176 results about "Manifest file" patented technology

Systems and methods are described for building artificial intelligence (“AI”) agents. A server can provide a user interface (UI) that includes options to select and connect various agent objects. The agent objects can include prompt objects, dataset objects, model objects, and one or more code objects. A subset of the agent objects can be identified as available for selection based on evaluation of at least one management policy associated with an administrative user. A manifest file is generated based on the connected agent objects, and the manifest is validated against dependency rules to ensure that the stages of the agent meet prerequisites for the stages. Then, the server performs a simulated execution of an agent that corresponds to the validated manifest file, including an identification of at least one execution metric associated with the simulated execution.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

Systems and methods are described for building artificial intelligence (“AI”) agents. A server can provide a user interface (UI) that includes options to select and connect various agent objects. The agent objects can include prompt objects, dataset objects, model objects, and one or more code objects. A subset of the agent objects can be identified as available for selection based on evaluation of at least one management policy associated with an administrative user. A manifest file is generated based on the connected agent objects, and the manifest is validated against dependency rules to ensure that the stages of the agent meet prerequisites for the stages. Then, the server performs a simulated execution of an agent that corresponds to the validated manifest file, including an identification of at least one execution metric associated with the simulated execution.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

In accordance with example embodiments of the invention there is at least a method and apparatus to perform executing a machine learning inference loop of a currently deployed or stored at least one machine learning model, wherein the currently deployed or stored at least one machine learning model is identified based on a manifest file received from a communication network; based on determined factors, requesting from the communication network a model update to trigger the model update for use with the currently deployed or stored at least one machine learning model; based on the request, receiving information from the communication network comprising the model update; and based on the information, performing a model update to update the currently deployed or stored at least one machine learning model. Further, receiving, based on determined factors, from a user equipment a communication to trigger a machine learning model update for use with a currently deployed or stored at least one machine learning model at the user equipment; based on the communication, determining information comprising the model update; based on the determining, sending towards the client the information comprising the model update for a model update to update the currently deployed or stored at least one machine learning model.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

A method includes identifying, by a processing device, a set of parameters to generate a container image for a container. The parameters comprise one or more dependencies associated with running the container in a cloud-based environment. A manifest file referencing the one or more dependencies is obtained and the container image is generated based on the set of parameters, wherein the manifest file is stored in a predetermined location associated with the container.

The invention relates to a mirror image file processing method and device, and relates to the technical field of container mirror image generation. The method comprises the steps of obtaining target file system directory information of a target container in response to a mirror image file export request for the target container; the target file system directory information of the target container is used for representing file system directory information of a writable layer of the target container; comparing the target file system directory information of the basic mirror image with the target file system directory information of the target container to obtain a difference file of the target container relative to the basic mirror image; constructing a layer file of a new incremental layer based on the difference file; writing a layer file of the incremental layer into a mirror image layer file directory of the basic mirror image, and updating a list file and an index file of the basic mirror image to obtain a mirror image file of the target container; the manifest file comprises metadata of each mirror image layer in the basic mirror image, and the index file comprises metadata of the manifest file. By adopting the method, the export efficiency of the container mirror image file can be improved.

The invention relates to the technical field of engineering cost, and discloses a data entry method for engineering cost software, which comprises the following steps of: S1, importing an engineering quantity list file in an Excel format through an interface of the engineering cost software, and automatically analyzing a data structure of the engineering quantity list file; s2, based on a preset intelligent matching algorithm, performing dynamic mapping on the Excel data field and a data field of a project cost software function module; s3, adopting a data type self-adaptive rule to automatically classify and convert numerical values, texts and compound data in the Excel; s4, based on a data association generation algorithm, automatically establishing a hierarchical relationship and a dependency relationship between the engineering quantity list items; s5, executing one-button data import, and writing the processed structured data into a project cost software database in batches; according to the method, high-precision automatic mapping of the Excel field and the software module is realized through an intelligent matching algorithm and a dynamic weight adjustment mechanism based on the feature vector similarity, the matching accuracy is greatly improved, and the manual correction frequency is greatly reduced.

Techniques for serving a manifest file of an adaptive streaming video include receiving a request for the manifest file from a user device. The video is encoded at different reference bitrates and each encoded reference bitrate is divided into segments to generate video segment files. The manifest file includes an ordered list of universal resource locators (URLs) that reference a set of video segment files encoded at a particular reference bitrate. A source manifest file that indicates the set of video segment files is identified based on the request. An issued manifest file that includes a first URL and a second URL is generated based on the source manifest file. The first URL references a first domain and the second URL references a second domain that is different from the first domain. The issued manifest file is transmitted to the user device as a response to the request.

The invention discloses a method and a system for automatically generating a PLC (Programmable Logic Controller) program, a storage medium and a program product. The method comprises the following steps: creating a PLC standard library file; establishing a code generation method library according to the PLC standard library file; creating a project control object list file, and establishing a corresponding equipment attribute set according to the attribute information of the project control object list file; and matching the equipment attribute set with the code generation method library to generate a corresponding PLC program. According to the method, the PLC program can be automatically generated through the code generation method library, an engineer does not need to manually write a large number of codes, the project development period is greatly shortened, and in addition, the readability and maintainability of the program written through the method are greatly improved; no matter how large the actual PLC project exists, the program can be quickly generated only by configuring the project control object list, so that the code writing efficiency is greatly improved, and meanwhile, the labor cost is greatly reduced.

Disclosed is a business process infrastructure container system. The system includes one or more business process infrastructure modules configured to perform a user-desired operation on a client platform. The system also includes a manifest file having details of one or more business process infrastructure modules. The system further includes computer-readable instructions configured to trigger the user-desired operation via one or more business process infrastructure modules and the manifest file.

The invention relates to the field of computers, and provides a deployment method for realizing distributed training on k8s by using a heterogeneous GPU (Graphics Processing Unit), which comprises the following steps of: compiling a distributed training task list file CR1 and submitting the file CR1 to the k8s; the first controller monitors the creation of the CR1, creates a plurality of CR2 according to the configuration of the CR1, and allocates training task parameters to each CR2; the controller II monitors the creation of each CR2, creates a plurality of Pods according to the configuration of each CR2, and allocates training task parameters to each Pod; the second controller judges whether current distributed training is elastic training or not, and if yes, an Hpa resource is created for each CR2; and after the current distributed training is completed, the controller I deletes all CR2 of the current distributed training task so as to delete all Pods. The technical problem that distributed training cannot be accelerated by simultaneously using multiple GPUs in one training task in the prior art is solved.

The invention relates to the technical field of data processing, and discloses a multi-source data difference attribution system and method based on tensor decomposition, and the method comprises the steps: obtaining an original engineering quantity list file, and then carrying out decoupling to generate a standardized list item text sequence and an initial value set, constructing unit prices to form a tetrahedral geometric model set, mapping the tetrahedral geometric model set to a holographic feature vector space, and generating a multi-dimensional list feature vector set; constructing a standard cost reference vector field, identifying a difference vector set and generating a visual cost difference topological data model; a natural language query instruction is responded, a target difference attribution tensor is locked, a logic verification chain is constructed, and an intelligent diagnosis report is output; according to the method, a computable logic distance is established in multi-source heterogeneous data by reversely reconstructing a high-dimensional price-rate feature space, so that the problem of attribution blocking caused by dimension collapse in traditional cost auditing is effectively solved, and accurate traceability and compliance automatic diagnosis of cost differences are realized.

Techniques are disclosed relating to the protection of secrets within a software development lifecycle. Developers can use an encryption service to encrypt a secret to be used by an application within a package. The secret can be associated with the application, and then encrypted and included in a package that is signed and passed through a software automation pipeline to a data center that hosts the production server for the application. The application executing on the production server can request that the secret be decrypted by a decryption service after package verification. A developer can also specify, in a manifest file, a set of secrets needed for applications executing in the same data center. The manifest file may be passed from the software development environment to the data center, where the specified secrets are created and used by the applications without ever residing or being accessible outside the data center.

Systems, apparatuses, and methods are described for assisting a content delivery network (CDN) in managing access restrictions to content. Access restrictions and / or entitlements may be reflected in a signing package, which may be included in a content item manifest file. The signing package may also be passed in requests for the content item, and may be passed in a form to allow it to remain unaltered as it is routed to a destination computing device.

A method for generating a bill of materials file includes a generation device obtaining target information, where the target information includes training dependency information, model composition information, and model metadata. The training dependency information is information about a training resource for training an artificial intelligence (AI) model. The model composition information is information about an intermediate model in a process of training the AI model, and the model metadata is attribute information of the AI model. The generation device generates a bill of materials file of the AI model, where the bill of materials file includes the target information.

Systems and methods enable video on demand playback startup times to be reduced. A redirect database is populated with redirect locators. A request from a device for an item of primary video content is received. A static manifest file is generated including locators corresponding to the requested item of primary video content and redirect database entries storing redirect locators to default interstitial media. The static manifest file is transmitted to the device. Potential items of interstitial media are identified by sources of interstitial media, and a first item of interstitial media is selected. A redirect locator in the redirect database is replaced with a redirect locator corresponding to the selected interstitial media. A request is received from the device directed to the redirect database location storing the redirect locator corresponding to the selected interstitial media. The selected interstitial media is streamed to the device.

To prevent an on-board train content player from malfunctioning, a streaming agent 162 cooperates with a cache unit 161 to provide stored media segments, a manifest unit 169 to provide track description files 125 and driver manifest files 126, a monitoring unit 163 to determine the quality of a connection with an external source CDN, a description unit 165 to obtain a textual description of requested media segments, and a substitution unit 164 to obtain substitute segments, for example, by generative AI generation from the textual description and optionally other segments of the same media content. The streaming agent 162 substitutes a media segment requested by the player with a substitute segment when the connection quality with the external source CDN is insufficient to provide the original media segments. [Fig. 1]

A resource scheduling method and apparatus based on a storage system, a medium, and an electronic device are provided, so that data processing tasks of different object buckets can be scheduled more fairly, and the timeliness and efficiency of task completion are improved. The method includes: acquiring a manifest file respectively corresponding to each object bucket in a storage system; performing loop traversal allocation for each object bucket based on a preset object allocation rule to obtain a target object allocation quota for each object bucket; generating a data processing task corresponding to each object bucket based on the target object allocation quota for each object bucket and the manifest file corresponding to each object bucket, where the data processing task is a task executed according to a manifest file granularity, and a number of expired objects in a manifest file executed by a total data processing task of an object bucket is not greater than a target object allocation quota for the object bucket; and controlling the data processing task of each object bucket to be executed in parallel.

Described herein are systems and methods for obfuscating variants of content segments. A manifest file configured to facilitate access to content may be provided. The manifest file may be based on an identifying sequence for a plurality of content segments of the content. The identifying sequence may indicate, for at least one content segment of the plurality of content segments, at least one variant of a plurality of variants.

The disclosed system (110) and method (500) enables muxing and storing a manifest file in a storage server (122). The method (500) includes receiving (502) one or more input streams from at least one streaming service. The input streams are received by an authorization unit communicatively coupled to a streaming server. The received one or more input streams are encoded (504) by an encoder using one or more predefined codec configurations to generate corresponding one or more encoded streams. The generated one or more encoded streams are multiplexed (506) by a muxer into at least one muxing. The muxing includes livestream data and embedded metadata. Further, at least one of the muxing and one or more input / output (I / O) services are linked (508) into a manifest file that is stored in a storage server.

The invention discloses a configuration data downloading method and device. The method comprises the following steps: acquiring a current downloading list file, a historical downloading list file and a bit number assignment list file; comparing the current downloading list file with the historical downloading list file to obtain a comparison result; determining a change list file based on the comparison result; generating configuration data based on the current downloading list file, the change list list file and the bit number assignment list file; and downloading the configuration data into the controller according to the mode of the interface file. Configuration data are downloaded into the controller in an interface file mode and can be directly compatible with configuration software, modification or redesign is not needed, and therefore the flexibility and expandability of the system are improved.

A method, apparatus, and computer program product for trickplay in HTTP live streaming (HLS), includes: establishing a connection to a content source; receiving a piece of content from a content source as a multimedia stream, wherein the multimedia stream comprises a digital living network alliance stream; converting the multimedia stream into a client stream that comprises a HLS stream, the HLS stream including a manifest file containing a plurality of transport stream packets; storing a pre-determined number of the plurality of transport stream packets in a temporary storage; outputting the client stream to a media player; receiving a first trickplay request from the media player, the first trickplay request being a pause request; in response to the first trickplay request: pausing the client stream; transmitting a signal keeping the connection to the content source alive and the multimedia stream active; and storing the multimedia stream in the temporary storage.