Task processing method and system, storage medium and electronic equipment

Abstract

The invention provides a task processing method and system, a storage medium and electronic equipment, and the method comprises the steps: responding to a starting operation of a target RPA task by near-end equipment, and determining and sending a starting instruction of the target RPA task to a server; the server determines an execution end from the near-end device and the cloud according to the starting instruction of the target RPA task, and sends an RPA instruction set of the target RPA task to the execution end; the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain an execution result of the target RPA task; and the near-end device obtains and displays an execution result of the target RPA task. Based on the scheme, the server side flexibly determines the execution side from the near-end device and the cloud side according to the starting instruction of the target RPA task, so that the processing flexibility of the RPA task is remarkably improved, and diversified processing requirements of the RPA task are effectively met.

Description

Technical Field

[0001] The present specification relates to the field of computer technology, and more specifically, to a task processing method, system, storage medium and electronic device in the field of computer technology. Background Art

[0002] Robotic Process Automation (RPA) is a technology that uses software robots to simulate human operations and automate business processes. In related technologies, RPA tasks initiated by local devices are generally processed by local devices or by the cloud. This method of processing RPA tasks by either the local device or the cloud is difficult to flexibly meet the diverse processing requirements of RPA tasks. Summary of the invention

[0003] This specification provides a task processing method, system, storage medium and electronic device, which can improve the flexibility of RPA task processing and effectively meet the diversified processing requirements of RPA tasks.

[0004] In a first aspect, a task processing method is provided, which is applied to a proximal device, and the method includes:

[0005] In response to the start operation of the target RPA task, determine the start instruction of the target RPA task, send the start instruction of the target RPA task to the server, so that the server can determine the execution end from the local device and the cloud according to the start instruction of the target RPA task, and send the RPA instruction set of the target RPA task to the execution end;

[0006] The execution result of the target RPA task is obtained and displayed, wherein the execution result of the target RPA task is obtained by the execution end executing each RPA instruction in the RPA instruction set of the target RPA task.

[0007] In combination with the first aspect, in some possible implementations, when the proximal device is determined as the execution end, in response to the start operation of the target RPA task, the start instruction of the target RPA task is determined, and after sending the start instruction of the target RPA task to the server, before obtaining and displaying the execution result of the target RPA task, it also includes: receiving the RPA instruction set of the target RPA task sent by the server; executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0008] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, when the cloud is determined as the execution end, the execution result of the target RPA task is obtained and displayed, including: receiving the execution result of the target RPA task sent by the cloud through the server; displaying the execution result of the target RPA task.

[0009] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, when the cloud is determined as the execution end, in response to the start operation of the target RPA task, the start instruction of the target RPA task is determined, and after sending the start instruction of the target RPA task to the server, before obtaining and displaying the execution result of the target RPA task, it also includes: receiving the human-computer interaction RPA instruction sent by the cloud through the server; rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instruction; determining the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface; and sending the human-computer interaction result information to the cloud through the server.

[0010] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instructions includes: rendering and displaying interaction prompt information and interaction controls according to the human-computer interaction RPA instructions to form a human-computer interaction interface, wherein the interaction prompt information is used to prompt the user to perform interaction operations, and the interaction controls are used to respond to the user's interaction operations.

[0011] In a second aspect, a task processing method is provided, which is applied to a server, and the method includes:

[0012] Receive the start instruction of the target RPA task sent by the proximal device;

[0013] According to the start instruction of the target RPA task, the execution end is determined from the local device and the cloud;

[0014] The RPA instruction set of the target RPA task is sent to the execution end, so that the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, and the local device obtains and displays the execution result of the target RPA task.

[0015] In combination with the second aspect, in some possible implementations, the execution end is determined from the proximal device and the cloud according to the startup instruction of the target RPA task, including: determining the authority level of the target RPA task according to the startup instruction of the target RPA task; when the authority level of the target RPA task is higher than the preset reference authority level, determining the proximal device as the execution end; when the authority level of the target RPA task is not higher than the preset reference authority level, determining the cloud as the execution end.

[0016] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, when the cloud is determined as the execution end, after sending the RPA instruction set of the target RPA task to the execution end, it also includes: determining the status of each RPA executor in the cloud, wherein the status of the RPA executor includes a busy state and an idle state; determining the target RPA executor from the RPA executors in the idle state in the cloud; generating an RPA executor call instruction according to the target RPA executor, and sending the RPA executor call instruction to the cloud, wherein the RPA executor call instruction is used to instruct the cloud to call the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task.

[0017] In a third aspect, a task processing method is provided, which is applied to a cloud, and the method includes:

[0018] Receiving an RPA instruction set of a target RPA task sent by a server, wherein the RPA instruction set of the target RPA task is sent by the server to the cloud when the server determines that the cloud is an execution end from among a proximal device and a cloud according to a start instruction of the target RPA task;

[0019] Each RPA instruction in the RPA instruction set of executing the target RPA task obtains the execution result of the target RPA task, so that the proximal device can obtain and display the execution result of the target RPA task.

[0020] In combination with the third aspect, in some possible implementations, each RPA instruction in the RPA instruction set of the target RPA task is executed to obtain the execution result of the target RPA task, so that the proximal device can obtain and display the execution result of the target RPA task, including: determining the execution order of each RPA instruction in the RPA instruction set of the target RPA task; traversing each RPA instruction in turn according to the execution order of each RPA instruction in the RPA instruction set of the target RPA task; executing the current RPA instruction for the current RPA instruction in each traversed RPA instruction; if the RPA instruction with the last execution order in each RPA instruction is executed, the execution result of the target RPA task is obtained, and the execution result of the target RPA task is sent to the proximal device through the server, so that the proximal device can receive and display the execution result of the target RPA task.

[0021] In combination with the third aspect and the above-mentioned implementation methods, in some possible implementation methods, for the current RPA instruction among the traversed RPA instructions, the current RPA instruction is executed, including: for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is a human-computer interaction RPA instruction, the human-computer interaction RPA instruction is sent to the proximal device through the server, the proximal device renders and displays the human-computer interaction interface according to the human-computer interaction RPA instruction, determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface, and sends the human-computer interaction result information to the cloud through the server; receives the human-computer interaction result information.

[0022] In combination with the third aspect and the above-mentioned implementation methods, in some possible implementation methods, for the current RPA instruction among the traversed RPA instructions, the current RPA instruction is executed, including: for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interactive pre-RPA instruction whose execution order is before the human-computer interaction RPA instruction, then the interactive prompt information is obtained according to the interactive pre-RPA instruction, and the interactive prompt information is filled into the human-computer interaction RPA instruction, wherein the interactive prompt information is used to prompt the user to perform interactive operations in the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction.

[0023] In combination with the third aspect and the above-mentioned implementation methods, in some possible implementation methods, for the current RPA instruction among the traversed RPA instructions, the current RPA instruction is executed, including: for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interaction post-RPA instruction whose execution order is after the human-computer interaction RPA instruction, the interaction post-RPA instruction is executed according to the received human-computer interaction result information, wherein the human-computer interaction result information is the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction, which is determined in response to the interaction operation on the human-computer interaction interface and sent to the cloud through the server.

[0024] In combination with the third aspect and the above-mentioned implementation methods, in some possible implementation methods, after receiving the RPA instruction set of the target RPA task sent by the server, before executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, it also includes: receiving an RPA executor call instruction sent by the server, wherein the RPA executor call instruction is generated by the server according to the target RPA executor in the cloud, and the target RPA executor is determined by the server from the idle RPA executors in the cloud; executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, including: according to the RPA executor call instruction, calling the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0025] In a fourth aspect, a task processing system is provided, the system comprising a proximal device, a server, and a cloud;

[0026] The proximal device is used to respond to the start operation of the target RPA task, determine the start instruction of the target RPA task, send the start instruction of the target RPA task to the server, and obtain and display the execution result of the target RPA task;

[0027] The server is used to receive the start instruction of the target RPA task sent by the proximal device; determine the execution end from the proximal device and the cloud according to the start instruction of the target RPA task; send the RPA instruction set of the target RPA task to the execution end, so that the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task;

[0028] The cloud end is used to receive the RPA instruction set of the target RPA task sent by the server end, wherein the RPA instruction set of the target RPA task is sent to the cloud end when the server end determines that the cloud end is the execution end from the proximal device and the cloud end according to the start instruction of the target RPA task; and executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0029] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the first aspect, the second aspect, the third aspect, or any possible implementation of the first aspect, the second aspect, and the third aspect.

[0030] In a sixth aspect, an electronic device is provided, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the steps of the above method.

[0031] In the seventh aspect, a computer program product is provided, which includes: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect, the second aspect, the third aspect, or any possible implementation of the first aspect, the second aspect, and the third aspect.

[0032] In the embodiments of this specification: the proximal device responds to the start operation of the target RPA task, determines and sends the start instruction of the target RPA task to the server; the server determines the execution end from the proximal device and the cloud according to the start instruction of the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end; the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task; the proximal device obtains and displays the execution result of the target RPA task. In this way, by introducing the server, the execution end can be flexibly determined from the proximal device and the cloud according to the start instruction of the target RPA task, which significantly improves the flexibility of RPA task processing, is not limited to the fixed processing of RPA tasks by the proximal device or the cloud alone, and effectively meets the diversified processing needs of RPA tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the architecture of a task processing system provided by an embodiment of this specification;

[0034] Figure 2 It is a flowchart of a task processing method provided in an embodiment of this specification;

[0035] Figure 3 It is a schematic diagram of a human-computer interaction process provided by an embodiment of this specification;

[0036] Figure 4 This is an example schematic diagram of a human-computer interaction interface provided in an embodiment of this specification;

[0037] Figure 5 This is an example schematic diagram of a human-computer interaction interface provided in an embodiment of this specification;

[0038] Figure 6 This is an example schematic diagram of a human-computer interaction interface provided in an embodiment of this specification;

[0039] Figure 7 It is a flowchart of a task processing method provided in an embodiment of this specification;

[0040] Figure 8 This is a schematic diagram of an example of a unit structure of a server provided in an embodiment of this specification;

[0041] Fig. 9 This is an example schematic diagram of a cloud RPA executor call provided in an embodiment of this specification;

[0042] Fig.10 It is a flowchart of a task processing method provided in an embodiment of this specification;

[0043] Fig.11This is a flowchart of executing an RPA instruction provided in an embodiment of this specification;

[0044] Fig.12 This is a schematic diagram of an interaction of a proximal device executing instructions provided in an embodiment of this specification;

[0045] Fig.13 This is an interactive schematic diagram of a proximal device executing instructions in a logistics information query scenario provided by an embodiment of this specification;

[0046] Fig.14 It is a schematic diagram of an interaction of cloud execution instructions provided in an embodiment of this specification;

[0047] Fig.15 It is an interactive schematic diagram of executing instructions on the cloud in a logistics information query scenario provided by an embodiment of this specification;

[0048] Fig.16 It is a structural schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0049] The technical solutions in this specification will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of this specification, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of this specification, "multiple" means two or more than two.

[0050] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0051] RPA is a technology that uses software robots to simulate human operations and automate business processes. In related technologies, RPA tasks initiated by proximal devices are generally processed by proximal devices or by the cloud. This method of processing RPA tasks by proximal devices or one end in the cloud has some disadvantages. For example, the computer resources of proximal devices are limited. If some RPA tasks that occupy a large amount of computer resources are processed by proximal devices, the operating efficiency of the proximal devices will be seriously affected. For another example, the cloud environment is more vulnerable to external attacks and unauthorized access than proximal devices. If some RPA tasks with higher authority levels are processed by the cloud, there may be risks of data security and privacy leakage. In short, it is difficult to flexibly meet the diversified processing requirements of RPA tasks by having proximal devices or one end in the cloud process RPA tasks.

[0052] In order to solve these problems, the embodiments of this specification propose to introduce a server between the local device and the cloud. Figure 1 , Figure 1 This is an architectural diagram of a task processing system provided in an embodiment of this specification, wherein the task processing system includes a proximal device, a server, and a cloud, and the proximal device, the server, and the cloud all contain corresponding hardware and software. For example, the proximal device can be a user's personal computer, a smart phone, or a tablet computer, and the server and the cloud can be servers, service devices, and server clusters. The above examples do not constitute limitations on the specific implementation forms or types of the proximal device, the server, and the cloud in this specification. It should be noted that in some cases, the server and the cloud each have independent hardware, that is, the server and the cloud do not share hardware; in other cases, the server and the cloud share all or part of the hardware.

[0053] The proximal device communicates with the server, and the server communicates with the cloud. In other words, the data forwarding function based on the server can realize data transmission between the proximal device and the cloud. For RPA tasks initiated by the proximal device, the server can flexibly select one end from the proximal device and the cloud to be responsible for processing the RPA task according to the RPA task, and realize the necessary data interaction between the proximal device and the cloud during the RPA task processing, so that the processing of the RPA task is supported by the proximal device and the cloud.

[0054] based on Figure 1 The system architecture shown below will be combined with Figure 2 - Fig.15 , the task processing method provided in the embodiments of this specification is introduced in detail.

[0055] See also Figure 2, which is a flowchart of a task processing method provided in the embodiment of this specification. Figure 2 As shown, the method of the embodiment of this specification is applied to a near-end device and may include the following steps S102 to S104.

[0056] S102, in response to the start operation of the target RPA task, determines the start instruction of the target RPA task, and sends the start instruction of the target RPA task to the server, so that the server can determine the execution end from the local device and the cloud according to the start instruction of the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end.

[0057] Specifically, the RPA task involved in this embodiment refers to a task that simulates human operations through software robots to automate business processes. RPA tasks may involve data input, data processing, system interaction and other aspects. There is at least one RPA task supported by the proximal device and the cloud, and the target RPA task refers to an RPA task determined based on the user's startup operation on the proximal device among at least one RPA task supported by the proximal device and the cloud. The target RPA task can also be understood as a specific RPA task that represents the user's current need to pay attention to or process. It is understandable that the target RPA task can be one or more RPA tasks, which is not limited in this embodiment.

[0058] First, the user performs a start operation of the target RPA task on the proximal device. Accordingly, the proximal device determines the start instruction of the target RPA task in response to the start operation of the target RPA task. The start instruction of the target RPA task is a specific instruction for starting the target RPA task. The start instruction of the target RPA task includes at least the identification information of the target RPA task. The identification information of the RPA task is used to distinguish different RPA tasks. In addition, the specific instruction of the target RPA task may also include other parameters that help indicate the processing of the target RPA task.

[0059] In a possible implementation, the proximal device provides an RPA task start interface, which includes a start control corresponding to the target RPA task. When a user clicks the start control corresponding to the target RPA task in the RPA task start interface, it is deemed that the start operation of the target RPA task has been performed. Accordingly, the proximal device determines the start instruction of the target RPA task in response to the start operation of the target RPA task.

[0060] In one possible implementation, the target RPA task is configured to be bound to other operations of the user on the proximal device. For example, the target RPA task is configured to be bound to the user's power-on operation on the proximal device. When the user powers on the proximal device, based on the binding relationship, it is deemed that the start-up operation of the target RPA task has been performed. Accordingly, the proximal device determines the start-up instruction of the target RPA task in response to the start-up operation of the target RPA task.

[0061] In addition to the two possible implementation methods listed above, triggering the start operation of the target RPA task based on a physical button and triggering the start operation of the target RPA task based on a timer are all optional implementation methods, which are not listed one by one in this embodiment.

[0062] After determining the start instruction of the target RPA task, the local device sends the start instruction of the target RPA task to the server. Correspondingly, the server receives the start instruction of the target RPA task, determines the execution end from the local device and the cloud according to the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end.

[0063] The RPA instruction set of the target RPA task can be pre-stored by the server, or generated in real time by the server according to the target RPA task. The RPA instruction set of the target RPA task includes at least one RPA instruction of the target RPA task. The execution end processes the target RPA task, which is actually manifested as the execution end executing the RPA instructions in the RPA instruction set of the target RPA task. The RPA instructions are a series of commands that instruct the execution end to automatically execute the corresponding steps, simulating human operations to achieve transaction process automation.

[0064] In one possible implementation, the RPA instruction includes the following parameters:

[0065] Basic attribute parameters: include at least one of the following: RPA instruction name, RPA instruction identifier, and remark information. The RPA instruction name is used to identify the specific name of the RPA instruction; the RPA instruction identifier is used to uniquely identify the number of each RPA instruction; and the remark information is used to provide additional descriptions or comments on the RPA instruction.

[0066] Type parameter: includes at least one of the operation type and interaction type. The operation type is used to define the specific operation performed by the RPA instruction, such as operations on pages (opening websites, controlling interface elements, obtaining interface element values), operations on networks (obtaining remote HTTP / WS / TCP / UDF and other protocol interface data), operations on local files (adding, deleting, modifying and checking local files), operations on the execution end system (calling operating system windows, command execution windows, etc.), operations on large models (generating text content and image content based on contextual prompt information), etc., which will not be described in detail; the interaction type is used to indicate the type of RPA instruction that requires human intervention, which is used to achieve human-computer collaboration.

[0067] Input parameter: represents dependency information and is used to indicate the input data required for the execution of RPA instructions. For example, the RPA instruction to open a URL needs to specify the Uniform Resource Locator (URL), and the RPA instruction to obtain the value of a page element needs to specify the XML path (XML Path, or XPath) of the document object model (DOM) of the page or the Cascading Style Sheets Selector (CSS Selector).

[0068] Output parameters: include at least one of normal output value, abnormal environment information, and execution result status. The normal output value is the return result after the RPA instruction is successfully executed; the abnormal environment information is the environment information captured when the RPA instruction is executed abnormally; the execution result status is used to indicate the result of the RPA instruction execution, including success, failure, interruption and other states.

[0069] Fault tolerance parameters: represent the fault tolerance mechanism. The fault tolerance mechanism indicates the response measures taken when the RPA instruction execution encounters an abnormal situation, such as execution timeout processing, retry mechanism, interruption of execution, etc.

[0070] Execution order parameter: represents the execution order of RPA instructions, ensuring that the RPA instructions corresponding to the RPA task are executed in the predetermined order.

[0071] The above parameters together constitute the complete definition of RPA instructions, supporting the flexible combination of automated operations and manual intervention in RPA tasks in various transaction scenarios.

[0072] In one possible case, the proximal device is determined as the execution end. The proximal device receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, and obtains the execution result of the target RPA task.

[0073] In one possible scenario, the cloud is determined as the execution end. The cloud receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, obtains the execution result of the target RPA task, and then sends the execution result of the target RPA task to the proximal device through the server.

[0074] It should be noted that the execution result of the target RPA task refers to the information obtained after the target RPA task is completed, which may include, for example, output values ​​(such as the data that needs to be obtained), abnormal environment information (such as the context when an error occurs), execution status (such as successful execution, failed execution) and any output of manual intervention, which fully reflects the final execution status of the target RPA task.

[0075] S104, obtaining and displaying the execution result of the target RPA task, wherein the execution result of the target RPA task is obtained by the execution end executing each RPA instruction in the RPA instruction set of the target RPA task.

[0076] Specifically, in one possible case, the proximal device is determined as the execution end, then the proximal device executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, and the execution result of the target RPA task is stored locally on the proximal device. Furthermore, the proximal device can first obtain the execution result of the locally stored target RPA task, and then display the execution result of the target RPA task.

[0077] In one possible scenario, the cloud is determined as the execution end, then the cloud executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, and the cloud sends the execution result of the target RPA task to the near-end device through the server. Further, the near-end device can receive the execution result of the target RPA task and then display the execution result of the target RPA task.

[0078] It should be noted that in a possible implementation, during the processing of the target RPA task, the user can perform a task abort operation on the proximal device. Accordingly, the proximal device responds to the task abort operation, determines a task abort instruction, and sends the task abort instruction to the server. The server receives the task abort instruction and aborts the processing of the target RPA task on the execution end according to the task abort instruction. In this way, the user can decide whether to abort the processing of the target RPA task.

[0079] It should be noted that the above-mentioned proximal device can run on any operating system such as Windows, Linux, macOS, iOS, Android, HarmonyOS, etc., without any restriction.

[0080] In this embodiment, the proximal device responds to the start operation of the target RPA task, determines and sends the start instruction of the target RPA task to the server; the server determines the execution end from the proximal device and the cloud according to the start instruction of the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end; the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task; the proximal device obtains and displays the execution result of the target RPA task. In this way, by introducing the server, the execution end can be flexibly determined from the proximal device and the cloud according to the start instruction of the target RPA task, which significantly improves the flexibility of RPA task processing, is not limited to the fixed processing of RPA tasks by the proximal device or the cloud alone, and effectively meets the diversified processing needs of RPA tasks.

[0081] In one embodiment, when the proximal device is determined as the execution end, Figure 2 In the illustrated embodiment, after step S102 and before step S104, the following steps may also be included:

[0082] Receive the RPA instruction set of the target RPA task sent by the server;

[0083] Execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0084] Specifically, when the proximal device is determined as the execution end, the server will send the RPA instruction set of the target RPA task to the proximal device. Accordingly, the proximal device receives the RPA instruction set of the target RPA task sent by the server; determines the execution order of each RPA instruction in the RPA instruction set of the target RPA task; traverses each RPA instruction in sequence according to the execution order of each RPA instruction in the RPA instruction set of the target RPA task; executes the current RPA instruction for the current RPA instruction in each traversed RPA instruction; if the RPA instruction with the last execution order in each RPA instruction is executed, the execution result of the target RPA task is obtained.

[0085] In a possible implementation, for any of the above RPA instructions, during the execution of the RPA instruction, the proximal device will obtain the required data according to the input parameters of the RPA instruction, and perform the corresponding operation (such as opening a URL, filling in an input box, etc.) according to the operation type. After the RPA instruction is executed, output parameters will be generated, including normal output values, abnormal environment information, execution result status, etc. The proximal device may collect the output parameters of the RPA instruction to provide them to the next RPA instruction as input parameters, or to form the execution result of the target RPA task.

[0086] In this embodiment, the server assigns the target RPA task to the proximal device for processing. The proximal device can receive the RPA instruction set of the target RPA task sent by the server, and execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task. For some RPA tasks that require human-computer interaction or are sensitive to permissions, this embodiment can effectively meet the processing requirements of such RPA tasks, improve the convenience of human-computer interaction and the security of RPA task processing.

[0087] In one embodiment, when the cloud is determined as the execution end, Figure 2 In the illustrated embodiment, step S104 is further refined and may include the following steps:

[0088] Receive the execution results of the target RPA tasks sent by the cloud through the server;

[0089] Displays the execution results of the target RPA task.

[0090] Specifically, when the cloud is determined as the execution end, the server will send the RPA instruction set of the target RPA task to the cloud. Accordingly, the cloud receives the RPA instruction set of the target RPA task sent by the server; determines the execution order of each RPA instruction in the RPA instruction set of the target RPA task; traverses each RPA instruction in sequence according to the execution order of each RPA instruction in the RPA instruction set of the target RPA task; executes the current RPA instruction for the current RPA instruction in each traversed RPA instruction; if the RPA instruction with the last execution order in each RPA instruction is executed, the execution result of the target RPA task is obtained. Furthermore, the cloud sends the execution result of the target RPA task to the proximal device through the server.

[0091] Accordingly, the proximal device receives the execution result of the target RPA task and then displays the execution result of the target RPA task. To facilitate understanding of the present embodiment regarding displaying the execution result of the target RPA task, several examples are provided below:

[0092] In one example, if the execution result of the target RPA task includes text information, the proximal device may display the text information in a text box or a label.

[0093] In one example, if the execution result of the target RPA task includes image information, the proximal device may display the image information in a certain interface.

[0094] In one example, if the execution result of the target RPA task contains multiple data items, and there is an obvious structural relationship between these data items, a corresponding table can be constructed and displayed according to the execution result of the target RPA task, wherein each row of the table represents a data item, and each column represents an attribute of the data item.

[0095] In one example, for the execution results of the target RPA task that require visual analysis, the proximal device can construct and display a corresponding chart (such as a line chart, a bar chart, a pie chart, etc.) based on the execution results of the target RPA task.

[0096] In one example, if the execution result of the target RPA task needs to be notified to the user in a timely manner, the proximal device can display the execution result of the target RPA task in a pop-up window.

[0097] In one example, if the execution result of the target RPA task affects certain interface elements of the proximal device interface (such as button status, input box content, etc.), the proximal device can update the status or content of these interface elements according to the execution result of the target RPA task.

[0098] It should be noted that the above example does not constitute a limitation on the step of displaying the execution result of the target RPA task. The execution result of the target RPA task may include a variety of information, and the methods of displaying the execution result of the target RPA task may also be diverse.

[0099] In this embodiment, the server assigns the target RPA task to the cloud for processing. The cloud can receive the RPA instruction set of the target RPA task sent by the server, and execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task. The near-end device can obtain the execution result of the target RPA task. For some RPA tasks that require more resources or are not sensitive to permissions, this embodiment can effectively meet the processing requirements of such RPA tasks, reduce the resource usage of the near-end device, and use the computing power of the cloud to improve the efficiency of RPA task processing.

[0100] See also Figure 3 , which is a schematic diagram of a human-computer interaction process for the embodiment of this specification. Figure 3 As shown, when the cloud is determined as the execution end, the method of the embodiment of this specification is Figure 2 In the illustrated embodiment, after step S102 and before step S104 , the following steps S202 to S208 may also be included.

[0101] S202, receiving a human-computer interaction RPA instruction sent by the cloud through the server;

[0102] S204, rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instruction;

[0103] S206, determining human-computer interaction result information in response to the interactive operation on the human-computer interaction interface;

[0104] S208, sending human-computer interaction result information to the cloud through the server.

[0105] Specifically, when the cloud is determined as the execution end, the cloud will receive the RPA instruction set of the target RPA task sent by the server; determine the execution order of each RPA instruction in the RPA instruction set of the target RPA task; and execute each RPA instruction in sequence according to the execution order of each RPA instruction in the RPA instruction set of the target RPA task.

[0106] In the process of executing each RPA instruction in sequence on the cloud, some RPA instructions may be human-computer interaction RPA instructions. Among them, human-computer interaction RPA instructions refer to RPA instructions that require human intervention to complete. Since the cloud cannot be directly operated by users or lacks corresponding permissions, it cannot complete the interactive actions required by human-computer interaction RPA instructions alone. Therefore, the way to execute human-computer interaction RPA instructions on the cloud is to send human-computer interaction RPA instructions to the proximal device through the server.

[0107] Correspondingly, the proximal device receives the human-computer interaction RPA instructions sent by the cloud through the server, and then renders and displays the human-computer interaction interface according to the human-computer interaction RPA instructions.

[0108] In a possible implementation, the human-computer interaction RPA instruction includes interface configuration information required for rendering and displaying the human-computer interaction interface. In this case, the near-end device parses the human-computer interaction RPA instruction to obtain the interface configuration information, and renders and displays the human-computer interaction interface according to the interface configuration information.

[0109] In one possible implementation, the human-computer interaction RPA instruction does not include the interface configuration information required for rendering and displaying the human-computer interaction interface, but the near-end device locally stores the interface configuration information required for rendering and displaying the human-computer interaction interface. In this case, the near-end device calls the locally stored interface configuration information according to the human-computer interaction RPA instruction, and renders and displays the human-computer interaction interface according to the interface configuration information.

[0110] The above interface configuration information refers to various information required for describing and constructing a human-computer interaction interface. For example, the interface configuration information may include the layout, style, color, font, interactive control type, interactive control position, interactive control size, interactive control properties, etc. of the human-computer interaction interface, as well as the specific configuration of interface elements such as text and images that need to be displayed on the human-computer interaction interface.

[0111] The above-mentioned human-computer interaction interface at least includes interactive controls. Among them, interactive controls refer to interface elements in the human-computer interaction interface used to interact with users. Interactive controls usually have specific functions and behaviors, can respond to user interactive operations, and execute corresponding logical steps or display corresponding results according to user interactive operations.

[0112] Therefore, the user can perform interactive operations on the interactive controls in the human-computer interaction interface. Accordingly, the proximal device determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface. Among them, the interactive operation may include a data input operation and a decision operation. The human-computer interaction result information determined by the proximal device in response to the data input operation on the human-computer interaction interface may include input data corresponding to the data input operation; the human-computer interaction result information determined by the proximal device in response to the decision operation on the human-computer interaction interface may include decision data corresponding to the decision operation.

[0113] After obtaining the human-computer interaction result information, the near-end device sends the human-computer interaction result information to the cloud through the server. Correspondingly, the cloud receives the human-computer interaction result information and executes subsequent RPA instructions according to the human-computer interaction result information.

[0114] In this embodiment, in the case where the cloud needs human intervention in the process of processing the target RPA task, the cloud can send a human-computer interaction instruction to the proximal device through the server. The proximal device renders and displays the human-computer interaction interface according to the received human-computer interaction instruction, determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface, and sends the human-computer interaction result information to the cloud through the server. In this way, the cloud can execute subsequent RPA instructions based on the received human-computer interaction result information. Based on the scheme of this embodiment, the problem of inconvenience of human intervention in the process of processing RPA tasks in the cloud can be solved. While making full use of the computing power of the cloud to improve the efficiency of RPA task processing, it can also provide necessary human intervention in combination with the proximal device, thereby improving the efficiency and stability of RPA task processing.

[0115] In one embodiment, Figure 3 In the illustrated embodiment, step S204 is further refined and may include the following steps:

[0116] According to the human-computer interaction RPA instructions, interactive prompt information and interactive controls are rendered and displayed to form a human-computer interaction interface, wherein the interactive prompt information is used to prompt the user to perform interactive operations, and the interactive controls are used to respond to the user's interactive operations.

[0117] Specifically, the above-mentioned embodiment has pointed out that the interface configuration information refers to various information required for describing and constructing the human-computer interaction interface. The interface configuration information in this embodiment particularly includes interactive prompt information. Among them, the interactive prompt information is used to prompt the user to perform interactive operations. For example, the interactive prompt information can be image information such as a verification code image and an operation guide image, or text information such as an inquiry sentence and a prompt sentence, or multimedia information such as sound information and animation demonstration information, without limitation.

[0118] In one possible case, the interaction prompt information is obtained by the cloud during the process of executing the RPA instruction before the human-computer interaction RPA instruction, and is filled into the interface configuration information of the human-computer interaction RPA instruction by the cloud.

[0119] In one possible case, the interface configuration information of the human-computer interaction RPA instruction does not directly include the interaction prompt information, but the proximal device obtains the interaction prompt information according to the human-computer interaction RPA instruction.

[0120] The proximal device renders and displays the interactive prompt information and interactive controls according to the human-computer interaction RPA instructions to form a human-computer interaction interface. When rendering and displaying the human-computer interaction interface, the proximal device can be implemented in a variety of ways. For example, a front-end framework such as the React framework or the Vue framework can be used to render and display the human-computer interaction interface; for another example, the hypertext markup language (HTML), CSS, or JavaScript (JS) can be used to render and display the human-computer interaction interface. In addition, the human-computer interaction interface can also be rendered and displayed with the help of a graphics engine such as WebGL (Web Graphics Library). The above implementation method is only a supplementary explanation. In fact, the proximal device can also use a variety of other methods to render and display the human-computer interaction interface, which will not be listed here one by one.

[0121] It can be understood that the human-computer interaction interface at least includes interaction prompt information and interaction controls.

[0122] To facilitate understanding of the human-computer interaction interface involved in this embodiment, the following will be combined with Figure 4 - Figure 6 Please explain.

[0123] See also Figure 4 , Figure 4 is an example schematic diagram of a human-computer interaction interface provided in the embodiments of this specification. Figure 4In the human-computer interaction interface provided, the interactive prompt information 001 includes a verification code image, a verification code input operation prompt statement "Please enter the verification code in the picture", and a button control embedded word "Submit", wherein the verification code image contains the correct verification code "Test", the verification code input operation prompt statement is used to prompt the user to perform a verification code input operation on the verification code input box control, and the button control embedded word is used to prompt the user to click the submit button control; the interactive control 002 includes a verification code input box control and a submit button control. The user performs a verification code input operation on the verification code input box control in the human-computer interaction interface, and clicks the submit button control after the input is completed, and the proximal device can obtain the human-computer interaction result information. It can be understood that the above-mentioned verification code input operation on the verification code input box control can be regarded as a data input operation, and the human-computer interaction result information includes the input data corresponding to the data input operation, representing the verification code entered by the user.

[0124] See also Figure 5 , Figure 5 is an example schematic diagram of a human-computer interaction interface provided in the embodiments of this specification. Figure 5 In the provided human-computer interaction interface, the interactive prompt information 001 includes a check operation prompt statement "Please check the data to be exported", a check box prompt word "A data", "B data", "C data", "D data", "E data", "F data", and a button control embedded word "Submit", wherein the check operation prompt statement is used to prompt the user to check the check box control, the check box prompt word is used to indicate the data to be exported corresponding to the check box control, and the button control embedded word is used to prompt the user to click the submit button control; the interactive control 002 includes a check box control and a submit button control, wherein different check box controls correspond to different data to be exported. The user checks at least one check box control in the human-computer interaction interface, and clicks the submit button control after the check operation is completed, and the near-end device can obtain the human-computer interaction result information. It can be understood that the above-mentioned check operation on the check box control can be regarded as a data input operation, and the human-computer interaction result information includes the input data corresponding to the data input operation, which represents the data that the user has checked to determine to be exported.

[0125] See also Figure 6 , Figure 6 is an example schematic diagram of a human-computer interaction interface provided in an embodiment of this specification; Figure 6In the provided human-computer interaction interface, the interactive prompt information 001 includes a click operation prompt statement "The following items are expected to be unprocessed... Please ask whether to send a reminder message to the corresponding processor", and a button control embedded word "yes" and "no", wherein the click operation prompt statement is used to prompt the user to click the first decision button control or the second decision button control, and the button control embedded word is used to prompt the user to click the first decision button control to confirm sending the message (corresponding to the button control embedded word "yes"), and prompt the user to click the second decision button control to confirm not to send the message (corresponding to the button control embedded word "no"); the interactive control 002 includes the first decision button control and the second decision button control. The user clicks the first decision button control or the second decision button control in the human-computer interaction interface, and the near-end device can obtain the human-computer interaction result information. It can be understood that the above-mentioned click operation on the first decision button control or the second decision button control can be regarded as a decision operation, and the human-computer interaction result information includes the decision data corresponding to the decision operation, which indicates whether the user determines whether to send the message.

[0126] In this embodiment, the proximal device renders and displays interactive prompt information and interactive controls according to the human-computer interaction RPA instructions to form a human-computer interaction interface, wherein the interactive prompt information and interactive controls provide necessary support for the user's interactive operations, effectively improving the convenience of manual intervention in the RPA task processing process.

[0127] See also Figure 7 , which is a flowchart of a task processing method provided in the embodiment of this specification. Figure 7 As shown, the method of the embodiment of this specification is applied to the server and may include the following steps S302 to S306.

[0128] S302, receiving a start instruction of a target RPA task sent by a proximal device;

[0129] S304, determining an execution end from a local device and a cloud according to the start instruction of the target RPA task;

[0130] S306: Send the RPA instruction set of the target RPA task to the execution end, so that the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, and the proximal device obtains and displays the execution result of the target RPA task.

[0131] Specifically, first, the user performs a start operation of the target RPA task on the proximal device, and accordingly, the proximal device determines the start instruction of the target RPA task in response to the start operation of the target RPA task. After determining the start instruction of the target RPA task, the proximal device sends the start instruction of the target RPA task to the server.

[0132] Accordingly, the server receives the start instruction of the target RPA task, determines the execution end from the proximal device and the cloud according to the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end. The RPA instruction set of the target RPA task can be pre-stored by the server, or generated by the server in real time according to the target RPA task, and the RPA instruction set of the target RPA task includes at least one RPA instruction of the target RPA task.

[0133] In one possible case, the proximal device is determined as the execution end. The proximal device receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, and obtains the execution result of the target RPA task. In this case, the proximal device can first obtain the execution result of the target RPA task stored locally, and then display the execution result of the target RPA task.

[0134] In one possible scenario, the cloud is determined as the execution end. The cloud receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, obtains the execution result of the target RPA task, and then sends the execution result of the target RPA task to the near-end device through the server. In this case, the near-end device can receive the execution result of the target RPA task and then display the execution result of the target RPA task.

[0135] It should be noted that for details not explained in this embodiment, please refer to Figure 2 The embodiment shown is not described in detail here.

[0136] In this embodiment, the proximal device responds to the start operation of the target RPA task, determines and sends the start instruction of the target RPA task to the server; the server determines the execution end from the proximal device and the cloud according to the start instruction of the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end; the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task; the proximal device obtains and displays the execution result of the target RPA task. In this way, by introducing the server, the execution end can be flexibly determined from the proximal device and the cloud according to the start instruction of the target RPA task, which significantly improves the flexibility of RPA task processing, is not limited to the fixed processing of RPA tasks by the proximal device or the cloud alone, and effectively meets the diversified processing needs of RPA tasks.

[0137] In one embodiment, based on Figure 7 In the embodiment shown, the server includes multiple units to support it to implement multiple functions. Figure 8 , Figure 8This is an example schematic diagram of the unit structure of a server provided in an embodiment of this specification. The server includes a monitoring unit, a decision unit, a scheduling unit, and an execution unit. The scheduling unit includes an RPA executor resource pool. The following is an introduction to the purpose of each unit of the server:

[0138] Monitoring unit: responsible for real-time monitoring of the execution status of RPA tasks. In actual applications, RPA tasks may encounter various unexpected situations, such as network delays, insufficient system resources, or instruction execution errors. By collecting and analyzing the status information fed back by the execution end (whether it is a local device or the cloud), the monitoring unit can promptly discover and report any potential problems, providing a basis for subsequent decision-making and scheduling. In addition, the monitoring unit may also have the ability to automatically handle certain common problems, such as restarting tasks, adjusting resource allocation, etc., to further improve the stability and reliability of the system.

[0139] Decision-making unit: used to receive the start instruction of the target RPA task sent by the proximal device; determine the execution end from the proximal device and the cloud according to the start instruction of the target RPA task. In a possible implementation, the decision-making unit determines the authority level of the target RPA task according to the start instruction of the target RPA task, and determines the execution end from the proximal device and the cloud according to the authority level of the target RPA task, so as to ensure that the proximal device processes RPA tasks with higher authority levels, and the cloud processes RPA tasks with lower authority levels, thereby improving the security of RPA task processing; in a possible implementation, the decision-making unit determines the resource occupancy level of the target RPA task according to the start instruction of the target RPA task, and determines the execution end from the proximal device and the cloud according to the resource occupancy level of the target RPA task, so as to ensure that the proximal device processes RPA tasks with less resource occupancy, and the cloud processes RPA tasks with more resource occupancy, thereby improving the stability and efficiency of RPA task processing. In addition, the decision-making unit can also determine the execution end in the proximal device and the cloud according to other information provided by the start instruction of the target RPA task, so as to realize the flexible flow of RPA tasks, thereby ensuring that RPA tasks can run efficiently in the most suitable environment.

[0140] Scheduling unit: An RPA executor resource pool is provided. In one case, the RPA executor resource pool records the status of all RPA executors in the cloud; in another case, the RPA executor resource pool records the status of all RPA executors in the cloud and proximal devices. After the decision unit determines the execution end, the scheduling unit is responsible for selecting a suitable RPA executor from the RPA executor resource pool to execute each RPA instruction in the RPA instruction set of the target RPA task. In addition, the server can also receive the heartbeat signal sent by the cloud in real time. The heartbeat signal contains the status information of the RPA executor in the cloud. The scheduling unit of the server parses the heartbeat signal to obtain the status information of the RPA executor in the cloud, and maintains the RPA executor resource pool according to the status information of the RPA executor in the cloud, so that the RPA executor resource pool reflects the status of the RPA executor in the cloud in real time.

[0141] Execution unit: Mainly responsible for data forwarding during RPA task processing. For example, after the scheduling unit determines the appropriate RPA executor, the execution unit sends the RPA instruction set of the target RPA task to the execution end. For another example, when the cloud is the execution end, the execution unit receives the human-computer interaction instruction sent by the cloud, and forwards the human-computer interaction instruction to the proximal device, and then the execution unit receives the human-computer interaction result information sent by the proximal device, and forwards the human-computer interaction result information to the cloud; for another example, when the cloud is the execution end, the execution unit receives the execution result of the target RPA task sent by the cloud, and forwards the execution result of the target RPA task to the proximal device.

[0142] In this embodiment, the server not only improves the stability and reliability of RPA task processing through close collaboration of the monitoring unit, decision unit, scheduling unit and execution unit, but also ensures that RPA tasks can be dynamically allocated between proximal devices and the cloud according to actual needs, thereby meeting the needs of diverse transaction scenarios.

[0143] In one embodiment, Figure 7 In the illustrated embodiment, step S304 is further refined and may include the following steps:

[0144] Determine the permission level of the target RPA task based on the start instruction of the target RPA task;

[0145] When the permission level of the target RPA task is higher than the preset reference permission level, the near-end device is determined as the execution end;

[0146] When the authority level of the target RPA task is not higher than the preset reference authority level, the cloud is determined as the execution end.

[0147] Specifically, this embodiment proposes to characterize the importance of the permissions required for RPA tasks by permission level, and different RPA tasks may correspond to different permission levels. Among them, the higher the permission level, the more important (or more sensitive) the permissions required for the corresponding RPA task are. Therefore, considering that the cloud environment is more vulnerable to external attacks and unauthorized access than the proximal device, or the process of data interaction between the proximal device and the cloud is prone to data eavesdropping, RPA tasks with higher permission levels are more suitable for processing by proximal devices.

[0148] To this end, after receiving the start instruction of the target RPA task, the server will determine the permission level of the target RPA task according to the start instruction of the target RPA task. In one possible implementation, the start instruction of the target RPA task carries permission level information, and the server parses the corresponding permission level information from the start instruction of the target RPA task to determine the permission level of the target RPA task; in one possible implementation, the server stores the mapping relationship between the RPA task and the permission level, and queries the mapping relationship according to the target RPA task to determine the permission level of the target RPA task.

[0149] Then, the server obtains the preset reference permission level, compares the permission level of the target RPA task with the reference permission level, and obtains the comparison result. The reference permission level is a preset threshold used to determine whether the RPA task is suitable for execution on the local device or in the cloud. It represents the boundary of a permission level. When the permission level of the RPA task is higher than this limit, the RPA task will be executed on the local device first for security and privacy protection; and when the permission level of the RPA task is not higher than this limit, in order to make full use of the resources and computing power of the cloud, the RPA task will be executed on the cloud first.

[0150] Therefore, if the comparison result indicates that the authority level of the target RPA task is higher than the reference authority level, then the proximal device is determined as the execution end; if the comparison result indicates that the authority level of the target RPA task is not higher than the reference authority level, then the cloud is determined as the execution end.

[0151] To facilitate understanding of this embodiment, an example is provided below:

[0152] In a specific numerical example, Figure 7 Step S304 in the illustrated embodiment is detailed as follows:

[0153] Assume that there are three RPA tasks, namely RPA Task A, RPA Task B, and RPA Task C, and the corresponding permission levels are 4, 2, and 6, respectively. At the same time, the preset reference permission level is set to 3.

[0154] When the server receives the start instruction of RPA task A, it first parses the start instruction of RPA task A to find that the permission level of RPA task A is 4 (or obtains it by querying the stored mapping relationship). Then, the server compares the permission level 4 of RPA task A with the reference permission level 3. Since 4 is greater than 3, the server determines that the permission level of RPA task A is higher, so for security and privacy protection considerations, the near-end device is determined as the execution end of RPA task A.

[0155] Similarly, when the server receives the start instruction of RPA task B, it determines that the permission level of RPA task B is 2. Comparing the permission level 2 of RPA task B with the reference permission level 3, it is found that 2 is not greater than 3. Therefore, in order to fully utilize the resources and computing power of the cloud, the server determines the cloud as the execution end of RPA task B.

[0156] Similarly, when the server receives the start instruction of RPA task C, it determines that the permission level of RPA task C is 6. The permission level 6 of RPA task C is compared with the reference permission level 3. Since 6 is greater than 3, the server also determines the near-end device as the execution end of RPA task C for security and privacy protection considerations.

[0157] In this embodiment, by comparing the permission level of the target RPA task with the preset reference permission level, the server can determine whether the RPA task contains sensitive or important permissions, thereby deciding whether to execute it by the proximal device or the cloud. This allocation strategy based on permission level ensures that RPA tasks with high permission levels are executed in a relatively safer proximal device environment, effectively reducing the risk of data leakage and unauthorized access. At the same time, for RPA tasks with lower permission levels, the resources and computing power of the cloud are fully utilized to improve the efficiency of task processing. In summary, this embodiment not only enhances the security and privacy protection of RPA task execution, but also optimizes resource utilization, achieving a dual improvement in security and efficiency.

[0158] In one embodiment, when the cloud is determined as the execution end, Figure 7 In the illustrated embodiment, after step S306, the following steps may also be included:

[0159] Determine the status of each RPA executor in the cloud, where the status of the RPA executor includes a busy state and an idle state;

[0160] Determine the target RPA executor from the idle RPA executors in the cloud;

[0161] An RPA executor call instruction is generated according to the target RPA executor, and the RPA executor call instruction is sent to the cloud, wherein the RPA executor call instruction is used to instruct the cloud to call the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task.

[0162] Specifically, in the RPA task processing flow, after the cloud is determined as the execution end, the server needs to further manage the RPA executor resources on the cloud to ensure that the target RPA task can be executed efficiently and accurately.

[0163] First, the server needs to determine the status of each RPA executor in the cloud. The RPA executor is an entity in the cloud used to execute RPA instructions, and its status may include busy and idle. Among them, the busy state means that the executor is currently processing other RPA tasks and cannot accept new RPA tasks immediately; or the busy state means that the number of RPA tasks currently processed by the executor has reached the upper limit and cannot accept new RPA tasks immediately; the idle state means that the executor currently has no RPA tasks to execute and can accept new RPA tasks; or the idle state means that the RPA tasks currently processed by the executor have not reached the upper limit and can accept new RPA tasks.

[0164] In order to determine the status of each RPA executor on the cloud, in a possible implementation, the server communicates with the cloud to query the status of all RPA executors on the cloud; in a possible implementation, the server can also receive a heartbeat signal sent by the cloud in real time, and the heartbeat signal includes the status information of the RPA executors on the cloud. The scheduling unit of the server parses the heartbeat signal to obtain the status information of the RPA executors on the cloud, and maintains the RPA executor resource pool according to the status information of the RPA executors on the cloud, so that the RPA executor resource pool reflects the status of the RPA executors on the cloud in real time, and directly queries the status of all RPA executors on the cloud from the RPA executor resource pool when necessary.

[0165] After determining the status of each RPA executor in the cloud, the server needs to determine at least one target RPA executor from the RPA executors in the idle state. For example, the server can randomly select at least one target RPA executor from the RPA executors in the idle state; for another example, the server can sort or filter the RPA executors in the idle state according to the performance, load capacity, historical execution records and other parameters of the RPA executors in the idle state, so as to select at least one executor suitable for executing the target RPA task as the target RPA executor.

[0166] After determining the target RPA executor, the server needs to generate an RPA executor call instruction based on the target RPA executor. The RPA executor call instruction is sent by the server to the cloud, and is used to instruct the cloud to call the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task. Specifically, the RPA executor call instruction may contain the identification information of the target RPA executor, the identification information of the RPA instruction set to be executed, execution parameters and other information. This information enables the cloud to accurately call the target RPA executor and execute the corresponding RPA instructions according to the instructions.

[0167] Finally, the server sends the generated RPA executor call instruction to the cloud. Correspondingly, after receiving the RPA executor call instruction, the cloud will call the target RPA executor according to the information in the RPA executor call instruction and start executing each RPA instruction in the RPA instruction set of the target RPA task.

[0168] For easier understanding of this embodiment, please refer to Fig. 9 , Fig. 9 It is an example schematic diagram of a cloud-based RPA executor call provided in an embodiment of this specification. As an example, a cloud-based virtual machine can run multiple processes at the same time, each process corresponds to an RPA task, and each process involves at least one RPA executor. Assuming that the target RPA task corresponds to process 1, then the RPA executor 1-1, RPA executor 1-2, ..., RPA executor 1-x involved in process 1, a total of x RPA executors are used to execute each RPA instruction in the RPA instruction set of the target RPA task. Similarly, assuming that the target RPA task corresponds to process n, then the RPA executor 2-1, RPA executor 2-2, ..., RPA executor 2-y involved in process n, a total of y RPA executors are used to execute each RPA instruction in the RPA instruction set of the target RPA task. It should be noted that the above-mentioned virtual machine can run on any operating system such as Windows, Linux, macOS, etc., without limitation.

[0169] In this embodiment, by determining the status of each RPA executor in the cloud in real time, the server can accurately grasp the availability of the RPA executor, avoiding resource waste and conflict. Secondly, the target executor is intelligently selected from the idle RPA executors, which not only improves the rationality of resource allocation, but also ensures the efficiency and quality of task execution. Finally, by generating and sending RPA executor call instructions, the server can accurately command the cloud to execute the target RPA task, realizing remote control and automated processing of tasks.

[0170] See also Fig.10 , which is a flowchart of a task processing method provided in the embodiment of this specification. Fig.10 As shown, the method of the embodiment of this specification is applied to the cloud and may include the following steps S402 to S404.

[0171] S402, receiving an RPA instruction set of a target RPA task sent by the server, wherein the RPA instruction set of the target RPA task is sent to the cloud when the server determines that the cloud is the execution end from the proximal device and the cloud according to the start instruction of the target RPA task;

[0172] S404, executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, so that the proximal device can obtain and display the execution result of the target RPA task.

[0173] Specifically, first, the user performs a start operation of the target RPA task on the proximal device, and accordingly, the proximal device determines the start instruction of the target RPA task in response to the start operation of the target RPA task. After determining the start instruction of the target RPA task, the proximal device sends the start instruction of the target RPA task to the server.

[0174] Accordingly, the server receives the start instruction of the target RPA task, determines the cloud as the execution end from the proximal device and the cloud according to the target RPA task, and sends the RPA instruction set of the target RPA task to the cloud. The RPA instruction set of the target RPA task can be pre-stored by the server, or generated by the server in real time according to the target RPA task, and the RPA instruction set of the target RPA task includes at least one RPA instruction of the target RPA task.

[0175] The cloud receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, obtains the execution result of the target RPA task, and then sends the execution result of the target RPA task to the near-end device through the server. Correspondingly, the near-end device receives the execution result of the target RPA task and then displays the execution result of the target RPA task.

[0176] It should be noted that for details not explained in this embodiment, please refer to Figure 2 The embodiment shown is not described in detail here.

[0177] In this embodiment, the proximal device responds to the start operation of the target RPA task, determines and sends the start instruction of the target RPA task to the server; the server determines the execution end from the proximal device and the cloud according to the start instruction of the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end; the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task; the proximal device obtains and displays the execution result of the target RPA task. In this way, by introducing the server, the execution end can be flexibly determined from the proximal device and the cloud according to the start instruction of the target RPA task, which significantly improves the flexibility of RPA task processing, is not limited to the fixed processing of RPA tasks by the proximal device or the cloud alone, and effectively meets the diversified processing needs of RPA tasks.

[0178] See also Fig.11 , which is a flowchart of executing RPA instructions in the embodiment of this specification. Fig.11 As shown, the method of the embodiment of this specification may include the following steps S502 to S508, where steps S502 to S508 are used as Fig.10 The illustrated embodiment further refines step S404.

[0179] S502, determining the execution order of each RPA instruction in the RPA instruction set of the target RPA task;

[0180] S504, traversing each RPA instruction in sequence according to the execution order of each RPA instruction in the RPA instruction set of the target RPA task;

[0181] S506, executing the current RPA instruction among the traversed RPA instructions;

[0182] S508, if the RPA instruction with the last execution order in the RPA instructions is executed, the execution result of the target RPA task is obtained, and the execution result of the target RPA task is sent to the proximal device through the server, so that the proximal device receives and displays the execution result of the target RPA task.

[0183] Specifically, an RPA instruction set usually contains multiple RPA instructions, each of which corresponds to specific steps, such as data input, data processing, data interaction, etc. These RPA instructions need to be executed in a specific order to ensure that the RPA task can be completed correctly. After receiving the RPA instruction set of the target RPA task, the cloud needs to determine the execution order of each RPA instruction in the RPA instruction set of the target RPA task. Among them, the RPA instruction includes an execution order parameter, which is used to characterize the execution order of the RPA instruction, that is, the cloud can determine the execution order of the RPA instruction according to the execution order parameter in the RPA instruction.

[0184] Furthermore, the cloud traverses each RPA instruction in the RPA instruction set of the target RPA task in the order in which they are executed. The traversal process is actually an iterative process. The cloud checks each RPA instruction in the RPA instruction set one by one and processes them in the order in which they are executed, ensuring that each RPA instruction can be correctly identified and executed without omission or confusion.

[0185] During the traversal process, for the current RPA instruction in each traversed RPA instruction, the cloud simulates human operations to execute corresponding steps according to the specific content and parameters of the current RPA instruction, such as data input, data processing, data interaction, etc. It can be understood that as the cloud continues to traverse each RPA instruction, the current RPA instruction can be any traversed RPA instruction in the RPA instruction set.

[0186] Finally, the cloud will determine whether the last RPA instruction in the execution order has been executed. If so, it means that the target RPA task has been fully executed according to the preset process, and the cloud will get the execution result of the target RPA task. The cloud will send the execution result of the target RPA task to the near-end device through the server. Furthermore, the near-end device can receive the execution result of the target RPA task and then display the execution result of the target RPA task.

[0187] In this embodiment, by determining the execution order of RPA instructions, the cloud can process each instruction in an orderly manner, avoiding confusion and errors in the execution of RPA instructions. Secondly, the process of traversing each RPA instruction in turn ensures that each RPA instruction can be correctly identified and executed, improving the integrity and accuracy of task execution. For each current RPA instruction, the cloud implements automated processing according to the current RPA instruction, improving work efficiency. Finally, after the last RPA instruction is executed, the cloud promptly sends the execution result of the target RPA task to the proximal device through the server, so that the proximal device can obtain and display the execution result of the target RPA task in real time. In summary, this embodiment optimizes the processing process of RPA tasks and improves the execution efficiency and accuracy of RPA tasks.

[0188] In one embodiment, Fig.11 In the illustrated embodiment, step S506 is further refined and may include the following steps:

[0189] For the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is a human-computer interaction RPA instruction, the human-computer interaction RPA instruction is sent to the proximal device through the server, and the proximal device renders and displays the human-computer interaction interface according to the human-computer interaction RPA instruction, determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface, and sends the human-computer interaction result information to the cloud through the server;

[0190] Receive human-computer interaction result information.

[0191] Specifically, the RPA instruction includes a type parameter, and the type parameter includes at least one of an operation type and an interaction type. The operation type is used to define the specific operation performed by the RPA instruction, such as "open a URL" and "fill in an input box", etc. The interaction type is used to indicate the type of RPA instruction that requires human intervention, which is used to achieve human-computer collaboration. It can be understood that an RPA instruction with an interaction type as a type parameter is a human-computer interaction RPA instruction.

[0192] In the process of executing each RPA instruction in sequence on the cloud, some RPA instructions may be human-computer interaction RPA instructions. Since the cloud cannot be directly operated by the user or lacks the corresponding authority, it cannot complete the interactive actions required by the human-computer interaction RPA instructions alone. Therefore, for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is a human-computer interaction RPA instruction, the way to execute the human-computer interaction RPA instruction on the cloud is to send the human-computer interaction RPA instruction to the proximal device through the server.

[0193] Accordingly, the proximal device receives the human-computer interaction RPA instruction sent by the cloud through the server, and then renders and displays the human-computer interaction interface according to the human-computer interaction RPA instruction. The user can interact with the interactive controls in the human-computer interaction interface. Accordingly, the proximal device determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface. After obtaining the human-computer interaction result information, the proximal device sends the human-computer interaction result information to the cloud through the server. Accordingly, the cloud receives the human-computer interaction result information and executes subsequent RPA instructions according to the human-computer interaction result information.

[0194] In this embodiment, the cloud can accurately determine whether the current RPA instruction is a human-computer interaction instruction that requires manual intervention. For human-computer interaction RPA instructions, the cloud sends the instruction to the proximal device through the server. The proximal device renders and displays the human-computer interaction interface based on the received human-computer interaction instruction, determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface, and sends the human-computer interaction result information to the cloud through the server. In this way, the cloud can execute subsequent RPA instructions based on the received human-computer interaction result information. Based on the solution of this embodiment, the problem of inconvenience of manual intervention in the process of processing RPA tasks on the cloud can be solved. While making full use of the computing power of the cloud to improve the efficiency of RPA task processing, it can also provide necessary manual intervention in combination with the proximal device, thereby improving the efficiency and stability of RPA task processing.

[0195] In one embodiment, Fig.11 In the illustrated embodiment, step S506 is further refined and may include the following steps:

[0196] For the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interactive predecessor RPA instruction whose execution order is before the human-computer interaction RPA instruction, the interactive prompt information is obtained according to the interactive predecessor RPA instruction, and the interactive prompt information is filled into the human-computer interaction RPA instruction, wherein the interactive prompt information is used to prompt the user to perform interactive operations in the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction.

[0197] Specifically, the aforementioned embodiment has pointed out that the RPA instruction whose type parameter is the interactive type is the human-computer interaction RPA instruction. The interactive pre-RPA instruction involved in this embodiment does not belong to the human-computer interaction RPA instruction, that is, the type parameter of the interactive pre-RPA instruction is the operation type.

[0198] In the process of processing the target RPA task, in order to ensure the smooth progress of human-computer interaction, it is sometimes necessary to execute some pre-interaction instructions before the actual human-computer interaction instructions. The purpose of the pre-interaction instructions is to obtain necessary information or prepare the corresponding environment so as to provide users with correct prompts and guidance in the subsequent human-computer interaction.

[0199] In the process of traversing each RPA instruction, if the current RPA instruction encountered by the cloud is an interactive pre-RPA instruction whose execution order is before the human-computer interaction RPA instruction, the interactive pre-RPA instruction needs to be executed. Specifically, the interactive prompt information is obtained according to the interactive pre-RPA instruction, and the interactive prompt information is filled into the interface configuration information of the human-computer interaction RPA instruction. This process is actually a dynamic modification or enhancement of the human-computer interaction RPA instruction, so that it can contain more contextual information or user guidance in subsequent execution. Among them, the interactive prompt information is used to prompt the user to perform interactive operations in the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction. For example, the interactive prompt information can be image information such as a verification code image and an operation guide image, or text information such as an inquiry statement and a prompt statement, or multimedia information such as sound information and animation demonstration information, without limitation.

[0200] To facilitate understanding of the present embodiment, an example is provided below: Assume that the human-computer interaction instruction is used to provide a proximal device with a rendered and displayed human-computer interaction interface, and the user needs to enter the verification code corresponding to the verification code image in the human-computer interaction interface. Then, when the cloud executes the interactive pre-RPA instruction before the human-computer interaction instruction, it can obtain the verification code image as the interaction prompt information, and fill the interaction prompt information into the interface configuration information of the human-computer interaction RPA instruction. The human-computer interaction interface subsequently rendered and displayed by the proximal device based on the interface configuration information of the human-computer interaction RPA instruction can include the verification code image, and the verification code image provides reference content for the user to enter the verification code.

[0201] In this embodiment, by executing the interactive pre-command before the human-computer interaction RPA command, the cloud can obtain the necessary interactive prompt information and fill it into the human-computer interaction RPA command. This process not only enriches the content of the human-computer interaction interface, but also provides users with clearer and more accurate interaction guidance.

[0202] In one embodiment, Fig.11 In the illustrated embodiment, step S506 is further refined and may include the following steps:

[0203] For the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interaction post-RPA instruction whose execution order is after the human-computer interaction RPA instruction, the interaction post-RPA instruction is executed according to the received human-computer interaction result information, wherein the human-computer interaction result information is the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction, and is determined in response to the interaction operation on the human-computer interaction interface and sent to the cloud through the server.

[0204] Specifically, the following embodiments have pointed out that the RPA instruction whose type parameter is the interactive type is the human-computer interaction RPA instruction. The interactive post-RPA instruction involved in this embodiment does not belong to the human-computer interaction RPA instruction, that is, the type parameter of the interactive post-RPA instruction is the operation type.

[0205] In the process of processing the target RPA task, in order to ensure the continuity of the automation process, it is sometimes necessary to execute some post-interaction instructions after the actual human-computer interaction instructions. Among them, the post-interaction instructions use the human-computer interaction result information as input parameters.

[0206] When the cloud is traversing each RPA instruction, if the current RPA instruction encountered is an interactive post-RPA instruction whose execution order is after the human-computer interaction RPA instruction, it is necessary to execute the interactive post-RPA instruction according to the received human-computer interaction result information. Specifically, the human-computer interaction result information may include input data corresponding to the data input operation and / or decision data corresponding to the decision operation.

[0207] To facilitate understanding of the present embodiment, an example is provided below: Assume that the human-computer interaction instruction is used to provide a near-end device to render and display a human-computer interaction interface, and the user needs to enter the verification code corresponding to the verification code image in the human-computer interaction interface. Then, the human-computer interaction result information received by the cloud includes the input data corresponding to the data input operation, that is, the verification code entered by the user. Furthermore, the cloud executes the post-interaction RPA instruction according to the verification code entered by the user, and fills the verification code entered by the user into the corresponding verification code input box to complete the verification.

[0208] This embodiment refines step S506. After the human-computer interaction RPA instruction is executed, the cloud can automatically execute the post-interaction RPA instruction based on the interaction result information provided by the user, thereby achieving seamless connection of the automation process and improving the processing efficiency of the RPA task.

[0209] In one embodiment, Fig.10 In the illustrated embodiment, after step S402 and before step S404, the following steps may also be included:

[0210] Receive an RPA executor call instruction sent by the server, wherein the RPA executor call instruction is generated by the server according to a target RPA executor in the cloud, and the target RPA executor is determined by the server from RPA executors in an idle state in the cloud;

[0211] right Fig.10 In the illustrated embodiment, step S404 is further refined and may include the following steps:

[0212] According to the RPA executor calling instruction, the target RPA executor is called to execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0213] Specifically, first, the server needs to determine the status of each RPA executor in the cloud. The RPA executor is an entity in the cloud used to execute RPA instructions, and its status may include busy and idle. Among them, the busy state means that the executor is currently processing other RPA tasks and cannot accept new RPA tasks immediately; or, the busy state means that the number of RPA tasks currently processed by the executor has reached the upper limit and cannot accept new RPA tasks immediately; the idle state means that the executor currently has no RPA tasks to execute and can accept new RPA tasks; or the idle state means that the RPA tasks currently processed by the executor have not reached the upper limit and can accept new RPA tasks.

[0214] After determining the status of each RPA executor in the cloud, the server needs to determine at least one target RPA executor from the RPA executors in the idle state. After determining the target RPA executor, the server generates an RPA executor call instruction based on the target RPA executor. Among them, the RPA executor call instruction is used to instruct the cloud to call the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task. Specifically, the RPA executor call instruction may include identification information of the target RPA executor, identification information of the RPA instruction set to be executed, execution parameters and other information. This information enables the cloud to accurately call the target RPA executor and execute the corresponding RPA instructions according to the instructions.

[0215] The server sends the generated RPA executor call instruction to the cloud. Correspondingly, when the cloud receives the RPA executor call instruction sent by the server, it will enter a series of processing procedures to ensure that the target RPA executor can be called correctly and start processing the instruction.

[0216] First, the cloud will parse the received RPA executor call instructions to extract the identification information of the target RPA executor, the identification information of the RPA instruction set to be executed, and the execution parameters.

[0217] Next, the cloud will locate the specific RPA executor based on the identification information of the target RPA executor. In the cloud resource pool, there may be multiple RPA executors, each with its own unique identification information. By matching the identification information, the cloud can accurately find the target RPA executor that needs to be called.

[0218] After finding the target RPA executor, the cloud will check the current status of the target RPA executor. Although the server has determined that the RPA executor is in the idle state in the previous step, the cloud will usually confirm again before the actual call to avoid conflicts caused by status update delays or errors. If the target RPA executor is still in the idle state, the cloud will proceed to the next step; if the target RPA executor has become busy, the cloud may return an error message to the server or try to call other RPA executors that are in the idle state.

[0219] After confirming that the target RPA executor is in idle state, the cloud obtains the RPA instruction set of the target RPA task to be executed based on the identification information of the RPA instruction set, and calls the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0220] For easier understanding of this embodiment, please refer to Fig. 9 , Fig. 9 This is an example diagram of a cloud-based RPA executor call provided in an embodiment of this specification. As an example, a virtual machine in the cloud can run multiple processes at the same time, each process corresponds to an RPA task, and each process involves at least one RPA executor. Assuming that the RPA executor call instruction indicates that the target RPA executor is RPA executor 1-1, RPA executor 1-2, ..., RPA executor 1-x, a total of x RPA executors, then the cloud can create process 1, and call RPA executor 1-1, RPA executor 1-2, ..., RPA executor 1-x through process 1 to execute each RPA instruction in the RPA instruction set of the target RPA task. Similarly, assuming that the RPA executor call instruction indicates that the target RPA executors are RPA executor 2-1, RPA executor 2-2, ..., RPA executor 2-y, a total of y RPA executors, then the cloud can create process n, and call RPA executor 2-1, RPA executor 2-2, ..., RPA executor 2-y through process n to execute each RPA instruction in the RPA instruction set of the target RPA task.

[0221] In this embodiment, the real-time monitoring and intelligent scheduling of the status of the cloud RPA executor by the server ensures that the RPA tasks can be quickly and accurately assigned to the RPA executor in the idle state, thereby improving the response speed and execution efficiency of RPA task processing. At the same time, it ensures that the cloud can accurately locate and execute the target RPA task after receiving the RPA executor call instruction, avoiding resource conflicts and delays in task processing. In addition, this embodiment also supports the parallel calling of multiple RPA executors, and realizes multi-threaded processing of RPA tasks by creating multiple processes, further improving the throughput and performance of RPA task processing. In summary, this embodiment improves the processing efficiency and accuracy of RPA tasks by optimizing the calling process and task processing method of the RPA executor.

[0222] Based on the introduction of the above task processing method embodiment, the following will be combined with Fig.12 - Fig.15 , presents examples of interactions between proximal devices, servers, and the cloud.

[0223] See also Fig.12 , Fig.12 This is an interactive schematic diagram of a proximal device executing instructions provided in an embodiment of this specification.

[0224] Specifically, first, the user performs a start operation of the target RPA task on the proximal device, and accordingly, the proximal device determines the start instruction of the target RPA task in response to the start operation of the target RPA task. After determining the start instruction of the target RPA task, the proximal device sends the start instruction of the target RPA task to the server.

[0225] Accordingly, the server receives the start instruction of the target RPA task, determines the proximal device as the execution end from the proximal device and the cloud according to the target RPA task, and sends the RPA instruction set of the target RPA task to the proximal device. The RPA instruction set of the target RPA task can be pre-stored by the server, or generated by the server in real time according to the target RPA task, and the RPA instruction set of the target RPA task includes at least one RPA instruction of the target RPA task.

[0226] The proximal device receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, and obtains the execution result of the target RPA task. Then, the proximal device obtains the execution result of the target RPA task locally and displays the execution result of the target RPA task.

[0227] See also Fig.13 , Fig.13 It is an interactive schematic diagram of a proximal device executing instructions in a logistics information query scenario provided by an embodiment of this specification.

[0228] Specifically, when the target RPA task is a logistics information query task, the user first performs a start operation of the logistics information query task on the proximal device, and accordingly, the proximal device responds to the start operation of the logistics information query task and determines the start instruction of the logistics information query task. After determining the start instruction of the logistics information query task, the proximal device sends the start instruction of the logistics information query task to the server.

[0229] Correspondingly, the server receives the start instruction of the logistics information query task, determines the proximal device as the execution end from the proximal device and the cloud according to the logistics information query task, and sends the RPA instruction set of the logistics information query task to the proximal device. Among them, the RPA instruction set of the logistics information query task can be pre-stored by the server, or it can be generated by the server in real time according to the logistics information query task, and the RPA instruction set of the logistics information query task includes RPA instructions 1 to RPA instructions 8 of the logistics information query task.

[0230] The proximal device will receive the RPA instruction set of the logistics information query task sent by the server, and execute each RPA instruction in the RPA instruction set of the logistics information query task in sequence to obtain the execution result of the logistics information query task. The execution result of the logistics information query task is the logistics information corresponding to the logistics ID (the unique identifier of the logistics order) to be queried (used to indicate the current status of the logistics order).

[0231] The RPA instructions in the RPA instruction set for the near-end device to perform the logistics information query task are as follows:

[0232] The near-end device executes RPA instruction 1 to open the logistics website. Specifically, the near-end device automatically navigates to the logistics website URL specified by RPA instruction 1 by calling the system browser or built-in browser component, ensuring that subsequent logistics information query operations can be performed in the correct web page environment.

[0233] The near-end device executes RPA instruction 2 to determine the logistics ID input box. Specifically, the near-end device uses the page element recognition capability of the RPA technology to locate the logistics ID input box on the logistics query page to prepare for subsequent input operations.

[0234] The near-end device executes RPA instruction 3 and inputs the logistics ID to be queried into the logistics ID input box. Specifically, the near-end device inputs the logistics ID string provided by RPA instruction 3 into the previously located logistics ID input box character by character by simulating keyboard input to ensure that the information is accurate.

[0235] The near-end device executes RPA instruction 4 and clicks the query button control to display the verification code input interface. Specifically, after the logistics ID is entered, the near-end device automatically triggers the operation of clicking the query button and jumps to display the verification code input interface.

[0236] The near-end device executes RPA instruction 5, and in response to the operation, inputs the verification code into the verification code input box in the verification code input interface. Specifically, the user manually inputs the verification code into the verification code input box in the verification code input interface to pass the verification mechanism of the website.

[0237] The near-end device executes RPA instruction 6 and clicks the confirmation button control. Specifically, after the verification code is correctly entered, the near-end device automatically clicks the confirmation button control, submits the query request, and waits for the server to return the query result.

[0238] The near-end device executes RPA instruction 7 and waits for the query result page to be rendered and displayed. Since the web query result may take some time to load, the near-end device will suspend the execution of subsequent instructions at this stage until it detects that the query result page is completely loaded and displayed.

[0239] The near-end device executes RPA instruction 8 to determine the logistics information corresponding to the logistics ID to be queried from the query result page. Specifically, the near-end device uses the page parsing capability of RPA to extract specific logistics information matching the input logistics ID from the query result page, such as the package location, estimated arrival time, etc., for the user to view or further process.

[0240] Finally, the proximal device obtains the logistics information corresponding to the logistics ID to be queried locally, and then displays the logistics information corresponding to the logistics ID to be queried.

[0241] See also Fig.14 , Fig.14 It is an interactive schematic diagram of a cloud execution instruction provided in an embodiment of this specification.

[0242] Specifically, first, the user performs a start operation of the target RPA task on the proximal device, and accordingly, the proximal device determines the start instruction of the target RPA task in response to the start operation of the target RPA task. After determining the start instruction of the target RPA task, the proximal device sends the start instruction of the target RPA task to the server.

[0243] Accordingly, the server receives the start instruction of the target RPA task, determines the cloud as the execution end from the proximal device and the cloud according to the target RPA task, and sends the RPA instruction set of the target RPA task to the cloud. The RPA instruction set of the target RPA task can be pre-stored by the server, or generated by the server in real time according to the target RPA task, and the RPA instruction set of the target RPA task includes at least one RPA instruction of the target RPA task.

[0244] The cloud receives the RPA instruction set of the target RPA task sent by the server, executes each RPA instruction in the RPA instruction set of the target RPA task in sequence, obtains the execution result of the target RPA task, and then sends the execution result of the target RPA task to the near-end device through the server. Correspondingly, the near-end device receives the execution result of the target RPA task and then displays the execution result of the target RPA task.

[0245] See also Fig.15 , Fig.15 It is an interactive schematic diagram of executing instructions in the cloud in a logistics information query scenario provided by an embodiment of this specification.

[0246] Specifically, when the target RPA task is a logistics information query task, the user first performs a start operation of the logistics information query task on the proximal device, and accordingly, the proximal device responds to the start operation of the logistics information query task and determines the start instruction of the logistics information query task. After determining the start instruction of the logistics information query task, the proximal device sends the start instruction of the logistics information query task to the server.

[0247] Correspondingly, the server receives the start instruction of the logistics information query task, determines the cloud as the execution end from the near-end device and the cloud according to the logistics information query task, and sends the RPA instruction set of the logistics information query task to the cloud. Among them, the RPA instruction set of the logistics information query task can be pre-stored by the server, or it can be generated by the server in real time according to the logistics information query task, and the RPA instruction set of the logistics information query task includes RPA instructions 1 to RPA instructions 10 of the logistics information query task.

[0248] The cloud will receive the RPA instruction set of the logistics information query task sent by the server, and execute each RPA instruction in the RPA instruction set of the logistics information query task in turn to obtain the execution result of the logistics information query task. The execution result of the logistics information query task is the logistics information corresponding to the logistics ID (the unique identifier of the logistics order) to be queried (used to indicate the current status of the logistics order).

[0249] The RPA instructions in the cloud-based RPA instruction set for performing logistics information query tasks are as follows:

[0250] Automatically navigate to the logistics website URL specified by RPA instruction 1 to ensure that subsequent logistics information query operations can be performed in the correct web environment.

[0251] The cloud executes RPA instruction 2 to determine the logistics ID input box. Specifically, the cloud uses the page element recognition capability of RPA technology to locate the logistics ID input box on the logistics query page and prepare for subsequent input operations.

[0252] The cloud executes RPA instruction 3 and inputs the logistics ID to be queried into the logistics ID input box. Specifically, the cloud inputs the logistics ID string provided by RPA instruction 3 into the previously located logistics ID input box character by character by simulating keyboard input to ensure that the information is accurate.

[0253] The cloud executes RPA instruction 4 and clicks the query button control to display the verification code input interface. Specifically, after entering the logistics ID, the cloud automatically triggers the operation of clicking the query button and jumps to display the verification code input interface.

[0254] The cloud executes RPA instruction 5, obtains the verification code image from the verification code input interface and fills it into RPA instruction 6. Specifically, the cloud uses the page element recognition capability of the RPA technology to locate the verification code image in the verification code input interface, and then obtains the verification code image and fills it into RPA instruction 6.

[0255] The cloud executes RPA instruction 6 and sends RPA instruction 6. Specifically, the cloud sends RPA instruction 6 to the server. After receiving RPA instruction 6, the server forwards RPA instruction 6 to the near-end device. The near-end device renders and displays the human-computer interaction interface according to RPA instruction 6, determines the verification code in response to the interactive operation on the human-computer interaction interface, and sends the verification code to the server. After receiving the verification code, the server forwards the verification code to the cloud. Finally, the cloud receives the verification code.

[0256] The cloud executes RPA instruction 7 to input the verification code into the verification code input box in the verification code input interface. Specifically, the cloud automatically inputs the verification code into the verification code input box in the verification code input interface to pass the verification mechanism of the website.

[0257] The cloud executes RPA instruction 8 and clicks the confirmation button control. Specifically, after the verification code is correctly entered, the cloud automatically clicks the confirmation button control, submits the query request, and waits for the server to return the query result.

[0258] The cloud executes RPA instruction 9 and waits for the query result page to be rendered and displayed. Since the web query results may take some time to load, the cloud will suspend the execution of subsequent instructions at this stage until it detects that the query result page is fully loaded and displayed.

[0259] The cloud executes RPA instruction 10 to determine the logistics information corresponding to the logistics ID to be queried from the query result page. Specifically, the cloud uses the page parsing capability of RPA to extract specific logistics information matching the input logistics ID from the query result page, such as the package location, estimated arrival time, etc., for the user to view or further process.

[0260] Finally, the cloud sends the logistics information corresponding to the logistics ID to be queried to the server. The server receives the logistics information corresponding to the logistics ID to be queried, and forwards the logistics information corresponding to the logistics ID to be queried to the near-end device. The near-end device receives the logistics information corresponding to the logistics ID to be queried, and further displays the logistics information corresponding to the logistics ID to be queried.

[0261] See also Fig.16 , is a schematic diagram of the structure of an electronic device provided in the embodiment of this specification. Fig.16 As shown, the electronic device 1000 may include: at least one processor 1001, such as a CPU, at least one network interface 1004, an input / output interface 1003, a memory 1005, and at least one communication bus 1002. The communication bus 1002 is used to realize the connection and communication between these components. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk storage. The memory 1005 may optionally be at least one storage device located away from the aforementioned processor 1001. As shown in FIG. Fig.16 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, an input / output interface module, and a task processing application.

[0262] exist Fig.16 In the electronic device 1000 shown, the input-output interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user.

[0263] In one embodiment, the processor 1001 may be used to call the task processing application stored in the memory 1005, and specifically perform the following operations:

[0264] In response to the start operation of the target RPA task, determine the start instruction of the target RPA task, send the start instruction of the target RPA task to the server, so that the server can determine the execution end from the local device and the cloud according to the start instruction of the target RPA task, and send the RPA instruction set of the target RPA task to the execution end;

[0265] The execution result of the target RPA task is obtained and displayed, wherein the execution result of the target RPA task is obtained by the execution end executing each RPA instruction in the RPA instruction set of the target RPA task.

[0266] Optionally, when the proximal device is determined as the execution end, the processor 1001, after executing a startup operation in response to the target RPA task, determines the startup instruction of the target RPA task, sends the startup instruction of the target RPA task to the server, and before obtaining and displaying the execution result of the target RPA task, specifically performs the following operations: receiving the RPA instruction set of the target RPA task sent by the server; executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0267] Optionally, when the cloud is determined as the execution end, the processor 1001 performs the following operations when acquiring and displaying the execution result of the target RPA task: receiving the execution result of the target RPA task sent by the cloud through the server; and displaying the execution result of the target RPA task.

[0268] Optionally, when the cloud is determined as the execution end, after the processor 1001 executes a startup operation in response to the target RPA task, determines the startup instruction of the target RPA task, and sends the startup instruction of the target RPA task to the server, and before executing to obtain and display the execution result of the target RPA task, it specifically performs the following operations: receiving the human-computer interaction RPA instruction sent by the cloud through the server; rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instruction; determining the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface; and sending the human-computer interaction result information to the cloud through the server.

[0269] Optionally, when the processor 1001 executes rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instruction, the processor 1001 specifically performs the following operations: rendering and displaying interaction prompt information and interaction controls according to the human-computer interaction RPA instruction to form a human-computer interaction interface, wherein the interaction prompt information is used to prompt the user to perform interaction operations, and the interaction controls are used to respond to the user's interaction operations.

[0270] In one embodiment, the processor 1001 may be used to call the task processing application stored in the memory 1005, and specifically perform the following operations:

[0271] Receive the start instruction of the target RPA task sent by the proximal device;

[0272] According to the start instruction of the target RPA task, the execution end is determined from the local device and the cloud;

[0273] The RPA instruction set of the target RPA task is sent to the execution end, so that the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, and the local device obtains and displays the execution result of the target RPA task.

[0274] Optionally, when the processor 1001 determines the execution end from the proximal device and the cloud according to the startup instruction of the target RPA task, it specifically performs the following operations: determine the authority level of the target RPA task according to the startup instruction of the target RPA task; when the authority level of the target RPA task is higher than the preset reference authority level, determine the proximal device as the execution end; when the authority level of the target RPA task is not higher than the preset reference authority level, determine the cloud as the execution end.

[0275] Optionally, in the case where the cloud is determined as the execution end, after executing the RPA instruction set for sending the target RPA task to the execution end, the processor 1001 specifically performs the following operations: determining the status of each RPA executor in the cloud, wherein the status of the RPA executor includes a busy state and an idle state; determining the target RPA executor from the RPA executors in the idle state in the cloud; generating an RPA executor call instruction based on the target RPA executor, and sending the RPA executor call instruction to the cloud, wherein the RPA executor call instruction is used to instruct the cloud to call the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task.

[0276] In one embodiment, the processor 1001 may be used to call the task processing application stored in the memory 1005, and specifically perform the following operations:

[0277] Receiving an RPA instruction set of a target RPA task sent by a server, wherein the RPA instruction set of the target RPA task is sent by the server to the cloud when the server determines that the cloud is the execution end from among the proximal device and the cloud according to the start instruction of the target RPA task;

[0278] Each RPA instruction in the RPA instruction set of executing the target RPA task obtains the execution result of the target RPA task, so that the proximal device can obtain and display the execution result of the target RPA task.

[0279] Optionally, when the processor 1001 executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task so that the proximal device can obtain and display the execution result of the target RPA task, the following specific operations are performed: determining the execution order of each RPA instruction in the RPA instruction set of the target RPA task; traversing each RPA instruction in sequence according to the execution order of each RPA instruction in the RPA instruction set of the target RPA task; executing the current RPA instruction for the current RPA instruction in each traversed RPA instruction; if the RPA instruction with the last execution order in each RPA instruction is executed, the execution result of the target RPA task is obtained, and the execution result of the target RPA task is sent to the proximal device through the server, so that the proximal device can receive and display the execution result of the target RPA task.

[0280] Optionally, when executing the current RPA instruction among the traversed RPA instructions, the processor 1001 specifically performs the following operations: for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is a human-computer interaction RPA instruction, the human-computer interaction RPA instruction is sent to the proximal device through the server, the proximal device renders and displays the human-computer interaction interface according to the human-computer interaction RPA instruction, determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface, and sends the human-computer interaction result information to the cloud through the server; and receives the human-computer interaction result information.

[0281] Optionally, when executing the current RPA instruction among the traversed RPA instructions, the processor 1001 specifically performs the following operations: for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interactive pre-RPA instruction whose execution order is before the human-computer interaction RPA instruction, then obtain interaction prompt information according to the interactive pre-RPA instruction, and fill the interaction prompt information into the human-computer interaction RPA instruction, wherein the interaction prompt information is used to prompt the user to perform interactive operations in the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction.

[0282] Optionally, when executing the current RPA instruction among the traversed RPA instructions, the processor 1001 specifically performs the following operations: for the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interaction post-RPA instruction whose execution order is after the human-computer interaction RPA instruction, then the interaction post-RPA instruction is executed according to the received human-computer interaction result information, wherein the human-computer interaction result information is the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction, which is determined in response to the interaction operation on the human-computer interaction interface and sent to the cloud through the server.

[0283] Optionally, after executing the RPA instruction set of the target RPA task sent by the receiving server, the processor 1001 specifically performs the following operations before executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task: receiving an RPA executor call instruction sent by the server, wherein the RPA executor call instruction is generated by the server based on the target RPA executor in the cloud, and the target RPA executor is determined by the server from the idle RPA executors in the cloud; when the processor 1001 executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, the processor 1001 specifically performs the following operations: according to the RPA executor call instruction, calling the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

[0284] For the effects that can be achieved by this embodiment, please refer to the relevant embodiments of the above-mentioned task processing method, which will not be repeated here.

[0285] The present specification also provides a computer storage medium that can store multiple program instructions, which are suitable for being loaded and executed by a processor as described above. Figure 2 - Fig.15 The method steps of the embodiment shown in the figure can be found in the specific implementation process. Figure 2 - Fig.15 The specific description of the illustrated embodiment will not be repeated here.

[0286] The embodiment of the present specification also provides a computer program product, which stores at least one instruction, and the at least one instruction is loaded and executed by a processor as described above. Figure 2 - Fig.15 The task processing method of the embodiment shown in the figure can be found in the specific execution process. Figure 2 - Fig.15 The specific description of the illustrated embodiment will not be repeated here.

[0287] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0288] The above disclosure is only the preferred embodiment of this specification, which certainly cannot be used to limit the scope of rights of this specification. Therefore, equivalent changes made according to the claims of this specification are still within the scope covered by this specification.

Claims

1. A task processing method, applied to a proximal device, comprising: In response to the start operation of the target RPA task, determine the start instruction of the target RPA task, send the start instruction of the target RPA task to the server, so that the server determines the execution end from the proximal device and the cloud according to the start instruction of the target RPA task, and sends the RPA instruction set of the target RPA task to the execution end; Obtain and display the execution result of the target RPA task, wherein the execution result of the target RPA task is obtained by the execution end executing each RPA instruction in the RPA instruction set of the target RPA task.

2. According to the method of claim 1, when the proximal device is determined as the execution end, after determining the start instruction of the target RPA task in response to the start operation of the target RPA task, sending the start instruction of the target RPA task to the server, and before acquiring and displaying the execution result of the target RPA task, the method further comprises: Receiving an RPA instruction set of a target RPA task sent by the server; Execute each RPA instruction in the RPA instruction set of the target RPA task to obtain an execution result of the target RPA task.

3. According to the method of claim 1, when the cloud is determined as the execution end, obtaining and displaying the execution result of the target RPA task includes: Receiving the execution result of the target RPA task sent by the cloud through the server; The execution result of the target RPA task is displayed.

4. The method according to claim 1, when the cloud is determined as the execution end, after determining the start instruction of the target RPA task in response to the start operation of the target RPA task, sending the start instruction of the target RPA task to the server, and before acquiring and displaying the execution result of the target RPA task, further comprises: Receiving a human-computer interaction RPA instruction sent by the cloud through the server; Rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instruction; Determining human-computer interaction result information in response to an interactive operation on the human-computer interaction interface; The human-computer interaction result information is sent to the cloud through the server.

5. According to the method of claim 4, rendering and displaying the human-computer interaction interface according to the human-computer interaction RPA instruction comprises: According to the human-computer interaction RPA instruction, interactive prompt information and interactive controls are rendered and displayed to form the human-computer interaction interface, wherein the interactive prompt information is used to prompt the user to perform interactive operations, and the interactive controls are used to respond to the user's interactive operations.

6. A task processing method, applied to a server, comprising: Receive the start instruction of the target RPA task sent by the proximal device; According to the start instruction of the target RPA task, determining the execution end from the local device and the cloud; The RPA instruction set of the target RPA task is sent to the execution end, so that the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, and the proximal device obtains and displays the execution result of the target RPA task.

7. The method according to claim 6, wherein determining the execution end from the local device and the cloud according to the start instruction of the target RPA task comprises: Determining the permission level of the target RPA task according to the start instruction of the target RPA task; When the authority level of the target RPA task is higher than a preset reference authority level, determining the proximal device as the execution end; When the authority level of the target RPA task is not higher than the preset reference authority level, the cloud is determined as the execution end.

8. The method according to claim 6, when the cloud is determined as the execution end, after sending the RPA instruction set of the target RPA task to the execution end, further comprises: Determine the status of each RPA executor in the cloud, wherein the status of the RPA executor includes a busy state and an idle state; Determine a target RPA executor from the RPA executors in the cloud that are in an idle state; An RPA executor calling instruction is generated according to the target RPA executor, and the RPA executor calling instruction is sent to the cloud, wherein the RPA executor calling instruction is used to instruct the cloud to call the target RPA executor to execute each RPA instruction in the RPA instruction set of the target RPA task.

9. A task processing method, applied in the cloud, comprising: Receiving an RPA instruction set of a target RPA task sent by a server, wherein the RPA instruction set of the target RPA task is sent by the server to the cloud when the server determines that the cloud is an execution end from among a proximal device and the cloud according to a start instruction of the target RPA task; Execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, so that the proximal device can obtain and display the execution result of the target RPA task.

10. The method according to claim 9, wherein each RPA instruction in the RPA instruction set for executing the target RPA task obtains the execution result of the target RPA task so that the proximal device obtains and displays the execution result of the target RPA task, comprising: Determine the execution order of each RPA instruction in the RPA instruction set of the target RPA task; According to the execution order of each RPA instruction in the RPA instruction set of the target RPA task, traverse each RPA instruction in turn; For a current RPA instruction among the traversed RPA instructions, execute the current RPA instruction; If the RPA instruction that is the last one in the execution order among the RPA instructions is executed, the execution result of the target RPA task is obtained, and the execution result of the target RPA task is sent to the proximal device through the server, so that the proximal device receives and displays the execution result of the target RPA task.

11. The method according to claim 10, wherein the step of executing the current RPA instruction in each of the traversed RPA instructions comprises: For the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is a human-computer interaction RPA instruction, the human-computer interaction RPA instruction is sent to the proximal device through the server, the proximal device renders and displays the human-computer interaction interface according to the human-computer interaction RPA instruction, determines the human-computer interaction result information in response to the interactive operation on the human-computer interaction interface, and sends the human-computer interaction result information to the cloud through the server; The human-computer interaction result information is received.

12. The method according to claim 10, wherein the step of executing the current RPA instruction in each of the traversed RPA instructions comprises: For the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interactive pre-RPA instruction whose execution order is before the human-computer interaction RPA instruction, then the interactive prompt information is obtained according to the interactive pre-RPA instruction, and the interactive prompt information is filled into the human-computer interaction RPA instruction, wherein the interactive prompt information is used to prompt the user to perform interactive operations in the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction.

13. The method according to claim 10, wherein the step of executing the current RPA instruction in each of the traversed RPA instructions comprises: For the current RPA instruction among the traversed RPA instructions, if the current RPA instruction is an interaction post-RPA instruction whose execution order is after the human-computer interaction RPA instruction, the interaction post-RPA instruction is executed according to the received human-computer interaction result information, wherein the human-computer interaction result information is the human-computer interaction interface rendered and displayed by the proximal device according to the human-computer interaction RPA instruction, and is determined in response to the interaction operation on the human-computer interaction interface and sent to the cloud through the server.

14. The method according to claim 9, after receiving the RPA instruction set of the target RPA task sent by the server, and before executing each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task, further comprising: Receive an RPA executor call instruction sent by the server, wherein the RPA executor call instruction is generated by the server according to a target RPA executor on the cloud, and the target RPA executor is determined by the server from the RPA executors in an idle state on the cloud; The RPA instructions in the RPA instruction set for executing the target RPA task obtain the execution result of the target RPA task, including: According to the RPA executor calling instruction, the target RPA executor is called to execute each RPA instruction in the RPA instruction set of the target RPA task to obtain the execution result of the target RPA task.

15. A task processing system, the system comprising a local device, a server and a cloud; The proximal device is used to determine the start instruction of the target RPA task in response to the start operation of the target RPA task, send the start instruction of the target RPA task to the server, and obtain and display the execution result of the target RPA task; The server is configured to receive a start instruction of the target RPA task sent by the proximal device; determine an execution end from the proximal device and the cloud according to the start instruction of the target RPA task; and send an RPA instruction set of the target RPA task to the execution end, so that the execution end executes each RPA instruction in the RPA instruction set of the target RPA task to obtain an execution result of the target RPA task; The cloud end is used to receive the RPA instruction set of the target RPA task sent by the server, wherein: The RPA instruction set of the target RPA task is sent by the server to the cloud when the server determines that the cloud is the execution end from the proximal device and the cloud according to the startup instruction of the target RPA task; and each RPA instruction in the RPA instruction set of the target RPA task is executed to obtain the execution result of the target RPA task.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program code, and when the computer program code is executed, the method according to any one of claims 1 to 14 is implemented.

17. An electronic device comprising: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the steps of the method according to any one of claims 1 to 14.

18. A computer program product having at least one instruction stored thereon, wherein when the at least one instruction is executed by a processor, the steps of the method according to any one of claims 1 to 14 are implemented.

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