1249 results about "Plug-in" patented technology

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.

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 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 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 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 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 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.

The invention discloses an enterprise data analysis system based on natural language interaction, and relates to the field of enterprise data analysis, the system comprises seven core function modules: a dialogue management module supports a user to create a new dialogue and automatically jumps to an initial page; the report interaction module realizes query support and switching functions of a real-time report and a T + 1 report through a floating button; the file import module allows uploading of Word, PDF and JPG format files to supplement question and answer contexts; the model configuration module supports dynamic switching of different AI service interfaces; the interaction auxiliary module provides a quick question button and a dialogue interruption function; the report preview module integrates Excel and PDF plug-ins to realize detail data preview; the session sharing module generates a sharing link and sets an access permission rule; dynamic model configuration optimizes response speed and accuracy; the operation process is simplified by a suspension button and a quick questioning function; the session sharing mechanism supports cross-team cooperation; and the real-time collaborative design with the T + 1 report meets the multi-dimensional data analysis requirement.

The invention discloses a method and system for realizing the AI processing capability of an operating system, and the method comprises the steps: carrying out the variable definition of a captured user instruction through an AI adapter, and transmitting a variable to an intention engine in a logic processing engine; an intention engine in the logic processing engine carries out corresponding processing through a cue word engine in the logic processing engine to generate a reasoning stream, and the reasoning stream is sent to the AI model for processing; when the AI model processes and executes the reasoning flow, calling the corresponding AI model for reasoning; and generating a task flow according to a reasoning result, wherein each execution process in the task flow is executed by calling a corresponding task execution module and tool through the AI adapter. According to the invention, the AI capability is added to the OS of the traditional terminal, and a multi-device platform and a multi-operating system are supported; various AI models such as language models, visual models, audio models, database indexes and the like are supported; the plug-in flexible adaptation of the AI model is supported; and the data privacy problem is avoided as far as possible by taking an end-side model as a main

The invention relates to the technical field of computer software development and application deployment, and discloses a mobile terminal productization configuration method and system.The method comprises the steps that a cross-platform development framework and a front-end framework are selected and configured; common parts in page logic are extracted into independent modules, and differential requirements in different environments are met in a parameterization mode; loading a corresponding configuration file according to a target environment, wherein the target environment comprises a development environment and a production environment; defining a mapping relation between the input path and the output path, and dynamically synchronizing the function file under the input path to the output path in the construction process; and controlling the synchronization logic of the configuration file and the code file through the life cycle of the plug-in, wherein the synchronization logic comprises real-time monitoring in a development environment and one-time synchronization in a production environment. According to the method, the problem that customization and productization are difficult to consider in a traditional development mode is solved, and the development efficiency and the convenience of later maintenance are improved through a systematic technical means.

The invention provides a lightweight configurable cue word labeling method and system for a Web system, and relates to the technical field of Web front-end development and man-machine interaction, and the system comprises a front-end labeling plug-in module, a cue word content service module, a cue word management module and an intelligent recommendation module. The front-end labeling plug-in captures text content selected by the user by monitoring a global shortcut key, and allows the user to add prompt words of a text, a rich text or a link type; the prompt word content service module provides an API (Application Program Interface) to realize persistent storage of data; the prompt word management module provides a unified management interface for an administrator; and the intelligent recommendation module automatically judges the prompt word display priority through a candidate recall and sorting algorithm based on the user click behavior data, and continuously optimizes the recommendation result by using an online learning mechanism. The method is integrated to an existing Web system in a non-intrusive mode, business core codes do not need to be modified, the use threshold of the system is remarkably lowered, and precipitation and sharing of business knowledge are promoted.

In various examples, a declarative configuration format defines a machine learning pipeline using nodes and edges that define the data flow between those nodes. Partial pipelines may be defined independently and referenced by multiple full pipelines. The configuration format may allow for constructing applications for a range of hardware and deployment environments. The system may support both graphical and programmatic interfaces for defining, modifying, and visualizing pipelines. The machine learning pipelines may be implemented on or interact with an underlying machine learning pipeline framework that provides runtime objects and a plugin architecture. The configuration data may be used to generate an application that includes the processing components and corresponding runtime dependencies of a machine learning pipeline in a containerized image.

A computing system including one or more processing devices configured to receive a prompt. At a machine learning model that has an output token vocabulary including candidate output tokens, the one or more processing devices are further configured to compute output token probabilities over the output token vocabulary based at least in part on the prompt. At a decoder plugin, the one or more processing devices are further configured to compute a constrained output token vocabulary as a proper subset of the output token vocabulary. The one or more processing devices are further configured to select output tokens based at least in part on the computed output token probabilities. The output tokens are selected from among the candidate output tokens included in the constrained output token vocabulary. The one or more processing devices are further configured to transmit an output including the output tokens to an additional computing process.

The invention provides a self-service terminal hardware service driving method, system and device for achieving cross-platform self-adaption and a medium, and belongs to the technical field of hardware service driving. The method comprises the steps that a front-end application is received to generate a hardware service request; the service bus dynamically loads a corresponding hardware service plug-in from a plug-in library according to the target hardware identifier; the interface adaptation layer selects a protocol template according to the interface type, and injects an operation parameter into the selected protocol template to generate an intermediate instruction; the loaded hardware service plug-in converts the intermediate instruction into a platform-independent hardware instruction; the platform adaptation layer detects the type of a current operating system, and calls a corresponding bottom driver library to convert a platform irrelevant hardware instruction into an operating system level hardware instruction; and sending an operating system level hardware instruction to the physical hardware, packaging a return result into a uniform response format, and returning the return result to the front-end application. According to the invention, cross-platform adaptive hardware driving is realized, and compatibility, flexibility and maintenance efficiency are improved.

The invention discloses a robot dynamic voice interaction method based on multi-modal state management, and belongs to the technical field of intelligent robots, and the method comprises the steps: S1, collecting multi-modal instruction data inputted by a user; s2, carrying out data processing on the multi-mode instruction data, and then generating an input text packet with an environment context mark; s3, performing intention analysis on the input text packet, and binding the input text packet with a historical context to generate an intention vector; s4, updating the environment matrix in real time through the intention vector; s5, dynamically calculating the task weight W through the updated environment matrix, and dynamically adjusting the priority of each task; and S6, calling a corresponding function module according to the priority of each task through a plug-in interface, and executing the corresponding task, so as to achieve the purposes of realizing cross-scene context continuity, multi-task priority dynamic scheduling, supporting hot plug function extension and having active abnormal interaction capability.

The invention relates to the technical field of intelligent gateways, in particular to a method and system for automatically expanding intelligent router plug-ins through LLM. The method comprises the steps that a user describes a plug-in function requirement of the intelligent router in a natural language through voice or text input equipment; and the cloud preprocessing service carries out character conversion processing on the voice data, carries out contradiction check and invalid information filtering on natural language requirements, extracts structured requirement information and inputs the structured requirement information to the cloud big language model. According to the intelligent router plug-in development method and system, the problems that in traditional intelligent router plug-in development, the manual intervention degree is high, the process is long and compatibility is insufficient are effectively solved by constructing an automatic system with the cloud large language model and the multi-service module cooperating. Through cooperation of multiple technical modules, a full-automatic process covering demand input, code generation, engineering integration, test verification and terminal deployment is constructed, and the intelligent router plug-in development efficiency and quality are remarkably improved.

The embodiment of the invention discloses a process template generation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a process generation demand of a user, and determining structured process logic description information based on the process generation demand, a preset process design cue word and a preset large language model; generating cue words and a preset large language model based on the process logic description information, a preset process template, and determining a first process template required by the user; performing rule verification on the first process template based on a preset verification plug-in, and determining a verification result; and if the verification result is that the verification is not passed, adjusting the first process template by utilizing a preset large language model, and determining a second process template required by the user. Through the technical scheme of the embodiment of the invention, the executable process template can be directly generated according to the demand described by the natural language, the node attribute and the logic relationship do not need to be manually configured, and the generality, the efficiency and the accuracy of the process template generation are improved.

The invention relates to the technical field of prefabricated part modeling, in particular to an interaction system for prefabricated part steel bar parameter driving design and a modularization implementation method. Incrementally updating the engine; the model application module is used for acting the change patch sequence on the three-dimensional reinforcement model in a transaction mode and driving display refreshing; the system further comprises a rule base module and an interpretable verification module. The rule base module stores a steel bar arrangement rule and / or a standard verification rule in a constraint declaration form; the interpretable verification module is used for performing compliance verification on the three-dimensional reinforcement model or the derived quantity thereof based on the evidence data field, and outputting a violation item list; the interactive interface comprises parameter panels and a violation interactive area, and the parameter panels are displayed in groups according to component type parameters, geometric parameters, steel bar parameters and specification options and support interactive modification. According to the method, the script dependency is reduced, the dependency graph increment patch is updated in real time, the automatic specification matching and positioning are realized, and the low-cost expansion is governed by the plug-in.