7013 results about "Application procedure" patented technology

Systems and methods for automatically generating and applying selected conditions to process data are provided. A system receives an application request is received, which includes one or more fields and one or more corresponding data items. The system also receives a configuration file from a configuration repository and processes the same to identify a plurality of rules. For each selected rule of the plurality of rules applicable to selected fields the one or more fields, the system evaluates the selected rules against selected data items associated with the selected fields. Based on the evaluating, the system determines a result of the application request and transmits the result for display.

An example operation may include one or more of receiving a loan application of a user, extracting a plurality of personal attributes about the user from the loan application, querying a machine learning model via an application programming interface (API) based on the plurality of attributes about the user to identify one or more rules for auto-adjudicating the loan application, determining whether or not to approve the loan application based on the one or more rules identified via the machine learning model, and transmitting notice of the determination to a device associated with the user.

An example operation may include one or more of executing a waiting period of time within a software application being accessed by a user, executing an animation via the software application during the waiting period, determining a result of the software application being accessed by the user, determining additional time to add to the waiting period of time based on the result, via the software application, executing the waiting period with the additional time, augmenting the animation based on the additional time to add to the waiting period, via the software application, and executing the augmented animation via the software application during the additional time. At least one portion of the example operation: integrates with an artificial intelligence (AI) chatbot, interacts with the AI chatbot, is performed by the AI chatbot, and / or is associated with an AI model.

A network system to use machine learning systems to create chaos testing scenarios on cloud-based applications. The system uses inputs from applications that are implemented on user computing devices to allow users to interface with a network or other system. The system creates a model of the application based on input data received from a network of applications, the model representing a structure, method, and dependencies of the application. The system identifies points of failure of the application and generates one or more chaos testing simulation scenarios that target the identified points of failure. The system performs the chaos testing based on the received simulation scenarios and logs the results of the testing. The system generates recommendations to revise code of the application based on the outcome of the chaos testing. A large language model may be used to provide documentation and analysis of the chaos testing.

Technology is disclosed herein for content assistance processes via foundation model integrations in software applications. In an implementation, a computing device receives natural language input from a user relating to content of a document in a user interface of an application. The computing device generates a first prompt for a foundation model to generate at least a completion to the natural language input. The computing device receives a reply to the first prompt from the foundation model which includes a completion to the natural language input. The computing device causes display of the completion in association with the natural language input in the user interface and receives user input comprising an indication to combine the input and the completion, resulting in a revised natural language input. The computing device submits a second prompt including the revised natural language input to the foundation model.

A method for using a large language model to generate executable code for workflow execution in a manner that integrates user feedback and adjusts the workflow as needed while preserving data privacy is provided. The method includes: receiving first information that relates to a workflow context, second information that relates to at least one application programming interface (API), and third information that relates to a code generation request; using the received information to generate a lecture, and transmitting the lecture to a language model; receiving a user query that relates to performing a task, and transmitting the query to the language model; receiving a workflow that is automatically generated by the language model based on the lecture and the query; and executing the workflow in order to generate an output that is responsive to the query.

The invention provides a security data penetration test method. The method comprises the steps of pre-establishing a multi-thread application program race condition vulnerability feature library, performing static analysis on source codes of a target application program, identifying potential race condition vulnerability points, and obtaining a preliminary vulnerability candidate set; for monitored suspected race condition events, abstracting event context information into constraint conditions, exploring an input combination of suspected static conditions by using a constraint solver, and determining a minimum input set of stable triggering race conditions; aiming at memory models and synchronous primitives of different programming languages, obtaining a race condition inverse mode, and extracting universal utilization primitives covering various race condition vulnerabilities; in the penetration test process, static analysis, dynamic monitoring and symbolic execution are applied to mine race condition vulnerabilities of a target application system, the availability of the vulnerabilities is verified, and evaluation of system security is assisted to be completed.

Systems and methods for large language model (LLM)-agnostic data anonymization. Data anonymization includes data obfuscation (and data deobfuscation) to protect confidential information a user is going to send to an LLM service or application programming interface (API). Encryption can be used for data obfuscation and particularly, for securing data from unauthorized access. Likewise, decryption can be used for data de-obfuscation.

Techniques for identifying malware based on system API function pointers are disclosed. In some embodiments, a system / process / computer program product for identifying malware based on system API function pointers includes monitoring changes in memory during execution of a malware sample in a computing environment; detecting a dynamic evasion behavior using an Application Programming Interface (API) vector comprising a plurality of system API function pointers identified in the memory during execution of the malware sample in the computing environment; and generating a signature based on the API vector for automatically detecting the malware during execution in the memory, wherein the malware sample was determined to be malicious.

An application may receive a prompt from a user related to an input for a text field of digital content. An application may generate context data about the digital content. An application may provide the prompt and the context data to a generative language model. An application may receive a response generated by the generative language model and provide the response as a suggestion for the input for the text field.

Embodiments of the disclosed technologies include, responsive to a first use of a first application by a first user, configuring, in a first prompt, at least one instruction based on first application context data and first user context data. The first prompt is stored in a memory that is accessible to the first application and a second application. Via the second application, first output of a generative artificial intelligence (GAI) model is presented to the first user. Based on the first output of the GAI model, at least one second use of the first application by the first user, or at least one first use of a third application by the first user, is configured.

A computer-implemented method for intelligent query response in an enterprise resource planning (ERP) system is disclosed. The method can receive, from a user interface of the ERP system, a natural language user query for processing data of a target object and invoke a function call through an application programming interface of the ERP system based on the user query. Invoking the function call includes extract denormalized data from one or more database tables, generating a prompt using a prompt template and the denormalized data, prompting a large language model using the prompt, and receiving a response generated by the large language model. The method can generate an output on the user interface based on the response generated by the large language model. Related systems and software for implementing the method are also disclosed.

Systems and methods described herein relate to automated troubleshooting for application development tools. First data comprise a plurality of delta objects and a user query. The plurality of delta objects identify design-time changes made to an application using a development tool. The user query is received via a user interface and relates to at least one of the design-time changes. The first data is preprocessed to obtain second data. The preprocessing of the first data includes modifying a subset of the first data and adding one or more predetermined instructions to the first data. The second data is provided to a machine learning model to obtain a response to the user query. Output indicative of the response is caused to be presented in the user interface.

Apparatuses, systems, and techniques to perform an application programming interface (API) to add one or more graph nodes to a software graph, wherein the API is to cause an event wait node to be added to a software graph based, at least in part, on a dependency type indicated by the API. In at least one embodiment, one or more nodes are added to a graph in accordance to one or more dependency types.

Various embodiments of the technology described herein cause an LLM to intelligently process data based on a user query and a schema determined for a data set. Certain embodiments programmatically leverage an LLM and utilize its output based on a user query. In this manner, data is processed without the LLM having to access an entire data set, and instead only utilizes information associated with the user query and the schema. The schema comprises a textual description, such as a string of alphanumeric characters, that describes the data, data types, and / or data structure of the data set. Embodiments of the technology described herein are performed by an LLM interface layer separate from a user device layer and an LLM layer. The LLM interface layer is positioned between an LLM abstraction layer and an application layer by which a user can interface with the LLM interface layer.

An online system improves the development and deployment of LLM-based applications providing offering an application workflow user interface to developers of these applications. The application workflow UI is a user interface that includes different sections for the efficient design of a workflow and logic for an application operating on the online system. The application workflow UI allows the user to generate UI elements for stages within the overall application workflow and connect those stages through a simple to use interface. The application workflow UI improves the development process of LLM-based applications by allowing the user to set parameters for stages that involve prompting an LLM through the same interface. Specifically, the application workflow UI includes a parameters section that allows the user to specify parameters for prompting the LLM.

The invention provides a cross-environment AI task collaborative execution method and device based on an MCP protocol and a storage medium, a plurality of different application programs deployed on a local system are packaged into uniform interface APIs, each application program corresponds to one uniform interface API, and the packaged uniform interface APIs support context awareness operation; the method comprises the following steps: constructing an MCP protocol at a cloud end, and obtaining a current state of each application program executing a task through a uniform interface API based on the MCP protocol, so that data among different application programs are kept consistent; an operation request input by a user is received at a cloud end, the operation request of the user is converted into an operation command of at least one application program based on an MCP protocol, the operation command is transmitted to a corresponding application program deployed on a local system through a uniform interface API, and the application program executes corresponding operation based on the operation command. According to the invention, a two-way operation path between the cloud AI and the local non-API software is established, and the success rate of cross-environment tasks is improved.

The invention discloses a system (100) for generating conversational content using a generative artificial intelligence (AI), said system (100) comprising: a user (101), an administrator (102), an application programming interface (API) server (103), a generative artificial intelligence (AI) server (104), a plurality of databases (105), a generative artificial intelligence (AI) processor (106), an audio generate processor (107), a text-to-speech processor / service provider (108), a video generation service (109), a video generation processor (110), and a memory communicatively coupled to the processor, wherein the memory stores processors instructions, which, on execution, causes the processor to generate at least one of conversational script, audio, video, or combination thereof. The system (100) allows users to create and customize various aspects of conversational content, including characters / personas / speakers, groups (of personas / characters / speakers), tones, content types, topics, conversation formats, and tone.

An application mapping engine may determine dependencies in existing executable application by monitoring and analyzing process flow and data flow of the application during runtime execution. The application mapping engine may generate dependency visualization maps that illustrate dependency interaction information.

Techniques are disclosed relating to a multi-agent search client. In an example method, a search agent application receives a query. The search agent application determines, using a search agent, one or more agents to each execute a portion of the query. The search agent application outputs, to a domain agent, a portion of the query. The search agent application determines, using the domain agent, an execution step based on the portion of the query and information about an executor. The executor generates instructions based on the execution step that are configured to generate a response to the execution step and outputs a command to execute the instructions. The executor then outputs, to the first domain agent, the response to the execution step. The search agent application outputs, using the search agent, a response to the query based on the response to the execution step.

The invention provides a method and device for an intelligent computing center to provide computing power resources through computing power packages, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructure, and the method comprises the steps: S1, determining a computing power package corresponding to a to-be-processed computing power task under the condition that the computing power resources need to be called, the computing power task is a task needing to call computing power resource processing, and the computing power package is used for metering the computing power of the intelligent computing center according to the calculated amount; s2, computing power resources are called based on an application program interface corresponding to the computing power package, the application program interface comprises a code program corresponding to operation for executing the computing power task, and the computing power resources called by the application program interface are matched with the operation environment of the computing power task. According to the method, the scheduling efficiency of the computing power resources can be improved, the computing power is metered according to the calculated amount through the computing power package, and wide application of the general computing power is achieved.

Apparatuses, systems, and techniques to perform an application programming interface (API) to cause dependency type information of one or more user-indicated graph nodes of a software graph to be indicated. In at least one embodiment, one or more dependency types from a graph are indicated.

Embodiments of the present invention provide computer-implemented methods, computer program product, and computer systems. One or more processors analyze user prompts using one or more natural language understanding techniques. One or more processors then enrich the user prompts by integrating contextual data from user interaction history and adapt the enriched user prompts to align with characteristics of Large Language Models (LLMs) and Application Programming Interfaces (API) requirements of the LLMs.

A method, system, computer program product of providing a FiniteStateMachine (FSM) with embedded business rules, processing data & events, where each state is individually saved to blockchain ledger, a data record including a unique identifier / name, a set of input field(s) or input data slots, state rules in a rule language, and set of output field names or output data slots, method including: executing of a Smart Contract by identifying state by id or name, loading corresponding Component State from blockchain, adding / executing code for processing the State's behavior, where the code includes rules for the state in the rule language (e.g., but not limited to. Open Policy Agent, Rego, Prolog, DataLog, RuleML, Drools Rule Language, NRules, and JavaScriptObjectNotation(JSON), etc.). System includes processor(s), application program interface (API(s)) for communicating, blockchain, rule processor, and memory. This enhances transparency, immutability, and secure execution of business rules within FSM architecture.

Methods and systems for generating a live digital document are provided. The method includes receiving a static document file including human-readable data. Then, parsing the static document file into a plurality of subunits. Then, generating a sharable document splice of the static document file. Hie sharable document splice includes access to a subset of the plurality of subunits, and the access is provided through an Application Programming Interface (API) or Software Development Kit (SDK) endpoint for each subunit in the subset. Then, executing a digital thread script to generate the live digital document from the sharable document splice and an input digital model representation, using API or SDK endpoints in the sharable document splice. The live digital document is configured through the digital thread script to reflect changes in the input digital model representation. Finally, adding execution metadata for the execution of the digital thread script to the live digital document.

Apparatuses, systems, and techniques to determine a matrix multiplication algorithm for a matrix multiplication operation. In at least one embodiment, a matrix multiplication operation is analyzed to determine an appropriate matrix multiplication algorithm to perform the matrix multiplication algorithm.

A user of an identity management system may configure a software agent with a set of parameters within one or more user interfaces of an agent management service. The set of parameters may include an identifier of an application programming interface (API) endpoint of a first service that the software agent is authorized to query and one or more permissions associated with queries to the API endpoint by the software agent. Further, the user may receive an authentication token for the software agent from the agent management service. The software agent may use the authentication token for accessing resources of the service via the API endpoint in accordance with the one or more permissions. Thus, the user may configure the first software agent with the authentication token to enable the software agent to perform the queries to the API endpoint of the first service.

To provide a data processing device capable of facilitating application creation, a data processing method, and a program.SOLUTION: A data processing device comprises an input unit which accepts a user input, a processing unit which performs specific processing using a data generation model which can generate data according to input contents, and an output unit which outputs the results of specific processing. The processing unit acquires application requirement definitions specified by a user input using an output of the data generation model when the input contents generated on the basis of the application requirement definitions were input. When an instruction to create an application creation in the requirement definitions is made, the processing unit creates an application on the basis of the output results from a data creation model obtained by inputting a prompt according to a creation stage of the application as the input contents.SELECTED DRAWING: Figure 3C

A system and method for automatically generating a change history of source code using a generative artificial intelligence (“AI”) system. In examples, a generative AI system receives a request inquiring about one or more changes made to software code of a software service or application. In response to receiving the request, the generative AI system navigates one or more information sources to collect code change context relevant to history of the code change(s). The generative AI system generates an instruction corresponding to the received request, where the instruction and the code change context are provided as input to a language model (LM) (e.g., a generative AI model). Based on the inquiry of the request, the LM processes the input, generates, and provides a corresponding output. The generative AI system then uses the output to generates and provide an explanation about the code change(s) to a requestor of the request.

Apparatuses, systems, and techniques to cause information to be invalidated in a second cache location after information is stored in a first cache location. In at least one embodiment, one or more circuits are to perform an application programming interface (API) to cause information to be invalidated in a second cache location after information is stored in a first cache location.