1500 results about "Plug-in" patented technology

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

The invention is suitable for the field of GPU management, and provides an intelligent dynamic management method for GPU computing power and a cloud platform, and the method comprises the following steps: collecting task data and GPU state data, and generating a task queue and a resource allocation strategy in combination with a scheduling plug-in; based on the task queue and the GPU real-time load, dynamically adjusting a resource allocation proportion through reinforcement learning to analyze a task dependency relationship and generate a migration plan; optimizing a communication path and adjusting asynchronous transmission delay according to the task dependency relationship and the GPU communication topology, and outputting a synchronous state mark; and monitoring abnormity in combination with the synchronization state and the GPU hardware state, executing thermal migration according to the migration plan, performing video memory recovery, and updating the resource idle list. According to the invention, through algorithm innovation and hardware collaborative optimization, intelligent, dynamic and efficient resource scheduling in the multi-GPU system is realized.

The embodiment of the invention provides a code exception analysis method and device, a storage medium and a program product. In the embodiment of the invention, in the preset plug-in, the global knowledge graph is constructed through the logic syntax tree of the plurality of original business codes, so that intelligent anomaly analysis is carried out on the modified to-be-detected codes, multi-language and heterogeneous programming styles and complex dependency limitation are broken through, and cross-language and cross-file analysis is supported; change code snippets and associated influence code snippets thereof are accurately identified, and a data basis is tamped and analyzed; the analysis depth is deepened and the accuracy is improved through a multi-dimensional anomaly analysis large model and four-dimensional collaborative analysis in combination with an adaptive review rule and a knowledge graph; and finally, performing correction based on the generated repair scheme. Through the technical fusion of an MCP protocol, a multi-AI model, a syntax tree and a knowledge graph, the high efficiency, accuracy and real-time performance of code examination and repair are realized, and the service development quality and the system operation stability are remarkably improved.

The invention relates to the technical field of automatic data analysis, in particular to an intelligent data report generation method and system based on an MCP protocol. The method comprises the following steps: constructing a semantic intention vector through a context semantic structure according to an obtained natural language instruction of a user; constructing a semantic task path graph based on the semantic intention vector by utilizing a knowledge graph; according to the constructed semantic task path diagram, performing intention path and tool capability mapping based on an MCP protocol; constructing a task flow based on an MCP protocol and performing task scheduling optimization; carrying out data source unified modeling based on the constructed task flow, and generating a stable and controllable calculation task flow; and visual expression generation from data to graphs is realized through an intelligent recommendation and structural modeling mechanism. According to the method, a semantic-driven MCP plug-in tool chain and a chart capability component index are constructed, so that a full-automatic closed loop from a natural language intention to data analysis and chart generation is realized, and meanwhile, the use threshold of non-technical users is reduced.

Techniques disclosed integrate generative AI assistant plugins with a large language model (LLM) to enhance conversational interactions. The techniques include receiving a user's input and retrieving relevant text passages based on a query derived from this input. A complex LLM prompt is generated, including these passages, descriptions of candidate plugins, and the user's input. This prompt is sent to an LLM service, which selects the most suitable plugin for the user's needs. Following this, a query is sent to the chosen plugin, and its response is used to craft the agent's reply to the user. The techniques emphasize dynamic selection and integration of specialized plugins based on real-time user input, leveraging LLM capabilities to interpret and recommend the best plugin response. This approach ensures tailored, informed interactions by providing responses that are both relevant and enriched with specialized plugin knowledge or functionality.

The invention relates to the technical field of data acquisition, in particular to a multi-source heterogeneous bus data acquisition protocol configuration method, which realizes protocol identification and structure analysis of CAN (Controller Area Network), Modbus and Ethernet / IP (Internet Protocol) bus data by dynamically compiling protocol source codes and registering analysis classes, and comprises the following steps of: extracting protocol feature information from a data stream; the method comprises the following steps of: calling a corresponding protocol analysis class to perform recursive analysis, and executing parameter analysis and mapping, in addition, defining a new protocol semantic feature and dynamically generating a protocol analysis plug-in through an XML (Extensible Markup Language) configuration file to realize protocol semantic-level custom extension, adopting source code level dynamic compilation and plug-in design, supporting a new protocol plug-and-play mode, and being high in practicability. System codes do not need to be modified and redeployed, and the flexibility and expandability of the system are effectively improved.

Disclosed herein is an audio system that can be customized by the user (including the developer) and that may allow the user to control more than just the sound levels and may allow the user to select more than one of a few pre-determined settings. Disclosed herein is a development platform that allows manufacturers (including the developers) to test various different parameters, settings, algorithms, functions, processes, accessories, and the like. The development platform allows the manufacturer to simulate the performances from possible options for the audio system, and then load the selected option from the development platform to the audio system. Additionally, the development platform that enables the end user to have the same level of control and ability to access, upload, and control plugins on the end user's device(s).

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

According to the urban traffic automatic simulation plug-in based on the large language model and the implementation method, after a user inputs a request for a road network and a request for vehicle routing by using a natural language, the request is transmitted into a full-process automatic simulation module, and the full-process automatic simulation module carries out simulation; the input analysis agent extracts a key value from a natural language to generate a character string in a Json format, then the character string is spliced, a prompt input simulation input construction agent containing detailed simulation information is generated, the simulation input construction agent calls a packaged tool function, a vehicle route xml file and a road network xml file are generated respectively, and the vehicle route xml file and the road network xml file are connected with the simulation input construction agent. And the simulation execution intelligent body opens the SUMO-gu i to start simulation, and returns a result through a graphical interface. According to the method, the technical complexity of traditional traffic simulation is effectively simplified, a simulation tool is promoted to be transformed from professional modeling to intelligent decision support, and an innovative technical path is provided for optimization and management of a dynamic traffic system.

The invention relates to the technical field of artificial intelligence, and discloses an enterprise-level large-model agent application system supporting multi-modal collaboration, and the system comprises a user interaction terminal, an agent engine server, a knowledge engine server, a plug-in integration center, and a distributed storage unit. The agent engine server is responsible for intention recognition and task arrangement of a multi-modal input signal, and dynamically loads a differential reasoning strategy based on an environment isolation mechanism. And the knowledge engine server constructs a cross-modal semantic anchor point, analyzes an unstructured document into a tetrad knowledge unit, and realizes accurate recall of images and texts by using a hybrid retrieval algorithm. And the plug-in integration center executes outbound replacement and inbound restoration of the sensitive data through the context-aware dynamic desensitization gateway. According to the method, through a multi-modal semantic association and closed-loop verification mechanism, the problems of low complex document retrieval precision and leakage of external calling data are solved, and the service processing capacity and safety of the system are improved.

The invention discloses a gallery integrated internal production software system based on a modular low-coupling architecture, which is characterized in that a system function is divided into a plurality of modularized modules and the modularized modules are packaged and deployed by a uniform interface, so that the coupling degree between the modules is remarkably reduced, and the problem of global code change caused by module dependence in a traditional single architecture is avoided; direct calling is replaced by an event-driven mechanism, asynchronous communication and decoupling cooperation between modules are realized, and the stability and maintainability of the system during function change or addition are improved; the configuration driving mechanism enables the business process to be dynamically adjusted, different business requirements can be met without modifying a program source code, the plug-in management mechanism provides a standardized third-party extension access channel and supports function loading according to requirements, and the limitation that a traditional system is fixed in function and closed in development is broken through; according to the method, the software can run consistently in Windows, Linux, MacOS and other environments, and the key problems that in the prior art, the coupling degree is high, the expansibility is poor, configuration is not flexible, and the platform adaptation capacity is weak can be effectively solved.

The invention discloses an automatic compiling and adapting method for an RISC-V extension instruction, and belongs to the technical field of compilers. According to the method, a dynamic DSL (Digital Subscriber Line) for registering a custom instruction, adding register use constraints and defining a specific code mode is designed. The LLVM plug-in is used for automatically integrating the registered custom instruction in the compiling process. The invention relates to a self-defined instruction rapid adaptation mechanism which is specially provided for a continuously provided RISC-V self-defined instruction expansion scene, and by automatically generating correct assembly codes of registered self-defined instructions, correct registers are automatically distributed and reserved according to register use constraints; the method comprises the following steps of: searching a defined specific code mode and semantics, and automatically generating and inserting a registered custom instruction in a program, so as to realize the rapid adaptation of a compiler to an RISC-V custom extension instruction and the automatic use of a program code to the custom instruction, and the whole process does not need a developer to manually modify the compiler or a program source code.

A content editor or a plugin thereto automatically generates authorship tokens that identify content authored by a human author or an artificial author. The authorship tokens are applied to the work while the work is being produced. Thus, subsequent review of the work can identify regions produced by a human author and other regions produced by an artificial intelligence.

The invention discloses a network data integration analysis system and method based on a model context protocol MCP, and relates to the technical field of computer networks. The system comprises an MCP-LSP adaptation layer, a network analysis language server, an IDE plug-in, a remote cooperation management module, an MCP analysis engine, an LSP client and an IDE UI component. According to the invention, deep fusion of the network protocol analysis capability and the integrated development environment is realized; by constructing an MCP-LSP adaptation layer, a network analysis language server can convert a semantic analysis result of an MCP analysis engine into an LSP standard message format, and standardized services of functions such as protocol analysis, session state and anomaly detection are realized; the working efficiency of a developer is improved by the IDE plug-in; the remote cooperation management module realizes synchronization and sharing of session states, improves integration, expandability and cooperation efficiency of network analysis, and is suitable for diversified requirements of modern software development teams.

The invention provides a simulation scene construction and simulation method and system for a large-scale unmanned cluster, and relates to the technical field of unmanned system simulation. The method comprises the steps of modeling a target task based on execution logic for the target task of the large-scale unmanned cluster to obtain an execution structure; decoupling the target task into a plurality of weak coupling subsystems based on the execution structure, and constructing a parallel simulation environment for the target task; based on the execution function category of the target task, constructing a bus interface of a corresponding category; constructing an intelligent algorithm plug-in corresponding to the execution function category based on the bus interface of each category; integrating the intelligent algorithm plug-in into the execution structure of the target task to form an execution model of the target task; and deploying the execution model to a parallel simulation environment to obtain a simulation scene of the target task. The problems that in large-scale unmanned cluster complex task simulation, the calculated amount is large, real-time simulation cannot be achieved, and the simulation accuracy and effect of cross-platform complex tasks are poor are solved.

Disclosed in the present application is a code generation method, which is applied to a code development platform. The code development platform comprises a main plug-in and a plurality of extension plug-ins, wherein the main plug-in is used for providing an actual value of a basic variable of a prompt, and the plurality of extension plug-ins are used for extending the prompt in terms of a programming language, scenario or development framework. The method comprises: a main plug-in receiving a code generation instruction, and then determining, in response to the code generation instruction, at least one extension plug-in corresponding to the code generation instruction from among a plurality of extension plug-ins; the main plug-in receiving a prompt returned by the at least one extension plug-in, wherein the prompt is obtained by means of the at least one extension plug-in extracting an actual value of an extension variable on the basis of extraction logic and replacing an extension variable in a prompt template with the actual value of the extension variable; the main plug-in performing inference by means of a language model and on the basis of the prompt, so as to obtain a second code segment. In the method, a prompt of a specific code generation task and the implementation of prompt engineering is entrusted to corresponding extension plug-ins, thereby realizing flexible extension of prompts.

The present disclosure relates to implementing, updating, and managing operation of a client agent on a client device (e.g., computing device, virtual device) in a way that enables isolation of features and functionality while also allowing the client agent to self-heal and intelligently update discrete features thereon. The client agent includes a collection of plugins that are isolated and run in accordance with respective plugin policies. The client agent makes use of device-level, agent-level, and plugin-level health monitors that collectively monitor a health status of discrete components of the client agent in a way that enables the client agent to selectively discontinue scheduling certain plugins without interrupting functionality of other plugins or of the client agent as a whole. Indeed, features described herein enable the client agent to intelligently update and self-heal with respect to individual plugins based on information obtained by the respective health monitors.

The invention provides a DAG arrangement and execution method and system based on operator dynamic management, and the method comprises the steps: constructing an initial directed acyclic graph DAG, dynamically loading operator plug-ins registered in the initial DAG, obtaining context information during operation, and storing the context information to a context container; dynamically selecting a next execution path based on the real-time data in the context container, generating an executable operator queue according to the updated DAG structure, and monitoring the execution state of the operator node in real time; and dynamically modifying the DAG structure according to a trigger condition in the execution process, and outputting a final result after the DAG is executed. According to the DAG arrangement and execution method and system based on operator dynamic management, flexible configuration of the task process, dynamic scheduling of the operator level and intelligent decision making during operation are achieved, and therefore the universality, adaptability and execution efficiency of the system are remarkably improved.

The invention provides an intelligent number asking method suitable for a sales data query scene, which belongs to the technical field of data processing and comprises the following steps of: (1) inputting a natural language; (2) dialogue type number asking; (3) accessing a plug-in model; (4) carrying out multi-modal analysis; and (5) carrying out platform service. According to the intelligent data asking system architecture, an industry knowledge graph is used as a cognitive footstone, a large language model is used as an interaction engine, and dynamic data association is used as execution blood vessel three-in-one. The core pain point of'water and soil disability 'in vertical industry application of a general AI model is solved, the method is a key for really changing the AI from'chatting' to'drying ', and unprecedented agility and accuracy are provided for data-driven decision making.

The invention provides a processing method, system and device for expanding an OpenResty request based on a WASM plug-in and a medium, and belongs to the fields of network communication, application gateways and the like, and the method specifically comprises the steps that in the starting stage of an OpenResty working process, a WASM running environment supporting a WASI interface is initialized and embedded; the method comprises the following steps: dividing execution stages of an OpenResty request processing flow, and setting a hook point in each stage; a WebAssessment plug-in module is called, and the WebAssessment plug Executing access control, security detection or request filtering processing according to the input data, and generating a processing result containing an allowing, intercepting or modifying instruction; and the plug-in management module judges whether to continue to execute a subsequent OpenResty processing flow or not according to the received processing result, and supports hot updating or unloading operation on the WebAssembly plug-in module when the configuration is changed. By introducing a WASM plug-in mechanism, the OpenResty is endowed with higher expandability and flexibility in the aspects of flow processing, access control, security detection and the like.

The present disclosure relates to systems and methods for creating a copilot. The copilot uses plugins to provide additional features and functionalities to the copilot. The systems and methods use a large language model (LLM) pipeline to generate a knowledge resource used by the plugins and / or an LLM in the copilot to answer queries from a user.

The invention discloses a k8s heterogeneous resource scheduling method, system and device based on intelligent sensing and a medium, belongs to the technical field of cloud computing and resource scheduling, and aims to solve the technical problems that a traditional scheduler is weak in sensing capacity, extensive in scheduling decision, low in resource utilization rate and high in resource utilization rate in a heterogeneous environment. According to the technical scheme, the method comprises the steps that a multi-dimensional resource sensing layer is constructed, specifically, real-time collection and convergence of heterogeneous hardware dynamic performance indexes are achieved by deploying an expanded monitoring equipment plug-in, and fine-grained runtime data of hardware including a CPU, an FPGA and an AI acceleration card are abstracted into a standardized index data set in a unified mode; constructing a node dynamic resource portrait: constructing the dynamic resource portrait based on the standardized index data set through a feature fusion and modeling technology, and generating a quantitative capability evaluation vector for each computing node in the cluster; and intelligent scheduling decision making: through a decision engine based on reinforcement learning, obtaining an optimal scheduling target according to the resource demand characteristics of the Pod to be scheduled and the dynamic resource portraits of the nodes.

The invention provides an external plug-in system based on retrieval enhancement. The external plug-in system comprises an indexing module, a retrieval module and a generation module, the index module is used for performing cleaning, segmentation, organization, semantic coding and storage tasks of text data; the index module comprises a dynamic data management sub-module, a strategy decision case library management sub-module, a Chinese character recursive segmentation sub-module, a tree index structure construction sub-module and a vectorization storage sub-module; the retrieval module is used for completing semantic matching and sorting on the basis of the structured index; the retrieval module comprises a double-tower rough arrangement sub-module, a cross fine arrangement sub-module, a real-time update sensing sub-module and a cache management sub-module; the generation module is used for carrying out integration and semantic modeling on the high-quality intelligence information provided by the retrieval module; the generation module comprises an information integration and reasoning sub-module and a credibility evaluation and feedback sub-module; the method supports fact alignment, real-time updating, logic interpretability and output evaluability.

The invention discloses a high-formwork optimization design method and system based on BIM and finite element analysis, and the method comprises the steps: S100, building a three-dimensional BIM model of a main body structure, and creating an intelligent parameterization frame body family which is mapped with a main body structure family and has a self-verification function; s200, importing a parameterized family and linking the main body model, generating a plurality of groups of frame body arrangement schemes through spatial topology analysis, and performing a three-dimensional collision test after optimization; s300, setting dynamic boundary constraints and construction loads in stages, and generating a geometric and mechanical integrated data packet; s400, data packet parameters are automatically mapped to finite element software through a plug-in, models are built in stages, multi-working-condition analysis is carried out, if the parameters exceed the limit, frame body parameters are modified, iterative optimization is carried out until the parameters meet the standard, and a result is synchronized to a three-dimensional BIM model; and S500, a construction drawing is automatically generated, and visual disclosure and high formwork monitoring point selection are carried out. According to the method, design, computational analysis and construction application data linkage and closed-loop management from design to construction to monitoring are achieved, and the high formwork design efficiency and safety are improved.

The invention discloses an industrial software intelligent building system and method based on a plug-in mechanism, and relates to the technical field of industrial Internet of Things, and the method comprises the following steps: defining a standardized format and an interface of a plug-in, and ensuring the compatibility and the expandability of the plug-in; establishing a plug-in library, and analyzing and recording a dependency relationship between plug-ins; performing semantic similarity matching on the user demand and the plug-in function, and screening plug-ins in combination with a plug-in historical success rate to form a plug-in combination; conflict analysis is carried out on the plug-in combinations, CPU occupancy rate detection is carried out on feasible plug-in combinations based on the conflict analysis, and plug-in combinations with unqualified CPU occupancy rates are removed; and activating the plug-ins according to the plug-in combination selected by the user to complete software function implementation, and executing dynamic updating of the plug-ins.

The invention discloses a risk control strategy-based decision engine and method, and relates to the technical field of financial risk control, and the decision engine comprises a strategy warehouse module, a mapping service module, an execution engine module, a data management module, a version rollback module, a security scale module, and a monitoring alarm module. According to the invention, function decoupling is realized through collaborative design of the seven modules, and the modules interact through a unified interface, support strategy dynamic loading, gray release, distributed parallel execution, version governance and security compliance capabilities, and ensure high cohesion and low coupling of the system; through unique strategy version management, intelligent mapping and gray release, plug-in parallel execution, multi-version consistency view, block chain audit rollback, security compliance management and control, intelligent monitoring and other technical innovations, a complex, dynamic and high-concurrency risk control business scene is effectively supported; the security, the flexibility, the expandability and the auditing performance of the decision engine are remarkably improved, and the technical advancement and the industry creativity are high.

The invention discloses an inference type large model first token performance test method and device and a medium, belongs to the technical field of software development, and aims to solve the technical problem of how to truly simulate a system load in a high-concurrency environment and accurately evaluate the processing performance of a first token of a large model. Based on a first token performance test plug-in, data interaction is realized through an OkHttpClient client by adopting a streaming transmission protocol, and the method specifically comprises the following steps: capturing a receiving timestamp of a first token in an interface response stream, taking the receiving timestamp of the first token as a measurement index of first token response time, immediately terminating current stream transmission, and concurrently triggering multiple test requests through a multi-thread mechanism, the system load in a high-concurrency environment is truly simulated, and the first token processing performance of a large model is accurately evaluated.

The embodiment of the invention discloses an interface permission control method and device, and the method comprises the steps: setting a user-defined permission annotation on at least one target API method of a business API interface, and enabling the user-defined permission annotation to comprise a preset permission code used for uniquely identifying the target API method; obtaining a permission configuration file deployed along with the plug-in, wherein the permission configuration file records a declaration permission list which is declarated by the plug-in and is formed by one or more permission codes which are allowed to be called by the plug-in; during running of the plug-in, when it is detected that the plug-in tries to call a target API method, intercepting the call request through a aspect programming mechanism; in response to interception, a preset permission code is extracted from a user-defined permission annotation of the called target API method to serve as a target permission code, a declaration permission list is obtained, and whether the target permission code exists in the declaration permission list or not is checked; and according to a verification result, if the verification is passed, allowing the call request to continue to be executed, and if the verification is not passed, stopping the execution of the call request.

Techniques for processing change requests for software projects are disclosed. An example method includes receiving a change request describing new source code for a software project. The method also includes generating, by a processing device, a prompt comprising context information and a plugin, wherein the context information comprises source code from the software project and the plugin comprises text that describes a supplemental work product to be generated. The method also includes providing the prompt to a machine learning model, wherein the context information trains the machine learning model to provide the supplemental work product with a correct content and format. The method also includes receiving the supplemental work product from the machine learning model. The method also includes applying the supplemental work product to the software project.

Provided in the present application are a conversation parsing method and apparatus. Information of a plug-in interface is stored by means of a conditional knowledge graph, so as to achieve the flexible configurability and extensibility of the plug-in interface, such that interface invocation and interface adjustment can be implemented more accurately, and conversation content that better meets the needs of a user can be output. The method comprises: acquiring first input text; on the basis of the first input text, determining a plurality of keywords and a first user intent corresponding to the first input text; on the basis of a conditional knowledge graph, determining at least one first interface corresponding to the first user intent, wherein the conditional knowledge graph comprises information of a plurality of interfaces, or the information of the plurality of interfaces forms the conditional knowledge graph, the plurality of interfaces being interfaces of plug-ins used for implementing at least one function; and acquiring output text on the basis of the plurality of keywords and a field corresponding to the at least one first interface, wherein the output text is a reply to the first input text.