Task processing method and device and information aggregation system

Abstract

The invention discloses a task processing method and device and an information aggregation system. The method comprises the following steps: analyzing task description information to obtain a plurality of atomic tasks; the atomic capabilities corresponding to the atomic tasks are called to execute the atomic tasks, multiple execution results are obtained, and the atomic capabilities are the capabilities obtained by disassembling the capabilities of the application. According to the task processing method provided by the embodiment of the invention, the cost of research and development and iterative updating of the application can be reduced.

Description

Technical Field

[0001] This application belongs to the field of application technology, and in particular relates to a task processing method, apparatus and information aggregation system. Background Technology

[0002] Currently, applications can execute tasks within their capabilities. If a task exceeds the application's capabilities, meaning it presents new requirements, then a new application needs to be developed to meet these new requirements, or the existing application needs to be iteratively updated to satisfy users' growing needs. However, developing new applications and iteratively updating existing applications are costly. Summary of the Invention

[0003] This application provides a task processing method, apparatus, information aggregation system, device, storage medium, and vehicle, which can reduce the cost of application development and iterative updates.

[0004] In a first aspect, embodiments of this application provide a task processing method, the method comprising:

[0005] The task description information is parsed to obtain multiple atomic tasks;

[0006] The atomic capabilities corresponding to the multiple atomic tasks are invoked to execute the multiple atomic tasks, resulting in multiple execution results. The atomic capabilities are capabilities obtained by decomposing the capabilities of the application.

[0007] In one possible implementation, parsing the task description information to obtain multiple atomic tasks includes:

[0008] The task description information is parsed to obtain the multiple atomic tasks and the dependencies between them.

[0009] In one possible implementation, the invocation of the atomic capabilities corresponding to the plurality of atomic tasks to execute the plurality of atomic tasks, resulting in a plurality of execution results, including:

[0010] The execution order of the multiple atomic tasks is determined based on the dependencies;

[0011] The atomic tasks are added to multiple task execution queues in the order described above.

[0012] The atomic capabilities corresponding to the multiple atomic tasks are invoked to execute the multiple atomic tasks in the multiple task execution queues, resulting in multiple execution results.

[0013] In one possible implementation, the task description information includes interface task description information and its corresponding data task description information; the multiple atomic tasks include multiple node acquisition tasks and multiple data acquisition tasks; and parsing the task description information to obtain multiple atomic tasks includes:

[0014] The interface task description information is parsed to obtain the interface layout task, which includes the multiple node acquisition tasks.

[0015] The data task description information is parsed to obtain the multiple data acquisition tasks.

[0016] In one possible implementation, the multiple execution results include business data corresponding to the data acquisition task and node information corresponding to the node acquisition task. After obtaining the multiple execution results, the method further includes:

[0017] Establish the correspondence between the business data and the node information;

[0018] The generative framework is invoked, and based on the correspondence between the business data and the node information, multiple sets of business data and multiple sets of node information are rendered according to the interface layout task to obtain and display generative information.

[0019] Secondly, embodiments of this application provide a task processing apparatus, the apparatus comprising:

[0020] The parsing module is used to parse the task description information to obtain multiple atomic tasks;

[0021] The execution module is used to call the atomic capabilities corresponding to the multiple atomic tasks to execute the multiple atomic tasks and obtain multiple execution results. The atomic capabilities are capabilities obtained by decomposing the capabilities of the application.

[0022] Thirdly, embodiments of this application provide an information aggregation system, including:

[0023] A parsing engine is used to receive task description information, parse the task description information, and obtain interface layout tasks and multiple data acquisition tasks. The interface layout tasks include multiple node acquisition tasks corresponding to the multiple data acquisition tasks.

[0024] An execution engine is used to receive the interface layout task and the multiple data acquisition tasks sent by the parsing engine, call the atomic capabilities corresponding to the multiple data acquisition tasks to execute the multiple data acquisition tasks, obtain multiple business data, and call the atomic capabilities corresponding to the multiple node acquisition tasks to execute the multiple node acquisition tasks, obtain multiple node information. The atomic capabilities are capabilities obtained by decomposing the application's capabilities.

[0025] The generation engine is used to receive the interface layout task, the multiple business data, and the multiple node information sent by the execution engine, and to call the generative framework to render the multiple business data and the multiple node information according to the interface layout task, so as to obtain and display generative information.

[0026] Fourthly, embodiments of this application provide an electronic device, which includes: a processor and a memory storing computer program instructions;

[0027] When the processor executes the computer program instructions, it implements any of the possible implementations of the first aspect described above.

[0028] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the method in any of the possible implementations of the first aspect described above.

[0029] Sixthly, embodiments of this application provide a vehicle that includes at least one of the following:

[0030] The task processing apparatus as described in any embodiment of the second aspect;

[0031] An information aggregation system as described in any embodiment of the third aspect;

[0032] The electronic device as described in any embodiment of the fourth aspect;

[0033] Computer-readable storage medium as described in any embodiment of the fifth aspect.

[0034] In this embodiment, since the application's capabilities have been broken down into multiple atomic capabilities, multiple atomic tasks are obtained by parsing the task description information. Furthermore, the atomic capabilities corresponding to each atomic task are invoked to execute these tasks, resulting in multiple execution results. In other words, task instructions can be executed by invoking the corresponding atomic capabilities of the application, rather than by invoking the entire application. Thus, this embodiment allows developers to focus on expanding atomic capabilities without investing excessive time and effort in the application's interface and interaction methods, thereby reducing the cost of application development and iterative updates. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic diagram of the structure of a task processing system provided in an embodiment of this application;

[0037] Figure 2 This is a flowchart illustrating a task processing method provided in an embodiment of this application;

[0038] Figure 3 This is a schematic diagram of the structure of a task processing device provided in an embodiment of this application;

[0039] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0040] To better understand the above-mentioned objectives, features, and advantages of this application, the solution of this application will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0041] Many specific details are set forth in the following description in order to provide a full understanding of this application, but this application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of this application, and not all embodiments.

[0042] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0043] As described in the background section, to address the problems of the prior art, embodiments of this application provide a task processing method, apparatus, information aggregation system, device, storage medium, and vehicle. The task processing method can be applied to scenarios where users interact with applications. This task processing method can be executed by an information aggregation system. The information aggregation system, also known as an information aggregation framework, is part of the task processing system.

[0044] The task processing system provided in the embodiments of this application will be described below.

[0045] Figure 1 A schematic diagram of the structure of a task processing system provided in an embodiment of this application is shown. Figure 1 As shown, the task processing system provided in this embodiment may include an interaction module 11, an information aggregation framework 12, a task processing engine 13, and a generative framework 14. The information aggregation framework 12 may include a parsing engine 121, an execution engine 122, and a generation engine 123.

[0046] Specifically, the interaction module 11 can be used to receive task instructions, generate task description information corresponding to the task instructions, and send the task description information to the information aggregation framework 12. The task instructions can include user instructions and system instructions. System instructions can be instructions automatically generated by the system under preset conditions. For example, a system instruction could be automatically generated to turn on the air conditioner and set the air conditioner mode to heating mode when the vehicle temperature is lower than a preset temperature.

[0047] As an example, interaction module 11 may include an interactive interface and a large-scale artificial intelligence model. The interactive interface can be set up on a terminal for interaction with the user. Multiple applications can be installed on the terminal, including self-developed applications and third-party applications. Self-developed applications may include applications (APPs) with interactive interfaces and system services without interactive interfaces. The interactive interface of interaction module 11 can display icons corresponding to each of the multiple applications. In addition, user commands can be used to interact with multiple applications. The input methods for user commands may include voice input, text input, touch input, and gesture input, etc., without limitation. User commands could be, for example, "find movies currently showing in theaters" or "recommend nearby restaurants."

[0048] Furthermore, large-scale AI models refer to high-performance AI models built with massive training samples and computational resources. These models can learn vast amounts of language knowledge, image features, and speech patterns, and can reason and generate outputs similar to humans, finding wide applications in natural language processing, image recognition, and speech recognition. Examples of large-scale AI models include Large Language Models (LLMs), ChatGPT (Chat Generative Pre-trained Transformer), multimodal large models, and multimodal cognitive large models. Specifically, large-scale AI models can parse user commands, determine user intent, and generate task description information corresponding to that intent. This task description information can include command scenario information, interface task description information, and data task description information. There can be a correspondence between these three types of information. Command scenario information can represent the application scenario of the user command. Examples include navigation scenarios, food recommendation scenarios, and movie recommendation scenarios. Additionally, data task description information can be used to describe data acquisition tasks, which can be used to acquire business data. The interface task description information can be used to describe the interface layout task. The interface layout task can include a node retrieval task. The node retrieval task can be used to retrieve node information displayed on the interface. The interface layout task can be used to arrange the display method of node information and business data.

[0049] As a more specific example, if the user's command is the voice command "Find movies currently showing in theaters," and the terminal has video software A, video software B, and video software C installed, then the AI ​​big data model can determine that the user's intent includes finding movies currently showing in theaters from video software A, video software B, and video software C. After determining the user's intent, task description information corresponding to that intent can be generated. This task description information may include, for example, the command scenario information "movie recommendation scenario," data task description information for retrieving movie data currently showing in theaters from video software A, video software B, and video software C respectively, node information such as icons and controls corresponding to video software A, video software B, and video software C respectively, and interface task description information for laying out the node information and movie data.

[0050] Since the task description information is output by the large artificial intelligence model in the interaction module 11, the task description information can conform to the domain-specific language (DSL) corresponding to the large artificial intelligence model.

[0051] After the large artificial intelligence model outputs the task description information, the interaction module 11 can send the task description information to the information aggregation framework 12.

[0052] In addition, it should be noted that large-scale artificial intelligence models can be set up on the terminal or in the cloud, without any limitation.

[0053] The information aggregation framework 12 (i.e., the information aggregation system) may include a parsing engine 121, an execution engine 122, and a generation engine 123.

[0054] Specifically, the parsing engine 121 can receive task description information sent by the interaction module 11, parse the task description information, and obtain interface layout tasks and multiple data acquisition tasks. The interface layout tasks can include multiple node acquisition tasks corresponding to the multiple data acquisition tasks. Both data acquisition tasks and node acquisition tasks are atomic tasks. Atomic tasks can be executed by atomic capabilities. Atomic capabilities are capabilities obtained by decomposing application functions. An atomic capability can be a small, independent, atomic functional module, described and implemented according to a specified format, and can be dynamically loaded and called to implement specific business functions or services. It has clear interfaces and functional definitions and can be independently called and managed.

[0055] Afterwards, the parsing engine 121 can send interface layout tasks and multiple data acquisition tasks to the execution engine 122.

[0056] After receiving multiple data acquisition tasks, execution engine 122 can invoke the atomic capabilities corresponding to each data acquisition task to execute the tasks and obtain multiple business data. Similarly, after receiving a UI layout task, it can first determine the node acquisition tasks from the layout task, and then invoke the atomic capabilities corresponding to each node acquisition task to execute these tasks and obtain multiple node information.

[0057] For example, the task processing system may or may not include a configuration module. If the task processing system includes a configuration module, the configuration module can be used to configure the correspondence between interface layout tasks and interface layout templates. Therefore, the configuration module may include the interface layout template corresponding to the interface layout task. Based on this, after receiving the interface layout task, the execution engine 122 can also request the interface layout template corresponding to the interface layout task from the configuration module. In addition, the configuration module may also include multiple node information. Besides calling the atomic capabilities corresponding to multiple node acquisition tasks to execute multiple node acquisition tasks and obtain multiple node information, the execution engine 122 can also obtain multiple node information from the configuration module, which is not limited here. After obtaining the business data and node information, the execution engine 122 can send the interface layout template, multiple business data, and multiple node information to the generation engine 123. Among them, the interface layout template and multiple node information can be collectively referred to as the aggregated UI.

[0058] If the task processing system does not include a configuration module, the execution engine 122 can send multiple business data, multiple node information, and description information of the interface layout task to the generation engine 123. The multiple node information and the description information of the interface layout task can be collectively referred to as the aggregated UI.

[0059] After receiving the UI layout task (including its description and corresponding template), multiple business data points, and multiple node information, the generation engine can invoke the generative framework 14 to render the data and node information based on the task, obtaining and displaying generative information. This generative information can be obtained by integrating multiple execution results. The generative information can be displayed within the generative application. Users can interact with the generative application.

[0060] For example, the generative framework 14 can first render multiple node information according to the interface layout task to generate initial generative information, and then update the initial generative information using multiple business data based on the correspondence between multiple business data and multiple node information to obtain and display the generative information. Alternatively, the generative framework 14 can also directly render multiple node information and the multiple business data corresponding to each node information according to the interface layout task to obtain and display the generative information. The generative information may include interactive controls. Users can implement interface navigation functions by clicking on the interactive controls.

[0061] Furthermore, the execution engine 122 also possesses the ability to diagnose exceptions such as task timeouts and task execution failures. These tasks can include node retrieval tasks and data retrieval tasks. Specifically, if a task is not completed within the specified time, its execution status can be recorded and timeout exception information can be reported. If a task fails during execution, its execution status and error information can be recorded, and the task can be re-executed with a status update.

[0062] In the task processing system of this application embodiment, since the application's capabilities have been broken down into multiple atomic capabilities, multiple atomic tasks are obtained by parsing the task description information, and the atomic capabilities corresponding to each atomic task are called to execute these atomic tasks, resulting in multiple execution results. That is, task instructions can be executed by calling the corresponding atomic capabilities of the application, rather than calling the entire application. Thus, through this application embodiment, developers can focus on expanding atomic capabilities without investing excessive time and effort in the application's interface, interaction methods, etc., thereby reducing the cost of application development and iterative updates.

[0063] The task processing method provided in the embodiments of this application is described below.

[0064] Figure 2 A flowchart illustrating a task processing method provided in an embodiment of this application is shown. This task processing method can be executed by an information aggregation system. Figure 2 As shown, the task processing method provided in this application includes the following steps:

[0065] S210. Parse the task description information to obtain multiple atomic tasks;

[0066] S220: Call the atomic capabilities corresponding to multiple atomic tasks to execute multiple atomic tasks and obtain multiple execution results. Atomic capabilities are capabilities obtained by decomposing the capabilities of an application.

[0067] In the task processing method of this application embodiment, since the application's capabilities have been broken down into multiple atomic capabilities, multiple atomic tasks are obtained by parsing the task description information, and the atomic capabilities corresponding to each atomic task are called to execute the multiple atomic tasks, resulting in multiple execution results. That is, task instructions can be executed by calling the atomic capabilities corresponding to the application, rather than calling the entire application. Thus, through this application embodiment, developers can focus on expanding atomic capabilities without investing too much time and effort in the application's interface, interaction methods, etc., thereby reducing the cost of application development and iterative updates.

[0068] The specific implementation methods for each of the above steps are described below.

[0069] In some embodiments, in S210, the task description information can be descriptive information obtained by describing the task instructions. The task instructions can include user instructions and system instructions. User instructions can be used to interact with applications. The input form of user instructions can include voice input, text input, touch input, and gesture input, etc., and is not limited thereto. User instructions can be, for example, "find movies currently showing in theaters" or "recommend nearby restaurants." If the terminal receiving the user instruction has three video apps installed, and the user instruction is "find movies currently showing in theaters," then after receiving the user instruction, the terminal can search for movies currently showing in theaters from each of the three video apps.

[0070] Task description information can include instruction scenario information corresponding to the task command, interface task description information, and data task description information. There can be a correspondence between these three types of information. Instruction scenario information represents the application scenario of the task command. Examples of instruction scenario information include navigation, food recommendation, and movie recommendation scenarios.

[0071] As an example, the instruction scenario information corresponding to the task description information can be one or more, without limitation. For instance, if the user instruction is "Find a movie currently showing in a cinema and navigate to location A", then the task description information can include instruction scenario information corresponding to the movie search scenario and instruction scenario information corresponding to the navigation scenario.

[0072] Additionally, data task description information can be used to describe data acquisition tasks. Data acquisition tasks can be used to acquire business data. Interface task description information can be used to describe interface layout tasks. Interface layout tasks can include node acquisition tasks. Node acquisition tasks can be used to acquire node information displayed in the interface. Node information can include, for example, files, icons, images, controls, etc. Furthermore, interface layout tasks can be used to arrange the display methods of node information and business data, and to establish the correspondence between node information and business data. Both data acquisition tasks and node acquisition tasks can be atomic tasks.

[0073] Thus, by parsing the task description information, multiple atomic tasks, including data acquisition tasks and node acquisition tasks, can be obtained.

[0074] As mentioned above, the task description information may include interface task description information and data task description information. Therefore, to ensure the accuracy of multiple atomic tasks, in some embodiments, the above-mentioned S210 may specifically include:

[0075] The interface task description information is parsed to obtain the interface layout task, which includes multiple node acquisition tasks.

[0076] The data task description information is parsed to obtain multiple data acquisition tasks.

[0077] Explanations of the interface layout task, node acquisition task, and data acquisition task can be found in the relevant descriptions above, and will not be repeated here. Furthermore, since there can be a correspondence between the interface task description information and the data task description information, there can also be a correspondence between multiple node acquisition tasks and multiple data acquisition tasks.

[0078] By parsing the interface task description information and the data task description information separately, the accuracy of multiple atomic tasks can be guaranteed.

[0079] Furthermore, the task description information can also describe the dependencies between multiple atomic tasks. If multiple atomic tasks include task A, task B, and task C, where the input of task B depends on the output of task A, the input of task C depends on the output of task B, or the outputs of tasks A and B are both inputs of task C, then a dependency relationship exists between tasks A, B, and C.

[0080] If the task description information describes the dependencies between multiple atomic tasks, then by parsing the task description information, the multiple atomic tasks and the dependencies between them can be obtained.

[0081] In some embodiments, in S220, the atomic task can be executed by the corresponding atomic capability of the application. An atomic capability can be a capability obtained by minimizing and decomposing the application's capabilities. For example, if the application's capability includes querying noodles near address A, then multiple atomic capabilities obtained by minimizing and decomposing the application's capabilities can include querying address A, querying food near address A, filtering noodles from the queried food, and displaying the filtered noodle list, etc. Furthermore, there can be a one-to-one correspondence between atomic tasks and atomic capabilities. An atomic task can be an atomic task determined by an artificial intelligence model based on the application's existing atomic capabilities.

[0082] When an atomic task retrieves a task for a node, the node information can include its storage location, links, and other details. The node can be retrieved using its storage location, links, and other information. Each time the execution engine retrieves node information, it adds it to the resource cache for later use.

[0083] Furthermore, an execution result can be obtained by executing a single atomic task, or it can be determined jointly by multiple atomic tasks. If multiple atomic tasks have dependencies on each other, then multiple atomic tasks can collectively correspond to a single execution result.

[0084] As an example, if multiple data processing atomic tasks include task A, task B, and task C, where the outputs of task A and task B are both inputs of task C, then the sub-execution results corresponding to task A, task B, and task C can all correspond to a single execution result.

[0085] Therefore, in order to ensure the smooth execution of multiple atomic tasks and the accuracy of multiple execution results, in some embodiments, the above-mentioned S220 may specifically include:

[0086] The execution order of multiple atomic tasks is determined based on dependencies;

[0087] Add multiple atomic tasks to multiple task execution queues in the order of execution;

[0088] Multiple atomic tasks are executed by calling the atomic capabilities corresponding to each atomic task in the execution queue, resulting in multiple execution results.

[0089] Here, if there is a dependency between two atomic tasks, then there can be a definite execution order between them. If there is no dependency between two atomic tasks, then there is no restriction on their execution order. Furthermore, if two atomic tasks have a defined execution order, then they can be added to the same task execution queue according to that order. Each execution queue can correspond to one execution result.

[0090] As an example, if multiple atomic tasks include tasks A, B, C, D, E, and F, where the output of task A is the input of task B, the output of task B is the input of task C, the output of task C is the input of task D, and the output of task E is the input of task F, then the execution order among tasks A, B, C, and D can be [task A, task B, task C, task D], and the execution order among tasks E and F can be [task E, task F]. Here, [task A, task B, task C, task D] can be one task execution queue, and [task E, task F] can be another task execution queue.

[0091] As an example, if multiple atomic tasks include data acquisition tasks corresponding to video software A, video software B, and video software C respectively, then these multiple atomic tasks can correspond to at least three task execution queues. That is, the data acquisition task corresponding to each video software can correspond to at least one task execution queue.

[0092] After determining multiple task execution queues, the execution engine can invoke the task processing engine to execute atomic tasks within those queues. Within the same task execution queue, multiple atomic tasks can have a defined execution order. The execution order between different task execution queues is not restricted.

[0093] As a more concrete example, for each task execution queue, the task processing engine can invoke the atomic capabilities corresponding to multiple atomic tasks according to the execution order in the task execution queue, and execute the atomic tasks to obtain the execution result corresponding to multiple atomic tasks. The execution result can be data obtained by the task processing engine. After the execution engine obtains the data by invoking the task processing engine, it can perform simple calculations or data transformations on the obtained data to obtain business data, which is then added to the data cache for later use. For example, if the execution result is data such as the latitude and longitude information of food-related businesses, their contact information, the name of the food, and its price, then by filtering the execution result, the obtained business data can include the name and price of the food. In addition, the execution engine can also convert the execution result according to a preset data format to obtain business data.

[0094] In this way, by determining the execution order of multiple atomic tasks based on their dependencies, and by executing multiple atomic tasks according to their execution order, we can ensure the smooth execution of multiple atomic tasks and the accuracy of multiple execution results.

[0095] Furthermore, as mentioned above, multiple atomic tasks can include multiple data acquisition tasks and multiple node acquisition tasks. Therefore, multiple execution results can include business data corresponding to data acquisition tasks and node information corresponding to node acquisition tasks.

[0096] Therefore, in order to ensure the presentation and usability of multiple execution results and improve the user's visual experience, in some embodiments, after obtaining multiple execution results, the method may further include:

[0097] Establish the correspondence between business data and node information;

[0098] The generative framework is invoked, and based on the correspondence between business data and node information, multiple business data and multiple node information are rendered according to the interface layout task to obtain and display generative information.

[0099] Here, since there is a correspondence between data acquisition tasks and node acquisition tasks, a correspondence between business data and node information can be established based on this correspondence. Additionally, generative information can be information obtained by integrating multiple execution results. Generative information can include images, data, interactive controls, and other information displayed on the interface.

[0100] Additionally, generative information can be displayed within a generative application. This application can be a blank application, a self-developed application with UI generation capabilities, or a third-party application; there are no specific limitations. Users can interact with the generative application. When the node is an interactive control, the generative information can also include information corresponding to the interactive events bound to the interactive control. These interactive events can describe the interface transitions when the user clicks on an interactive control.

[0101] For example, the generation engine can invoke a generative framework to generate and display generative information. Specifically, the generative framework can first render multiple node information according to the interface layout task to generate initial generative information, and then update the initial generative information using multiple business data based on the correspondence between business data and node information to obtain and display the generative information. Alternatively, the generative framework can also directly render multiple node information and the multiple business data corresponding to each node information according to the interface layout task to obtain and display generative information.

[0102] In this way, by calling the generative framework, based on the correspondence between business data and node information, multiple business data and multiple node information are rendered according to the interface layout task to obtain and display generative information, which can ensure the presentation and usage effects of multiple execution results and improve the user's visual experience.

[0103] To better describe the overall solution, some specific examples are given based on the above embodiments.

[0104] For example, the parsing engine can receive task description information corresponding to user commands. After receiving the task description information, the parsing engine can parse it to obtain at least one command scenario, as well as interface task description information and data task description information corresponding to each command scenario. The data task description information can be used to describe data acquisition tasks. Data acquisition tasks can be used to acquire business data. The interface task description information can be used to describe interface layout tasks. Interface layout tasks can include node acquisition tasks. Node acquisition tasks can be used to acquire node information displayed on the interface. Interface layout tasks can be used to layout the display methods of node information and business data.

[0105] The execution engine can execute node acquisition tasks and data acquisition tasks separately, adding the execution results of node acquisition tasks (i.e., node information) to the resource cache and the execution results of data acquisition tasks (i.e., business data) to the data cache. For each instruction scenario, after all tasks corresponding to the instruction scenario have been completed, the interface layout task, multiple node information, and multiple business data can be sent to the generation engine. The generation engine can call the generative framework to generate generative information corresponding to the task description information. Generative information can include multiple views. If the display form of the generative information is a generative interface corresponding to the user instruction "Find movies currently showing in cinemas", then the multiple views can include views corresponding to video software A, video software B, and video software C respectively.

[0106] Therefore, the information aggregation system can complete the construction of functional scenarios. By receiving DSLs sent by the interaction module, it dynamically constructs interface layout tasks including multiple node acquisition tasks, multiple data acquisition tasks corresponding to the interface layout tasks, and creates interfaces and interactions that meet user needs based on the interface layout tasks and their corresponding multiple data acquisition tasks. The above method can be produced and implemented on the terminal side in a pipeline manner, saving product and R&D investment. Specifically, the embodiments of this application are based on consistent capabilities and standard protocols. Scenarios constructed according to product rules can be quickly presented through the information aggregation framework, allowing R&D to focus only on enriching interface elements and expanding atomic capabilities, without having to invest too much time and energy in the application's interface, interaction methods, etc., thereby reducing the cost of application development and iterative updates.

[0107] Based on the task processing method provided in the above embodiments, this application also provides specific implementations of the task processing apparatus. Please refer to the following embodiments.

[0108] like Figure 3As shown, the task processing device 300 provided in this application embodiment includes the following modules:

[0109] The parsing module 310 is used to parse the task description information to obtain multiple atomic tasks;

[0110] The execution module 320 is used to call the atomic capabilities corresponding to multiple atomic tasks to execute multiple atomic tasks and obtain multiple execution results. Atomic capabilities are capabilities obtained by decomposing the capabilities of the application.

[0111] The task processing device 300 described above will be described in detail below:

[0112] In some embodiments, the parsing module 310 may specifically include:

[0113] The first parsing submodule is used to parse the task description information to obtain multiple atomic tasks and the dependencies between them.

[0114] In some embodiments, the execution module 320 may specifically include:

[0115] The determination submodule is used to determine the execution order of multiple atomic tasks based on dependencies;

[0116] Add a submodule to add multiple atomic tasks to multiple task execution queues in the order of execution;

[0117] The first execution submodule is used to call the atomic capabilities corresponding to multiple atomic tasks to execute multiple atomic tasks in multiple task execution queues and obtain multiple execution results.

[0118] In some embodiments, the task description information includes interface task description information and its corresponding data task description information, and the multiple atomic tasks include multiple node acquisition tasks and multiple data acquisition tasks. Based on this, the parsing module 310 may specifically include:

[0119] The second parsing submodule is used to parse the interface task description information to obtain the interface layout task, which includes multiple node acquisition tasks.

[0120] The third parsing submodule is used to parse the data task description information to obtain multiple data acquisition tasks.

[0121] In some embodiments, the multiple execution results include business data corresponding to the data acquisition task and node information corresponding to the node acquisition task. Based on this, the task processing device 300 may further include:

[0122] The module is used to establish the correspondence between business data and node information after obtaining multiple execution results;

[0123] The rendering module is used to call the generative framework, and based on the correspondence between business data and node information, renders multiple business data and multiple node information according to the interface layout task to obtain and display generative information.

[0124] In the task processing apparatus of this application embodiment, since the application's capabilities have been broken down into multiple atomic capabilities, multiple atomic tasks are obtained by parsing the task description information, and the atomic capabilities corresponding to each atomic task are called to execute these atomic tasks, resulting in multiple execution results. That is, task instructions can be executed by calling the atomic capabilities corresponding to the application, rather than calling the entire application. Thus, through this application embodiment, developers can focus on expanding atomic capabilities without investing excessive time and effort in the application's interface, interaction methods, etc., thereby reducing the cost of application development and iterative updates.

[0125] Based on the task processing method provided in the above embodiments, this application also provides specific implementation methods for electronic devices. Figure 4 A schematic diagram of an electronic device 400 provided in an embodiment of this application is shown.

[0126] Electronic device 400 may include processor 410 and memory 420 storing computer program instructions.

[0127] Specifically, the processor 410 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0128] Memory 420 may include mass storage for data or instructions. For example, and not limitingly, memory 420 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where suitable, memory 420 may include removable or non-removable (or fixed) media. Where suitable, memory 420 may be internal or external to electronic device 400. In a particular embodiment, memory 420 is a non-volatile solid-state memory.

[0129] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to the first aspect of this application.

[0130] The processor 410 implements any of the task processing methods described in the above embodiments by reading and executing computer program instructions stored in the memory 420.

[0131] In one example, the electronic device 400 may also include a communication interface 430 and a bus 440. For example, Figure 4 As shown, the processor 410, memory 420, and communication interface 430 are connected through bus 440 and complete communication with each other.

[0132] The communication interface 430 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0133] Bus 440 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 440 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0134] For example, the electronic device 400 can be a mobile phone, tablet computer, laptop computer, handheld computer, in-vehicle electronic device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc.

[0135] The electronic device can execute the task processing method described in the embodiments of this application, thereby achieving a combination Figures 2 to 3 The described task processing methods and apparatus.

[0136] Furthermore, in conjunction with the task processing methods in the above embodiments, this application embodiment can provide a computer-readable storage medium for implementation. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the task processing methods in the above embodiments.

[0137] In addition, this application embodiment also provides a vehicle, which may include at least one of the following:

[0138] The task processing apparatus as described in any embodiment of the second aspect;

[0139] The electronic device as described in any embodiment of the third aspect;

[0140] Computer-readable storage media as described in any embodiment of the fourth aspect. Further details will not be provided here.

[0141] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0142] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0143] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0144] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0145] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A task processing method characterized by, The method comprises the steps of: parsing task description information to obtain a plurality of atomic tasks; calling atomic capabilities corresponding to the plurality of atomic tasks to execute the plurality of atomic tasks, and obtaining a plurality of execution results, wherein the atomic capabilities are capabilities obtained by decomposing the capabilities of an application.

2. The method of claim 1, wherein, The method comprises the steps of: parsing the task description information to obtain the plurality of atomic tasks and a dependency relationship between the plurality of atomic tasks.

3. The method of claim 2, wherein, The method comprises the steps of: determining an execution order of the plurality of atomic tasks according to the dependency relationship; adding the plurality of atomic tasks to a plurality of task execution queues according to the execution order; calling atomic capabilities corresponding to the plurality of atomic tasks to execute the plurality of atomic tasks in the plurality of task execution queues, and obtaining a plurality of execution results.

4. The method of claim 1, wherein, The task description information comprises interface task description information and corresponding data task description information, the plurality of atomic tasks comprises a plurality of node acquisition tasks and a plurality of data acquisition tasks, and the parsing of the task description information to obtain the plurality of atomic tasks comprises the steps of: parsing the interface task description information to obtain an interface layout task, wherein the interface layout task comprises the plurality of node acquisition tasks; parsing the data task description information to obtain the plurality of data acquisition tasks.

5. The method of claim 4, wherein, The plurality of execution results comprises business data corresponding to the data acquisition tasks and node information corresponding to the node acquisition tasks, and after the plurality of execution results are obtained, the method further comprises the steps of: establishing a corresponding relationship between the business data and the node information; calling a generative framework to render a plurality of the business data and a plurality of the node information according to the interface layout task based on the corresponding relationship between the business data and the node information, and obtaining and displaying generative information.

6. A task processing apparatus characterized by comprising: The device comprises: a parsing module configured to parse task description information to obtain a plurality of atomic tasks; an execution module configured to call atomic capabilities corresponding to the plurality of atomic tasks to execute the plurality of atomic tasks, and obtain a plurality of execution results, wherein the atomic capabilities are capabilities obtained by decomposing the capabilities of an application.

7. An information aggregation system characterized by, The device comprises: a parsing engine configured to receive task description information, parse the task description information to obtain an interface layout task and a plurality of data acquisition tasks, and wherein the interface layout task comprises a plurality of node acquisition tasks corresponding to the plurality of data acquisition tasks; an execution engine configured to receive the interface layout task and the plurality of data acquisition tasks sent by the parsing engine, call atomic capabilities corresponding to the plurality of data acquisition tasks to execute the plurality of data acquisition tasks, obtain a plurality of business data, call atomic capabilities corresponding to the plurality of node acquisition tasks to execute the plurality of node acquisition tasks, and obtain a plurality of node information, wherein the atomic capabilities are capabilities obtained by decomposing the capabilities of an application. A generation engine is configured to receive the interface layout task, the plurality of business data and the plurality of node information sent by the execution engine, and invoke a generative framework to render the plurality of business data and the plurality of node information according to the interface layout task to obtain and display generative information.

8. An electronic device, comprising: The electronic device comprises a processor and a memory storing computer program instructions; The processor executes the computer program instructions to implement the task processing method of any one of claims 1-5.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer program instructions, and the computer program instructions are executed by the processor to implement the task processing method of any one of claims 1-5.

10. A vehicle characterized by comprising: The task processing apparatus comprises at least one of the following: The task processing apparatus according to claim 6; The information aggregation system according to claim 7; The electronic device according to claim 8; The computer readable storage medium according to claim 9.

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