CN112130951A - AI-based RPA flow generation end flow generation method, equipment and storage medium - Google Patents
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Abstract
The application provides a flow generation method, equipment and a storage medium of an RPA flow generation terminal based on AI. Relates to the technical field of AI and RPA, the method comprises the following steps: acquiring a main process and an auxiliary process of a target project, wherein the main process is not connected with the auxiliary process; and generating a flow of the target project according to the main flow and the auxiliary flow. According to the method and the device, the auxiliary process which is not connected with the main process is set, the process architecture of the target project can be clearer, a user can check and modify the auxiliary process in a targeted manner when the process of the target project is maintained, and the maintenance difficulty is reduced.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to the fields of Artificial Intelligence (AI) and Robot Process Automation (RPA), and more particularly, to a method, an apparatus, and a storage medium for generating an RPA Process based on AI.
Background
Robot Process Automation (RPA) is a process task that simulates human operations on a computer by specific "robot software" and executes automatically according to rules. In order to improve the convenience of RPA process development, visual process editing software is more and more widely used. Such software provides a visual editing interface for the user. The user can select a control on the interface to construct the flowchart and edit the program instructions within the flowchart block in the flowchart. And the software background generates corresponding program codes according to the flow chart constructed by the user, so that the user can conveniently and visually design the RPA flow according to the service requirement.
Artificial Intelligence (AI) is a new technology science for researching and developing theories, methods, techniques and application systems for simulating, extending and expanding human Intelligence. Research in the field of artificial intelligence includes robotics, language recognition, image recognition, natural language processing, and expert systems, among others.
Typically, a user constructs a flow chart for a project. In which the user adds and edits the required flow blocks to accomplish the various tasks of the project.
However, for items with more tasks, there are more flow blocks in the flow chart, which makes it difficult for a user to view and modify the flow corresponding to a certain task, and is inconvenient for maintenance.
Disclosure of Invention
The embodiment of the application provides a flow generation method, equipment and a storage medium of an RPA flow generation terminal based on AI, so as to solve the problem that the current flow generation mode is inconvenient to maintain.
In a first aspect, an embodiment of the present application provides a flow generating method for an AI-based RPA flow generating end, which is applied to an electronic device, where the electronic device provides a user graphical interface based on Natural Language Processing (NLP), and the method includes the following steps:
acquiring a main process and an auxiliary process of a target project, wherein the main process and the auxiliary process are not connected;
and generating a process of the target project according to the main process and the auxiliary process.
In one possible embodiment, there is no process connection line between the main process and the auxiliary process.
In one possible embodiment, there are no common process elements between the main process and the auxiliary process.
In a possible embodiment, the program of the auxiliary process is intended to be run during the program run of the main process.
In a possible implementation manner, a first control corresponding to a flow element and a second control corresponding to the flow connecting line are included in the NLP-based user graphical interface;
the method for acquiring the main process and the auxiliary process of the target project, wherein the main process and the auxiliary process are not connected with each other, comprises the following steps:
and responding to the control operation of the user on the first control and the second control, and constructing and displaying the main flow and the auxiliary flow in the NLP-based user graphic interface.
In a possible implementation manner, a running control and/or a debugging control are further included in the NLP-based user graphical interface;
the method further comprises the following steps:
and responding to the triggering operation of the user on the running control and/or the debugging control, executing the program of the main flow, and executing the program of the auxiliary flow during the program running of the main flow.
In a possible implementation, the process of generating the target item according to the main process and the auxiliary process includes:
generating a program of the main flow according to the flow elements, the flow connecting lines and the first preset program template of the main flow, and generating a program of the auxiliary flow according to the flow elements, the flow connecting lines and the second preset program template of the auxiliary flow;
and establishing an association relationship between the program of the main flow and the program of the auxiliary flow to obtain the flow of the target item, wherein the association relationship is used for enabling the program of the auxiliary flow to run during the running of the program of the main flow.
In one possible embodiment, the method further comprises:
when monitoring a preset control operation of a user, displaying prompt information representing connection prohibition in the NLP-based user graphical interface, wherein the preset control operation comprises a connection operation between a flow element of the main flow and a flow element of the auxiliary flow and/or a connection operation between flow elements of the two auxiliary flows.
In one possible embodiment, the flow elements of the auxiliary flow include a start block;
the method further comprises the following steps:
in response to the selection operation of the user for the starting block of the auxiliary process, displaying description information of the auxiliary process in the NLP-based user graphical interface, and/or displaying process elements and process connecting lines of the auxiliary process according to a preset display pattern.
In one possible embodiment, the flow elements of the auxiliary flow include a start block;
the method further comprises the following steps:
modifying a name of a starting block of the auxiliary flow in response to a user's editing operation for the starting block of the auxiliary flow.
In one possible embodiment, the flow element of the main flow includes a start block, and the flow element of the auxiliary flow does not include a start block.
In a second aspect, an embodiment of the present application provides a flow generating apparatus of an AI-based RPA flow generating end, which is applied to an electronic device, where the electronic device provides a user graphical interface based on NLP, and the apparatus includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a main process and an auxiliary process of a target project, and the main process is not connected with the auxiliary process;
and the processing module is used for generating the flow of the target project according to the main flow and the auxiliary flow.
In one possible embodiment, there is no process connection line between the main process and the auxiliary process.
In one possible embodiment, there are no common process elements between the main process and the auxiliary process.
In a possible embodiment, the program of the auxiliary process is intended to be run during the program run of the main process.
In a possible implementation manner, a first control corresponding to a flow element and a second control corresponding to the flow connecting line are included in the NLP-based user graphical interface;
the acquisition module is specifically configured to:
and responding to the control operation of the user on the first control and the second control, and constructing and displaying the main flow and the auxiliary flow in the NLP-based user graphic interface.
In a possible implementation manner, a running control and/or a debugging control are further included in the NLP-based user graphical interface;
the processing module is further configured to:
and responding to the triggering operation of the user on the running control and/or the debugging control, executing the program of the main flow, and executing the program of the auxiliary flow during the program running of the main flow.
In a possible implementation manner, the processing module is specifically configured to:
generating a program of the main flow according to the flow elements, the flow connecting lines and the first preset program template of the main flow, and generating a program of the auxiliary flow according to the flow elements, the flow connecting lines and the second preset program template of the auxiliary flow;
and establishing an association relationship between the program of the main flow and the program of the auxiliary flow to obtain the flow of the target item, wherein the association relationship is used for enabling the program of the auxiliary flow to run during the running of the program of the main flow.
In a possible implementation, the processing module is further configured to:
when monitoring a preset control operation of a user, displaying prompt information representing connection prohibition in the NLP-based user graphical interface, wherein the preset control operation comprises a connection operation between a flow element of the main flow and a flow element of the auxiliary flow and/or a connection operation between flow elements of the two auxiliary flows.
In one possible embodiment, the flow elements of the auxiliary flow include a start block;
the processing module is further configured to:
in response to the selection operation of the user for the starting block of the auxiliary process, displaying description information of the auxiliary process in the NLP-based user graphical interface, and/or displaying process elements and process connecting lines of the auxiliary process according to a preset display pattern.
In one possible embodiment, the flow elements of the auxiliary flow include a start block;
the processing module is further configured to:
modifying a name of a starting block of the auxiliary flow in response to a user's editing operation for the starting block of the auxiliary flow.
In one possible embodiment, the flow element of the main flow includes a start block, and the flow element of the auxiliary flow does not include a start block.
In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the flow generation method of the AI-based RPA flow generation end according to the first aspect and various possible implementations of the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where a computer executing instruction is stored in the computer-readable storage medium, and when a processor executes the computer executing instruction, the method for generating a flow at an AI-based RPA flow generating end according to the first aspect and various possible implementations of the first aspect is implemented.
According to the flow generation method, the equipment and the storage medium of the RPA flow generation end based on the AI, the electronic equipment provides a user graphical interface based on the NLP, and acquires a main flow and an auxiliary flow of a target project, wherein the main flow and the auxiliary flow are not connected; the flow of the target project is generated according to the main flow and the auxiliary flow, and the auxiliary flow which is not connected with the main flow is set, so that the flow architecture of the target project can be clearer, a user can check and modify the auxiliary flow in a targeted manner when maintaining the flow of the target project, and the maintenance difficulty is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic view of a scenario of a flow generating method of an AI-based RPA flow generating end according to an embodiment of the present application;
fig. 2 is a schematic diagram of an NLP-based user graphical interface provided in an embodiment of the present application;
fig. 3 is a schematic diagram of an NLP-based user graphical interface provided by another embodiment of the present application;
fig. 4A is a schematic diagram of a flowchart obtained in a flow generation manner of an existing AI-based RPA flow generation end;
fig. 4B is a schematic diagram of a flow chart obtained by the flow chart generating method of the AI-based RPA flow generating terminal according to the embodiment of the present application;
fig. 5 is a schematic flowchart of a flow generating method of an AI-based RPA flow generating end according to an embodiment of the present application;
fig. 6 is a schematic flowchart of a flow generating method of an AI-based RPA flow generating end according to another embodiment of the present application;
fig. 7 is a schematic structural diagram of a flow generating device at an AI-based RPA flow generating end according to an embodiment of the present application;
fig. 8 is a schematic hardware structure diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the description of embodiments of the present application, the term "flow element" refers to an element that constitutes a flow diagram, including but not limited to at least one of the following: a start block, a flow block, a decision block, and an end block of the flow. Where the start block is the beginning of the entire flow. The blocks may be edited by a user to edit desired program instructions to implement particular functions. The judging block has at least two branches, and the program runtime can execute different branches according to the expressions filled in the judging block. The end block indicates that the flow execution is to end here.
The term "process connection line" is a connection line between process elements and indicates an execution relationship between the process elements.
Compared with the existing program for generating a project by drawing all program instructions of the project in a flow chart, the method for generating the project by combining the main flow and the auxiliary flow is provided, and one or more auxiliary flows can be owned by one project so that a user can set the program instructions of each task of the project in the auxiliary flows. The main process and the auxiliary process are not connected with each other in the user graphical interface based on the NLP, so that a user can clearly distinguish the main process from each auxiliary process, and each task is conveniently maintained by adding, deleting and modifying the auxiliary processes, thereby reducing the difficulty of program maintenance.
Fig. 1 is a schematic view of a scenario of a flow generating method of an AI-based RPA flow generating end according to an embodiment of the present application. As shown in fig. 1, the scene includes an electronic device 11 and a user. The electronic device 11 may be a terminal having a display screen, such as a desktop computer, a notebook computer, a tablet computer, a mobile phone, and a vehicle-mounted terminal. The electronic device 11 may execute a computer to execute instructions to implement the flow generation method of the AI-based RPA flow generation end provided in the embodiment of the present application.
The user may control electronic device 11 to display an NLP-based user graphical interface for editing the process. For example, a NLP based user graphical interface is shown in fig. 2. Controls for editing the process, and a process drawing window 210 may be included on the NLP-based user graphical interface. Wherein, the control can include but is not limited to one of the following items: a first control 220 corresponding to the flow element, a second control 230 corresponding to the flow connecting line, a running control 240 and a debugging control 250. Specifically, the first control 220 may include a control 221 corresponding to the main process start block, a control 222 corresponding to the auxiliary process start block, a control 223 corresponding to the process block, a control 224 corresponding to judgment, and a control 225 corresponding to ending. The user can draw the main flow and the auxiliary flow of the target project in the flow drawing window 210 by controlling the control, edit the flow blocks in the main flow and the auxiliary flow, and input the program instruction. The electronic device 11 generates a flow of the target item based on the main flow and the subsidiary flow. The user can control the run control 240/debug control 250 to run/debug the flow of the target item. It should be noted that, the user graphical interface based on NLP may extract information of specific contents in the main flow and the auxiliary flow of the target item by using an NLP technique, so that the operation/debugging of the flow of the target item is performed by the operation control 240/the debugging control 250.
As another example, an NLP-based user graphical interface may be as shown in fig. 3. The NLP-based user graphical interface includes controls for editing programs, and a flow drawing window 310. Wherein, the control can include: the first control 320 corresponding to the flow element, the new control 330 for creating a new project flow, the save control 340 for storing the drawn flow, the import control 350 for importing a flow file, the run control 360 for running the flow, the release control 370 for releasing the flow, and the like. The first control 320 includes a control 321 corresponding to the main process starting block, a control 322 corresponding to the auxiliary process starting block, a control 323 corresponding to the process block, a control 324 corresponding to judgment, and a control 325 corresponding to ending. The first control 320 is displayed in a floating window superimposed on the flow drawing window 310. The control 322 corresponding to the auxiliary process starting block, the control 323 corresponding to the process block, and the corner mark number at the upper right corner of the judgment corresponding control 324 represent the number of the process elements used in the current flowchart. Also included on the NLP based user graphical interface is a property display window 380. When the user selects the starting block of the auxiliary flow in the flow drawing window 310, the attributes of the auxiliary flow may be displayed in the attribute display window 380 for the user to view. Alternatively, the user may edit the properties of the auxiliary flow within the property display window 380. For example, the user may add information such as the function or implementation principle implemented by the auxiliary flow to the attribute.
When drawing the flow chart, a user may add a flow element to the flow drawing window 310 by dragging or selecting the first control 320 corresponding to the flow element, and connect the flow element through a flow connection line to obtain a main flow and an auxiliary flow. A main flow and a sub-flow are drawn in the current-flow drawing window 310. Wherein, there is no flow connecting line between the main flow and the auxiliary flow. There are also no common flow elements between the main flow and the auxiliary flow. So that the user can clearly distinguish between the different processes. Within the current flow drawing window 310, the name of the beginning block of the auxiliary flow is named "monitoring data", which characterizes the task of the auxiliary flow for implementing the monitoring data. The main process and the auxiliary process jointly form a process of an item, and the item is used for acquiring the price of the commodity browsed by the user and comparing the prices of the commodities to obtain a comparison result in the process that the user browses the commodities. The main process is used for realizing the task of acquiring the name and the price of the commodity browsed by the user, for example, the user graphical interface can extract the name and the price of the commodity browsed by the user based on the NLP, so that the main process can acquire the name and the price of the commodity browsed by the user. The auxiliary process is used for detecting data in the data table and analyzing and processing the data in the data table. The user can click the launch control 360 to launch the program for the flow of the project. Wherein the program of the auxiliary process is run during the program run of the main process. The user can debug and modify the process by running the process of the project.
The following describes a conventional flow generation method and a flow generation method of an AI-based RPA flow generation end provided in the embodiment of the present application, taking target item a, including tasks a1, a2, A3, and a4, as examples. Refer to fig. 4A and 4B. As shown in fig. 4A, the execution of programs that implement tasks a1, a2, A3, and a4 in the prior art is depicted in the same flowchart, and each task is implemented by one or more flow blocks. Task A1 is implemented by program instructions in block 1 and block 2; task A2 is implemented by program instructions in block 2 and block N; task A3 is implemented by program instructions in block N; task a4 is implemented by program instructions in block 3. Program instructions of different tasks are easily mixed together and are inconvenient to view and modify. As shown in fig. 4B, in the embodiment of the present application, task a1 may be implemented through a main flow, and tasks a2, A3, and a4 are implemented through three auxiliary flows, respectively, so that a user can view and modify a certain task conveniently, and program maintenance is facilitated.
Fig. 5 is a flowchart illustrating a flow generating method of an AI-based RPA flow generating end according to an embodiment of the present application. As shown in fig. 5, the main implementation of the method is the electronic device in fig. 1. The electronic device provides an NLP-based user graphical interface. The method comprises the following steps:
and S1, acquiring a main process and an auxiliary process of the target item, wherein the main process and the auxiliary process are not connected.
In this embodiment, the main process of the target item is one, and the auxiliary processes of the target item may be one or more. The user can create a project file of the target project and draw the main flow and the auxiliary flow of the target project through the control on the NLP-based user graphical interface in the project file of the target project. Wherein, there is no connection between the main flow and the auxiliary flow, and the main flow and the auxiliary flow are displayed in the user graphic interface based on the NLP independently. Optionally, the number of the auxiliary processes is multiple, there is no connection between the auxiliary processes, and the display of each auxiliary process in the NLP-based user graphical interface is relatively independent. Optionally, there is no connection between the main flow and the auxiliary flow, and the method may include: there is no flow connection line between the main flow and the auxiliary flow, and/or there is no shared flow element between the main flow and the auxiliary flow.
Optionally, the user may also import the created main flow and the created auxiliary flow into the electronic device, and edit the created main flow and the created auxiliary flow on the NLP-based user graphical interface. The electronic equipment receives a main process and an auxiliary process of a target project imported or edited by a user.
And S2, generating a flow of the target item according to the main flow and the auxiliary flow.
In this embodiment, a first preset program template corresponding to the main process and a second preset program template corresponding to the auxiliary process are preset in the electronic device. And obtaining a program of the main flow and a program of the auxiliary flow according to the first preset program template and the second preset program template, and further obtaining a flow of the target project. The programs corresponding to the target item flow include a main flow program and an auxiliary flow program.
This is explained below with reference to a specific example. In this example, the target item is used to automatically acquire the browsing information of the user on the mobile phone when the user browses the shopping website. It is assumed that the browsing information includes the model, price, and picture of the mobile phone browsed by the user. The acquisition of each browsing information may be regarded as one task.
In the prior art, a user constructs a flow chart of the target item, and program instructions are edited in the flow chart through one or more flow blocks, so as to acquire the model, price and picture of a mobile phone browsed by the user. During subsequent program maintenance, due to changes in service requirements, tasks of acquiring configuration parameters and browsing duration of a mobile phone browsed by a user need to be added. At this time, the user needs to edit the original flowchart, and adds the relevant instruction for obtaining the configuration parameters and the browsing duration of the mobile phone browsed by the user into the flowchart. The user needs to understand the execution process in the original flowchart, and adds the configuration parameters and the browsing duration of the mobile phone browsed by the user to a proper position, so as to realize the newly added task under the condition of ensuring the normal realization of the original task.
By adopting the flow generation mode of the RPA flow generation terminal based on AI provided by the embodiment of the application, the user can construct the main flow and the auxiliary flow. There is no connection between the main flow and the auxiliary flow. In addition, the user graphical interface based on the NLP can extract the flow contents of the main flow and the auxiliary flow through the NLP, thereby acquiring the related information. For example, the model of the mobile phone browsed by the user is acquired through the main process, the price of the mobile phone browsed by the user is acquired through one auxiliary process, and the picture of the mobile phone browsed by the user is acquired through the other auxiliary process. During subsequent process maintenance, due to the change of service requirements, tasks of acquiring configuration parameters and browsing duration of a mobile phone browsed by a user need to be added. The user can add an auxiliary process to acquire the configuration parameters of the mobile phone browsed by the user on the basis of the original main process and the auxiliary process, and add an auxiliary process to acquire the browsing duration of the mobile phone browsed by the user. Therefore, the user does not need to adjust the original main flow and auxiliary flow, and can conveniently and quickly modify and edit the flow. And if the specific acquisition rule or mode of a certain task needs to be modified subsequently, the auxiliary flow related to the task can be quickly found for modification. In this example, the data acquired by the main flow and each auxiliary flow may be passed through parameters, allocated to storage addresses, and the like to generate summarized data for the user to view.
In the embodiment of the application, the electronic equipment provides a user graphical interface based on NLP, and acquires a main flow and an auxiliary flow of a target project, wherein the main flow and the auxiliary flow are not connected; the flow of the target project is generated according to the main flow and the auxiliary flow, and the auxiliary flow which is not connected with the main flow is set, so that the flow architecture of the target project can be clearer, a user can check and modify the auxiliary flow in a targeted manner when maintaining the flow of the target project, and the maintenance difficulty is reduced.
Optionally, the program of the auxiliary process is adapted to be run during the running of the program of the main process. The program of the auxiliary process can be executed only when the program of the main process is executed, that is, the program of the auxiliary process is executed at the start time not earlier than the program of the main process, and the program of the auxiliary process is executed at the end time not later than the program of the main process. The program of the auxiliary process is operated along with the program of the main process, and the program of the auxiliary process cannot be operated independently.
As an embodiment of the present application, a detailed description is given of how to obtain the specific implementation processes of the main flow and the auxiliary flow of the target item based on the embodiment shown in fig. 5. The AI-based user graphical interface may include a first control corresponding to the process element and a second control corresponding to the process connection line, and the main process and the auxiliary process for obtaining the target item according to the first control corresponding to the process element and the second control corresponding to the process connection line may include:
and constructing and displaying the main flow and the auxiliary flow in the NLP-based user graphic interface in response to the control operation of the user on the first control and the second control.
In this embodiment, the flow elements may include multiple types, and each type of flow element corresponds to one first control. For example, as shown in fig. 2 and 3, the flow elements may include a main flow start module, an auxiliary flow start module, a flow block, a determination block, a main flow end block, and an auxiliary flow end block. The user can select or drag the control corresponding to the flow elements, add the flow elements in the flow drawing window, and add flow connecting lines between the flow elements through the second control to draw the main flow and the auxiliary flow. For the flow block, the user can select the flow block and edit the program instruction in the flow block. And the electronic equipment responds to the control operation of the user on the first control and the second control, and constructs and displays the main flow and the auxiliary flow in the NLP-based user graphic interface.
The present embodiment provides the first control and the second control through the NLP-based user graphical interface, so that the user can conveniently construct the main flow and the auxiliary flow of the target program, and the user can conveniently edit the main flow and the auxiliary flow.
As an embodiment of the present application, on the basis of any of the above embodiments, a run control and/or a debug control is further included in the NLP-based user graphical interface. After generating the flow of the target item according to the main flow and the auxiliary flow, the method further comprises:
and S3, responding to the trigger operation of the user for the running control and/or the debugging control, executing the program of the main flow, and executing the program of the auxiliary flow during the program running of the main flow.
In this embodiment, a user may instruct the electronic device to run the program of the target project by triggering the running control; and triggering the debugging control to instruct the electronic equipment to run the program of the target item for program debugging. For example, the electronic device may run the program of the target item in a fixed point debugging mode, a single step debugging mode, a timing debugging mode and the like to perform program debugging. And the electronic equipment responds to the triggering operation of the user for the running control and/or the debugging control, and executes the program of the auxiliary flow during the execution of the program of the main flow.
In the embodiment, the operation control and/or the debugging control are provided through the user graphical interface based on the NLP, so that the user can conveniently perform program operation and debugging, and in the process of operating the program, the program of the auxiliary flow is executed during the program operation period of the main flow, so that the auxiliary flow is ensured not to be executed independently, and the program operation error is avoided. Meanwhile, the user graphical interface based on the NLP can extract information of specific contents in the main flow and the auxiliary flow by adopting an NLP technology, so that debugging of the main flow and the auxiliary flow is facilitated.
Fig. 6 is a schematic flow chart of a process of generating a target project according to a main process and an auxiliary process according to another embodiment of the present application. In this embodiment, a specific implementation process of generating a target project flow according to a main flow and an auxiliary flow is described in detail on the basis of any one of the above embodiments. As shown in fig. 6, the process of generating the target item may include:
and S21, generating a program of the main flow according to the flow element, the flow connecting line and the first preset program template of the main flow, and generating a program of the auxiliary flow according to the flow element, the flow connecting line and the second preset program template of the auxiliary flow.
And S22, establishing an association relationship between the program of the main flow and the program of the auxiliary flow to obtain the flow of the target project, wherein the association relationship is used for enabling the program of the auxiliary flow to run during the running of the program of the main flow.
In this embodiment, the program of the main flow and the program of the auxiliary flow are associated with each other by the electronic device, so that the program of the auxiliary flow runs during the running of the program of the main flow. For example, the association relationship may be established by causing the program of the auxiliary process to run during the program running of the main process by means of a flag, setting a default running condition of the auxiliary process, and the like, which is not limited herein.
In the embodiment, the main process and the auxiliary process do not have a process connection line in the NLP-based user graphical interface, but the association relationship is established by the electronic device, so that the program of the auxiliary process is ensured to run during the program running period of the main process, the program maintenance of a user is facilitated, the mutual relation between the main process and the auxiliary process is ensured, and the target project is realized together.
As an embodiment of the present invention, on the basis of any of the above embodiments, the method may further include:
when monitoring a preset control operation of a user, displaying prompt information representing connection prohibition in a user graphical interface based on the NLP, wherein the preset control operation comprises a connection operation between a flow element of a main flow and a flow element of an auxiliary flow and/or a connection operation between flow elements of two auxiliary flows.
In this embodiment, when it is monitored that a user attempts to connect a flow element of a main flow and a flow element of an auxiliary flow, or connects flow elements of two auxiliary flows, the electronic device displays prompt information in a user graphical interface based on NLP to prompt the user that the connection cannot be performed, and when the user performs an erroneous connection, the prompt information is displayed, so that user experience can be improved.
As an embodiment of the present invention, on the basis of any of the above embodiments, the flow element of the auxiliary flow includes a start block, and the method may further include:
and in response to the selection operation of the user for the starting block of the auxiliary process, displaying description information of the auxiliary process in the NLP-based user graphical interface, and/or displaying the process elements and the process connecting lines of the auxiliary process according to a preset display pattern.
In this embodiment, the main process includes a main process start block, and the auxiliary process includes an auxiliary process start block. The selection operation may include, but is not limited to, a click operation and a hover operation. The preset display style may include highlighting, displaying in a preset color, and the like.
In one implementation, when the user selects a start block of the auxiliary flow, the electronic device may display description information of the auxiliary flow within the NLP-based user graphical interface to describe the content of the auxiliary flow. In one implementation, when the user selects the start block of the auxiliary flow, the electronic device may display the flow elements and the flow connection lines of the auxiliary flow in a preset display pattern within the NLP-based user graphical interface, so that the user can clearly view all the flow elements and the flow connection lines of the auxiliary flow. In one implementation, when the user selects the start block of the auxiliary flow, the electronic device may display description information of the auxiliary flow in the NLP-based user graphical interface, and display flow elements and flow connection lines of the auxiliary flow according to a preset display pattern.
As an embodiment of the present invention, on the basis of any of the above embodiments, the method may further include:
the name of the start block of the auxiliary flow is modified in response to an editing operation by a user with respect to the start block of the auxiliary flow.
In this embodiment, the name of the start block of the auxiliary flow may be modified. The user can select and edit the starting block of the auxiliary flow, and the starting block of the auxiliary flow is modified into a required name. For example, the user may modify the name of the starting block of the auxiliary flow to the name of the task implemented by the auxiliary flow, so that the user can quickly know the task implemented by the auxiliary flow by looking at the name of the starting block of the auxiliary flow. Taking an auxiliary process for obtaining the configuration parameters of the mobile phone browsed by the user as an example, the user may modify the starting block name of the auxiliary process to the start of obtaining the configuration parameters of the mobile phone.
As an embodiment of the present invention, in the present embodiment, the flow element of the main flow includes a start block, and the flow element of the auxiliary flow does not include a start block.
In the present embodiment, the auxiliary flow may not be provided with a start block because the program of the auxiliary flow is run during the program running of the main flow, and a separate start block may not be provided to perform the start.
Fig. 7 is a schematic structural diagram of a flow generating device at an AI-based RPA flow generating end according to an embodiment of the present application. The flow generating device 70 of the AI-based RPA flow generating terminal is applied to an electronic device, and the electronic device provides a NLP-based user graphical interface. As shown in fig. 7, the flow device 70 of the AI-based RPA flow generating end includes: an acquisition module 701 and a processing module 702.
The acquiring module 701 is configured to acquire a main flow and an auxiliary flow of a target item, where the main flow and the auxiliary flow are not connected.
And the processing module 702 is configured to generate a flow of the target item according to the main flow and the auxiliary flow.
In the embodiment of the application, the electronic equipment provides a user graphical interface based on NLP, and acquires a main flow and an auxiliary flow of a target project, wherein the main flow and the auxiliary flow are not connected; the flow of the target project is generated according to the main flow and the auxiliary flow, and the auxiliary flow which is not connected with the main flow is set, so that the flow architecture of the target project can be clearer, a user can check and modify the auxiliary flow in a targeted manner when maintaining the flow of the target project, and the maintenance difficulty is reduced.
Optionally, there is no process connection line between the main process and the auxiliary process.
Optionally, there are no common flow elements between the main flow and the auxiliary flow.
Optionally, the program of the auxiliary process is adapted to be run during the running of the program of the main process.
Optionally, a first control corresponding to the flow element and a second control corresponding to the flow connecting line are included in the NLP-based user graphical interface;
the obtaining module 701 is specifically configured to:
and constructing and displaying the main flow and the auxiliary flow in the NLP-based user graphic interface in response to the control operation of the user on the first control and the second control.
Optionally, a run control and/or a debug control are further included in the NLP-based user graphical interface;
the processing module 702 is further configured to:
and in response to the triggering operation of the user on the running control and/or the debugging control, executing the program of the main flow, and executing the program of the auxiliary flow during the running of the program of the main flow.
Optionally, the processing module 702 is specifically configured to:
generating a program of the main flow according to the flow elements, the flow connecting lines and the first preset program template of the main flow, and generating a program of the auxiliary flow according to the flow elements, the flow connecting lines and the second preset program template of the auxiliary flow;
and establishing an association relation between the program of the main flow and the program of the auxiliary flow to obtain the flow of the target item, wherein the association relation is used for enabling the program of the auxiliary flow to run during the running of the program of the main flow.
Optionally, the processing module 702 is further configured to:
when monitoring a preset control operation of a user, displaying prompt information representing connection prohibition in a user graphical interface based on the NLP, wherein the preset control operation comprises a connection operation between a flow element of a main flow and a flow element of an auxiliary flow and/or a connection operation between flow elements of two auxiliary flows.
Optionally, the flow element of the auxiliary flow comprises a start block;
the processing module 702 is further configured to:
and in response to the selection operation of the user for the starting block of the auxiliary process, displaying description information of the auxiliary process in the NLP-based user graphical interface, and/or displaying the process elements and the process connecting lines of the auxiliary process according to a preset display pattern.
Optionally, the flow element of the auxiliary flow comprises a start block;
the processing module 702 is further configured to:
the name of the start block of the auxiliary flow is modified in response to an editing operation by a user with respect to the start block of the auxiliary flow.
Optionally, the flow elements of the main flow include a start block and the flow elements of the auxiliary flow do not include a start block.
The flow generation device of the AI-based RPA flow generation end according to the embodiment of the present application may be configured to execute the method embodiments described above, and the implementation principle and the technical effect are similar, which are not described herein again.
Fig. 8 is a schematic hardware structure diagram of an electronic device according to an embodiment of the present application. As shown in fig. 8, the electronic device 80 provided in the present embodiment includes: at least one processor 801 and a memory 802. The electronic device 80 further comprises a communication component 803. The processor 801, the memory 802, and the communication unit 803 are connected by a bus 804. The electronic device 80 also includes a display screen through which the NLP based user graphical interface is provided.
In a specific implementation process, the at least one processor 801 executes the computer-executable instructions stored in the memory 802, so that the at least one processor 801 executes the flow generation method of the AI-based RPA flow generation end as described above.
For a specific implementation process of the processor 801, reference may be made to the above method embodiments, which have similar implementation principles and technical effects, and details of this embodiment are not described herein again.
In the embodiment shown in fig. 8, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in the incorporated application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.
The memory may comprise high speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The present application further provides a computer-readable storage medium, in which computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the method for generating a flow at an RPA flow generating end based on AI as described above is implemented.
The readable storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the readable storage medium may also reside as discrete components in the apparatus.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (24)
1. A flow generation method of an RPA flow generation end based on AI is characterized in that the method is applied to an electronic device, the electronic device provides a user graphical interface based on Natural Language Processing (NLP), and the method comprises the following steps:
s1, acquiring a main process and an auxiliary process of a target project, wherein the main process and the auxiliary process are not connected;
and S2, generating the flow of the target project according to the main flow and the auxiliary flow.
2. The method of claim 1, wherein there is no process connection between the main process and the auxiliary process.
3. The method of claim 1, wherein there are no common flow elements between the primary flow and the secondary flow.
4. The method of claim 1, wherein the program of the secondary process is configured to run during the program run of the primary process.
5. The method according to claim 1, wherein a first control corresponding to a flow element and a second control corresponding to a flow connecting line are included in the NLP-based user graphical interface;
the method for acquiring the main process and the auxiliary process of the target project, wherein the main process and the auxiliary process are not connected with each other, comprises the following steps:
s11, responding to the control operation of the user on the first control and the second control, and constructing and displaying the main flow and the auxiliary flow in the NLP-based user graphic interface.
6. The method according to claim 1, wherein the NLP-based user graphical interface further comprises a run control and/or a debug control;
the method further comprises the following steps:
and S3, responding to the trigger operation of the user for the running control and/or the debugging control, executing the program of the main flow, and executing the program of the auxiliary flow during the program running period of the main flow.
7. The method according to any one of claims 1-6, wherein said generating a flow of said target item from said main flow and said auxiliary flow comprises:
s21, generating a program of the main flow according to the flow element, the flow connecting line and the first preset program template of the main flow, and generating a program of the auxiliary flow according to the flow element, the flow connecting line and the second preset program template of the auxiliary flow;
and S22, establishing an association relationship between the program of the main flow and the program of the auxiliary flow to obtain the flow of the target item, wherein the association relationship is used for enabling the program of the auxiliary flow to run during the running period of the program of the main flow.
8. The method according to any one of claims 1-6, further comprising:
when monitoring a preset control operation of a user, displaying prompt information representing connection prohibition in the NLP-based user graphical interface, wherein the preset control operation comprises a connection operation between a flow element of the main flow and a flow element of the auxiliary flow and/or a connection operation between flow elements of the two auxiliary flows.
9. The method of any of claims 1-6, wherein the flow elements of the auxiliary flow comprise a start block;
the method further comprises the following steps:
in response to the selection operation of the user for the starting block of the auxiliary process, displaying description information of the auxiliary process in the NLP-based user graphical interface, and/or displaying process elements and process connecting lines of the auxiliary process according to a preset display pattern.
10. The method of any of claims 1-6, wherein the flow elements of the auxiliary flow comprise a start block;
the method further comprises the following steps:
modifying a name of a starting block of the auxiliary flow in response to a user's editing operation for the starting block of the auxiliary flow.
11. The method according to any of claims 1-6, wherein the flow elements of the primary flow include a start block and the flow elements of the secondary flow do not include a start block.
12. A flow generating device of an RPA flow generating terminal based on AI is characterized in that the flow generating device is applied to an electronic device, the electronic device provides a user graphic interface based on NLP, and the device comprises:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a main process and an auxiliary process of a target project, and the main process is not connected with the auxiliary process;
and the processing module is used for generating the flow of the target project according to the main flow and the auxiliary flow.
13. The apparatus of claim 12, wherein there is no process connection between the main process and the auxiliary process.
14. The apparatus of claim 12, wherein there are no common flow elements between the primary flow and the secondary flow.
15. The apparatus of claim 12, wherein the program of the secondary process is configured to run during the program run of the primary process.
16. The apparatus of claim 12, wherein a first control corresponding to a flow element and a second control corresponding to a flow connection line are included in the NLP-based user graphical interface;
the acquisition module is specifically configured to:
and responding to the control operation of the user on the first control and the second control, and constructing and displaying the main flow and the auxiliary flow in the NLP-based user graphic interface.
17. The apparatus of claim 12, further comprising a run control and/or a debug control within the NLP based user graphical interface;
the processing module is further configured to:
and responding to the triggering operation of the user on the running control and/or the debugging control, executing the program of the main flow, and executing the program of the auxiliary flow during the program running of the main flow.
18. The apparatus according to any one of claims 12 to 17, wherein the processing module is specifically configured to:
generating a program of the main flow according to the flow elements, the flow connecting lines and the first preset program template of the main flow, and generating a program of the auxiliary flow according to the flow elements, the flow connecting lines and the second preset program template of the auxiliary flow;
and establishing an association relationship between the program of the main flow and the program of the auxiliary flow to obtain the flow of the target item, wherein the association relationship is used for enabling the program of the auxiliary flow to run during the running of the program of the main flow.
19. The apparatus of any one of claims 12-17, wherein the processing module is further configured to:
when monitoring a preset control operation of a user, displaying prompt information representing connection prohibition in the NLP-based user graphical interface, wherein the preset control operation comprises a connection operation between a flow element of the main flow and a flow element of the auxiliary flow and/or a connection operation between flow elements of the two auxiliary flows.
20. The apparatus of any of claims 12-17, wherein the flow elements of the auxiliary flow comprise a start block;
the processing module is further configured to:
in response to the selection operation of the user for the starting block of the auxiliary process, displaying description information of the auxiliary process in the NLP-based user graphical interface, and/or displaying process elements and process connecting lines of the auxiliary process according to a preset display pattern.
21. The apparatus of any of claims 12-17, wherein the flow elements of the auxiliary flow comprise a start block;
the processing module is further configured to:
modifying a name of a starting block of the auxiliary flow in response to a user's editing operation for the starting block of the auxiliary flow.
22. The apparatus according to any of claims 12-17, wherein the flow elements of the primary flow include a start block and the flow elements of the secondary flow do not include a start block.
23. An electronic device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the process generation method of the AI-based RPA process generating terminal of any of claims 1-11.
24. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein computer-executable instructions, which, when executed by a processor, implement the flow generation method of the AI-based RPA flow generation side according to any one of claims 1 to 11.
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| CN112558954A (en) * | 2020-12-29 | 2021-03-26 | 北京来也网络科技有限公司 | Information extraction method, device, medium and electronic equipment combining RPA and AI |
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| CN115357309B (en) * | 2022-10-24 | 2023-07-14 | 深信服科技股份有限公司 | Data processing method, device, system and computer readable storage medium |
| CN118227114B (en) * | 2024-05-23 | 2024-07-30 | 安徽思高智能科技有限公司 | RPA combined flow recommending method, storage medium and electronic equipment |
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