Process processing method, device and equipment combining RPA and AI, and storage medium

Abstract

The embodiment of the application discloses a process processing method and device combining RPA and AI, equipment and a storage medium. It relates to the technical field of RPA and AI, wherein the method is applied to an RPA execution end, and comprises the following steps: acquiring RPA process requirement information of each RPA execution end; and sending the RPA process requirement information to an RPA control end. Therefore, by acquiring the process requirement information of each RPA execution end and sending the process requirement information to the RPA control end, the RPA process can be automatically reconstructed, the automation of the process is further promoted, the artificial participation rate is reduced, the process efficiency is improved, and the work burden of relevant staff is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of robotic process automation, in particular to a process processing method and device combining RPA (Robotic Process Automation) and AI (Artificial Intelligence), equipment and storage medium. BACKGROUND

[0002] Robotic process automation (RPA) is to simulate human operation on a computer through specific "robotic software" and automatically execute process tasks according to rules.

[0003] Artificial intelligence (Artificial Intelligence) is abbreviated as AI. It is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science, which aims to understand the essence of intelligence and produce a new intelligent machine that can react in a similar way to human intelligence. The research in this field includes robots, speech recognition, image recognition, natural language processing and expert systems.

[0004] At present, in the field of robotic process automation, process automation can be realized, and RPA process execution end, RPA process control end and RPA process generation end are usually used together. Among them, the RPA process control end is mainly used to control the execution of the RPA process by the RPA process execution end, but the current RPA process control end usually needs to control and deploy the RPA process manually, and then start the execution of the RPA process. However, if the process execution of the PRA process execution end fails after starting the execution of the RPA process, there is currently no corresponding automatic processing method, which is not conducive to process automation. SUMMARY

[0005] The embodiments of the present application disclose a process processing method and device combining RPA and AI, equipment and storage medium, by acquiring the process requirement information of each RPA execution end and sending it to the RPA control end, so as to automatically rebuild the RPA process, further promote the automation of the process, reduce the participation rate of manual work, improve the efficiency of the process and reduce the work burden of the relevant staff.

[0006] In a first aspect, the embodiments of the present application disclose a process processing method combining RPA and AI, which comprises:

[0007] acquiring the RPA process requirement information of each RPA execution end;

[0008] Send the RPA process requirement information to an RPA control end.

[0009] Optionally, the acquiring the RPA process requirement information of each RPA execution end comprises: accessing an interface of each RPA execution end to acquire execution feedback of the RPA process of each RPA execution end; performing natural language processing (NLP) on the execution feedback of the RPA process of each RPA execution end to determine an RPA execution end that needs to reconstruct the RPA process; and generating a process reconstruction requirement according to the RPA execution end that needs to reconstruct the RPA process and the RPA process that needs to be reconstructed.

[0010] Optionally, the generating the process reconstruction requirement according to the RPA execution end that needs to reconstruct the RPA process and the RPA process that needs to be reconstructed comprises: acquiring identification information of the RPA execution end that needs to reconstruct the RPA process and RPA process code of the RPA process that needs to be reconstructed of the RPA execution end; and adding the identification information of the RPA execution end that needs to reconstruct the RPA process and the corresponding RPA process code of the RPA process that needs to be reconstructed to the RPA process requirement information.

[0011] Optionally, the acquiring the identification information of the RPA execution end that needs to reconstruct the RPA process and the RPA process code of the RPA process that needs to be reconstructed of the RPA execution end comprises: acquiring the identification information of the RPA execution end that needs to reconstruct the RPA process; and acquiring the RPA process code corresponding to the identification information based on a preset correspondence.

[0012] Optionally, the method further comprises: acquiring an authorized account and an authorized password of the RPA control end and a current process code from the RPA control end; and the RPA process requirement information comprises the authorized account, the authorized password, and the current process code.

[0013] Optionally, the method comprises: acquiring task parameter information required by an RPA process to be created from an interface of each RPA robot execution end; and adding the task parameter information to the RPA process requirement information.

[0014] Optionally, the method comprises: receiving an RPA process creation task identifier, an RPA execution end identifier corresponding to the creation task identifier, and corresponding task parameters issued by the RPA control end; issuing the RPA process creation task identifier and the corresponding task parameters to the corresponding RPA robot execution end based on the corresponding RPA robot execution end identifier; and receiving feedback of the creation task of the corresponding RPA robot execution end.

[0015] Optionally, when the feedback of the corresponding RPA robot performing the end creation task is that the task creation fails, the creation of the next task is continued.

[0016] To achieve the above object, a second aspect of the present application provides another process processing device combining RPA and AI, comprising: a first acquisition module configured to acquire RPA process requirement information of each RPA execution end; and a sending module configured to send the RPA process requirement information to an RPA control end.

[0017] Optionally, the first acquisition module comprises: an acquisition unit configured to access each RPA execution end interface to acquire execution feedback of the RPA process of each RPA execution end; a determination unit configured to perform natural language processing on the execution feedback of the RPA process of each RPA execution end to determine an RPA execution end whose RPA process needs to be rebuilt; and a generation unit configured to generate process rebuilding requirements according to the RPA execution end whose RPA process needs to be rebuilt and the RPA process that needs to be rebuilt.

[0018] Optionally, the generation unit is specifically configured to: acquire identification information of the RPA execution end whose RPA process needs to be rebuilt and RPA process code of the RPA process that needs to be rebuilt; and associate and add the identification information of the RPA execution end whose RPA process needs to be rebuilt and the corresponding RPA process code of the RPA process that needs to be rebuilt to the RPA process requirement information.

[0019] Optionally, acquiring the identification information of the RPA execution end whose RPA process needs to be rebuilt and the RPA process code of the RPA process that needs to be rebuilt comprises: acquiring the identification information of the RPA execution end whose RPA process needs to be rebuilt; and acquiring the RPA process code of the RPA process that needs to be rebuilt corresponding to the identification information based on a preset corresponding relationship.

[0020] Optionally, the device further comprises a second acquisition module configured to acquire an authorized account, an authorized password, and a current process code of the RPA control end from the RPA control end; and the RPA process requirement information comprises the authorized account, the authorized password, and the current process code.

[0021] Optionally, the device further comprises a third acquisition module configured to acquire task parameter information required by an RPA process to be created from each RPA robot execution end interface; and an adding module configured to add the task parameter information to the RPA process requirement information.

[0022] Optionally, the apparatus comprises: a first receiving module, configured to receive an RPA process creation task identifier issued by an RPA control end, an RPA execution end identifier corresponding to the creation task identifier, and corresponding task parameters; a sending module, configured to send the RPA process creation task identifier and the corresponding task parameters to the corresponding RPA robot execution end based on the corresponding RPA robot execution end identifier; and a second receiving module, configured to receive feedback of the corresponding RPA robot execution end creating a task.

[0023] Optionally, when the feedback of the corresponding RPA robot execution end creating a task is that the task creation fails, the creation of the next task is continued.

[0024] To achieve the above object, a third aspect of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the combination of RPA and AI process processing method as described in the above embodiments is implemented.

[0025] To achieve the above object, a fourth aspect of the present application provides a non-transitory computer readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the combination of RPA and AI process processing method as described in the above embodiments is implemented.

[0026] The technical solutions provided by the embodiments of the present application have at least the following beneficial technical effects:

[0027] The RPA process requirement information of each RPA execution end is acquired, and the RPA process requirement information is sent to an RPA control end. In this way, by acquiring the process requirement information of each RPA execution end and sending it to the RPA control end, the RPA process is automatically reconstructed, the automation of the process is further promoted, the manual participation rate is reduced, the process efficiency is improved, and the work burden of the relevant staff is reduced.

[0028] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0030] Figure 1A flowchart of a process processing method combining RPA and AI provided by an embodiment of the present application;

[0031] Figure 2 A flowchart of another process processing method combining RPA and AI provided by an embodiment of the present application;

[0032] Figure 3 A flowchart of still another process processing method combining RPA and AI provided by an embodiment of the present application;

[0033] Figure 4 An example diagram of a process processing method combining RPA and AI provided by an embodiment of the present application;

[0034] Figure 5 A structural diagram of a process processing apparatus combining RPA and AI provided by an embodiment of the present application;

[0035] Figure 6 A structural diagram of another process processing apparatus combining RPA and AI provided by an embodiment of the present application;

[0036] Figure 7 A structural diagram of still another process processing apparatus combining RPA and AI provided by an embodiment of the present application;

[0037] Figure 8 A structural diagram of yet another process processing apparatus combining RPA and AI provided by an embodiment of the present application;

[0038] Figure 9 A structural diagram of still another process processing apparatus combining RPA and AI provided by an embodiment of the present application;

[0039] Figure 10 A hardware structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0041] It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present application and the accompanying drawings are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but can optionally further include steps or units not listed, or can optionally further include other steps or units inherent to the process, method, product or device.

[0042] The process handling method, device, electronic equipment and storage medium combining RPA and AI according to the embodiments of the present application are described below with reference to the accompanying drawings.

[0043] Specifically, the present application is applied to an RPA (robotic process automation) execution end. In the embodiments, the RPA execution end can obtain task parameter information required for creating an RPA process from each RPA robot execution end interface, then put the task parameter information into a corresponding data queue, and then create a process task corresponding to the task parameter information, so as to achieve the purpose of re-executing a process task that has failed to execute.

[0044] Figure 1 A flowchart of a process handling method combining RPA and AI according to an embodiment of the present application.

[0045] As shown in Figure 1 The process handling method includes the following steps:

[0046] Step 101: Obtain RPA process requirement information of each RPA execution end.

[0047] Step 102: Send the RPA process requirement information to an RPA control end.

[0048] Specifically, the RPA process requirement information includes one or more of execution feedback of the RPA process of each RPA execution end (including execution success or failure information), an authorized account of the RPA control end, an authorized password, and current process code, and one or more of task parameter information required for creating an RPA process obtained by each RPA robot execution end interface, which can be selected and set according to actual application needs.

[0049] Therefore, there are many ways to obtain the RPA process requirement information of each RPA execution end, which are illustrated as follows:

[0050] The first example is to access each RPA execution end interface to obtain execution feedback of the RPA process of each RPA execution end, determine an RPA execution end that needs to rebuild an RPA process according to the execution feedback of the RPA process of each RPA execution end, and generate a process rebuild requirement according to the RPA execution end that needs to rebuild the RPA process and the RPA process that needs to be rebuilt.

[0051] The second example obtains the authorized account and password of the RPA control end and the current process code from the RPA control end.

[0052] The third example obtains the task parameter information required by the RPA process to be created from the RPA robot execution end interface.

[0053] Further, the RPA process requirement information is sent to the RPA control end, which can be the process reconstruction requirement sent to the RPA control end, or the authorized account and password of the RPA control end, and the current process code sent to the RPA control end. Therefore, the RPA control end can create the RPA process creation task according to the RPA process requirement information, that is, the RPA execution end and the corresponding task parameters, so that the RPA robot execution end can execute the corresponding task according to the task parameters, such as collecting medical insurance data.

[0054] In summary, the process processing method combining RPA and AI provided by the embodiments of the present application obtains the RPA process requirement information of each RPA execution end, and sends the RPA process requirement information to the RPA control end. Therefore, by obtaining the process requirement information of each RPA execution end and sending it to the RPA control end, the RPA process can be automatically reconstructed, further promoting the automation of the process, reducing the participation rate of manual work, improving the efficiency of the process, and reducing the work burden of the relevant staff.

[0055] Based on the above description, the process processing method combining RPA and AI provided by the present application can be applied to the RPA execution end to determine whether to reconstruct the PRA process according to the execution feedback of the RPA process of each RPA execution end, so as to ensure that the PRA process is successfully executed and the target data is collected. The following will be described in detail. Figure 2

[0056] Figure 2 Another process diagram of the process processing method combining RPA and AI provided by the embodiments of the present application.

[0057] As Figure 2 shown, the process processing method combining RPA and AI includes the following steps:

[0058] Step 201, access each RPA execution end interface to obtain the execution feedback of the RPA process of each RPA execution end.

[0059] Specifically, the execution feedback of the RPA process of each RPA execution end can be obtained by accessing each RPA execution end interface, that is, two feedback results of whether the RPA process of each RPA execution end is successfully executed or failed.

[0060] ​At step 202, the execution feedback of the RPA process of each RPA execution end is subjected to natural language processing to determine the RPA execution end that needs to rebuild the RPA process.

[0061] At step 203, the process reconstruction requirement is generated according to the RPA execution end that needs to rebuild the RPA process and the RPA process that needs to be rebuilt and sent to the RPA control end.

[0062] Specifically, after obtaining the execution feedback of the RPA process of each RPA execution end, the execution feedback is subjected to natural language processing, such as semantic analysis, to obtain task execution failure or execution success messages, and the RPA execution end that fails to execute is determined as the RPA execution end that needs to rebuild the RPA process, and the corresponding RPA process that needs to be rebuilt is obtained. According to the RPA execution end that needs to rebuild the RPA process and the RPA process that needs to be rebuilt, the process reconstruction requirement is generated and sent to the RPA control end.

[0063] It can be understood that there are many ways to generate the process reconstruction requirement according to the RPA execution end that needs to rebuild the RPA process and the RPA process that needs to be rebuilt. As one possible implementation, the identification information of the RPA execution end that needs to rebuild the RPA process and the RPA process code of the RPA execution end that needs to rebuild the RPA process are obtained, and the identification information of the RPA execution end that needs to rebuild the RPA process and the corresponding RPA process code of the RPA execution end that needs to rebuild the RPA process are associated and added to the RPA process requirement information.

[0064] Among them, different RPA execution ends correspond to different process codes. As an example, the identification information of the RPA execution end that needs to rebuild the RPA process is obtained; based on a preset correspondence, the RPA process code corresponding to the identification information is obtained. That is, the correspondence between the identification information of the RPA execution end and the RPA process code that needs to be rebuilt is established in advance, and the RPA process code corresponding to the identification information can be obtained through the identification information of the RPA execution end.

[0065] For example, there are multiple stores in a region, and multiple RPA execution ends in a store, such as 3 stores in region A, and 2 RPA execution ends used in the entire region, i.e. 2 process codes (1 region * 2 RPA execution ends, i.e. two process codes are written, and the process code is not directly bound to a certain store); assuming that the two process codes are A001 and A002, when calling OpenAPI to dynamically create a task, RPA processes can be created according to the number of stores, i.e. A001+1 store, A001+2 store, A001+3 store, A002+1 store, A002+2 store, A002+3 store, a total of 6 RPA processes, and the RPA process is executed in the form of a store. Each RPA process only executes the summary data collection and reporting process of a certain store.

[0066] Thus, by accessing each RPA execution end interface, the execution feedback of the RPA process of each RPA execution end is obtained, the RPA execution end that needs to be reconstructed is determined according to the execution feedback of the RPA process of each RPA execution end, the process reconstruction requirement is generated and sent to the RPA control end according to the RPA execution end that needs to be reconstructed and the RPA process that needs to be reconstructed, the automatic reconstruction of the RPA process is realized, the automation of the process is further promoted, the artificial participation rate is reduced, the process efficiency is improved, and the work burden of the related staff is reduced.

[0067] Figure 3 A flowchart of another process processing method combining RPA and AI provided by an embodiment of the present application.

[0068] As shown in Figure 3 The process processing method combining RPA and AI includes the following steps:

[0069] Step 301: Obtain the task parameter information required by the RPA process to be created from each RPA robot execution end interface.

[0070] Step 302: Add the task parameter information to the RPA process requirement information, and send the RPA process requirement information to the RPA control end.

[0071] Specifically, a corresponding RPA process can be created for each RPA robot execution end to realize that each RPA robot execution end collects data as needed and provides it to the user, so the task parameter information required by the RPA process to be created is obtained from each RPA robot execution end interface, such as store number, store location, and payment category task parameter information, and the task parameter information is further added to the RPA process requirement information, and the RPA process requirement information is sent to the RPA control end. When the RPA process is created, a general process is usually created, and before starting to execute the RPA process, the RPA control end will determine the task parameter information according to the running environment of this RPA process and the running purpose of the RPA process. The task parameter information determined based on the running environment can be the store number and the store location, and the task parameter information determined based on the running purpose can be the payment category, the payment account, and the collection object for the bill grabbing RPA process.

[0072] Step 303: Receive the RPA process creation task identifier, the RPA execution end identifier corresponding to the creation task identifier, and the corresponding task parameter issued by the RPA control end.

[0073] Step 304: Based on the corresponding RPA robot execution end identifier, the RPA process creation task identifier and the corresponding task parameter are issued to the corresponding RPA robot execution end.

[0074] Step 305, receiving feedback of the corresponding RPA robot execution end creating the task.

[0075] Specifically, the RPA control end can generate RPA process creation task identifier, RPA execution end identifier corresponding to the creation task identifier, and corresponding task parameters according to the task parameter information in the RPA process requirement information and send them to the RPA execution end. Therefore, the RPA execution end receives the RPA process creation task identifier, the RPA execution end identifier corresponding to the creation task identifier, and the corresponding task parameters issued by the RPA control end, and then issues the RPA process creation task identifier and the corresponding task parameters to the corresponding RPA robot execution end based on the corresponding RPA robot execution end identifier. The RPA robot execution end collects data according to the task parameters.

[0076] It should be noted that when the feedback of the corresponding RPA robot execution end creating the task is a creation task failure, the creation of the next task is continued. The task identifier returned by the creation task interface is used to uniquely identify a task, and the return value (key field) can determine the task state (whether the task is created successfully).

[0077] Therefore, the task parameter information required for creating the RPA process is obtained from each RPA robot execution end interface, the task parameter information is added to the RPA process requirement information, the RPA process requirement information is sent to the RPA control end, the RPA process creation task identifier, the RPA execution end identifier corresponding to the creation task identifier, and the corresponding task parameters issued by the RPA control end are received, the RPA process creation task identifier and the corresponding task parameters are issued to the corresponding RPA robot execution end based on the corresponding RPA robot execution end identifier, and the feedback of the corresponding RPA robot execution end creating the task is received. In order to automatically rebuild the RPA process, further promote the automation of the process, reduce the manual participation rate, improve the process efficiency, and reduce the work burden of the relevant staff.

[0078] In order for those skilled in the art to better understand the above process, the following will combine Figure 4 For example, the RPA execution end can obtain the task parameter information required for creating the RPA process from each RPA robot execution end interface, then put the task parameter information into the corresponding data queue, and then create the process task corresponding to the task parameter information to achieve the purpose of re-executing the execution failed process task.

[0079] Specifically, as Figure 4As shown, (1) initialize global variables, load all process blocks involved data (RPA process requirement information) and the like, output including dictionary type, all process blocks required data, output dictionary key field including RPA control end authorization account, authorization password and current process code (the unique identifier of the process on the RPA control end) and the server address deployed by the RPA control end; (2) get store list, get the task parameter information needed to create by calling the get store information interface, the output array type is the task parameter information required to create RPA process; (3) get a data of the list, increase the readability of the process; (4) add data to the data queue, put the task parameter information required by the RPA process into the corresponding data queue of the RPA control end, the data put into the data queue is the data obtained by the get store interface; (5) create data corresponding task, according to the store information returned by the get store information interface, get the current process code to be executed by the mapping relationship, create process task using open platform, input is store information, RPA control end open platform authentication information and RPA control end deployed server address; (6) create own process task, run after all RPA processes are created and executed, because RPA process may fail to execute due to exception.

[0080] Therefore, by obtaining the process requirement information of each RPA execution end and sending it to the RPA control end, the RPA process can be automatically rebuilt, the process automation is further promoted, the manual participation rate is reduced, the process efficiency is improved, and the work burden of related personnel is reduced.

[0081] In order to realize the above-mentioned embodiment, the application further provides a process processing device combining RPA and AI. Figure 5 It is a structural schematic diagram of a process processing device combining RPA and AI according to the application, as Figure 5 shown, the process processing device comprises a first acquisition module 501 and a sending module 502, wherein,

[0082] The first acquisition module 501 is configured to acquire RPA process requirement information of each RPA execution end.

[0083] The sending module 502 is configured to send the RPA process requirement information to the RPA control end.

[0084] In an embodiment of the application, as Figure 6 shown, on the basis of as Figure 5 shown, the first acquisition module 501 comprises an acquisition unit 5011, a determination unit 5012 and a generation unit 5013.

[0085] The acquisition unit 5011 is configured to access each RPA execution end interface and acquire execution feedback of the RPA process of each RPA execution end.

[0086] The determination unit 5012 is configured to perform natural language processing on the execution feedback of the RPA process of each RPA execution end, and determine an RPA execution end that needs to reconstruct the RPA process.

[0087] The generation unit 5013 is configured to generate a process reconstruction requirement according to the RPA execution end that needs to reconstruct the RPA process and the RPA process that needs to be reconstructed.

[0088] In an embodiment of the present application, the generation unit 5013 is specifically configured to: obtain identification information of the RPA execution end that needs to reconstruct the RPA process and RPA process code of the RPA execution end that needs to reconstruct the RPA process; and add the identification information of the RPA execution end that needs to reconstruct the RPA process and the corresponding RPA process code to the RPA process requirement information.

[0089] In an embodiment of the present application, the obtaining of the identification information of the RPA execution end that needs to reconstruct the RPA process and the RPA process code of the RPA execution end that needs to reconstruct the RPA process includes: obtaining the identification information of the RPA execution end that needs to reconstruct the RPA process; and obtaining the RPA process code corresponding to the identification information based on a preset correspondence relationship.

[0090] In an embodiment of the present application, as shown in Figure 7 , on the basis of Figure 5 , further comprising a second acquisition module 503.

[0091] The second acquisition module 503 is configured to obtain an authorized account, an authorized password, and a current process code of an RPA control end from the RPA control end; and the RPA process requirement information includes the authorized account, the authorized password, and the current process code.

[0092] In an embodiment of the present application, as shown in Figure 8 , on the basis of Figure 5 , further comprising a third acquisition module 504 and an adding module 505.

[0093] The third acquisition module 504 is configured to obtain task parameter information required by an RPA process to be created from each RPA robot execution end interface.

[0094] The adding module 505 is configured to add the task parameter information to the RPA process requirement information.

[0095] In an embodiment of the present application, as shown in Figure 9 , on the basis of Figure 5On the basis of the shown, further comprising: a first receiving module 506, a delivery module 507 and a second receiving module 508.

[0096] The first receiving module 506 is configured to receive an RPA process creation task identifier delivered by an RPA control end, an RPA execution end identifier corresponding to the creation task identifier, and corresponding task parameters.

[0097] The delivery module 507 is configured to deliver the RPA process creation task identifier and the corresponding task parameters to the corresponding RPA robot execution end based on the corresponding RPA robot execution end identifier.

[0098] The second receiving module 508 is configured to receive feedback of the task created by the corresponding RPA robot execution end.

[0099] In an embodiment of the present application, when the feedback of the task created by the corresponding RPA robot execution end is a task creation failure, the creation of the next task is continued.

[0100] It should be noted that the foregoing explanation and description of the process processing method embodiments are also applicable to the process processing device of this embodiment, which will not be described here.

[0101] In summary, the process processing device combining RPA and AI provided in the embodiments of the present application acquires RPA process requirement information of each RPA execution end and sends the RPA process requirement information to an RPA control end. Thus, by acquiring the process requirement information of each RPA execution end and sending the process requirement information to the RPA control end, the RPA process is automatically reconstructed, the automation of the process is further promoted, the manual participation rate is reduced, the process efficiency is improved, and the work burden of the related staff is reduced.

[0102] The electronic device provided in the embodiments can be used to execute the technical solutions of the above method embodiments, and has similar implementation principles and technical effects, which will not be described here.

[0103] Reference Figure 10 Fig. 9 shows a structural schematic diagram of an electronic device 900 suitable for implementing the embodiments of the present application, which can be a terminal device or a server. The terminal device can include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, personal digital assistants (PDA), tablet computers (PAD), portable media players (PMP), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, as well as fixed terminals such as digital TVs, desktop computers, and the like. Figure 10The electronic device shown is merely an example and should not bring any limitation to the function and use range of the embodiments of the present application.

[0104] As shown in Figure 10 The electronic device 900 can include a processing device (e.g., a central processor, a graphics processor, etc.) 901 that can perform various appropriate actions and processes according to programs stored in a Read Only Memory (ROM) 902 or loaded from a storage device 908 into a Random Access Memory (RAM) 903. Various programs and data required for the operation of the electronic device 900 are also stored in the RAM 903. The processing device 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. An Input / Output (I / O) interface 905 is also connected to the bus 904.

[0105] Generally, the following devices can be connected to the I / O interface 905: input devices 906 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 907 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, etc.; storage devices 908 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 909. The communication devices 909 can allow the electronic device 900 to communicate with other devices wirelessly or through wires to exchange data. Although Figure 10 The electronic device 900 is shown with various devices, but it should be understood that all of the shown devices are not required to be implemented or present. More or less devices can alternatively be implemented or present.

[0106] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication devices 909, or installed from the storage devices 908, or installed from the ROM 902. When the computer program is executed by the processing device 901, the above-mentioned functions defined in the methods of embodiments of the present application are performed.

[0107] To implement the above-mentioned embodiments, the present application also proposes an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the process handling method combining RPA and AI in the above-mentioned embodiments when executing the computer program.

[0108] To achieve the above-mentioned embodiments, the application further provides a non-transitory computer-readable storage medium, which, when instructions in the storage medium are executed by a processor, enables the process method for combining RPA and AI to be performed.

[0109] It should be noted that the computer readable medium of the application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer readable program code. Such a propagated data signal can take many forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium other than the computer readable storage medium, which can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or apparatus. The program code contained in the computer readable medium can be transmitted by any suitable medium, including but not limited to a wire, a cable, a RF (radio frequency) or the like, or any suitable combination of the above.

[0110] The computer readable medium described above can be contained in the electronic device described above; or can exist separately and not be assembled into the electronic device.

[0111] The computer readable medium described above carries one or more programs, which, when executed by the electronic device, enable the electronic device to perform the method shown in the above embodiments.

[0112] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0113] The computer program instructions can also be loaded onto a computer or other programmable information processing apparatus to cause a series of operations to be performed on the computer or other programmable information processing apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable information processing apparatus implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0114] The units described in the embodiments of the present application can be implemented by software, or by hardware. In some cases, the names of the units do not constitute a limitation on the units themselves. For example, the first obtaining unit can also be described as a unit for obtaining at least two Internet protocol addresses.

[0115] The functions described above in the specification of the present application can be performed by one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Program-specific Integrated Circuits (ASICs), Program-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.

[0116] In the context of this application, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include a lined-inked electrical connection, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] The above description is only the preferred embodiment of the present application and the explanation of the technical principles used. It should be understood by those skilled in the art that the disclosed scope of the present application is not limited to the technical solutions formed by the specific combinations of the technical features described above, and should also cover other technical solutions formed by any combinations of the technical features described above or their equivalent features without departing from the disclosed concept. For example, the technical solutions formed by the mutual replacement of the above-described features and the technical features with similar functions disclosed in the present application (but not limited to).

[0118] Furthermore, although the operations have been depicted in a particular order, this should not be understood as requiring the operations to be performed in the particular order shown or in sequential order, and that certain operations can be performed in parallel or in any order. Also, although the above discussion has included several specific examples, these should not be construed as limiting the scope of the application, but as merely providing illustrations of the various aspects of the present application. Thus, various modifications and changes can be made to the methods described without departing from the scope of the present application. Certain features described in the context of separate embodiments can be combined with each other. Conversely, various features described in the context of a single embodiment can be separated and performed in multiple embodiments.

[0119] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.

Claims

1. A process processing method combining RPA and AI, characterized in that: Applied to the RPA execution end, including: Obtaining RPA process requirement information of each RPA execution end, which includes: accessing each RPA execution end interface to obtain execution feedback of the RPA process of each RPA execution end; Perform natural language processing on the execution feedback of the RPA process on each RPA execution end to determine the RPA execution end that needs to rebuild the RPA process; Generate process reconstruction requirements based on the RPA execution end of the RPA process that needs to be rebuilt and the RPA process that needs to be rebuilt; Sending the RPA process requirement information to the RPA control end; Obtain the task parameter information required for the RPA process to be created from the execution interface of each RPA robot. The task parameter information is determined by the RPA control end based on the operating environment and the purpose of the RPA process. Adding the task parameter information to the RPA process requirement information; Receive the RPA process creation task identifier, the RPA execution end identifier corresponding to the creation task identifier, and the corresponding task parameters issued by the RPA control end; Based on the corresponding RPA robot execution end identifier, the RPA process creation task identifier and the corresponding task parameters are sent to the corresponding RPA robot execution end; Generating a process reconstruction requirement based on the RPA execution end of the RPA process to be rebuilt and the RPA process to be rebuilt includes: Obtain identification information of the RPA execution end of the RPA process that needs to be rebuilt, and the RPA process code that needs to be rebuilt of the RPA execution end of the RPA process that needs to be rebuilt; The identification information of the RPA execution end of the RPA process that needs to be rebuilt and its corresponding RPA process code that needs to be rebuilt are associated and added to the RPA process requirement information, wherein the RPA process requirement information includes: an authorized account, an authorized password, and a current process code.

2. The method according to claim 1, characterized in that The obtaining of the identification information of the RPA execution end of the RPA process that needs to be rebuilt and the RPA process code that needs to be rebuilt of the RPA execution end of the RPA process that needs to be rebuilt includes: Obtain identification information of the RPA execution end of the RPA process to be rebuilt; Based on the preset corresponding relationship, the RPA process code to be rebuilt corresponding to the identification information is obtained.

3. The method according to claim 1, characterized in that The method further comprises: Obtain the RPA control end's authorization account, authorization password, and current process code from the RPA control end.

4. The method according to claim 1, wherein The method further comprises: Receive feedback on the task created by the corresponding RPA robot execution end.

5. The method according to claim 4, wherein When the feedback from the corresponding RPA robot execution end on creating the task is that the task creation failed, continue to create the next task.

6. A process processing device combining RPA and AI, characterized in that: include: The first acquisition module is used to obtain the RPA process requirement information of each RPA execution end; A sending module, configured to send the RPA process requirement information to the RPA control end; The third acquisition module is configured to obtain task parameter information required for the RPA process to be created from the execution end interface of each RPA robot. The task parameter information is determined by the RPA control end based on the operating environment and the purpose of the RPA process. An adding module, configured to add the task parameter information to the RPA process requirement information; The first receiving module is configured to receive an RPA process creation task identifier, an RPA execution end identifier corresponding to the creation task identifier, and corresponding task parameters, issued by the RPA control end; The sending module is used to send the RPA process creation task identifier and the corresponding task parameters to the corresponding RPA robot execution end based on the corresponding RPA robot execution end identifier. The first acquisition module is further configured to access the interfaces of each RPA execution terminal to obtain execution feedback of the RPA process of each RPA execution terminal; Perform natural language processing on the execution feedback of the RPA process on each RPA execution end to determine the RPA execution end that needs to rebuild the RPA process; Generate process reconstruction requirements based on the RPA execution end of the RPA process that needs to be rebuilt and the RPA process that needs to be rebuilt; The generating of the process reconstruction requirement according to the RPA execution end of the RPA process to be rebuilt and the RPA process to be rebuilt includes: Obtain identification information of the RPA execution end of the RPA process that needs to be rebuilt, and the RPA process code that needs to be rebuilt of the RPA execution end of the RPA process that needs to be rebuilt; The identification information of the RPA execution end of the RPA process that needs to be rebuilt and its corresponding RPA process code that needs to be rebuilt are associated and added to the RPA process requirement information, wherein the RPA process requirement information includes: an authorized account, an authorized password, and a current process code.

7. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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