40 results about "Context manager" patented technology

The present invention belongs to the fields of network security, distributed systems, zero trust, and micro-services, and disclosed are a method for a micro-service dynamic access control policy under a zero trust architecture, and an apparatus. The method specifically comprises: obtaining context information in a micro-service runtime context event by means of an event tracker of a node; a context manager collecting and aggregating the context information and reporting same to a micro-service control plane global manager; the global manager determining whether a new micro-service instance is present according to a global context mapping table value, and if yes, updating a global and local tag mapping table; when a message is received by a node, a message validator obtaining a tag value carried by the message, and micro-service context information corresponding to the message being obtained by means of the local tag mapping table; after a local policy table and a global policy table are queried, running a decision algorithm, and executing a corresponding access control policy. The present invention uses context to identify a communication endpoint, and has the advantages of being dynamic, precise, and extensible.

The invention provides an agent collaborative question-answering method and system based on context awareness and authority control, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring user query, and triggering a user context manager to generate a session state user context object containing a permission label and preference; the central scheduler performs task decomposition based on the query intention and the context, dynamically selects an intelligent agent through a multi-dimensional scoring model and binds a knowledge source; the authority-aware agent execution engine executes triple authority verification and intermediate result desensitization processing in the whole process, and supports agent fault tolerance and audit log recording. The method realizes unification of knowledge security and access flexibility, supports multi-scene adaptive question and answer, and has good expandability and fault-tolerant capability.

This disclosure describes a large language model (LLM)-based agent operating system comprising an application layer, a kernel layer, and a hardware layer. The kernel layer comprises an AIOS kernel comprising: LLM core(s), an agent scheduler, a context manager, a memory manager, a storage manager, and a system call interface configured to manage interactions among the agent scheduler, the context manager, the memory manager, and the storage manager.

A direct memory access controller (DMAC) includes a virtual channel, a physical channel, and a context manager. The virtual channel is configured to generate a flow control signal for executing a direct memory access (DMA) command. The physical channel includes read and write control logic to initiate data transmission from the source device to the destination device in accordance with the DMA command in response to the flow control signal. In one embodiment, a context manager includes: allocation logic configured to arbitrate between allocation requests from virtual channels and to allocate physical channels to selected virtual channels; and routing logic configured to route a flow control signal from the selected virtual channel to the allocated physical channel, and to route a status signal between the allocated physical channel and the selected virtual channel.

The invention belongs to the field of software development tools, and discloses a dynamic context-aware text string editing and verification system and method.The system comprises a text string editing user interface component, a verification engine, a predefined function storage library and a variable context manager; the text character string editing user interface component receives a text character string input by a user; the verification engine is used for verifying the text character string in real time, and sending an error result and a modification suggestion for the error result if an error is found through verification; the text character string editing user interface component receives and displays the error result and the modification suggestion, receives a correct text character string input by a user, and triggers the verification engine to perform verification again; the verification mode comprises a strict verification mode and a loose verification mode. According to the method, the context is dynamically perceived, the variable is dynamically generated, comprehensive, real-time and accurate verification on the text character string is facilitated, and the accuracy of the text character string is improved.

The invention discloses an agent context management system and device based on importance sampling, and belongs to the technical field of artificial intelligence and agents, the agent context management system and device based on importance sampling comprise a global context manager used for maintaining and managing eight types of context information; the task stack manager is used for receiving a new request and performing task splitting; and the recursive execution engine is used for executing the task in a recursive mode and controlling the recursive depth. Eight types of context information are maintained through a global context manager, splitting and storage of complex tasks are achieved through a task stack manager, a recursive execution engine provides an efficient task execution mechanism and controls the recursive depth, an importance sampler selects related contexts based on a joint probability model, and the task execution efficiency is improved. And the context compressor combines the sampling fragments into a final context, and the task scheduler coordinates the working process of each component, so that a complete agent collaborative context management system is constructed.

The application discloses a kind of microservice dynamic access control strategy under zero trust architecture method and device, belong to network security, distributed system, zero trust, microservice field, it specifically includes: by the event tracker of node to obtain the context information in microservice runtime context event, context manager collects and aggregates context information and is reported to microservice control face global manager, global manager is according to global context mapping table value, judge whether it is new microservice instance, if yes then update global and local Tag mapping table, when node receives message, message verifier obtains the Tag value carried by this message, by local Tag mapping table to obtain the microservice context information corresponding to this message, after inquiring local strategy table and global strategy table, run decision algorithm, execute corresponding access control strategy, use context to identify communication endpoint, with dynamic, accurate, scalable advantage.

Techniques for intelligently managing task automation across multiple tasks and multiple automated assistants are provided. In one aspect, an intelligent multitasking system includes: a context manager configured to use human-centric input data to determine a context of a user; an intent mapper configured to map human communication to automated task intents; and an interruption manager configured to schedule automated tasks for performance by automated assistants based on the context of the user and the automated task intents. The context manager can be hosted on a cloud having MQTT clients (e.g., IoT sensors) and an MQTT broker. The intent mapper can include a human-machine software communication interface that identifies verbal and / or non-verbal communications. A method for intelligent multitasking is also provided.

A mixed reality automotive meta service (MR AMS) client of the present invention, which is provided in a vehicle and provides an MR AMS, comprises: a context manager requesting context corresponding to a user request to an MR AMS server provided outside a vehicle; a scene manager for managing MR scene information provided to a display provided in the vehicle; and a UX scenario database providing UX rules to the context manager and / or the scene manager.

An agent-centric workflow system includes a workflow engine operable to receive a workflow identifier and return a machine-readable response including instructions and success criteria for use by an AI agent. The workflow engine can include a next path generator operable to identify a possible next step in an identified workflow, dependencies between nodes of the identified workflow, and a consequence of the possible next step using a configuration file that corresponds to an API for the identified workflow, as well as an agent context manager operable to use the configuration file to construct the machine-readable response. The system can further include a large language model (LLM) agent operable to receive the machine-readable response and execute the instructions in a zero-shot execution. The system can include a target system including one or more APIs through which the LLM agent communicates with an identity provider or policy decision point.

The invention relates to an electronic medical record quality evaluation and verification method, which comprises the following steps of: S1, cleaning, analyzing and standardizing a complete electronic medical record to obtain a standardized patient panoramic context and a text block set capable of being retrieved by a vector; s2, constructing a mixed quality control knowledge base according to the external medical knowledge base and the quality control rule set; and S3, inputting the patient panoramic context, the mixed quality control knowledge base and a to-be-executed quality control point into a dynamic context manager, checking the document sequence set by adopting a quality evaluation function, and outputting a structured defect report. According to the method, an electronic medical record quality evaluation and verification framework integrating dynamic context management, multi-source knowledge fusion and large-scale language model reasoning ability is constructed, and the core contribution of the method is that the context window limitation of LLM is effectively avoided by designing an exquisite context manager mathcal {M}, and the reliability of the system is improved. And therefore, deep and explainable logic review can be executed on high-dimensional and time-sequence EMR (Empirical Mode Register) data.

The application discloses a kind of text context dynamic reconstruction methods, comprising: to original document is step length overlap segmentation processing, generate semantic fragment and record physical offset index information;Build document context manager storage original document complete content;Perform vector retrieval and obtain the physical offset index of matching fragment;Real-time analysis and determine the physical position boundary of fragment in original document;From original document, real-time extraction predecessor and successor text block;Splice form complete logical context window.The application establishes the accurate position anchor point of semantic fragment and original document by physical offset index, realizes zero-cost backtracking original;Adopt retrieval time dynamic reconstruction, support according to the context expansion range of adaptive adjustment of retrieval confidence;Provide three-level context mode to meet different retrieval scene demand;Intelligent deduplication eliminates redundant content.Compared with traditional RAG system, retrieval accuracy is improved by about 18%, context completeness is improved by about 31%, and Token consumption is reduced by about 30%.

The invention discloses a multi-tenant container cloud-oriented RDMA performance isolation system. A monitoring module comprises an eBPF monitoring program and a global context manager; the control path scheduler is deployed in a user mode library of a tenant and is used for receiving feedback information of the monitoring module and limiting or rejecting the original intonation rate of the control path exceeding a threshold value; and the data path scheduler is used for shaping and scheduling a data path task request issued by the tenant application program so as to control the sequence and the speed of entering the RDMA network card. According to the method, the eBPF monitoring program is adopted to monitor the original intonation frequency of the control paths of all tenants and the resource use condition of the RDMA network card, and millisecond-level response to RDMA control path operation is achieved. Meanwhile, a dynamic task segmentation mechanism based on active delay is adopted, and RDMA network card resource occupation of different tenants is balanced; and fairness is ensured based on a scheduling strategy of admission control.

A user controls a computer application with a first multi-modal agent and a second multi modal agent. A shared context manager is configured to receive from the first agent a first intent having a first data field, and to receive from the second agent a second intent having a second data field. The shared context manager forms a modified second intent based upon the first data field, and provides the modified second intent to the second agent. An intent stack is configured to receive the first intent and the modified second intent from the shared context manager and to store the first intent and the modified second intent.

A processing core for executing threads is provided. The processing core comprises: one or more functional units; a shared register file comprising a plurality of registers, each register of the shared register file being configured to store data for executing any thread; and a multi-thread elaboration unit, MTEU, the MTEU comprising: a control module configured to: receive an indication of a plurality of active threads for a given scheduling window; and receive instructions for each of the plurality of active threads; a context manager module configured to load, for each of the plurality of active threads, data required for executing a next one or more of the instructions into a respective one or more registers of the shared register file; and an instruction scheduler module configured to schedule the instructions of the active threads for execution based on availability of the one or more functional units.

The application discloses a kind of text context dynamic reconstruction methods, comprising: to original document is step length overlap segmentation processing, generate semantic fragment and record physical offset index information;Build document context manager storage original document complete content;Perform vector retrieval and obtain the physical offset index of matching fragment;Real-time analysis and determine the physical position boundary of fragment in original document;From original document, real-time extraction predecessor and successor text block;Splice form complete logical context window.The application establishes the accurate position anchor point of semantic fragment and original document by physical offset index, realizes zero-cost backtracking original;Adopt retrieval time dynamic reconstruction, support according to the context expansion range of adaptive adjustment of retrieval confidence;Provide three-level context mode to meet different retrieval scene demand;Intelligent deduplication eliminates redundant content.Compared with traditional RAG system, retrieval accuracy is improved by about 18%, context completeness is improved by about 31%, and Token consumption is reduced by about 30%.

The invention discloses a transaction control system and method for a database. As an openGauss kernel extension module, the system is composed of a session transaction context manager, an SQL statement classification interceptor, a DML transaction state machine engine, a DDL transaction coordinator and a PL / pgSQL transaction boundary analyzer. The system supports session-level automatic submission mode configuration, a DML transaction block is automatically started through a state machine in a non-automatic submission mode, and multi-statement atomicity can be achieved without depending on BEGIN statements; the DDL operation is independently and automatically submitted according to a strategy or is decoupled from a DML transaction for execution; and the PL / pgSQL storage process analyzes a forced explicit transaction boundary through a static code. According to the method, transaction management codes are simplified, atomic damage caused by omission of BEGIN is avoided, unified arrangement of DDL and DML is supported, the robustness of the storage process is improved, and the method is transparent and compatible with standard application and has good expandability.

The invention provides a model precision alignment testing method and system based on code blocks and electronic equipment, and relates to the technical field of deep learning testing. The method comprises the following steps: delimiting an execution boundary for a to-be-tested code block through a context manager and monitoring the execution boundary; executing the code block under monitoring based on input data in a reference calculation record prepared for the code block, and automatically capturing a generated forward data set; the forward data set at least comprises an input tensor input into the code block and an intermediate tensor generated in the code block; after the reverse gradient calculation is completed, automatically capturing a gradient data set corresponding to the forward data set; and finally, comparing the captured forward data set and / or gradient data set with corresponding data in the reference calculation record to generate a precision alignment test report. According to the method, fine-grained and low-intrusive precision testing of the calculation process of any code snippets in the deep learning model is realized, and the problems that the testing granularity is too coarse and the flexibility is poor in a traditional method are solved.

Provided in the present application are a method and apparatus for type inference of a programming language. The method comprises: in the process of developing program codes, acquiring a node to be inferred in an abstract syntax tree, wherein said node indicates a field to be inferred in the program codes, said field comprising one of the following fields: a variable, a class, a function, or a parameter; acquiring a constraint related to said node, wherein the constraint is used for indicating a relationship involved in said node in the abstract syntax tree; and on the basis of the constraint, determining the type of said node, wherein the type of said node is one of the following: a numeric type, a sequence type, a mapping type, a set type, an iterator type, a context manager type, a module type, a meta type, a null value type, or a callable type. The solution of the present application is conducive to reducing the memory usage of type inference.

The invention discloses a multi-source heterogeneous JSON (JavaScript Object Notation) data stream processing method based on Flink SQL (Structured Query Language), which specifically comprises the following steps of: establishing a Kafka connection table, defining a Topic field and an original data field extracted from Kafka metadata in a table structure of the connection table, and starting a dynamic Schema mode; creating an independent structure context manager for each physical processing task instance of the Flink SQL, wherein the manager maintains structure contexts of different Topic in a key value pair form; analyzing the key value pair of each JSON, performing key name standardization processing, and executing newly added field addition or type conflict processing based on the Schema cache; recursively unfolding the object and the array type field, and generating an unfolding structure according to the maximum unfolding depth limitation and the position marking rule; constructing an output line according to the Schema cache, filling a missing field into a null value, and injecting a Kafka metadata field and an expansion position mark; and outputting Row objects in a uniform format to form a dynamic Schema data stream, and butting an Flink Table API (Application Program Interface) to support direct query of a dynamic extension field.

The invention relates to an alarm event processing method and device in a server, computer equipment and a medium, and the method comprises the steps: responding to an alarm system configuration operation, and transmitting configuration dynamic data corresponding to the alarm system configuration operation to a jLogtail collector; acquiring an original log of a server collected by a jLogtail collector, converting the collected original log into a standard format event, and pushing the standard format event to a message queue; calling an MCP context manager to consume the standard format event from the message queue, supplementing context information by taking a core identifier corresponding to the standard format event as a clue, and generating complete context information; and based on the complete context information, in combination with a dynamic threshold algorithm and a weighted diagnosis result of the diagnosis agent cluster, judging whether a preset alarm triggering condition is met. The whole scheme can realize efficient and accurate alarm event processing.

This invention discloses a method and system for small-sample intent assessment and situational awareness based on a large language model, belonging to the field of natural language processing. It mainly includes: retrieving the most relevant few-sample examples and known intent descriptions for queries using a dynamic context manager; concatenating prompts and invoking a large language model for inference, outputting intent recognition results and discovering new intents; employing a joint training strategy of supervised contrastive learning and adversarial enhancement to refine the feature space on pseudo-labeled data; and calculating anomaly scores for samples based on Mahalanobis distance to identify out-of-distribution new intents (abnormal intents). This invention, through a two-stage hybrid framework of "generative guidance and discriminative refinement," effectively solves the technical challenges caused by data scarcity and dynamic evolution of intent in open environments, achieving highly robust, low-cost, and sustainably evolving intent discovery and recognition. It can be widely applied in small-sample fields such as military activities, cybersecurity, financial risk control, and public opinion analysis.

Apparatus, methods, and systems that operate to provide interactive streaming content identification and processing are disclosed. An example apparatus includes a classifier to determine an audio characteristic value representative of an audio characteristic in audio; a transition detector to detect a transition between a first category and a second category by comparing the audio characteristic value to a threshold value among a set of threshold values, the set of threshold values corresponding to the first category and the second category; and a context manager to control a device to switch from a first fingerprinting algorithm to a second fingerprinting algorithm different than the first fingerprinting algorithm, responsive to the detected transition between the first category and the second category.

The invention relates to an electronic certificate arrangement method and device and a medium, and belongs to the technical field of electronic certificate management, and the method comprises the following steps: storing a preset electronic certificate business arrangement rule in a local configuration file, and calling a local parser to parse the rule to generate a memory data structure; and receiving the structure by using a constructor, generating a plurality of service components and electronic certificate service arrangement metadata, and connecting the service components to construct an electronic certificate service chain arrangement rule. And executing a context manager to obtain context data, loading a chain arrangement rule, and injecting the data into the rule. And obtaining a to-be-arranged electronic certificate, and performing arrangement processing according to the arrangement metadata and the chain arrangement rule. According to the invention, the arrangement rule is constructed by connecting the business components according to the sequence defined by the rule and the logic, so that the business process definition is more flexible and diverse.

The following descriptions concern a system for providing and interacting with a context-aware omnichannel vehicle assistant, comprising: a generic context manager implemented on a server for receiving and processing data from a variety of entities to collect real-time data on the vehicle status, the driver's condition, environmental conditions, and / or driver interactions across various touchpoints; a first local context manager implemented in a first entity and a second local context manager implemented in at least one further entity for local data processing; and at least one output unit.wherein the generic context manager includes a first machine learning and AI module for using machine learning algorithms to analyze the driver's preferences, predict the driver's needs, and adapt services accordingly, wherein the first learning and AI module enables a personalized driver experience and predictive adaptations, wherein the generic context manager communicates with the first local context manager and the second local context manager via an omnichannel interface for exchanging data and / or integrating the first entity with the at least one other entity.

A method for use in a computing device, the method comprising: transmitting, to a context manager, a context request associated with a process that is executed in a virtual machine; receiving, from the context manager, a context identifier in response to the context request; transmitting, to an introspection Application Programming Interface (API), a memory access request that is based, at least in part, on the context identifier.

The application provides an xml file parsing method, system, computer and readable storage medium, the method comprises the following steps: loading the parsing configuration instruction through the parsing engine; receiving the xml file set, and parsing each xml file in the xml file set through the parsing task flow to parse each xml file into the corresponding object respectively; reading the object into the context manager, and calling the corresponding rule calculator through the parsing configuration instruction; calculating the corresponding value of the object through reading the rule to calculate the attribute value corresponding to each xml file respectively; storing the attribute value in the context manager through the preset path, and making the context manager output the complete parsing structured file. Through the above method, the parsing of xml files with any structure can be realized, and the parsing efficiency of xml files is improved.

The application provides a code block-based model precision alignment test method and system and electronic equipment, and relates to the technical field of deep learning testing. The method comprises the following steps: defining an execution boundary for a code block to be tested by a context manager and monitoring; based on input data in a reference calculation record prepared for the code block, executing the code block under monitoring, and automatically capturing a generated forward data set; the forward data set at least includes an input tensor input to the code block and an intermediate tensor generated inside the code block; after the completion of reverse gradient calculation, a gradient data set corresponding to the forward data set is automatically captured; finally, the captured forward data set and / or gradient data set is compared with corresponding data in the reference calculation record, and a precision alignment test report is generated. The application realizes fine-grained and low-invasive precision testing of the calculation process of any code segment in a deep learning model, and solves the problem of coarse testing granularity and poor flexibility of traditional methods.

The application provides a type inference method and device of a programming language, the method comprising: in the development process of program code, obtaining a node to be inferred in an abstract syntax tree, the node to be inferred indicating a field to be inferred in the program code, the field to be inferred comprising one of the following: a variable, a class, a function or a parameter; obtaining a constraint related to the node to be inferred, the constraint being used to indicate a relationship involved by the node to be inferred in the abstract syntax tree; determining a type of the node to be inferred according to the constraint, the type of the node to be inferred being one of the following: a numeric type, a sequence type, a mapping type, a set type, an iterator type, a context manager type, a module type, a metatype, a null type or a callable type. The scheme of the application is beneficial to reducing the memory occupation of type inference.

The invention discloses a real-time table synchronization method based on spring and myabits frameworks, which belongs to the technical field of data processing, and comprises the following steps: extracting a table name from an sql statement, and setting a synchronization table list to an sql context manager according to the table name; the mybatis layer interceptor obtains a result of executing the sql statement by using the main data source and returns the result to the Dao layer interceptor, and a synchronization table list is extracted from the sql context manager; the Dao layer interceptor sets a slave library code in an sql context manager; a slave library connection is obtained according to a slave library code set in the sql context manager, the mybatis layer interceptor uses the slave library connection to execute the sql statement, and data synchronization is carried out on a slave library corresponding to the slave library connection; and after all library synchronization operations are completed, returning an execution result to a dao layer method name by the dao layer interceptor. According to the real-time table synchronization method based on spring and myabits frameworks, the problems that in an existing table synchronization method, a programmer needs to write service codes additionally, delay exists, and table synchronization is difficult to conduct between different databases are solved.