CN112260877B - AI-based RPA robot management method, platform and storage medium - Google Patents

AI-based RPA robot management method, platform and storage medium Download PDF

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Publication number
CN112260877B
CN112260877B CN202011173392.3A CN202011173392A CN112260877B CN 112260877 B CN112260877 B CN 112260877B CN 202011173392 A CN202011173392 A CN 202011173392A CN 112260877 B CN112260877 B CN 112260877B
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China
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management
service
request
platform
client
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CN112260877A (en
Inventor
汪冠春
胡一川
褚瑞
李玮
何亮
王真希
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Beijing Laiye Network Technology Co Ltd
Laiye Technology Beijing Co Ltd
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Beijing Laiye Network Technology Co Ltd
Laiye Technology Beijing Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H04L41/5041—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the time relationship between creation and deployment of a service
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
    • H04L63/105—Multiple levels of security
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/14—Session management
    • H04L67/141—Setup of application sessions

Abstract

The embodiment of the invention provides an AI-based RPA robot management method, an AI-based RPA robot management platform and a storage medium. The specific implementation scheme relates to the RPA field, which comprises the following steps: the method is applied to an AI-based RPA robot management platform, and the AI-based RPA robot management platform comprises an application layer, a service layer and a base layer which are sequentially connected in a communication manner; the method comprises the following steps: s1, an application layer receives a management request sent by a client, wherein the management request comprises: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and sending a management request to the service layer through the corresponding access connection mode; s2, the service layer carries out corresponding management response according to the management request; and S3, the base layer stores related data in the process of providing management service by the service layer. The universality of the RPA robot management platform is improved, and the RPA robot can be comprehensively and effectively managed.

Description

AI-based RPA robot management method, platform and storage medium
Technical Field
The embodiment of the invention relates to the technical field of robot automation processes, in particular to an AI-based RPA robot management method, an AI-based RPA robot platform and an AI-based RPA robot storage medium.
Background
Robot process automation (Robotic process automation, RPA for short) is to simulate the operation of a human on a computer through specific robot software, and automatically execute process tasks according to rules. The RPA robot can intelligently understand the existing application of enterprises through a user use interface, and automates the conventional operation based on rules to finish the work with high repeatability but fixed business logic. If the mail reading work is automatically repeated, files and reports are generated in batches, and the work such as boring file inspection is completed.
Artificial intelligence (Artificial Intelligence, AI for short) is a piece of technical science that studies, develops theories, methods, techniques and application systems for simulating, extending and expanding human intelligence.
The RPA robot includes: the development platform of the RPA robot (Creater for short), the execution platform of the RPA robot (workbench for short) and the management platform of the RPA robot (Commander for short). The development platform of the RPA robot is responsible for developing the RPA robot aiming at specific tasks. The execution platform of the RPA robot is responsible for automatically executing the corresponding tasks which the RPA robot has automatically completed. The management platform of the RPA robot is used for centralized management and control of data and monitoring the running condition of the RPA robot.
In the prior art, when the management platform of the RPA robot is used for managing the RPA robot, only the specific client is allowed to access the management platform of the RPA robot so as to realize management, so that the universality of the management platform of the RPA robot is poor, and the specific client is only allowed to manage specific data by the management platform of the RPA robot so as to not comprehensively and effectively manage the RPA robot.
Disclosure of Invention
The embodiment of the invention provides an AI-based RPA robot management method, an AI-based RPA robot management platform and a storage medium, which solve the technical problems that when the RPA robot is managed by adopting the RPA robot management platform in the prior art, the management platform of the RPA robot is only allowed to be accessed through a specific client so as to realize management, the universality of the RPA robot management platform is poor, and the specific client only allows the RPA robot management platform to manage specific data so as to not comprehensively and effectively manage the RPA robot.
In a first aspect, an embodiment of the present invention provides an AI-based RPA robot management method, which is applied to an AI-based RPA robot management platform, where the AI-based RPA robot management platform includes an application layer, a service layer, and a base layer that are sequentially connected in communication;
The method comprises the following steps:
s1, the application layer receives a management request sent by a client, wherein the management request comprises the following components: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to a service layer through the corresponding access connection mode;
s2, the service layer carries out corresponding management response according to the management request;
and S3, the base layer stores related data in the process of providing management service by the service layer.
In a second aspect, an embodiment of the present invention provides an AI-based RPA robot management platform, including: an application layer, a service layer and a base layer which are sequentially connected in a communication way;
the application layer is configured to receive a management request sent by a client, where the management request includes: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to a service layer through the corresponding access connection mode;
the service layer is used for carrying out corresponding management response according to the management request;
the base layer is used for storing related data in the process of providing management service by the service layer.
In a third aspect, an embodiment of the present invention provides an AI-based RPA robot management platform, including:
a memory, a processor, and a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any of the first aspects.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium having stored thereon a computer program for execution by a processor to implement the method of any of the first aspects.
The embodiment of the invention provides an AI-based RPA robot management method, an AI-based RPA robot platform and a storage medium, wherein the AI-based RPA robot management method, the AI-based RPA robot platform and the storage medium receive a management request sent by a client through an application layer, and the management request comprises the following steps: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and sending a management request to the service layer through the corresponding access connection mode, wherein the service layer carries out corresponding management response according to the management request, and the base layer stores related data in the process of providing management service by the service layer. Because the RPA robot management platform can be accessed by a plurality of different types of clients through different access connection modes, and further according to different clients, the RPA robot can perform corresponding management response aiming at different management requests, so that the universality of the RPA robot management platform is improved, and the RPA robot can be comprehensively and effectively managed.
It should be understood that the description of the invention above is not intended to limit key or critical features of embodiments of the invention, nor to limit the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic diagram of a system network architecture corresponding to an AI-based RPA robot management method according to an embodiment of the present invention;
FIG. 2 is a flowchart of an AI-based RPA robot management method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a system network architecture corresponding to an AI-based RPA robot management method according to a second embodiment of the present invention;
fig. 4 is a flowchart of an AI-based RPA robot management method according to a second embodiment of the present invention;
Fig. 5 is a flowchart of an AI-based RPA robot management method according to a third embodiment of the present invention;
fig. 6 is a flowchart of an AI-based RPA robot management method according to a fourth embodiment of the present invention;
fig. 7 is a flowchart of an AI-based RPA robot management method according to a fifth embodiment of the present invention;
fig. 8 is a flowchart of an AI-based RPA robot management method according to a sixth embodiment of the present invention;
fig. 9 is a flowchart of an AI-based RPA robot management method according to a seventh embodiment of the present invention;
fig. 10 is a first structural schematic diagram of an AI-based RPA robot management platform according to an eighth embodiment of the present invention;
fig. 11 is a second structural schematic diagram of an AI-based RPA robot management platform according to a ninth embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While the invention is susceptible of embodiment in the drawings, it is to be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided to provide a more thorough and complete understanding of the invention. It should be understood that the drawings and embodiments of the invention are for illustration purposes only and are not intended to limit the scope of the present invention.
The terms first, second, third, fourth and the like in the description and in the claims and in the above-described figures, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be capable of being practiced otherwise than as specifically illustrated and described. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The following describes an AI-based RPA robot management method, platform, and storage medium according to an embodiment of the present invention with reference to the accompanying drawings.
Example 1
Fig. 1 is a schematic diagram of a system network architecture corresponding to an AI-based RPA robot management method according to an embodiment of the present invention.
As shown in fig. 1, in this embodiment, a system corresponding to the AI-based RPA robot management method includes: client and AI-based RPA robot management platform 2. The AI-based RPA robot management platform 2 includes an application layer, a service layer, and a base layer. The application layer is configured to receive a management request sent by the client 1, and send the management request to the service layer through a corresponding access connection mode according to different clients. The service layer is used for carrying out corresponding management response according to the management request, and the base layer is used for storing related data in the process of providing management service by the service layer. The clients can be various clients, and each client is connected with the AI-based RPA robot management platform by adopting a corresponding access connection mode. As in fig. 1 the client comprises: the first client 11 corresponds to a first access connection, the second client 12 corresponds to a second access connection, and the third client 13 corresponds to a third access connection.
Fig. 2 is a flowchart of an AI-based RPA robot management method according to an embodiment of the present invention, and as shown in fig. 2, an execution subject of the embodiment is an AI-based RPA robot management platform, and the RPA robot management platform may be coupled to an electronic device, and the AI-based RPA robot management method according to the embodiment includes the following steps.
Step 1-S1, an application layer receives a management request sent by a client, wherein the management request comprises: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to the service layer through the corresponding access connection mode.
Specifically, in this embodiment, the application layer is in communication connection with the client, and before the application layer receives the management request sent by the client, a mapping relationship between the identification information of the client and the corresponding access connection mode may be pre-established and stored. After receiving the management request sent by the client, the application layer analyzes the management request to obtain the identification information of the client, and determines a corresponding access connection mode according to the identification information and the mapping relation of the client. After the corresponding access connection mode is determined, the management request is sent to the service layer through the corresponding access connection mode.
The client may be a web browser, an RPA robot execution platform client, an RPA robot development platform client, a third party platform, or the like. If the client is a web browser or an RPA robot execution platform client or an RPA robot development platform client, the corresponding access mode includes a first access connection mode, and the first access connection mode is an API interface connection mode of an RPA robot management platform. If the client is an RPA robot execution platform client, the corresponding access method may further include: the second access connection mode is a WebSocket protocol connection mode. If the client is a third party platform, the corresponding access connection mode may be a third access connection mode, and the third access connection mode may be an open API interface connection mode.
And step 1-S2, the service layer carries out corresponding management response according to the management request.
In this embodiment, according to different clients, the management requests received by the application layer may be different, and corresponding management responses are performed for each management request.
In one embodiment, the management request may further include: the management type is obtained after the service layer receives the management request, the corresponding management service is determined according to the management type, and then the corresponding management service carries out corresponding management response according to the management request.
Wherein, the management service may include: global services, institutional services, RPA services, etc.
It is understood that each management service includes a different underlying class of management services. After the corresponding management service is determined, the corresponding basic category management service is determined, and then the corresponding basic category management service performs corresponding management response according to the management request.
The global service is used for providing configuration services for the whole RPA robot, and basic category services included in the global service can comprise management platform configuration services, authorization management services, enterprise management services and the like of the RPA robot. The underlying category management services included by the facility services may include, for example: department management services, employee role management services, and the like. And the RPA service is used for providing the RPA business related service for the enterprise. The RPA service includes basic category management services that may include, for example, a flow package management service, a flow management service, an execution platform management service, a development platform management service, a task management service, a plan management service, and the like.
And step 1-S3, the base layer stores related data in the process of providing management service by the service layer.
In this embodiment, when the service layer performs a corresponding management response according to the management request, that is, when the service layer provides the management service, related data will be generated, and then the base layer stores the related data.
It can be understood that the base layer can classify corresponding related data generated in different management service processes, and further store the data in a classified manner. A different database may be included in the base layer. Including, for example, mySQL database, elastic Search database, and MinIO distributed file database, as applicable to persistent storage. Suitable databases for non-persistent storage, such as Redis databases and Rabbit MQ service databases.
In the AI-based RPA robot management method provided in this embodiment, an application layer receives a management request sent by a client, where the management request includes: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and sending a management request to the service layer through the corresponding access connection mode, wherein the service layer carries out corresponding management response according to the management request, and the base layer stores related data in the process of providing management service by the service layer. Because the RPA robot management platform can be accessed by a plurality of different types of clients through different access connection modes, and further according to different clients, the RPA robot can perform corresponding management response aiming at different management requests, so that the universality of the RPA robot management platform is improved, and the RPA robot can be comprehensively and effectively managed.
Example two
Fig. 3 is a schematic diagram of a system network architecture corresponding to an AI-based RPA robot management method according to a second embodiment of the present invention, as shown in fig. 3, in this embodiment, the system corresponding to the AI-based RPA robot management method includes: client and RPA robot management platform. The RPA robot management platform comprises an application layer, a service layer and a base layer. The application layer is used for receiving the management request sent by the client and sending the management request to the service layer through a corresponding access connection mode according to different clients. The service layer is used for carrying out corresponding management response according to the management request, and the base layer is used for storing related data in the process of providing management service by the service layer. And the client may coexist with the web browser 11, the RPA robot execution platform client 12, the RPA robot development platform client 13, or the third party platform 14.
The connection mode corresponding to the web browser 11 is a first access connection mode, and the connection mode corresponding to the RPA robot execution platform client 12 may include: the connection mode corresponding to the RPA robot development platform client 13 is the first access connection mode, and the connection mode of the third party platform 14 is the third connection mode. The first access connection mode is an API interface connection mode of the RPA robot management platform. The second access connection mode is a WebSocket protocol connection mode, and the third access connection mode can be an open API interface connection mode.
As shown in fig. 3, if the client is the Web browser 11, the Web browser 11 is connected to the application layer through the first access connection mode after passing through the Web service, and the application layer and the service layer communicate through the first access connection mode.
Fig. 4 is a flowchart of an AI-based RPA robot management method according to a second embodiment of the present invention, as shown in fig. 4, where, based on the AI-based RPA robot management method according to the first embodiment, steps 1-S1 to 1-S3 are further refined, the AI-based RPA robot management method according to the first embodiment includes the following steps:
step 2-S1, an application layer receives a management request sent by a client, wherein the management request comprises: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to the service layer through the corresponding access connection mode.
The identification information of the client may be a name of the client, a number of the client stored in the AI-based RPA robot management platform, or the like, which is not limited in this embodiment.
In this embodiment, the client is any one of the clients shown in fig. 3, that is, the client is any one of a web browser, an RPA robot execution platform client, an RPA robot development platform client, and a third party platform.
Further, in this embodiment, the management request further includes: the management type.
Wherein the management type may be a global type, an organization type, or an RPA type.
And step 2-S21, the service layer determines corresponding management service according to the management type.
In this embodiment, the service layer establishes a mapping relationship between the management type and the corresponding management service in advance, and then analyzes the management type after receiving the management request, and further determines the corresponding management service according to the mapping relationship.
As shown in fig. 3, the management service corresponding to the management type includes: global services, institutional services, and RPA services.
And step 2-S22, corresponding management service performs corresponding management response according to the management request.
Specifically, in this embodiment, the management response corresponding to the management request is different according to the management service.
In this embodiment, the global service includes a management platform configuration service, an authorization management service, an enterprise management service, and the like of the RPA robot. And the global service performs corresponding management response according to the management platform configuration request to configure the management platform according to the management platform configuration request. And the global service performs corresponding management response according to the authorization management request to perform corresponding authorization. And the global service performs corresponding management response according to the enterprise management request to perform corresponding enterprise management according to the enterprise management request.
In this embodiment, the institution service includes: department management services, employee role management services, and the like. The corresponding management response is carried out by the organization service according to the department management request to manage the departments according to the department management request. And the corresponding management response is carried out by the organization service according to the staff management request to manage staff according to the staff management request. And the corresponding management response is carried out by the organization service according to the employee role management request, so that the employee roles are managed according to the employee role management request.
In this embodiment, the RPA service includes: a flow package management service, a flow management service, an execution platform management service, a development platform management service, a task management service, a plan management service, and the like. And the RPA service carries out corresponding management response according to the flow packet management request to manage the flow packet according to the flow packet management request. The corresponding management response is similar for other basic classes of management services of the RPA service, and will not be described in detail here.
In this embodiment, when the service layer performs a corresponding management response according to the management request, the service layer determines a corresponding management service according to the management type, and the corresponding management service performs a corresponding management response according to the management request, so that the service layer can perform a corresponding management response by the corresponding management service according to the management type, and the management services do not affect each other, so that the RPA robot can be managed more reasonably and orderly, and the management efficiency of the RPA robot is improved.
And 2-S3, the base layer stores related data in the process of providing management service by the service layer.
In this embodiment, the base layer includes: a persistence component and an intermediary component.
Wherein the persistence component comprises: mySQL database, elastic Search database, and MinIO distributed file database. The intermediate assembly includes: redis database and Rabbit MQ services.
As shown in fig. 3, in this embodiment, the MySQL database is a relational database, and is configured to store service data with strong relevance: such as for storing department information, employee role information, and may also store data for processes, packages, tasks, plans, etc. of the execution platform or development platform.
In this embodiment, the Elastic Search database is used to store data generated in large amounts: for example, the method is used for storing data such as task running logs, task indexes, business logs and the like.
In this embodiment, the MinIO distributed file database is used to store various files and binary data, including flow files, screen recording files, and the like.
In this embodiment, the Redis database is used to cache distributed data or task queues, so that task scheduling queues can be implemented, and efficient task scheduling can be implemented.
In this embodiment, the rabit MQ service is configured to store messages interacted between the AI-based RPA robot management platform and the RPA robot execution platform or the RPA robot development platform, form a message queue, ensure stability of communication between the platforms, and improve load capacity of the RPA robot management platform.
In this embodiment, when the base layer stores the relevant data in the process of providing the management service by the service layer, the relevant data is classified and stored in the corresponding database according to the type of the relevant data, so that the data can be managed and stored more reasonably, and the efficiency of the RPA robot management platform for calling the relevant data is improved.
Example III
Fig. 5 is a flowchart of an AI-based RPA robot management method according to a third embodiment of the present invention, and as shown in fig. 5, the AI-based RPA robot management method according to the present embodiment further refines each step when the client is a web browser based on the first embodiment or the second embodiment, and then the AI-based RPA robot management method according to the present embodiment includes the following steps:
and step 3-S01, the application layer receives a global management interface display request triggered by the client through Web service.
In this embodiment, when a user has a need to manage an RPA robot through an AI-based RPA robot management platform, a global management interface display request is triggered through a client, and the global management interface display request is sent to an application layer through a first access connection mode after passing through Web services, and the application layer receives the global management interface display request and sends the global management interface display request to a service layer through the first access connection mode.
And step 3-S02, the service layer controls the client to display the global management interface according to the global management interface display request.
The service layer performs corresponding global management interface display response according to the global management interface display request, and sends the global management interface display response to the client through the application layer so as to control the client to display the global management interface according to the global management interface display response.
Wherein any one or more of the following management components are included in the global management interface:
the system comprises an organization management component, a data management component, a flow and flow package management component, an execution platform management component, a development platform management component, a task management component, a planning management component and a management platform setting component.
Step 3-S1, an application layer receives a management request sent by a client, wherein the management request comprises: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to the service layer through the corresponding access connection mode.
And step 3-S2, the service layer performs corresponding management response according to the management request.
Optionally, in this embodiment, the user may send, through each component in the global management interface displayed by the client, a corresponding management request to the AI-based RPA robot management platform, and after the application layer receives the management request sent by the client, the application layer sends the management request to the service layer through the first access connection manner, where the service layer of the AI-based RPA robot management platform performs a corresponding management response.
And step 3-S3, the base layer stores related data in the process of providing management service by the service layer.
In this embodiment, the implementation manner of the steps 3-S3 is similar to the implementation manner of the steps 2-S3 in the second embodiment of the present invention, and will not be described in detail herein.
According to the AI-based RPA robot management method provided by the embodiment, when the client is a Web browser, the application layer receives a global management interface display request triggered by the client through Web service before the application layer receives the management request sent by the client, the service layer controls the client to display the global management interface according to the global management interface display request, and a user can trigger the AI-based RPA robot management platform to manage the RPA robot through a management component on the global management interface, so that the interactivity with the user is improved, and the user experience is further improved.
Example IV
Fig. 6 is a flowchart of an AI-based RPA robot management method according to a fourth embodiment of the present invention, as shown in fig. 6, where the AI-based RPA robot management method according to the present embodiment is further refined in steps 1-S2 when a platform client is executed for an RPA robot by a client on the basis of the first embodiment or the second embodiment, and the access connection manner includes: the first access connection manner, the AI-based RPA robot management method provided in this embodiment includes the following steps:
And step 4-S2i, the RPA service authenticates the execution platform according to the flow issuing request.
And step 4-S2ii, if the execution platform passes the authentication, issuing the flow.
In this embodiment, when the management request is a flow issue request, the management service determined by the service layer is an RPA service, and then the RPA service authenticates the RPA robot execution platform according to the flow issue request first, determines whether the RPA robot execution platform has a task corresponding to the authority to execute the flow, and if the RPA robot execution platform has the task corresponding to the authority to execute the flow, the RPA robot execution platform passes the authentication, and issues the flow after the authentication passes.
The flow may be any flow that satisfies the execution condition. Or the flow issuing request comprises a flow identifier, and the flow is a flow corresponding to the flow identifier.
According to the RPA robot management method, when the RPA robot execution platform has the requirement of executing tasks corresponding to the flow, and the client of the RPA robot execution platform sends a flow issuing request, the RPA service firstly authenticates the RPA robot execution platform, and issues the flow after the authentication is passed, so that the safety of flow issuing link management is improved.
Optionally, on the basis of the technical scheme provided by the implementation IV of the invention, the management request is a task running log storage request; steps 1-S2 specifically include:
and the RPA service stores the task running log into a component corresponding to the base layer according to the task running log storage request.
In this embodiment, if the management request is a task running log storage request, the management service determined by the service layer is an RPA service, and the RPA service determines, according to the task running log storage request, a component in the base layer that needs to store the task running log, and stores the task running log in the component corresponding to the base layer.
In this embodiment, the task execution log may be stored in an Elastic Search database in the persistence component of the base layer.
In this embodiment, when the management request is a task running log storage request, the RPA service stores the task running log in a component corresponding to the base layer according to the task running log storage request, so that the task running log can be effectively managed, and when a fault occurs in the processing task of the RPA robot execution platform, the stored task running log can be used for rapidly checking the fault.
Example five
Fig. 7 is a flowchart of an AI-based RPA robot management method according to a fifth embodiment of the present invention, as shown in fig. 7, where, based on the first embodiment or the second embodiment, steps 1-S2 are further refined when a platform client is executed for an RPA robot by using the AI-based RPA robot management method according to the present embodiment, where, the management request is a data call request, and the access connection manner includes: the first access connection manner, the AI-based RPA robot management method provided in this embodiment includes the following steps:
step 5-S21), the RPA service obtains corresponding data from the corresponding component of the base layer according to the data call request.
Wherein, the corresponding subassembly is: rabbit MQ services.
In this embodiment, the second access connection mode is a WebSocket protocol connection mode, and long connection between the client and the management platform of the RPA robot can be ensured through heartbeat by the WebSocket protocol connection mode. When the application layer receives a data call request sent by the client, the application layer sends a management request to the service layer in a WebSocket protocol connection mode, the service layer further determines that the corresponding management service is RPA service, and corresponding data can be obtained from Rabbit MQ service of the base layer according to data identification information in the data call request.
The corresponding data may be data required for executing the task. The data may be stored in the form of message queues in the Rabbit MQ service.
Step 5-S22), the RPA service sends the data to the execution platform.
In this embodiment, the RPA service sends data to the execution platform in a WebSocket protocol connection manner through the application layer, so that the RPA robot execution platform executes a corresponding task according to the data.
Natural language processing (Natural Language Processing, abbreviated as NLP) is an important direction in the fields of computer science and AI, and the content of NLP research includes, but is not limited to, the following branch fields: text classification, information extraction, automatic abstracting, intelligent question and answer, topic recommendation, machine translation, topic word recognition, knowledge base construction, deep text representation, named entity recognition, text generation, text analysis (lexical, syntactic, grammatical, etc.), speech recognition and synthesis, and the like. The corpus is an important resource for NLP, and a knowledge base can be constructed by using the corpus and used for machine translation, intelligent question-answering and the like.
Optical character recognition (Optical Character Recognition, abbreviated as OCR) is an important aspect in the fields of automatic recognition technology and AI, and is a meaning of recognizing optical characters by image processing and pattern recognition technology.
In this embodiment, the RPA robot execution platform may automatically execute a process related to text, such as text classification, text generation, etc., by using NLP technology, or may automatically execute a process related to character recognition, such as automatically recognizing invoice codes, invoice numbers, invoicing dates, etc., in invoices by using OCR technology. Alternatively, the RPA robot execution platform may also perform processes related to text or character recognition using both OCR technology and NLP technology.
The method for managing the RPA robot based on AI provided in this embodiment, the access connection mode further includes: a second access connection mode; the management request is a data call request, and the service layer responds to the corresponding management according to the management request, the RPA service acquires corresponding data from the corresponding component of the base layer according to the data call request, the RPA service sends the data to the execution platform, long connection between the RPA robot execution platform and the RPA robot management platform can be ensured through a WebSocket protocol connection mode, and then connection is not required to be re-established when the RPA robot execution platform calls the data from the RPA robot management platform, so that the data call efficiency is improved.
Example six
Fig. 8 is a flowchart of an AI-based RPA robot management method according to a sixth embodiment of the present invention, as shown in fig. 8, where the AI-based RPA robot management method according to the present embodiment further refines steps 1-S2 when the client is an RPA robot development platform client based on the first embodiment or the second embodiment, and the management request is a flow release request, and the access connection manner includes: the first access connection manner, the AI-based RPA robot management method provided in this embodiment includes the following steps:
and step 6-S2a, the RPA service authenticates the development platform according to the flow release request.
And step 6-S2b, if the development platform passes the authentication, the RPA service issues the flow.
In this embodiment, when the management request is a flow release request, the management service determined by the service layer is an RPA service, and the RPA service authenticates the RPA robot development platform according to the flow release request first, determines whether the RPA robot development platform has a task corresponding to the authority release flow, and if the RPA robot development platform has a task corresponding to the authority release flow, the RPA robot development platform authenticates and releases the flow after the authentication passes.
The process may be any process that satisfies the release condition. Or the flow issuing request comprises a flow identifier, and the flow is a flow corresponding to the flow identifier.
In this embodiment, the RPA service publishing process is developed by the RPA robot development platform. In order to improve the convenience of RPA process development, the use of visual process editing software is becoming wider and wider. Such software may provide a visual editing interface for the user. The user may select a control on the interface to construct the flow chart and edit the program instructions within the flow blocks in the flow chart. The software background generates corresponding program codes according to the flow chart constructed by the user, so that the user can conveniently design the RPA flow in a visualized mode according to the service requirement.
The RPA robot development platform can provide a user graphical interface, acquire a main flow and an auxiliary flow of a target project by utilizing a control in the user graphical interface, and generate the flow of the target project according to the main flow and the auxiliary flow. The RPA robot development platform can extract information from specific contents in a main flow and an auxiliary flow in a target project by adopting an NLP technology based on the graphical interface so as to conveniently run or debug the flow of the target project.
According to the AI-based RPA robot management method provided by the embodiment, when the RPA robot development platform has a flow demand corresponding to a release task, a flow release request is sent through the client of the RPA robot development platform, the RPA service firstly authenticates the RPA robot development platform, releases the flow after the authentication is passed, and the safety of flow release link management is improved.
Example seven
Fig. 9 is a flowchart of an AI-based RPA robot management method according to a seventh embodiment of the present invention, as shown in fig. 9, where the AI-based RPA robot management method according to the present embodiment further refines steps 1-S2 when the client is an RPA robot development platform client based on the first embodiment or the second embodiment, and the management request is a data call request, and the access connection manner includes: the first access connection manner, the AI-based RPA robot management method provided in this embodiment includes the following steps:
and 7-S2A, the RPA service acquires corresponding data from the corresponding component of the base layer according to the data call request.
Wherein the data is any one of the following data: parameter data, task data, and data queues.
And step 7-S2B, the RPA service sends the data to the development platform.
Wherein, the data call request can comprise: data identification information.
In this embodiment, when the RPA robot development platform has the data required for developing the process, the application layer obtains the data call request through the first access connection mode and sends the data call request to the service layer through the first access connection mode, the service layer determines that the corresponding management service is the RPA service, and then determines the component and the database storing the data in the base layer according to the data identification information in the data call request through the RPA service, further obtains the data from the corresponding component and the database, sends the data to the application layer through the first access connection mode through the RPA service, and then sends the data to the RPA robot development platform client to send the data to the RPA robot development platform.
In this embodiment, if the data is parameter data, the database in the corresponding component is MySQL database. If the data is task data and the data queue, the database in the corresponding component is a Redis database.
According to the AI-based RPA robot management method provided by the embodiment, a client is an RPA robot development platform, and if a management request is a data call request, an RPA service acquires corresponding data from a component corresponding to a base layer according to the data call request; the RPA service sends the data to the development platform, so that the requirement that the RPA robot development platform acquires the data from the RPA robot management platform can be met.
Optionally, in the RPA robot management method provided by the present invention, on the basis of the first embodiment or the second embodiment, the client is a third party platform, and the access connection mode is a third access connection mode.
The third access connection mode is an open API interface connection mode.
In this embodiment, the third party platform is accessed to the RPA robot management platform through the third access connection mode, and may obtain the operations of parameters, operating the data queue, creating the task, setting the task parameters, querying the task result and the like from the RPA robot management platform.
According to the AI-based RPA robot management method provided by the embodiment, the client can be a third party platform and is communicated with the RPA robot management platform through a third access connection mode, so that interaction with the RPA robot management platform is realized, and the universality of the RPA robot management platform is further improved.
Example eight
Fig. 10 is a first structural schematic diagram of an AI-based RPA robot management platform according to an eighth embodiment of the present invention, and as shown in fig. 10, an AI-based RPA robot management platform 1000 according to the present embodiment includes: an application layer 1001, a service layer 1002, and a base layer 1003 which are sequentially communicatively connected;
The application layer 1001 is configured to receive a management request sent by a client, where the management request includes: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and sending a management request to the service layer through the corresponding access connection mode; a service layer 1002, configured to perform a corresponding management response according to the management request; the base layer 1003 is configured to store related data in a service layer providing management service.
The technical scheme of the method embodiment shown in fig. 1 can be executed by the AI-based RPA robot management platform provided in this embodiment, and its implementation principle and technical effects are similar, and will not be described here again.
Optionally, the management request further includes: a management type;
the service layer 1002 is specifically configured to: determining corresponding management service according to the management type; and corresponding management service performs corresponding management response according to the management request.
Wherein the management service comprises: global services, institutional services, and RPA services.
Optionally, the client is a web browser, the management request is a global management request, and the corresponding access connection mode is a first access connection mode;
the application layer 1001 is further configured to receive a global management interface display request triggered by the client through the Web service; the service layer 1002 is further configured to control, by the service layer, the client to display the global management interface according to the global management interface display request.
Wherein the global management interface comprises any one or more of the following management components:
the system comprises an organization management component, a data management component, a flow and flow package management component, an execution platform management component, a development platform management component, a task management component, a planning management component and a management platform setting component.
Optionally, the client is an RPA robot execution platform client, the management request is a flow issuing request, and the access connection mode includes: a first access connection mode;
the service layer is specifically used for: authenticating the execution platform according to the flow issuing request; and if the execution platform passes the authentication, issuing the flow.
Optionally, the management request is a task running log storage request;
the service layer 1002 is specifically configured to:
and the RPA service stores the task running log into a component corresponding to the base layer according to the task running log storage request.
Optionally, the access connection manner further includes: a second access connection mode; the management request is a data call request;
the service layer is specifically used for: acquiring corresponding data from the corresponding components of the base layer according to the data call request; transmitting the data to an execution platform; the corresponding components are: rabbit MQ services.
Optionally, the client is an RPA robot development platform client, the management request is a flow release request, and the access connection mode is a first access connection mode;
the service layer is specifically used for: authenticating the development platform according to the flow release request; and if the development platform passes the authentication, the RPA service issues the flow, wherein the flow is developed by the development platform by utilizing NLP.
Optionally, the management request is a data call request;
the service layer is specifically used for:
acquiring corresponding data from the corresponding components of the base layer according to the data call request; and sending the data to a development platform.
Wherein the data is any one of the following data: parameter data, task data, and data queues.
Optionally, the client is a third party platform, and the access connection mode is a third access connection mode.
Optionally, the base layer includes: a persistence component and an intermediate component;
the persistence component includes: mySQL database, elastic Search database, and MinIO distributed file database;
the intermediate assembly includes: redis database and Rabbit MQ services.
The RPA robot management platform provided in this embodiment may execute the technical solutions of the method embodiments shown in fig. 2 to 9, and its implementation principle and technical effects are similar, and are not described herein again.
Example nine
Fig. 11 is a second structural schematic diagram of an AI-based RPA robot management platform according to a ninth embodiment of the present invention, and as shown in fig. 11, an AI-based RPA robot management platform 1100 according to the present embodiment includes: memory 1101, processor 1102, and computer programs.
Wherein the computer program is stored in the memory 1101 and configured to be executed by the processor 1102 to implement the AI-based RPA robot management method provided by any one of the first to seventh embodiments.
The description may be understood by referring to the description and effects corresponding to the steps of fig. 1 to fig. 9, and the description is not repeated here.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, the computer program being executed by a processor to implement the AI-based RPA robot management method provided in any one of the first to seventh embodiments of the invention.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in hardware plus software functional modules.
Program code for carrying out methods of the present invention may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Moreover, although operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.

Claims (16)

1. The method is applied to an AI-based RPA robot management platform, and the AI-based RPA robot management platform comprises an application layer, a service layer and a base layer which are sequentially in communication connection;
the method comprises the following steps:
s1, the application layer receives a management request sent by a client, wherein the management request comprises the following components: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to a service layer through the corresponding access connection mode;
s2, the service layer carries out corresponding management response according to the management request;
s3, the base layer stores related data in the process of providing management service by the service layer;
the client is a web browser, an RPA robot execution platform client, an RPA robot development platform client or a third party platform;
Each client is connected with the AI-based RPA robot management platform by adopting a corresponding access connection mode.
2. The method according to claim 1, wherein the management request further includes: a management type;
the step S2 specifically comprises the following steps:
s21, the service layer determines corresponding management service according to the management type;
s22, the corresponding management service carries out corresponding management response according to the management request.
3. The method of claim 2, wherein the management service comprises: global services, institutional services, and RPA services.
4. The method of claim 1, wherein the client is a web browser, the management request is a global management request, the corresponding access connection mode is a first access connection mode, and the first access connection mode is an API interface connection mode of the RPA robot management platform;
before S1, the method further includes:
s01, the application layer receives a global management interface display request triggered by a client through Web service;
s02, the service layer controls the client to display a global management interface according to the global management interface display request.
5. The method of claim 4, wherein the global management interface includes any one or more of the following management components therein:
the system comprises an organization management component, a data management component, a flow and flow package management component, an execution platform management component, a development platform management component, a task management component, a planning management component and a management platform setting component.
6. The method of claim 3, wherein the client is an RPA robot execution platform client, the management request is a flow issue request, and the access connection manner includes: the first access connection mode is an API interface connection mode of the RPA robot management platform;
the step S2 specifically comprises the following steps:
s2i, the RPA service authenticates the execution platform according to the flow issuing request;
and S2ii, if the execution platform passes the authentication, issuing the flow.
7. The method of claim 6, wherein the management request is a task execution log storage request;
the step S2 specifically comprises the following steps:
and the RPA service stores the task running log into a component corresponding to the base layer according to the task running log storage request.
8. The method of claim 6, wherein the access connection means further comprises: a second access connection mode; the management request is a data call request;
the step S2 specifically comprises the following steps:
s21), the RPA service acquires corresponding data from the corresponding component of the base layer according to the data call request;
s22), the RPA service sends the data to the execution platform;
the corresponding components are as follows: rabbit MQ services.
9. The method of claim 3, wherein the client is an RPA robot development platform client, the management request is a flow release request, the access connection mode is a first access connection mode, and the first access connection mode is an API interface connection mode of an RPA robot management platform;
the step S2 specifically comprises the following steps:
s2a, the RPA service authenticates the development platform according to the flow release request;
and S2b, if the development platform passes the authentication, the RPA service issues the flow, wherein the flow is developed by the development platform by utilizing natural language processing NLP.
10. The method of claim 9, wherein the management request is a data call request;
The step S2 specifically comprises the following steps:
S2A, the RPA service acquires corresponding data from the corresponding component of the base layer according to the data call request;
and S2B, the RPA service sends the data to the development platform.
11. The method of claim 10, wherein the data is any one of the following:
parameter data, task data, and data queues.
12. The method of claim 1, wherein the client is a third party platform, the access connection is a third access connection, and the third access connection comprises an open API interface connection.
13. The method according to any of claims 1-12, wherein the base layer comprises: a persistence component and an intermediate component;
the persistence component includes: mySQL database, elastic Search database, and MinIO distributed file database;
the intermediate assembly includes: redis database and Rabbit MQ services.
14. An AI-based RPA robot management platform, comprising: an application layer, a service layer and a base layer which are sequentially connected in a communication way;
the application layer is configured to receive a management request sent by a client, where the management request includes: the client side identification information is used for determining a corresponding access connection mode according to the client side identification information, and the management request is sent to a service layer through the corresponding access connection mode;
The service layer is used for carrying out corresponding management response according to the management request;
the base layer is used for storing related data in the process of providing management service by the service layer;
the client is a web browser, an RPA robot execution platform client, an RPA robot development platform client or a third party platform;
each client is connected with the AI-based RPA robot management platform by adopting a corresponding access connection mode.
15. An AI-based RPA robot management platform, comprising:
a memory, a processor, and a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1-13.
16. A computer readable storage medium, having stored thereon a computer program, the computer program being executed by a processor to implement the method of any of claims 1-13.
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