Data processing method and device, electronic equipment and storage medium

Abstract

The invention discloses a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring first information; the first information is used for indicating a target application program to execute a target task, the first information is obtained by inputting a target interface output by a target object in the running process of the target application program, and the target interface comprises at least one task description; and in response to the first information, generating a target file based on a generative model, so that the target application program can execute the target task based on the target file.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data processing method, device, electronic device and storage medium. Background Art

[0002] In order to meet the diverse needs of users, applications usually need to include multiple functions to perform a variety of different tasks. However, these functions of the application will generate corresponding codes when they are built, resulting in a larger application size and occupying more storage space. This not only affects the download and installation speed of the application, but may also increase the storage pressure of the device and affect the user experience. Summary of the invention

[0003] In response to the above technical problems, the embodiments of the present application provide a data processing method, device, electronic device and storage medium.

[0004] The technical solution of the embodiment of the present application is implemented as follows:

[0005] In a first aspect, an embodiment of the present application provides a data processing method, including:

[0006] Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description;

[0007] In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

[0008] In some embodiments, in response to the first information, generating a target file based on a generative model includes:

[0009] In response to the first information, generating a task flow interface for the target application to execute the target task based on the generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0010] Execute the subtasks corresponding to the at least one task node in sequence based on the generative model;

[0011] When it is determined that the subtasks corresponding to the at least one task node have been executed by the generative model, the target file is generated based on the generative model; the target file is generated by the generative model based on the execution logic after all the subtasks corresponding to the at least one task node have been executed.

[0012] In some embodiments, in response to the first information, generating a target file based on a generative model includes:

[0013] In response to the first information, generating a task flow interface for the target application to execute the target task based on the generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0014] Generate a corresponding target file for the at least one task node based on the generative model; the target file is generated by the generative model based on the execution logic before the subtask corresponding to the at least one task node is executed;

[0015] The method further comprises:

[0016] The subtasks corresponding to the at least one task node are executed in sequence based on the target file corresponding to the at least one task node.

[0017] In some embodiments, generating a corresponding target file for the at least one task node based on the generative model includes:

[0018] Based on the generative model, a target file corresponding to the at least one task node is synchronously generated.

[0019] In some embodiments, generating a corresponding target file for the at least one task node based on the generative model includes:

[0020] Based on the generative model, target files corresponding to the at least one task node are generated one by one according to the execution order of the subtasks corresponding to the at least one task node; the target file corresponding to any remaining target task node among the at least one task node except the first task node is generated based on the execution result of the previous task node of the target task node.

[0021] In some embodiments, the data processing method further includes:

[0022] Obtaining second information; the second information includes operating environment information of the target application;

[0023] If it is determined based on the second information that the target application is running in the first environment, generating a first file based on the generative model so that the target application can perform the target task in the first environment based on the first file;

[0024] If it is determined based on the second information that the target application is running in the second environment, generating a second file based on the generative model so that the target application can perform the target task in the second environment based on the second file;

[0025] The first environment is different from the second environment.

[0026] In some embodiments, the data processing method further includes:

[0027] When it is determined that an abnormality occurs when the target application program executes the target task based on the target file, third information is obtained; the third information is obtained by inputting an abnormal interaction interface output by the target object in the process of the target application program executing the target task, and the abnormal interaction interface is generated by the generative model;

[0028] In response to the third information, the target file is adjusted based on the generative model.

[0029] In a second aspect, an embodiment of the present application provides a data processing device, including:

[0030] an acquisition module, configured to acquire first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0031] A response module is used to generate a target file based on a generative model in response to the first information, so that the target application can perform the target task based on the target file.

[0032] In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory is used to store executable data instructions; when the processor is used to execute the executable data instructions stored in the memory, the following steps are implemented:

[0033] Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description;

[0034] In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the following steps are implemented:

[0036] Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description;

[0037] In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, a brief introduction will be given below to the drawings required for use in the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 One of the flowcharts of a data processing method provided in an embodiment of the present application;

[0040] Figure 2 A second flowchart of a data processing method provided in an embodiment of the present application;

[0041] Figure 3 A third flowchart of a data processing method provided in an embodiment of the present application;

[0042] Figure 4 A fourth flowchart of a data processing method provided in an embodiment of the present application;

[0043] Figure 5 A fifth flow chart of a data processing method provided in an embodiment of the present application;

[0044] Figure 6 A sixth flow chart of a data processing method provided in an embodiment of the present application;

[0045] Figure 7 A seventh flowchart of a data processing method provided in an embodiment of the present application;

[0046] Figure 8 A schematic diagram of a software hierarchy structure provided for an embodiment of the present application;

[0047] Fig. 9A schematic diagram of the interaction process between a user, a micro-application construction environment, a micro-application, and an artificial intelligence model provided in an embodiment of the present application;

[0048] Fig.10 A schematic diagram of a micro-application interface for constructing a specific function provided in an embodiment of the present application;

[0049] Fig.11 A schematic diagram of a micro-application interface including a task description provided in an embodiment of the present application;

[0050] Fig.12 One of the schematic diagrams of an interface for performing a specific task "calculating average score" provided in an embodiment of the present application;

[0051] Fig.13 A second schematic diagram of an interface for performing a specific task "calculating average score" provided in an embodiment of the present application;

[0052] Fig.14 A third schematic diagram of an interface for performing a specific task "calculating average score" provided in an embodiment of the present application;

[0053] Fig.15 A fourth schematic diagram of an interface for performing a specific task "calculating average score" provided in an embodiment of the present application;

[0054] Fig.16 A fifth schematic diagram of an interface for performing a specific task "calculating average score" provided in an embodiment of the present application;

[0055] Fig.17 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application;

[0056] Fig.18 A schematic diagram of the physical structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the embodiments of the present application.

[0058] It should be noted that in the description of the embodiments of the present application, the terms "first", "second", etc. are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0059] In order to facilitate a clearer understanding of the embodiments of the present application, some relevant technical knowledge is first introduced as follows.

[0060] At present, many platforms have used artificial intelligence (AI) big models to achieve codeless or low-code rapid application construction. However, after the application code is generated, its logic and functions are usually fixed, that is, the output is determined. This means that if the input does not meet the expectations or format requirements of the application, the correct output may not be obtained. Moreover, even on codeless or low-code platforms, users still need to perform a certain degree of design, such as selecting components, setting properties, and configuring logic. These design processes may be difficult for users without programming experience. In addition, user needs are often accidental, that is, they may only need to complete a specific task at a specific moment; user needs may also be short-lived, that is, they may only need to use a specific function within a certain period of time. Therefore, how to dynamically build applications based on the different needs of different users at different times, so that the application can easily cope with changing user needs and new execution tasks to improve user experience, and reduce the size of the application, reduce the occupation of memory and storage resources, has become an important research direction in the current application development field.

[0061] The embodiments of the present application provide a data processing method, device, electronic device and storage medium, which only provide a task execution entry by designing a target application. The main function of the target application is to receive the user's task selection, and then dynamically generate the file required to execute the task based on the user's task selection using a generative model. The file contains the logic and data required to execute the specific task, and the target application itself does not need to predefine the execution logic and data for each possible task. The code base can be more streamlined, which helps to reduce the size of the target application and reduce the use of memory and storage resources. It can also enable the target application to easily respond to changing user needs and new execution tasks, thereby improving user experience.

[0062] The following is an illustrative introduction to the data processing method, device, electronic device and storage medium provided in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application.

[0063] Figure 1 One of the flow charts of a data processing method provided in an embodiment of the present application is as follows: Figure 1 As shown, the method includes:

[0064] S101. Obtain first information; the first information is used to instruct a target application to execute a target task, and the first information is obtained by inputting a target interface output by a target object during operation of the target application, and the target interface includes at least one task description.

[0065] It should be noted that the target application can be an application or software that can be run on a specific device (such as a computer, a mobile phone, etc.). The target application can output one or more interfaces during operation. The user can input information in any of these target interfaces to interact with the target application.

[0066] It should be noted that the target interface includes at least one task description, which may be presented in the form of text, icons or buttons, etc., to inform the user which tasks the target application can perform.

[0067] It should be noted that the target object refers to a user or system that interacts with the target application. In the embodiment of the present application, the target object can interact with the target interface output by the target application during operation in some way (such as clicking, inputting, etc.).

[0068] It should be noted that the first information is obtained by the target object inputting the target interface output by the target application during operation. Such input may include clicking a button, selecting an option, or entering specific text. The main function of the first information is to instruct the target application to perform a specific task (i.e., the target task in the embodiment of the present application).

[0069] In the embodiment of the present application, the target object can interact with the target interface output by the target application during operation. The target object inputs the first information to instruct the target application to execute a specific target task according to the task description in the target interface.

[0070] S102: In response to the first information, generate a target file based on a generative model, so that the target application can execute the target task based on the target file.

[0071] It should be noted that a generative model is an AI model. Generative models learn the characteristics and patterns of input information by training large amounts of diverse data. It usually has model parameters ranging from hundreds of millions to hundreds of billions (model parameters are variables that control the behavior of the target model), and can capture complex relationships and patterns in the input information. In an embodiment of the present application, a generative model can be used to generate a specific file based on instructions from a user or system, which may contain all the information or instructions (code snippets) required for the target application to perform a specific task. And the file can be a configuration file, script, data set, or any other form of file, depending on the requirements of a specific task. This requirement may be at the code level (such as a function or class that implements a specific function) or at a non-code level (such as a configuration file, data input, etc.).

[0072] In an embodiment of the present application, after obtaining the first information, the first information can be processed (including parsing, extracting key information, etc.) in response to the first information, and then the processed first information is passed as input to the generative model, so that the generative model can generate a target file related to the target task based on the input information. After the target file is generated based on the generative model, the target file can be output to a location accessible to the target application, so that the target application can then read and parse the target file to perform the target task based on the information in the target file.

[0073] It can be understood that the data processing method provided in the embodiment of the present application first obtains first information for instructing the target application to execute the target task, and the first information is obtained by the target object inputting the target interface output by the target application during operation, and then generates a target file based on the generative model in response to the first information, so that the target application can execute the target task based on the target file. In this way, the target application only provides a task execution entry, and its main function is to receive the user's task selection, and then dynamically generates the target file required to execute the target task based on the user's task selection using the generative model. The target file contains the information or instructions required to execute the target task, and the target application itself does not need to predefine the information or instructions required for execution for each possible task. Then, its code base can be more streamlined, which helps to reduce the size of the target application and reduce the occupancy of memory and storage resources. The progressive application generation method can also enable the target application to easily respond to changing user needs and new execution tasks, thereby improving user experience.

[0074] In some embodiments, in response to the first information, generating a target file based on a generative model includes:

[0075] In response to the first information, generating a task flow interface for the target application to execute the target task based on the generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0076] Execute the subtasks corresponding to the at least one task node in sequence based on the generative model;

[0077] When it is determined that the subtasks corresponding to the at least one task node have been executed by the generative model, the target file is generated based on the generative model; the target file is generated by the generative model based on the execution logic after all the subtasks corresponding to the at least one task node have been executed.

[0078] It should be noted that the task flow interface generated by the generative model is a visual interface that can display a series of steps or task nodes required by the target application to perform the target task. Each task node represents a specific subtask that the target application needs to complete when performing the target task. These subtasks are necessary to complete the target task. There are dependencies between task nodes, that is, some subtasks can only be executed after other subtasks are completed.

[0079] It should be noted that after the subtasks corresponding to at least one task node are executed by the generative model, the execution logic after all the subtasks corresponding to the at least one task node are executed can be obtained. The execution logic may refer to the rules, sequence, and execution dependencies followed by the subtasks corresponding to the at least one task node during the execution of the generative model.

[0080] In an embodiment of the present application, after obtaining the first information, the first information can be processed (including parsing, extracting key information, etc.) in response to the first information, and then the processed first information is passed as input to the generative model, so that the generative model can generate a task flow interface for the target application to execute the target task based on the input information, and then execute the subtasks corresponding to at least one task node in the task flow interface in sequence based on the generative model. Then, when it is determined that the subtask corresponding to at least one task node has been executed by the generative model, the target file is generated using the generative model based on the execution logic after all the subtasks corresponding to at least one task node have been executed.

[0081] For example, Figure 2 A second flow chart of a data processing method provided in an embodiment of the present application is as follows: Figure 2 As shown, the method includes:

[0082] S201, obtaining first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0083] S202: In response to the first information, generating a task flow interface for the target application to execute the target task based on a generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0084] S203, sequentially executing subtasks corresponding to the at least one task node based on the generative model;

[0085] S204. When it is determined that the subtasks corresponding to the at least one task node have been executed by the generative model, a target file is generated based on the generative model so that the target application can execute the target task based on the target file; the target file is generated by the generative model based on the execution logic after all the subtasks corresponding to the at least one task node have been executed.

[0086] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0087] It can be understood that the embodiment of the present application first generates a task flow interface for the target application to execute the target task based on the generative model, and then executes the subtasks corresponding to at least one task node in the task flow interface in sequence based on the generative model. Then, when it is determined that the subtask corresponding to at least one task node has been completed by the generative model, based on the execution logic after all the subtasks corresponding to at least one task node have been executed, the generative model is used to generate the target file. The whole process realizes the dynamic and automatic generation of the target file required for the target application to execute the target task by the generative model, without the need for human intervention, which greatly reduces the workload of manual design and coding.

[0088] In some embodiments, in response to the first information, generating a target file based on a generative model includes:

[0089] In response to the first information, generating a task flow interface for the target application to execute the target task based on the generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0090] Generate a corresponding target file for the at least one task node based on the generative model; the target file is generated by the generative model based on the execution logic before the subtask corresponding to the at least one task node is executed;

[0091] The data processing method further includes:

[0092] The subtasks corresponding to the at least one task node are executed in sequence based on the target file corresponding to the at least one task node.

[0093] It should be noted that the execution logic before the subtask corresponding to at least one task node is executed focuses on the logic of the subtask corresponding to each task node, which is different from the execution logic after the subtask corresponding to at least one task node is executed. The execution logic after the subtask corresponding to at least one task node is executed includes not only the logic of each subtask itself, but also the dependency relationship of the execution logic between the subtasks.

[0094] In an embodiment of the present application, after obtaining the first information, the first information can be processed (including parsing, extracting key information, etc.) in response to the first information, and then the processed first information is passed as input to the generative model, so that the generative model can generate a task flow interface for the target application to execute the target task based on the input information, and then generate a corresponding target file for at least one task node in the task flow interface based on the generative model, and finally, based on the target file corresponding to the at least one task node, the subtask corresponding to the at least one task node can be executed in sequence to complete the execution of the target task.

[0095] For example, Figure 3 A third flow chart of a data processing method provided in an embodiment of the present application is as follows: Figure 3 As shown, the method includes:

[0096] S301, obtaining first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0097] S302: In response to the first information, generating a task flow interface for the target application to execute the target task based on a generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0098] S303, generating a corresponding target file for the at least one task node based on the generative model; the target file is generated by the generative model based on the execution logic before the subtask corresponding to the at least one task node is executed;

[0099] S304. Execute subtasks corresponding to the at least one task node in sequence based on the target file corresponding to the at least one task node.

[0100] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0101] It can be understood that the embodiment of the present application first generates a task flow interface for the target application to execute the target task based on the generative model, and then generates a corresponding target file for at least one task node in the task flow interface based on the generative model. Finally, based on the target file corresponding to the at least one task node, the subtask corresponding to the at least one task node can be executed in sequence to complete the execution of the target task. The entire process realizes the automatic generation of the target file required for the target application to execute the target task without manual intervention, which greatly reduces the workload of manual design and coding.

[0102] In some embodiments, generating a corresponding target file for the at least one task node based on the generative model includes:

[0103] Based on the generative model, a target file corresponding to the at least one task node is synchronously generated.

[0104] In the embodiment of the present application, after the generation target application performs the task flow interface of the target task, the generative model will synchronously generate the target file corresponding to at least one task node in the task flow interface. It is understandable that, in the case of synchronous generation, the generative model can not consider the dependency between the task nodes, it just starts to generate the target file corresponding to each task node immediately after receiving the generation instruction, and does not care about the execution order between these task nodes. It can be applicable to the scene where the dependency between each task node is not strong or there is no strict execution order requirement, so that the generation efficiency can be improved.

[0105] For example, Figure 4 A fourth flow chart of a data processing method provided in an embodiment of the present application is as follows: Figure 4 As shown, the method includes:

[0106] S401, obtaining first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0107] S402: In response to the first information, generating a task flow interface for the target application to execute the target task based on a generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0108] S403, based on the generative model, synchronously generate a target file corresponding to the at least one task node; the target file is generated by the generative model based on the execution logic before the subtask corresponding to the at least one task node is executed;

[0109] S404: Execute subtasks corresponding to the at least one task node in sequence based on the target file corresponding to the at least one task node.

[0110] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0111] It can be understood that the embodiment of the present application can improve the generation efficiency of the target file by synchronously generating the target file corresponding to at least one task node in the task flow interface based on the generative model.

[0112] In some embodiments, generating a corresponding target file for the at least one task node based on the generative model includes:

[0113] Based on the generative model, target files corresponding to the at least one task node are generated one by one according to the execution order of the subtasks corresponding to the at least one task node; the target file corresponding to any remaining target task node among the at least one task node except the first task node is generated based on the execution result of the previous task node of the target task node.

[0114] In the embodiment of the present application, after the generative model generates the task flow interface of the target application program to execute the target task, the target file corresponding to at least one task node will be generated one by one according to the execution order of the subtask corresponding to at least one task node in the task flow interface, and the target file corresponding to the latter task node in each task node is generated based on the execution result of the previous task node. It is understandable that in this way, the generative model will ensure that before the target file corresponding to a certain task node is generated, the target file corresponding to its predecessor task node has been generated, and then the target file corresponding to the task node is generated based on the execution result of the predecessor task node, which helps to avoid errors caused by lack of pre-requisites or resources during task execution. It can be applied to the scene where there is a strong dependency between each task node or it needs to be executed strictly according to the execution order, so that it can ensure that the task has all necessary conditions and resources during execution.

[0115] For example, Figure 5 A fifth flow chart of a data processing method provided in an embodiment of the present application is as follows: Figure 5 As shown, the method includes:

[0116] S501, obtaining first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0117] S502: In response to the first information, generating a task flow interface for the target application to execute the target task based on a generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0118] S503, based on the generative model, generating target files corresponding to the at least one task node one by one according to the execution order of the subtasks corresponding to the at least one task node; the target file corresponding to any target task node other than the first task node in the at least one task node is generated based on the execution result of the previous task node of the target task node;

[0119] S504: Execute subtasks corresponding to the at least one task node in sequence based on the target file corresponding to the at least one task node.

[0120] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0121] It can be understood that the embodiment of the present application generates the target file corresponding to at least one task node one by one according to the execution order of the subtasks corresponding to at least one task node in the task flow interface based on the generative model, thereby ensuring that the dependencies and sequence between the subtasks are correctly maintained.

[0122] In some embodiments, the data processing method further includes:

[0123] Obtaining second information; the second information includes operating environment information of the target application;

[0124] If it is determined based on the second information that the target application is running in the first environment, generating a first file based on the generative model so that the target application can perform the target task in the first environment based on the first file;

[0125] If it is determined based on the second information that the target application is running in the second environment, generating a second file based on the generative model so that the target application can perform the target task in the second environment based on the second file;

[0126] The first environment is different from the second environment.

[0127] It should be noted that the target application's operating environment information may include hardware environment information and software environment information. The hardware environment information includes processors, memory, and storage devices, etc. The software environment information includes the operating system, software dependencies, and other related configurations required for the target application to run.

[0128] It should be noted that the first environment is different from the second environment, which can be understood as the operating environment information corresponding to the first environment is different from the operating environment information corresponding to the second environment.

[0129] It should be noted that the decision to generate different files can be based on the operating environment (first environment or second environment) of the target application. If the target application is determined to be running in the first environment based on the second information, the first file is generated based on the generative model. The first file may contain configuration information, data format or other content specific to the first environment related to the first environment. If the target application is determined to be running in the second environment based on the second information, the second file is generated based on the generative model. The content of the second file will be different from the first file because it reflects the specific requirements and configuration of the second environment.

[0130] It should be noted that, although the first file and the second file are different, the target application can perform the same target task based on the first file and the second file. The target application can perform the target task in the first environment based on the first file, and the target application can also perform the target task in the second environment based on the second file.

[0131] For example, for a target application running on an X86 platform and a target application running on an ARM platform, the corresponding operating environments are different. Since the X86 platform and the ARM platform have significant differences in instruction set architecture, performance characteristics, software ecology, and hardware design, these differences make them different operating environments. This application can dynamically generate adaptive operating code for the same function based on the platform where the application runs.

[0132] For example, Figure 6 A sixth flow chart of a data processing method provided in an embodiment of the present application is as follows: Figure 6 As shown, the method includes:

[0133] S601, obtaining first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0134] S602, obtaining second information; the second information includes the operating environment information of the target application;

[0135] S603: if it is determined based on the second information that the target application is running in the first environment, in response to the first information, generate a first file based on the generative model so that the target application can perform the target task in the first environment based on the first file;

[0136] S604: If it is determined based on the second information that the target application is running in the second environment, in response to the first information, generate a second file based on the generative model so that the target application can execute the target task in the second environment based on the second file.

[0137] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0138] It can be understood that the embodiment of the present application generates different target files based on the operating environment of the target application, which can ensure that the generated files are adapted to the operating environment of the target application, thereby making it possible to run the target application in different environments to perform the same target task without having to build different target applications for different environments to perform the target task.

[0139] In some embodiments, the data processing method further includes:

[0140] When it is determined that an abnormality occurs when the target application program executes the target task based on the target file, third information is obtained; the third information is obtained by inputting an abnormal interaction interface output by the target object in the process of the target application program executing the target task, and the abnormal interaction interface is generated by the generative model;

[0141] In response to the third information, the target file is adjusted based on the generative model.

[0142] In an embodiment of the present application, when the target application performs the target task based on the target file, if an exception (such as an error, failure or an unexpected result) is detected, the exception handling process is triggered. The generative model will generate an abnormal interaction interface according to the current abnormal situation at this time. This interface may include error prompts, recommended operating steps, or information that requires user input, etc. After seeing this abnormal interaction interface, the target object (which may be a user or a system) will perform corresponding operations or inputs to provide additional information or instructions (i.e., third information). After obtaining the third information, the target file can be adjusted based on the generative model in response to the third information. This adjustment may be to modify the content, format or structure of the target file so that the target application can successfully perform the target task.

[0143] For example, Figure 7 A seventh flow chart of a data processing method provided in an embodiment of the present application is as follows: Figure 7 As shown, the method includes:

[0144] S701, obtaining first information; the first information is used to instruct a target application to execute a target task, the first information is obtained by inputting a target interface output by a target object during operation of the target application, the target interface including at least one task description;

[0145] S702: In response to the first information, generate a target file based on a generative model, so that the target application can perform the target task based on the target file;

[0146] S703, when it is determined that an exception occurs when the target application program executes the target task based on the target file, obtaining third information; the third information is obtained by inputting an abnormal interaction interface output by the target object in the process of the target application program executing the target task, and the abnormal interaction interface is generated by the generative model;

[0147] S704: In response to the third information, adjust the target file based on the generative model.

[0148] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0149] It can be understood that in the embodiment of the present application, when an exception occurs when the target application executes the target task based on the target file, the generative model can quickly generate a user-friendly exception interaction interface, providing clear error prompts and recommended operation steps. The user can perform corresponding operations or inputs according to these prompts and steps, thereby easily solving the problem of abnormal execution of the target task and improving the overall user experience.

[0150] It should be noted that, for the implementation of the data processing method provided in the embodiment of the present application, the application layer of the software hierarchy may include Application RunTime (runtime environment), Al Model Service (artificial intelligence model service), MicroApp Factory (micro application construction environment) and MicroApp (micro application), such as Figure 8 These components work together to dynamically build micro-applications (i.e., applications) based on the data processing method provided in the embodiment of the present application, so that the built applications can easily cope with changing user needs and new execution tasks, thereby improving user experience.

[0151] For example, Fig. 9 A schematic diagram of the interaction process between a user, a micro-application construction environment, a micro-application, and an artificial intelligence model provided in an embodiment of the present application. Fig. 9 As shown in the figure, the user runs the initial micro-application from the micro-application construction environment. After the micro-application is started, it interacts with the artificial intelligence model based on the pre-generated intention instructions or semantic instructions. The artificial intelligence model generates interactive code or, based on actual data, concretizes the instructions into regular software instructions and other intention instructions to solve uncertain content, and finally completes the function construction of the specific task specified by the user. Fig.10 As shown, Fig. 9 Schematic diagram of the micro-application interface constructed with specific functions corresponding to the interaction process shown. Fig.11 It is a schematic diagram of the micro-application interface that includes task descriptions. Figures 12 to 16 This is a schematic diagram of the interface where the micro-application performs the "calculate average score" task in sequence.

[0152] In some embodiments, if the user clicks Fig.11 If you click the "Run" button corresponding to "Calculate average score" in the micro-application interface shown in the figure, the application will call the artificial intelligence model (i.e., the generative model) to execute TranslateToCodeWithAI("Calculate average score"). The artificial intelligence model infers and generates Fig.12 The task flow interface shown in the figure includes the following task flow nodes: select score file->identify data format->parse data->identify score column->calculate average score, and generate execution code corresponding to each task flow node. Then the application starts to execute the subtasks corresponding to each task flow node in turn. If the previous step fails to generate the execution code corresponding to the subsequent task flow node in advance, for example, the execution code corresponding to the current task flow node "identify data format" is not generated, the artificial intelligence model will execute such as TranslateToCodeWithAI("identify data format") to generate the execution code corresponding to the current task flow node.

[0153] It should be noted that the difference between the embodiment of the present application and the artificial intelligence assistant copliot launched by Microsoft is that in the embodiment of the present application, the functions of the application are generated in real time based on the user's current input, rather than being pre-generated based on the requirements document, and the application and the artificial intelligence model are not independent of each other, but complement each other.

[0154] It is understandable that in the embodiment of the present application, the application only includes the UI interface of the basic functional unit. When the user needs to use a certain function, the operation of the function is triggered from the UI interface. At this time, the artificial intelligence model generates the corresponding function code and proceeds step by step according to the instructions. In other words, the artificial intelligence model interacts with the user through a generative UI interface, and dynamically infers user needs based on the data characteristics of the user input, and automatically completes the application function design. In addition, when the application is running, for abnormal situations or non-standard links (such as user input data does not meet expectations), the artificial intelligence model dynamically generates an abnormal interaction interface to interact with the user, and dynamically improves the application function design, that is, using the artificial intelligence model as a runtime service to dynamically build the application. In this way, the embodiment of the present application can at least bring the following beneficial effects:

[0155] 1. Users can add application functions in real time to realize customized applications;

[0156] 2. There is no need to generate the functional code of the entire application at one time. The corresponding code is generated and run based on the artificial intelligence model when the corresponding function is running. That is, the complexity of the application is customized according to the actual use of the user, and the size of the application is smaller than that of general applications;

[0157] 3. The functional design of the application is automatically completed by the artificial intelligence model, which greatly reduces the threshold for application design;

[0158] 4. Dynamically build and improve applications at runtime, making them infinitely fault-tolerant.

[0159] The data processing device provided in the embodiment of the present application is described below. The data processing device described below and the data processing method described above can be referenced to each other.

[0160] Fig.17 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application is shown in FIG. Fig.17 As shown, the device includes: an acquisition module 1710 and a response module 1720; wherein:

[0161] The obtaining module 1710 is used to obtain first information; the first information is used to instruct the target application to execute the target task, and the first information is obtained by the target object inputting a target interface output by the target application during operation, and the target interface includes at least one task description;

[0162] The response module 1720 is used to generate a target file based on a generative model in response to the first information, so that the target application can perform the target task based on the target file.

[0163] The data processing device provided by the embodiment of the present application first obtains first information for instructing the target application to execute the target task, and the first information is obtained by the target object inputting the target interface output by the target application during operation, and then generates a target file based on the generative model in response to the first information, so that the target application can execute the target task based on the target file. In this way, the target application only provides a task execution entry, and its main function is to receive the user's task selection, and then dynamically generates the target file required to execute the target task based on the user's task selection using the generative model. The target file contains the information or instructions required to execute the target task, and the target application itself does not need to predefine the information or instructions required for execution for each possible task. Then, its code base can be more streamlined, which helps to reduce the size of the target application and reduce the occupancy of memory and storage resources. The progressive application generation method can also enable the target application to easily respond to changing user needs and new execution tasks, thereby improving user experience.

[0164] In some embodiments, the response module 1720 includes:

[0165] A response unit, configured to generate, in response to the first information, a task flow interface for the target application to execute the target task based on the generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0166] An execution unit, configured to sequentially execute subtasks corresponding to the at least one task node based on the generative model;

[0167] The first generation unit is used to generate the target file based on the generative model when it is determined that the subtasks corresponding to the at least one task node have been executed by the generative model; the target file is generated by the generative model based on the execution logic after all the subtasks corresponding to the at least one task node have been executed.

[0168] In some embodiments, the response module 1720 includes:

[0169] A response unit, configured to generate, in response to the first information, a task flow interface for the target application to execute the target task based on the generative model; the task flow interface includes at least one task node required for the target application to execute the target task;

[0170] A second generating unit is used to generate a corresponding target file for the at least one task node based on the generative model; the target file is generated by the generative model based on the execution logic before the subtask corresponding to the at least one task node is executed;

[0171] The device also includes:

[0172] An execution module is used to sequentially execute subtasks corresponding to the at least one task node based on the target file corresponding to the at least one task node.

[0173] In some embodiments, the second generating unit is further configured to:

[0174] Based on the generative model, a target file corresponding to the at least one task node is synchronously generated.

[0175] In some embodiments, the second generating unit is further configured to:

[0176] Based on the generative model, target files corresponding to the at least one task node are generated one by one according to the execution order of the subtasks corresponding to the at least one task node; the target file corresponding to any remaining target task node among the at least one task node except the first task node is generated based on the execution result of the previous task node of the target task node.

[0177] In some embodiments, the obtaining module 1710 is further used to: obtain second information; the second information includes the operating environment information of the target application;

[0178] The response module 1720 is also used for: if it is determined based on the second information that the target application is running in a first environment, generating a first file based on the generative model so that the target application can perform the target task in the first environment based on the first file; if it is determined based on the second information that the target application is running in a second environment, generating a second file based on the generative model so that the target application can perform the target task in the second environment based on the second file; the first environment is different from the second environment.

[0179] In some embodiments, the obtaining module 1710 is further used to: obtain third information when it is determined that an abnormality occurs when the target application executes the target task based on the target file; the third information is obtained by inputting an abnormal interaction interface output by the target object in the process of executing the target task by the target application, and the abnormal interaction interface is generated by the generative model;

[0180] The response module 1720 is further configured to: in response to the third information, adjust the target file based on the generative model.

[0181] It should be noted here that the above-mentioned data processing device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned data processing method embodiment, and can achieve the same technical effect. The parts and beneficial effects that are the same as the method embodiment in this embodiment will not be described in detail here.

[0182] Fig.18 A schematic diagram of the physical structure of an electronic device provided in an embodiment of the present application, such as Fig.18As shown, the electronic device may include: a processor 1810, a communication interface 1820, a memory 1830 and a communication bus 1840, wherein the processor 1810, the communication interface 1820 and the memory 1830 communicate with each other through the communication bus 1840. The processor 1810 may call the executable data instructions stored in the memory 1830 to execute the data processing method provided in the above embodiments, and the method includes:

[0183] Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description;

[0184] In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

[0185] In addition, the executable data instructions stored in the above-mentioned memory 1830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0186] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the data processing method provided in the above embodiments is implemented. The method includes:

[0187] Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description;

[0188] In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

[0189] The present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the data processing method provided in the above embodiments. The method includes:

[0190] Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description;

[0191] In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

[0192] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0193] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the embodiments of the present application may adopt the form of hardware embodiments, software embodiments, or embodiments in combination with software and hardware. Moreover, the embodiments of the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0194] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, 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, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0195] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0196] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0197] The above description is merely an optional embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A data processing method, comprising: Get first information; The first information is used to instruct the target application to execute the target task, and the first information is obtained by inputting the target object to the target interface output by the target application during operation, and the target interface includes at least one task description; In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

2. The data processing method according to claim 1, wherein in response to the first information, generating a target file based on a generative model comprises: In response to the first information, generating a task flow interface for the target application to execute the target task based on the generative model; The task flow interface includes at least one task node required for the target application to execute the target task; Execute the subtasks corresponding to the at least one task node in sequence based on the generative model; In a case where it is determined that the subtask corresponding to the at least one task node has been completed by the generative model, generating the target file based on the generative model; The target file is generated by the generative model based on the execution logic after all subtasks corresponding to the at least one task node are executed.

3. The data processing method according to claim 1, wherein in response to the first information, generating a target file based on a generative model comprises: In response to the first information, generating a task flow interface for the target application to execute the target task based on the generative model; The task flow interface includes at least one task node required for the target application to execute the target task; Generate a corresponding target file for the at least one task node based on the generative model; The target file is generated by the generative model based on the execution logic before the subtask corresponding to the at least one task node is executed; The method further comprises: The subtasks corresponding to the at least one task node are executed in sequence based on the target file corresponding to the at least one task node.

4. The data processing method according to claim 3, wherein generating a corresponding target file for the at least one task node based on the generative model comprises: Based on the generative model, a target file corresponding to the at least one task node is synchronously generated.

5. The data processing method according to claim 3, wherein generating a corresponding target file for the at least one task node based on the generative model comprises: Based on the generative model, generating target files corresponding to the at least one task node one by one according to the execution order of the subtasks corresponding to the at least one task node; The target file corresponding to any remaining target task node except the first task node among the at least one task node is generated based on the execution result of the previous task node of the target task node.

6. The data processing method according to any one of claims 1 to 5, further comprising: obtaining second information; The second information includes operating environment information of the target application; If it is determined based on the second information that the target application is running in the first environment, generating a first file based on the generative model so that the target application can perform the target task in the first environment based on the first file; If it is determined based on the second information that the target application is running in the second environment, generating a second file based on the generative model so that the target application can perform the target task in the second environment based on the second file; The first environment is different from the second environment.

7. The data processing method according to any one of claims 1 to 5, further comprising: When it is determined that an abnormality occurs when the target application program executes the target task based on the target file, obtaining third information; The third information is obtained by inputting the abnormal interaction interface output by the target object in the process of the target application executing the target task, and the abnormal interaction interface is generated by the generative model; In response to the third information, the target file is adjusted based on the generative model.

8. A data processing device, comprising: An obtaining module, used for obtaining first information; The first information is used to instruct the target application to execute the target task, and the first information is obtained by inputting the target object to the target interface output by the target application during operation, and the target interface includes at least one task description; A response module is used to generate a target file based on a generative model in response to the first information, so that the target application can perform the target task based on the target file.

9. An electronic device, comprising: A memory for storing executable data instructions; The processor is configured to implement the following steps when executing the executable data instructions stored in the memory: Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description; In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

10. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the following steps are implemented: Obtaining first information; the first information is used to instruct the target application to execute the target task, the first information is obtained by the target object inputting a target interface output by the target application during operation, the target interface including at least one task description; In response to the first information, a target file is generated based on a generative model, so that the target application can perform the target task based on the target file.

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