved, high-precision and high-efficiency database migration is realized, the migration efficiency is improved, and the data migration efficiency is improved. The method is suitable for scenes with strict requirements on data consistency and migration efficiency, such as financial, government affair and enterprise-level data centers.

The invention provides a method for carrying out model training based on k8s, which relates to the technical field of model training, and comprises the following steps: creating a service queue in a k8s cluster, allocating training tasks to a corresponding queue, identifying training stage characteristics and collecting performance data by a user-defined controller, determining an initial batch allocation value according to the characteristics and the data, and carrying out model training according to the initial batch allocation value. And continuously adjusting the batch allocation value based on the actual calculation time delay, finally updating the resource demand information in the yaml file, and selecting the training node meeting the resource demand to execute the model training task. According to the invention, resource allocation can be optimized, training efficiency is improved, and resource waste is reduced.

The invention provides an automatic testing method and system for AI vision, and is applied to the field of software UI automatic testing. According to the method, mobile terminal UI automatic test requirements are processed based on a visual processing model and a large language model, a JSON format test case is generated, and a YAML format test case for system execution and an XMIND format test case for test personnel to check and edit are generated after conversion and integrity check; the test equipment information is processed based on Appium service and WebDriver, and equipment interface screenshot information is obtained; processing the equipment interface screenshot and the element description information based on a visual processing model to generate element relative coordinates, and generating an operation result through coordinate conversion and operation processing; performing screenshot verification processing on the operation result to generate a test result record; and processing the test result record, the test case in the YAML format and the test case in the XMIND format to generate test report information.

The invention discloses a vulnerability scanning method and device based on a template cluster and a storage medium, and the method comprises the steps: responding to a vulnerability scanning request initiated by a user, and determining a scanning target of the vulnerability scanning request; loading at least one YAML classification template adapted to the scanning target to form a template cluster; performing global request merging and path optimization based on the address information of the scanning target and the request specification of each YAML classification template in the template cluster to obtain a detection request set; sending a detection request set to the scanning target, and receiving a response data set returned by the scanning target based on the detection request set; extracting a response matching rule of each YAML classification template in the template cluster, and performing matching analysis on the response data set through the response matching rule; and generating a vulnerability detection report according to a matching analysis result. According to the method, through template rule packaging and global intelligent optimization, scanning request magnitude reduction and efficient resource utilization are realized, and the detection efficiency and accuracy are remarkably improved.

The invention discloses an infrastructure and application management system based on a cloud native technology, and the system comprises a command line tool which is used for carrying out the communication with a server through an MQTT protocol, and executing the cluster management operation; the multi-tenant private cloud cluster module is used for realizing resource isolation and quota management among tenants; the mirror image warehouse module is used for storing and managing application mirror images; the declarative management module is used for defining a resource expectation state through a YAML configuration file; the CI / CD assembly line module is used for automatically constructing, testing and deploying applications; the gateway resource scheduling module is responsible for load balancing and flow control; the user authorization and authentication module is used for realizing authority control based on an RBAC model; the security module comprises data encryption and network isolation; and the asset library management module is used for managing a program component and a platform library. By integrating a cloud native technology stack, a set of efficient, safe and extensible infrastructure and application management system is constructed, and the deployment efficiency and the operation and maintenance capability of enterprise-level applications are remarkably improved.

The application provides a method for optimizing a target detection network, comprising the following steps: S1, modifying a network file yolov7-tiny.yaml; S2, training a model; and S3, comparing the precisions before and after modification and showing the effect. Through the method, the calculation amount can be greatly reduced while the precision is maintained.

The invention discloses a resource configuration synchronization method, a cloud edge cooperation system, a medium and a product. The resource configuration synchronization method applied to a center side comprises the following steps: acquiring a to-be-synchronized resource configuration item and a configuration item parameter value corresponding to the resource configuration item; calling a configuration change interface of an edge cluster according to the resource configuration item and the configuration item parameter value, so that the edge cluster updates an original configuration item parameter value corresponding to the resource configuration item in an edge configuration table according to the configuration item parameter value; and calling a configuration redeployment interface of the edge cluster to enable the edge cluster to generate a yaml file according to the yaml template and the updated edge configuration table, and performing application deployment on the yaml file, thereby solving the problem that the synchronous update of the cloud edge collaboration system needs manual maintenance, and improving the operation and maintenance efficiency and stability of the cloud edge collaboration system.

This application provides a method and apparatus for generating random instruction test cases, relating to the field of automated testing technology. First, target instructions or instruction sequences are encapsulated into C inline functions using inline assembly or macro definition, forming a unified function library. Next, a function parameter constraint system is constructed, defining parameter types, address ranges, instruction combination methods, and value range constraints for each encapsulated C inline function. Then, a multi-level nested structure is built based on the C inline functions to organize the instructions, where each level node is associated with a corresponding C inline function name and constraints. Finally, based on a YAML configuration file, the target C inline functions are determined from the multi-level nested structure and combined to generate random instruction test cases. The YAML configuration file includes at least the number of iterations, a random seed, a random strength factor, and test content configuration. The solution provided in this application has the advantages of improved verification efficiency and applicability to different scenarios.

The invention discloses a software test report generation method and device, a storage medium and computer equipment, and the method comprises the steps: responding to a test report generation instruction of target software for a target scene, and obtaining test index data of different data sources through a unified multi-data source adaptation layer interface, the different data sources comprise a Prometheus time sequence data source, a Grafana visual data source and a YAML test case data source; obtaining a test report generation template corresponding to the target scene, and determining an index association rule and a rendering type in the test report generation template; performing association analysis on the test index data of the different data sources on the basis of an index association rule, determining test conclusion data of the target software on the basis of an association analysis result, and rendering the test index data in the Grafana visual data source on the basis of a rendering type to obtain a rendered picture; and embedding the test index data, the test conclusion data and the rendering picture into a test report generation template to obtain a test report corresponding to the target software.

The invention relates to a file editing method and device, electronic equipment and a storage medium. The method comprises the steps that a target file type capable of being edited by a file editing assembly of a file system in an embedded system is obtained; performing file type conversion on the yaml file according to the target file type to obtain a target folder; the file type corresponding to the target folder is a target file type; and editing the file content in the target folder based on the file editing component to obtain an editing result. According to the method and the device, the file content of the original yaml file can be edited by utilizing the file editing component under the embedded system, and the editing requirements of adding, deleting and modifying the content of the yaml file under the embedded system are met.

The application discloses an implementation method, system and device of a serverless computing platform and a storage medium, belongs to the technical field of Internet, and solves the technical problem that the existing serverless computing solution cannot meet the needs. The method is: initializing various components of the serverless computing platform, including a front-end service, a back-end service, an online coding integrated development environment, a construction tool, a container scheduling component, a gateway service, a code repository and a container image repository that need to be called; creating a new serverless computing function on the interface of the front-end service and deploying the serverless computing function into a Kubernetes cluster to meet different development needs. The serverless computing platform built by the Kubernetes cluster can significantly improve resource utilization, optimize the scheduling and resource configuration of the serverless computing function, and conveniently apply the perfect monitoring function of the Kubernetes platform. When starting the serverless computing function, the user does not need to write Kubernetes YAML, thereby reducing the learning cost and difficulty.

The invention discloses a high-performance visual interface configuration service design method based on a yaml format, a visual large-screen interface is provided through database configuration without code writing, and the method comprises the following steps: interface configuration rules: one configuration represents one interface; the data acquisition engine acquires original data according to configuration; the data processing engine processes the original data according to the configuration to generate target chart data; and performing visual display, wherein the web page end displays a corresponding chart according to an interface response result. According to the method, data acquisition and data processing are decoupled, and the data processing flow is completed by the back-end service, so that the network data transmission quantity is greatly reduced, the data processing tasks of the web front-end equipment are reduced, and the rendering speed of the visualized large-screen chart is improved.

The application discloses a self-adaptive control method and device for cloud native cluster intelligent operation and maintenance, and relates to the technical field of cloud native application.The operation and maintenance demand of a K8s cluster is described through a YAML format file, and the operation and maintenance demand is acquired by analyzing the YAML format file; the planning control logic and the index analyzer are generated according to a rule trigger condition and an operation and maintenance operation supported by the cluster; the index collector type is determined according to an index type and an index parameter, and the corresponding index collector is generated according to a template; the index monitor to be created is determined according to the analyzed operation and maintenance demand, the index collector and the index analyzer are combined to obtain the index monitor, the index is automatically collected through the index collector, and the operation and maintenance planning logic corresponding to the operation and maintenance demand is determined through the index analyzer; the index monitor and the planning control logic are integrated, the code of the K8s controller is generated and deployed into the K8s cluster, and the self-adaptive control for the cloud native cluster intelligent operation and maintenance is realized.

The invention discloses a yaml-based automatic simulation method, which relates to the field of chip development, and comprises the following steps: S1, defining use case parameters; s2, analyzing the yaml file and storing parameters; s3, automatically compiling a C program; s4, automatically calling vcs for simulation; and S5, unified instruction triggering and result feedback. According to the method, yaml serves as a carrier, parameters are configured in a layered mode through a yaml format, global and local parameter multiplexing and coverage are achieved, parameter management efficiency is improved, repeated work is reduced, the parameters can be stored in use case simulation instructions in a dictionary mode, the simulation instructions of all use cases can be unified, the parameters can be conveniently and rapidly called, tool collaboration is enhanced, and the use case simulation efficiency is improved. In addition, parameters of different tools can be contained in a yaml mechanism at the same time, the direct running problem of the c use case in chip development work can be effectively solved, and isolation between the C use case and the UVM environment is eliminated.

The application provides a configuration-driven DL4NLP model automatic training and deployment method, which comprises the following steps: parsing a YAML configuration file and verifying parameters to generate a unified process configuration; automatically loading data and performing preprocessing according to the configuration to generate a model input tensor; instantiating model components through a component factory and assembling the model components into a complete network model; automatically configuring a training environment to train and evaluate the model to obtain an optimal model; exporting the model into a TorchScript format binary file; and automatically generating a standardized deployment package based on a template engine. The application abstracts the whole process of model development and deployment into a configuration-driven standardized pipeline by parsing the YAML configuration file, automatically performs data loading and preprocessing, model component instantiation and assembly, training optimization and deployment package generation, and solves the problems of low development efficiency, long cycle and technical gap between training and deployment caused by repeated code writing and manual conversion and deployment for different tasks in traditional model training and deployment.

The invention provides an Ansible-based automatic operation and maintenance method, a server, computer equipment and a storage medium. The method comprises the following steps of: configuring an ansible.cfg file; the method comprises the following steps: configuring a hosts file, wherein the hosts file carries information of a controlled host; wherein the information of the controlled host comprises a user name and a password of ip and ssh login and a password of a root user; configuring a user consign.yaml file, wherein the user consign.yaml file carries information that the controlled host runs an automatic disconnection tool to access a server side; and writing a linux.yaml script file, wherein the linux.yaml script file is used for configuring, deploying and managing the script of the controlled node. According to the Ansible-based automatic operation and maintenance method disclosed by the invention, unified management and configuration can be carried out on each client on the server.

The application discloses an agent automatic test method and system based on a Web platform, which comprises a test framework, a Web platform and a data storage layer, adopts six AI prompt words to form a string parallel pipeline, a large language model executes prompt word analysis to generate a three-section YAML test case set of an agent source code, a browser automation tool is used to create tasks in batches on the Web platform and record them to a task state list, breakpoint continuous measurement is supported, a state machine is used to poll and execute routing, intermediate reasoning and three-dimensional verification of product quality, a backend is directly connected or an authentication layer is bypassed through an interface, a session track and a product list containing tool calling and execution planning are accurately extracted, finally, a parallel execution process and product multi-dimensional quantitative evaluation are performed, a claim cross verification anti-illusion mechanism is introduced to verify claims one by one, and finally, an agent test report with eight sections is merged and exported. The application realizes full-link automatic test, and ensures that the evaluation result is real, reliable and traceable.

The invention discloses an automatic instrumentation method and system for embedded software, and relates to the technical field of embedded software testing and debugging, and the method comprises the following steps: S1, based on a dual-mode anchor point recognition engine of a traditional mode and a separated mode, scanning a source file line by line, positioning anchor points and generating an anchor point list; s2, analyzing the YAML configuration file to obtain a three-level hierarchical data structure, querying stub code contents corresponding to anchor points of a separation mode in the anchor point list in the three-level hierarchical data structure based on a three-level index query algorithm, and performing mapping to obtain anchor point-stub code mapping objects of the separation mode; and S3, performing source file modification and stub code insertion based on the anchor point-stub code mapping object of the separation mode and the anchor points of the traditional mode in the anchor point list. In the invention, the dual-mode instrumentation mechanism and the three-level index YAML configuration management are the core innovation, and the main technical problem to be solved by the invention is directly solved.

The application discloses a deployment method, a system and a storage medium, which comprises the following steps: generating a deployment service package corresponding to a front end and a service end respectively; creating at least one deployment task, wherein the deployment task is used for deploying at least one service; selecting and inputting the deployment service package into the deployment task; and converting the deployment service package in the deployment task into a yaml file mode for service deployment. Through the above method, the deployment environment standardization and the deployment process automation can be realized, the deployment work is greatly simplified, and the deployment efficiency is improved.

A system that captures runtime data for a pipeline execution, generates an intermediate hierarchical file that includes relationships between the captured data, and converts the intermediate file to alternative format pipeline files, such as YAML files. The present system employs dynamic instrumentation of pipeline executions, regardless of their type, to capture data during pipeline execution. This approach not only facilitates the capture of comprehensive execution data but also leverages this information to seamlessly generate equivalent pipelines on alternative continuous integration platforms.

The invention relates to the field of firmware updating, and discloses a firmware updating method and device of an IOS system and a storage medium. The method comprises the following steps: receiving firmware metadata, and generating a firmware downloading HTML file based on the firmware metadata; the firmware is analyzed to download the HTML file, and a firmware information YAML file is generated; analyzing and downloading the firmware information YAML file to obtain a firmware resource package; all firmware resource packages are placed in a resource storage area, and a firmware resource library is generated; on the basis of a CI / CD tool, a firmware release page is collected regularly, and a firmware update index is generated; when a firmware updating instruction of a user is received, the updated firmware resource library is inquired according to firmware information corresponding to the firmware updating instruction, an updated firmware package is obtained, and the updated firmware package is loaded. In the embodiment of the invention, the firmware resource packet does not need to be manually managed, and the specified firmware resource packet is automatically updated, so that the firmware packet management efficiency and timeliness of the IOS system are improved.

The invention provides an automatic report generation system and method based on a hybrid analytic model and a template engine, and the system comprises a hybrid document analysis module which converts an input semi-structured document into a structured YAML data file, builds and retains a context hierarchical relation through maintaining a stack data structure, and generates an automatic report when a title with a level of N is analyzed; popping up all title nodes with levels greater than or equal to N in the stack, and then pressing the title nodes with the current level of N into the stack; the multi-source data fusion and processing module is used for expanding static data extracted from the YAML data file based on the YAML data file; and the report generation module based on the template engine is used for realizing separation of contents and formats and dynamically generating table rows or paragraphs. According to the method and the device, the structured information with the context relation can be accurately and completely extracted from the semi-structured source document or the mixed document with variable formats, and the analysis precision, the data processing flexibility and the expansibility of the mixed document are effectively improved.

The invention relates to a Redis multi-data-source dynamic switching method, which comprises the following steps of: when a system is started, reading and analyzing an external configuration file in a YAML / Properties format by a dynamic configuration analysis module, and constructing configuration data after acquiring a Redis instance connection parameter and a connection pool parameter; in business code execution, when a method with a user-defined annotation is called, an annotation driving interception module triggers and extracts a data source name to a registration center to search for a corresponding instance, the data source name is bound to a current thread context through ThreadLocal, Redis methods such as get and set are called through a unified operation interface module, the thread context is cleaned after operation is completed, and the corresponding instance is stored in the registration center. If abnormity occurs in the whole process, standardized abnormity is thrown out, and detailed error information is recorded for debugging. According to the method, through annotation driving, dynamic configuration analysis and a thread security isolation mechanism, the multi-data source management process is simplified, and the flexibility and maintainability of the system are improved.

The application discloses an AST-aware hybrid block processing system for RAG system and belongs to the technical field of natural language processing.The application comprises the following steps: parsing a Markdown document and constructing an abstract syntax tree; performing one-time segmentation according to the title level of the abstract syntax tree node type, performing secondary segmentation when the text block length exceeds a threshold value, and setting an overlapping area; cleaning the content of the text block; parsing YAML Frontmatter metadata and traceability information in the header of the Markdown document; connecting with an external server through an end-to-end cloud pipeline; and realizing multi-process parallel and streaming processing through a parallel processing architecture.The application can realize end-to-end automation and high-performance parallel processing under the premise of ensuring block accuracy and semantic integrity.

The invention provides a unified operation and maintenance method and device for heterogeneous infrastructures, and belongs to the technical field of computer software, and the method comprises the following steps: obtaining a declarative YAML configuration file defined with resource pool information, global variables and application configuration information, and analyzing the configuration file to obtain a structured configuration object; identifying target resource types contained in application information, global variables and resource pool information in the structured configuration object; matching a corresponding target application template from a predefined template library, and rendering the target application template based on the global variable to generate an execution instruction; based on the execution instruction, generating an independent Ansible execution file for each application; and running the Ansible execution file to complete application installation, and after the application installation is completed, realizing state sharing between the applications based on a context management mechanism. According to the method, the problems of high configuration complexity, difficulty in ensuring consistency and difficulty in hybrid deployment in operation and maintenance management can be solved.

The invention relates to the technical field of cloud computing, and particularly provides a method and device for dynamically virtualizing video card resources in a container environment, and the method comprises the following steps: S1, deploying a basic container environment; s2, installing a display card driver; s3, a virtual configuration file gpu-profile. Yaml of the graphics card is added, and a virtual configuration file gpu-profile. Yaml is added; s4, installing a container engine plug-in; and S5, deploying container services. Compared with the prior art, the utilization rate of graphics card resources can be greatly improved, and the cost is reduced.

This application discloses a water plant cluster management method, apparatus, equipment, and storage medium based on a large language model and intelligent agents, relating to the field of artificial intelligence technology. The method includes: a main intelligent agent receiving tasks and sending asynchronous call messages containing load data to expert sub-intelligent agents in various domains; the sub-intelligent agents determining the current context by combining a YAML metadata dictionary and industry specifications, and judging whether industrial simulation is involved through a large language model. If so, the corresponding local code script is called, scheduled to a containerized physical isolation sandbox, and after passing the whitelist comparison by the permission control module, the result is calculated based on the load data and returned to the main intelligent agent. The main intelligent agent integrates multi-source datasets and calls the ACP proxy encapsulation module to construct JSON semantic instructions for managing the water plant cluster, thereby improving the efficiency of water plant cluster management.

The application relates to the technical field of Fintech (Fintech), and discloses a task scheduling method, which comprises the following steps: when an operation task is received, a container corresponding to the operation task is created; a preset mapping relationship table is queried, and a target Kubernetes cluster is determined according to a container parameter of the container; operation task corresponding running parameters are sent to a target Kubernetes interface corresponding to the target Kubernetes cluster, the running parameters are converted into a yaml file through the target Kubernetes interface, and the target Kubernetes cluster executes the operation task according to the yaml file. The application also discloses a task scheduling device, equipment and a computer readable storage medium. In the application, a Kubenetes Gateway device is used to replace a Kubernetes control plane, and high-efficiency management of a Kubenetes cluster is realized.

The invention relates to a business system container environment yaml file consistency checking method and device. Comprising the steps of obtaining a plurality of yaml files in a target container cloud platform; analyzing reference values of target general configuration items in the yaml files; analyzing an actual value of the target general configuration item in each yaml file; and comparing the reference value and the actual value of the general configuration item to obtain a consistency check result of the target general configuration item. According to the method, regular consistency checking and early warning of the yaml general configuration items are achieved, the accuracy of the yaml file is improved, the effectiveness of test implementation is guaranteed, the high-quality development requirement is met, and quality and efficiency are improved.