CN114445185B

CN114445185B - Software product delivery method, device, equipment and storage medium based on RPA and AI

Info

Publication number: CN114445185B
Application number: CN202210108940.7A
Authority: CN
Inventors: 李烨
Original assignee: Laiye Technology Beijing Co Ltd
Current assignee: Laiye Technology Beijing Co Ltd
Priority date: 2022-01-28
Filing date: 2022-01-28
Publication date: 2025-09-16
Anticipated expiration: 2042-01-28
Also published as: CN114445185A

Abstract

This application proposes a method, device, equipment, and storage medium for shipping software products based on RPA and AI. The method includes: obtaining basic information of pending orders and the sales contract corresponding to the pending orders from the CRM system; outputting basic information and obtaining the deployment environment corresponding to the pending orders input by the shipping applicant based on the basic information; obtaining the target image and pre-inspection result screenshot uploaded by the shipping applicant; sending the customer machine information identified from the target image and the pre-inspection result screenshot to the first reviewer for review, and receiving the software deployment authorization file uploaded by the first reviewer after the review is passed; packaging the pending shipment information to generate a deployment package, and sending the deployment package to the customer corresponding to the pending order for software product deployment. The software product shipping method based on RPA and AI can realize the automation of software product delivery, thereby saving manpower and improving delivery efficiency.

Description

Software product delivery method, device, equipment and storage medium based on RPA and AI

Technical Field

The application relates to the technical field of robot flow automation, in particular to a software product delivery method, device, equipment and storage medium based on RPA and AI.

Background

Robot process automation (Robotic Process Automation, RPA for short) is to simulate the operation of a person on a computer through specific robot software, and automatically execute process tasks according to rules.

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.

With the development of e-commerce technology, online shopping is becoming popular, people can directly order on a shopping website, a merchant carries out on-line delivery according to the order, the goods are delivered to a buyer in an express mail mode, and the buyer can also check the logistics progress online. However, the delivery method is limited to hardware products (i.e., physical commodity), and for software products (i.e., program products), delivery by express mail method cannot be performed directly.

In the related art, when a consumer needs to purchase a software product of a company, the consumer can provide order information of the required purchased software product to sales staff of the company, the sales staff contacts with related technicians according to the order information, the related technicians manually prepare related files for the required software product in the order information one by one, package the related files to obtain a deployment package, and manually send the deployment package to the consumer for deployment. Therefore, the current delivery mode of the software product is mainly realized by a manual mode, so that not only is labor consumption needed, but also the delivery efficiency is low.

Disclosure of Invention

The embodiment of the application provides a software product delivery method, device, equipment and storage medium based on RPA and AI, which can solve the problems of manpower consumption and low delivery efficiency of manually delivering software products in the related technology.

The technical proposal is as follows:

in a first aspect, an embodiment of the present application provides a software product shipping method based on RPA and AI, where the method is applied to a software product shipping platform, and the method includes:

Acquiring basic information of an order to be sent and a sales contract corresponding to the order to be sent from a customer relationship management CRM system;

outputting basic information, and acquiring a deployment environment corresponding to an order to be sent, which is input by a delivery applicant based on the basic information;

Acquiring a target picture and a front-end inspection result screenshot uploaded by a shipping applicant, wherein the target picture carries client machine information meeting a deployment environment, and the front-end inspection result screenshot comprises a result of legality inspection on a client machine corresponding to a to-be-shipped order according to a front-end inspection script, wherein the legality inspection is used for inspecting whether the client machine meets a product deployment requirement;

transmitting the client machine information identified by the target picture and the front-end inspection result screenshot to a first auditor for auditing, and receiving the software deployment authorization file uploaded after the first auditor audits;

Packaging the information to be shipped to generate a deployment package, and sending the deployment package to a client corresponding to the order to be shipped to deploy the software product, wherein the information to be shipped comprises basic information, deployment environment, target pictures, front-end inspection result screenshots and software deployment authorization files.

In one embodiment, obtaining basic information of an order to be shipped and a sales contract corresponding to the order to be shipped from a customer relationship management CRM system includes:

and acquiring basic information of the order to be sent and a sales contract corresponding to the order to be sent from the CRM system based on the first RPA robot.

In one embodiment, sending the client machine information and the pre-inspection result screenshot identified by the target picture to a first auditor for auditing includes:

When the target picture is a two-dimensional code, sending client machine information identified by the two-dimensional code and a front inspection result screenshot to a first inspector for inspection;

And when the target picture is not the two-dimensional code, transmitting the client machine information and the front inspection result screenshot which are recognized by the target picture based on the optical character recognition OCR to a first auditor for auditing.

In one embodiment, receiving the software deployment authorization file uploaded after the first auditor passes the audit includes:

determining whether a third party provider exists according to the sales contract;

if the third-party provider does not exist, receiving a self-research software deployment authorization file uploaded after the first auditor passes the audit;

And if the third party provider exists, receiving the third party software deployment authorization file uploaded after the first auditor passes the audit.

In one embodiment, the basic information includes at least one of:

a shipping application identifier, a customer name, a deployment type, an order number, a shipping applicant's shipping address, and product information for at least one software product;

Wherein the product information includes a product identification, a product activation time, and a product expiration time.

In one embodiment, when the to-be-shipped information further includes software deployment configuration information corresponding to each product identifier, before packaging the to-be-shipped information to generate the deployment package, the method further includes:

And acquiring software deployment configuration information corresponding to each product identifier in the basic information from the software service platform based on the second RPA robot, wherein the software deployment configuration information comprises a process image file, a configuration image file, service image information and a model image file.

In one embodiment, sending the deployment package to a customer corresponding to the order to be shipped for deployment of the software product includes:

And sending the deployment package to a receiving address of the delivery applicant so that the delivery applicant can send the deployment package to a client corresponding to the order to be delivered for software product deployment.

In one embodiment, before packaging the shipment information to generate the deployment package, the method further comprises:

and sending the information to be shipped to a second inspector for auditing, and after the auditing is passed, performing packaging on the information to be shipped to generate a deployment package.

In one embodiment, after packaging the shipment information to be shipped to generate the deployment package, the method further comprises:

and acquiring the software product deployment progress of the client, and synchronizing the software product deployment progress to the CRM.

In a second aspect, an embodiment of the present application provides an RPA and AI-based software product shipping apparatus, where the apparatus is applied to a software product shipping platform, the apparatus including:

the first acquisition unit is used for acquiring basic information of an order to be sent and a sales contract corresponding to the order to be sent from the customer relationship management CRM system;

An output unit for outputting the basic information;

the second acquisition unit is used for acquiring a deployment environment corresponding to the to-be-delivered order input by the delivery applicant based on the basic information;

The third acquisition unit is used for acquiring a target picture and a front-end inspection result screenshot uploaded by the shipping applicant, wherein the target picture carries client machine information meeting the deployment environment, and the front-end inspection result screenshot comprises a result of legality inspection on a client machine corresponding to the order to be shipped according to the front-end inspection script, and the legality inspection is used for inspecting whether the client machine meets the product deployment requirement;

The first sending unit is used for sending the client machine information identified by the target picture and the front-end inspection result screenshot to a first inspector for inspection;

the receiving unit is used for receiving the software deployment authorization file uploaded after the first inspector passes the inspection;

the packaging unit is used for packaging the information to be shipped to generate a deployment package;

The second sending unit is used for sending the deployment package to a client corresponding to the order to be shipped to perform software product deployment, wherein the information to be shipped comprises basic information, deployment environment, target pictures, front-end inspection result screenshots and software deployment authorization files.

In one embodiment, the first obtaining unit is configured to obtain, based on the first RPA robot, basic information of an order to be sent and a sales contract corresponding to the order to be sent from the CRM system.

In one embodiment, the first transmitting unit includes:

The first sending module is used for sending the client machine information identified by the two-dimension code and the front-end inspection result screenshot to a first inspector for inspection when the target picture is the two-dimension code;

And the second sending module is used for sending the client machine information and the front inspection result screenshot identified by the target picture based on the optical character recognition OCR to the first auditor for auditing when the target picture is not the two-dimensional code.

In one embodiment, a receiving unit includes:

The determining module is used for determining whether a third party provider exists according to the sales contract;

the receiving module is used for receiving the self-research software deployment authorization file uploaded after the first auditor audits to pass when the third-party provider does not exist, and receiving the third-party software deployment authorization file uploaded after the first auditor audits to pass when the third-party provider exists.

In one embodiment, the basic information includes at least one of:

In one embodiment, the apparatus further comprises:

The fourth obtaining unit is configured to obtain, based on the second RPA robot, software deployment configuration information corresponding to each product identifier in the basic information from the software service platform before packaging the to-be-shipped information to generate a deployment package when the to-be-shipped information further includes the software deployment configuration information corresponding to each product identifier, where the software deployment configuration information includes a process image file, a configuration image file, service image information, and a model image file.

In one embodiment, the second sending unit is configured to send the deployment package to a receiving address of the shipping applicant, so that the shipping applicant sends the deployment package to a client corresponding to the order to be shipped for deploying the software product.

In one embodiment, the apparatus further comprises:

The third sending unit is used for sending the information to be sent to a second inspector for auditing before the information to be sent is packaged to generate a deployment package, and executing packaging of the information to be sent to generate the deployment package after the auditing is passed.

In one embodiment, the apparatus further comprises:

And the fifth acquisition unit is used for acquiring the software product deployment progress of the client after the information to be shipped is packaged to generate the deployment package, and synchronizing the software product deployment progress to the CRM.

In a third aspect, an embodiment of the present application provides an electronic device, where the electronic device includes a processor and a memory, where the memory stores instructions, and the instructions are loaded and executed by the processor to implement a method in any implementation manner of the first aspect.

In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which when executed by a processor implements a method according to any one of the embodiments of the first aspect.

The advantages or beneficial effects in the technical scheme at least comprise:

1. The embodiment of the application provides a software product delivery platform, and based on the software product delivery platform, basic information of an order to be delivered and a sales contract corresponding to the order to be delivered are acquired from a customer relationship management CRM system, basic information is output, a deployment environment corresponding to the order to be delivered, which is input by a delivery applicant based on the basic information, is acquired, a target picture and a front inspection result screenshot uploaded by the delivery applicant are acquired, customer machine information and the front inspection result screenshot identified by the target picture are sent to a first auditor for auditing, a software deployment authorization file uploaded after the first auditor audits pass, deployment packages are generated by packaging the information to be delivered, and the deployment packages are sent to customers corresponding to the order to be delivered for software product deployment. Therefore, compared with the fact that in the related art, each software product needs to be manually shipped one by one, the embodiment of the application can realize shipment processing operation through the software product shipment platform, so that automation of software product shipment is realized, labor is saved, and shipment efficiency is improved.

2. Before generating the deployment package, the embodiment of the application obtains the software deployment configuration information corresponding to each product identifier in the basic information from the software service platform through the first RPA robot, and packages the software deployment configuration information as a part of the information to be sent, so that a customer does not need to manually obtain the software deployment configuration information through the software service platform, thereby saving manpower and improving the deployment efficiency.

3. The basic information of the order to be sent and the sales contract corresponding to the order to be sent are acquired from the CRM system based on the second RPA robot, and the information is not required to be acquired from the CRM system manually, so that manpower is saved, and the efficiency of acquiring the basic information and the sales contract is improved.

4. When uploading the client machine information, the target picture is directly uploaded and automatically identified to obtain the client machine information without manually inputting the client machine information with longer character strings, so that the labor force can be saved, the efficiency of obtaining the client machine information can be improved, the manual input error can be avoided, and the accuracy of obtaining the client machine information can be improved. When the target picture is a two-dimensional code, the two-dimensional code can be identified directly based on a two-dimensional code identification algorithm, and when the target picture is not the two-dimensional code, the target picture can be identified based on optical character recognition OCR.

5. The embodiment of the application not only can provide self-research software products for clients, but also can provide third-party software products for clients, thereby improving the selection range of clients. Wherein, whether a third party provider exists can be automatically judged by analyzing the contents in the sales contract without manual judgment.

6. By means of the second auditor checking again before packaging the information to be shipped, shipping errors can be prevented, and shipping accuracy is improved.

7. In order to facilitate the software product merchant to timely acquire the software product deployment progress, so as to timely find out whether the software product deployment has a problem (such as low deployment efficiency, etc.), after the deployment package is sent to the client corresponding to the order to be shipped to perform the software product deployment, the software product shipping platform can acquire the software product deployment progress of the client, and synchronize the software product deployment progress to the CRM.

The foregoing summary is for the purpose of the specification only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the present application will become apparent by reference to the drawings and the following detailed description.

Drawings

In the drawings, the same reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily drawn to scale. It is appreciated that these drawings depict only some embodiments according to the disclosure and are not therefore to be considered limiting of its scope.

FIG. 1 is a schematic flow chart of a software product shipping method based on RPA and AI according to an embodiment of the application;

FIG. 2 is a diagram illustrating an exemplary interface for a software product shipment flow based on RPA and AI according to one embodiment of the application;

FIG. 3 is a diagram illustrating another exemplary software product shipment flow interface based on RPA and AI provided by an embodiment of the application;

FIG. 4 is a diagram illustrating another exemplary software product shipment flow interface based on RPA and AI provided by an embodiment of the application;

FIG. 5 is a diagram illustrating another exemplary software product shipment flow interface based on RPA and AI provided by an embodiment of the application;

FIG. 6 is a diagram illustrating another exemplary software product shipment flow interface based on RPA and AI provided by an embodiment of the application;

FIG. 7 is a block diagram of an RPA and AI-based software product delivery apparatus according to an embodiment of the application;

fig. 8 is a schematic diagram of an electronic device according to an embodiment of the present application;

fig. 9 is a schematic diagram of another electronic device according to an embodiment of the present application.

Detailed Description

Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the application.

In order to clearly illustrate the embodiments of the present application, technical terms related to the embodiments of the present application will be explained first.

In the description of embodiments of the present application, the term "RPA", i.e., robotic process automation (Robotic Process Automation), is the automated execution of process tasks on rules by a specific "robot software", simulating the operation of a human on a computer.

In the description of embodiments of the present application, the term "AI", artificial intelligence (ARTIFICIAL INTELLIGENCE), is a piece of technical science that studies, develops theories, methods, techniques and application systems for simulating, extending and expanding human intelligence.

In the description of the embodiments of the present application, the term "software product delivery platform" is a platform that specifically provides a software product delivery function, and may be configured by a client for providing a man-machine interaction interface to a user (mainly, a staff member of a software product merchant), and a server for performing background processing operations such as packaging.

In the description of the embodiments of the present application, the term "CRM", that is, customer relationship management (Customer Relationship Management), refers to a process in which an enterprise coordinates interactions between the enterprise and customers in sales, marketing and services using corresponding information technologies and internet technologies in order to improve core competitiveness, thereby improving a management manner and providing innovative personalized customer interactions and services to the customers.

In the description of embodiments of the present application, the term "software product" refers to a program product.

In the description of embodiments of the present application, the term "shipping application identifier" is used to uniquely identify a shipping application.

In the description of the embodiments of the present application, the term "deployment type" includes POC (Proof of Concept) deployment and/or formal deployment, i.e., whether the present deployment is a formal deployment or a POC deployment can be determined by the deployment type.

In the description of the embodiments of the present application, the term "product activation time" refers to the sales contract validation time corresponding to the software product, and the term "product expiration time" refers to the sales contract expiration time corresponding to the software product.

In the description of embodiments of the present application, the term "deployment environment" is a type of processor used to run a software product.

In the description of embodiments of the present application, the term "CPU", i.e., central processing unit (Central Processing Unit) serves as the computing and control core of the computer system, and is the final execution unit for information processing and program execution.

In the description of embodiments of the present application, the term "GPU", i.e., graphics processor (Graphics Processing Unit), also known as display core, vision processor, display chip, is a microprocessor that performs image and graphics related operations specifically on a computer device.

In the description of the embodiments of the present application, the term "OCR" refers to optical character recognition (Optical Character Recognition), specifically refers to a process in which an electronic device checks characters printed on paper, determines their shapes by detecting dark and bright patterns, and translates the shapes into computer characters by a character recognition method, that is, a technology for converting characters in a paper document into an image file of a black-and-white lattice by adopting an optical manner with respect to a print character, and converting characters in an image into a text format by a recognition software for further editing and processing by a word processing software.

In describing embodiments of the present application, the term "NLP" refers to natural language processing (Natural Language Processing) that uses computer technology to analyze, understand, and process a subject of natural language, i.e., a computer is a powerful tool for language research, quantitatively researching language information with the support of the computer, and providing language descriptions that can be used together between humans and computers.

In the description of embodiments of the present application, the term "pre-deployment check" refers to a pre-deployment check operation that checks whether a client machine meets deployment requirements.

In the description of the embodiment of the application, the term "two-dimensional Code" is Quick Response Code (abbreviated as QR Code), which is a graph of data symbol information recorded with certain specific geometric patterns distributed on a plane (in two dimensions) according to a certain rule, wherein the graph is black-white, and can store more information and represent more data types than the traditional bar Code.

In the description of the embodiments of the present application, the term "software deployment authorization file" is an authorization file for a merchant to grant client software deployment rights, including self-developed software deployment authorization files and/or third party software deployment authorization files.

In the description of the embodiment of the present application, the term "process image file" refers to an image file obtained by performing image processing on a process code.

In the description of the embodiment of the present application, the term "mirroring" is a processing manner for obtaining a mirrored file, and may be, for example, a Docker (application container engine) mirroring process of the container cluster management system Kubernetes. Kubernetes deployment may be implemented in the context of a software service platform in which plug-ins to Kubernetes may be provided (e.g., helm plug-ins, istio plug-ins, storageClass plug-ins, etc.).

In the description of the embodiment of the present application, the term "configuration image file" refers to an image file obtained by performing image processing on a configuration file of a process code.

In the description of the embodiment of the present application, the term "service image information" refers to image information obtained by performing image processing on service information of a process code.

In the description of the embodiment of the present application, the term "model image file" refers to an image file obtained by performing image processing on a model file of a process code.

In the description of embodiments of the present application, the term "software service platform" refers to a platform that software product merchants offer to customers, including a variety of software services, through which desired services may be downloaded and purchased.

These and other aspects of embodiments of the application will be apparent from and elucidated with reference to the description and drawings described hereinafter. In the description and drawings, particular implementations of embodiments of the application are disclosed in detail as being indicative of some of the ways in which the principles of embodiments of the application may be employed, but it is understood that the scope of the embodiments of the application is not limited correspondingly. On the contrary, the embodiments of the application include all alternatives, modifications and equivalents as may be included within the spirit and scope of the appended claims.

The RPA technology can intelligently understand the existing application of the electronic equipment through a user use interface, and automate repeated, rule-based and massive conventional operations, such as automatically and repeatedly reading mails, reading Office components, operating databases, webpages, client software and the like, collect data and perform complicated calculation, and generate required files and reports in batches, so that the investment of labor cost can be greatly reduced through the RPA technology, and the Office efficiency is effectively improved. The AI technology can break through fixed rules, simulate human thinking and consciousness to automatically process some more complex application scenes. RPA has the unique advantage of low code, non-intrusive. The low code means that the RPA can operate without high IT level and the business personnel without programming can develop the flow, and the non-invasive means that the RPA can simulate the operation of the person without opening the interface by a software system. However, conventional RPA has certain limitations in that it is based on fixed rules only and has limited application scenarios. With the continuous development of the AI technology, the limitations of the traditional RPA are overcome by the deep fusion of the RPA and the AI, and the values of the labor force are greatly changed by the RPA+AI=hand work+head work. Based on the above, the embodiment of the application provides a software product delivery method based on RPA and AI, which can realize automatic delivery of the software product, thereby saving manpower and improving delivery efficiency.

Fig. 1 shows a flowchart of a software product shipping method based on RPA and AI according to an embodiment of the present application, where the method is applied to a software product shipping platform, and the software product shipping platform may be deployed in a private cloud or a public cloud, and the method may include the following steps, according to actual situations:

and step S101, the software product delivery platform acquires basic information of an order to be delivered and a sales contract corresponding to the order to be delivered from the CRM system.

After the customer places an order on the software service platform or places an order with the sales personnel of the software product merchant, the order information (including the order basic information and the sales contract) on the software service platform can be automatically synchronized to the CRM system, or the sales personnel can manually input the order information into the CRM system. The CRM system can sequentially synchronize to the software product delivery platform to start the delivery flow by taking the order as a unit according to the order sequence.

The basic information comprises at least one of a shipping application identifier, a customer name, a deployment type, an order number, a shipping applicant, a shipping address of the shipping applicant and product information of at least one software product, wherein the product information comprises a product identifier, a product activation time and a product expiration time.

The shipping application identifier refers to an application ID (Identity document, identification number) generated when the order to be shipped is applied for shipment, and is used for uniquely identifying a shipping application. The deployment type includes POC deployment and/or formal deployment. The shipping applicant refers to the person in the software product shipping platform that operates the shipping application, such as a sales person who may be a software product merchant. The shipping address of the shipping applicant is typically a network virtual address, such as a mailbox address, chat software address, or the like. The product identification is used to uniquely identify a piece of software product and may include a product name. The product activation time refers to the sales contract effective time corresponding to the software product, and the product expiration time refers to the sales contract expiration time corresponding to the software product. Software products include, but are not limited to, RPA products (e.g., process robots, process creators, process managers), AI products (e.g., OCR products, NLP products), IDP (INTELLIGENT DOCUMENT PROCESSING ) products, chatbot products.

In the RPA product, the process robot UiBot Worker is deployed in the process robot after the RPA process is written, and can be started manually according to the requirement or automatically when a specific trigger condition is met, so that tasks can be arranged and the process can be traced. The flow creator UiBot Creator is a programming tool for developing a flow, and specific steps such as interface automation operation, AI identification, data reading and writing and the like are performed in the flow. The flow creator allows people to easily assemble an automatic flow meeting business requirements by dragging each step by using a mouse in a flow chart and low code mode. The process manager UiBot Commander is a platform for unified management of a plurality of process robots in an enterprise, can rapidly issue tasks in batches, provide data, certificates, files and the like required by the process robots in operation, and can monitor the operation states of the process robots in real time or review the history records of the process robots.

The software product delivery platform can acquire the basic information of the order to be delivered and the sales contract corresponding to the order to be delivered from the CRM system based on the first RPA robot.

In one embodiment, an RPA program may be configured in the software product delivery platform, so that the software product delivery platform may simulate manual and automatic logging in the CRM system according to the rule set in the RPA program, and acquire, by using the CRM system, the basic information of the order to be delivered and the sales contract corresponding to the order to be delivered, and enter the basic information and the sales contract into the software product delivery platform. When logging in the CRM system, if the login interface popped up by the CRM system contains the verification code image, the first RPA robot can perform OCR (optical character recognition) on the verification code image to obtain the verification code content in the verification code image, and input the verification code content into a corresponding editing box, so that the CRM system is successfully logged in.

It should be added that the basic information in the CRM system may be different from the basic information to be used in the software product delivery platform in terms of field description, but the representative meanings are the same, for example, the "software delivery application order" field in the CRM system and the "order number" field in the software product delivery platform both represent order identifications. In this case, a basic information field mapping table may be preset, and basic information satisfying the requirements of the shipping platform of the software product may be obtained according to the basic information field mapping table after the basic information is obtained from the CRM system.

And S102, outputting basic information by a software product delivery platform, and acquiring a deployment environment corresponding to the to-be-delivered order input by a delivery applicant based on the basic information.

The deployment environment is a processor for running a software product, and may include a CPU and/or GPU. After outputting the basic information, the shipping applicant can view the basic information of the order to be shipped, click on the next step, and select the deployment environment corresponding to the order to be shipped, for example, select the CPU. As shown in fig. 2, the software product delivery platform mainly includes basic information, filling in deployment environment, filling in pre-examination results, uploading authorization files (i.e. software deployment authorization files), auditing, packaging, and deploying seven nodes, and the on-going nodes can be displayed in a thickened manner, and specific content related to the node is displayed below, and in fig. 2, taking "basic information" as an example, the detailed content included in the basic information is below.

After the shipping applicant clicks on the next step in fig. 2, the shipping applicant may enter the filling deployment environment interface shown in fig. 3, where fig. 3 includes two deployment environments, i.e., CPU and GPU, and may select an appropriate one of the deployment environment interfaces.

And step S103, the software product delivery platform acquires the target picture and the front-end inspection result screenshot uploaded by the delivery applicant.

The target picture carries client machine information meeting the deployment environment, and the pre-inspection result screenshot comprises a result of legality inspection on the client machine corresponding to the order to be shipped according to the pre-inspection script, wherein the legality inspection is used for inspecting whether the client machine meets the product deployment requirement. The client can download the pre-inspection script from the software product delivery platform, or the software product delivery platform actively transmits the pre-inspection script to the client, then the client machine is inspected whether to meet the product deployment requirement by running the pre-inspection script, the pre-inspection result screenshot is generated according to the client machine information meeting the deployment environment, the target picture and the pre-inspection result screenshot are fed back to the delivery applicant, and the delivery applicant uploads the target picture and the pre-inspection result screenshot.

When uploading the client machine information, the target picture is directly uploaded and automatically identified to obtain the client machine information without manually inputting the client machine information with longer character strings, so that the labor force can be saved, the efficiency of obtaining the client machine information can be improved, the manual input error can be avoided, and the accuracy of obtaining the client machine information can be improved. The target picture can be a two-dimensional code or a common picture intuitively carrying information of the client machine. And when the target picture is not the two-dimensional code, transmitting the client machine information and the front inspection result screenshot identified by the target picture based on OCR to the first auditing person for auditing. The first reviewer may be a person with higher rights than the shipping applicant, for example, a product marketplace manager.

Illustratively, as shown in fig. 4, the shipping applicant may upload the two-dimensional code, and the software product shipping platform may automatically identify the client machine information (such as the machine code) in the two-dimensional code, automatically fill the machine code into the corresponding input box for display, and then upload the pre-inspection result screenshot.

And step S104, the software product delivery platform sends the client machine information and the front inspection result screenshot identified by the target picture to a first auditor for auditing, and receives the software deployment authorization file uploaded after the first auditor passes the auditing.

The method comprises the steps that a delivery applicant and a first auditor have different accounts on a software product delivery platform, after a delivery applicant uploads a target picture and a front-end inspection result screenshot, a 'start audit' button can be clicked, after the software product delivery platform receives an audit initiating instruction, client machine information and the front-end inspection result screenshot which are identified by the target picture are sent to the account of the first auditor, so that the first auditor can audit the client machine information and the front-end inspection result screenshot after logging in the account, and after no problem is confirmed, the software deployment authorization file is uploaded.

In practical applications, software product merchants may sell self-developed software products as well as software products from third party vendors, and thus the required software deployment authorization files may be different. The software product delivery platform can determine whether a third-party provider exists according to a sales contract, if the third-party provider does not exist, the self-research software deployment authorization file uploaded after the first auditor passes the audit is received, and if the third-party provider exists, the third-party software deployment authorization file uploaded after the first auditor passes the audit is received. Wherein the software product shipping platform may parse the sales contract and determine if a third party provider exists based on NLP technology. And when the sales contract is in a non-editable image format, the software product delivery platform can recognize text content in the sales contract based on OCR technology and then analyze and judge based on NLP technology.

It should be added that there may be only one software product or there may be a plurality of software products in the order to be placed. When there are multiple software products, the multiple software products may correspond to one sales contract or may correspond to different sales contracts. When corresponding to different sales contracts, the software product delivery platform needs to determine whether a third party provider exists for the content of each sales contract separately. As shown in fig. 5, the first reviewer may review all of the software deployment authorization files involved in the order to be shipped directly on the software deployment authorization file upload interface.

And step 105, the software product delivery platform packages the information to be delivered to generate a deployment package, and sends the deployment package to a client corresponding to the order to be delivered to deploy the software product.

The information to be delivered comprises basic information, a deployment environment, a target picture, a front-end inspection result screenshot and a software deployment authorization file. The software product delivery platform can automatically pack the information to generate a deployment package, and send the deployment package to a receiving address of a delivery applicant, so that the delivery applicant can send the deployment package to a client corresponding to an order to be delivered for software product deployment, and the deployment package can be directly sent to a harvesting address of the client when the basic information also comprises the harvesting address of the client corresponding to the order to be delivered. After the packaging is completed, the detailed content contained in the deployment package can also be shown to the shipping applicant, as shown in fig. 6, the deployment package can also include related information of the packaged module generated by packaging, such as a module number, a module name, a module version and the like, besides the information to be sent.

In one embodiment, to further ensure that the information to be shipped is error-free, preventing the software product from being deployed unsuccessfully, the information to be shipped may be sent to a second inspector for inspection before the information to be shipped is packaged to generate a deployment package, and after the information to be shipped passes the inspection, the deployment package is packaged to generate a deployment package. The second auditor and the first auditor can be the same or different, and according to actual requirements, for example, the second auditor can be an operation and maintenance person.

In one embodiment, when a client deploys a software product based on a deployment package, it is often required to acquire software deployment configuration information such as a process image file, a configuration image file, service image information, and a model image file of each software product to be deployed from a software service platform, and then implement software product deployment based on the software deployment configuration information. Therefore, the deployment process needs more manual operation, and the manual operation efficiency is lower. In order to further save labor and improve deployment efficiency, before packaging the to-be-shipped information to generate a deployment package, the software product shipment platform can automatically acquire software deployment configuration information corresponding to each product identifier in the basic information from the software service platform based on the second RPA robot, and package to-be-shipped information further comprising the software deployment configuration information corresponding to each product identifier. The software deployment configuration information comprises a process image file, a configuration image file, service image information and a model image file.

The process image file refers to an image file obtained by performing image processing on a process code. The configuration image file refers to an image file obtained by performing image processing on the configuration file of the process code. Service image information refers to image information obtained by performing image processing on service information of a process code. The model image file refers to an image file obtained by performing image processing on the model file of the process code. The configuration file refers to the definition of the numerical value of each variable in the process code, and the operation of the process code can be realized by combining the definition of the numerical value of each variable with the process code. Service information refers to process routing information, data structures required for initialization at deployment, initialization data, data structure change information, and the like. The model file refers to a related file of a model which is needed in the process of executing the process code. For example, taking a text recognition service function as an example, if a process in the model needs to use an image recognition model, a model file of the process is a related file of the image recognition model, so that the process can conveniently call the image recognition model to obtain an image recognition result.

In one embodiment, an RPA program may be configured in the software product delivery platform, so that the software product delivery platform may simulate manual and automatic login to the software service platform according to a rule set in the RPA program, and acquire, through the software service platform, basic information of an order to be delivered and a sales contract corresponding to the order to be delivered, and enter the basic information and the sales contract into the software product delivery platform. When logging in the software service platform, if the login interface popped up by the software service platform contains the verification code image, the second RPA robot can perform OCR (optical character recognition) on the verification code image to obtain the verification code content in the verification code image, and input the verification code content into the corresponding editing box, so that the software service platform is successfully logged in.

The first RPA robot and the second RPA robot may be the same RPA robot or different RPA robots. That is, the functions of the first RPA robot and the second RPA robot may be deployed on the same RPA robot, or may be deployed on different RPA robots, respectively.

In one embodiment, in order to facilitate a software product merchant to timely acquire a software product deployment progress, so as to timely find out whether a problem exists in software product deployment (such as a problem of low deployment efficiency, etc.), after a deployment package is sent to a customer corresponding to an order to be shipped to perform software product deployment, a software product shipping platform may acquire the software product deployment progress of the customer, and synchronize the software product deployment progress to the CRM.

According to the software product delivery method based on the RPA and the AI, basic information of an order to be delivered and a sales contract corresponding to the order to be delivered can be obtained from a customer relationship management CRM system based on the software product delivery platform, the basic information is output, a deployment environment corresponding to the order to be delivered, which is input by a delivery applicant based on the basic information, is obtained, a target picture and a front inspection result screenshot uploaded by the delivery applicant are obtained, customer machine information and the front inspection result screenshot identified by the target picture are sent to a first auditor for auditing, a software deployment authorization file uploaded by the first auditor after the first auditor is audited is received, the information to be delivered is packaged to generate a deployment package, and the deployment package is sent to a customer corresponding to the order to be delivered for software product deployment. Therefore, compared with the fact that in the related art, each software product needs to be manually shipped one by one, the embodiment of the application can realize shipment processing operation through the software product shipment platform, so that automation of software product shipment is realized, labor is saved, and shipment efficiency is improved.

Fig. 7 shows a block diagram of an RPA and AI-based software product shipping apparatus according to another embodiment of the present application, the apparatus being applied to a software product shipping platform, the apparatus comprising:

A first obtaining unit 210, configured to obtain, from a customer relationship management CRM system, basic information of an order to be sent and a sales contract corresponding to the order to be sent;

An output unit 220 for outputting the basic information;

A second obtaining unit 230, configured to obtain a deployment environment corresponding to the to-be-delivered order input by the delivery applicant based on the basic information;

A third obtaining unit 240, configured to obtain a target picture uploaded by the shipping applicant and a pre-inspection result screenshot, where the target picture carries client machine information that meets a deployment environment, and the pre-inspection result screenshot includes a result of performing a validity inspection on a client machine corresponding to a to-be-shipped order according to the pre-inspection script, where the validity inspection is used to check whether the client machine meets a product deployment requirement;

The first sending unit 250 is configured to send the client machine information identified by the target picture and the pre-inspection result screenshot to a first inspector for inspection;

the receiving unit 260 is configured to receive the software deployment authorization file uploaded after the first inspector inspects that the first inspector passes the inspection;

A packaging unit 270, configured to package the information to be shipped to generate a deployment package;

And the second sending unit 280 is configured to send the deployment package to a client corresponding to the to-be-shipped order for deploying the software product, where the to-be-shipped information includes basic information, a deployment environment, a target picture, a pre-inspection result screenshot and a software deployment authorization file.

In one embodiment, the first obtaining unit 210 is configured to obtain, based on the first RPA robot, basic information of an order to be sent and a sales contract corresponding to the order to be sent from the CRM system.

In one embodiment, the first transmitting unit 250 includes:

In one embodiment, the receiving unit 260 includes:

In one embodiment, the basic information includes at least one of:

In one embodiment, the apparatus further comprises:

In one embodiment, the second sending unit 280 is configured to send the deployment package to the receiving address of the shipping applicant, so that the shipping applicant sends the deployment package to the client corresponding to the order to be shipped for deployment of the software product.

In one embodiment, the apparatus further comprises:

The functions of each module in each device of the embodiments of the present application may be referred to the corresponding descriptions in the above methods, and are not described herein again.

Fig. 8 is a block diagram of an electronic device according to another embodiment of the present application. The electronic device comprises a processor 310 and a memory 320, the memory 320 storing instructions that are loaded and executed by the processor 310 to implement a method as in any of the method embodiments described above. The number of memories 320 and processors 310 may be one or more.

As shown in fig. 9, the electronic device further includes:

and the communication interface 330 is used for communicating with external equipment and carrying out data interaction transmission.

If the memory 320, the processor 310, and the communication interface 330 are implemented independently, the memory 320, the processor 310, and the communication interface 330 may be connected to each other and communicate with each other through buses. The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.

In a specific implementation, if the memory 320, the processor 310, and the communication interface 330 are integrated on a single chip, the memory 320, the processor 310, and the communication interface 330 may communicate with each other through internal interfaces.

The embodiment of the application provides a computer readable storage medium, and a computer program is stored in the computer readable storage medium, and when the computer program is executed by a processor, the method provided by any one of the method embodiments is realized.

The embodiment of the application also provides a chip, which comprises a processor and is used for calling the instructions stored in the memory from the memory and running the instructions stored in the memory, so that the communication equipment provided with the chip executes the method provided by the embodiment of the application.

The embodiment of the application also provides a chip which comprises an input interface, an output interface, a processor and a memory, wherein the input interface, the output interface, the processor and the memory are connected through an internal connection path, the processor is used for executing codes in the memory, and when the codes are executed, the processor is used for executing the method provided by the application embodiment.

It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processor, digital signal processor (DIGITAL SIGNAL processing, DSP), application Specific Integrated Circuit (ASIC), field programmable gate array (fieldprogrammablegate array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. A general purpose processor may be a microprocessor or any conventional processor or the like. It is noted that the processor may be a processor supporting an advanced reduced instruction set machine (ADVANCED RISC MACHINES, ARM) architecture.

Further, optionally, the memory may include a read-only memory and a random access memory, and may further include a nonvolatile random access memory. The memory may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may include a read-only memory (ROM), a Programmable ROM (PROM), an erasable programmable ROM (erasable PROM), an electrically erasable programmable EPROM (EEPROM), or a flash memory, among others. Volatile memory can include random access memory (random access memory, RAM), which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available. For example, static random access memory (STATIC RAM, SRAM), dynamic random access memory (dynamic random access memory, DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (double DATA DATE SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (ENHANCED SDRAM, ESDRAM), synchronous link dynamic random access memory (SYNCHLINK DRAM, SLDRAM), and direct memory bus random access memory (direct rambus RAM, DR RAM).

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with the present application are fully or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. Computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.

Any process or method description in a flowchart or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process. And the scope of the preferred embodiments of the present application includes additional implementations in which functions may be performed in a substantially simultaneous manner or in an opposite order from that shown or discussed, including in accordance with the functions that are involved.

Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.

It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the methods of the embodiments described above may be performed by a program that, when executed, comprises one or a combination of the steps of the method embodiments, instructs the associated hardware to perform the method.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules described above, if implemented in the form of software functional modules and sold or used as a stand-alone product, may also be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a magnetic or optical disk, or the like.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that various changes and substitutions are possible within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims

1. A software product shipping method based on a robotic process automation RPA and an artificial intelligence AI, the method applied to a software product shipping platform, the method comprising:

Acquiring basic information of an order to be sent and a sales contract corresponding to the order to be sent from a customer relationship management CRM system based on a first RPA robot;

Outputting the basic information, and acquiring a deployment environment corresponding to the to-be-delivered order input by the delivery applicant based on the basic information;

Acquiring a target picture and a front-end inspection result screenshot uploaded by the shipping applicant, wherein the target picture carries client machine information meeting the deployment environment, the front-end inspection result screenshot comprises a result of legality inspection on a client machine corresponding to the to-be-shipped order according to a front-end inspection script, and the legality inspection is used for inspecting whether the client machine meets the product deployment requirement;

The method comprises the steps of sending client machine information identified by the target picture and the front inspection result screenshot to a first auditor for auditing, receiving a software deployment authorization file uploaded after the first auditor audits, and sending the client machine information identified by the target picture and the front inspection result screenshot to the first auditor for auditing, wherein when the target picture is a two-dimensional code, sending the client machine information identified by the two-dimensional code and the front inspection result screenshot to the first auditor for auditing, and when the target picture is not a two-dimensional code, sending the client machine information identified by the target picture and the front inspection result screenshot to the first auditor for auditing based on optical character recognition OCR;

packaging the information to be shipped to generate a deployment package, and sending the deployment package to a client corresponding to the order to be shipped to perform software product deployment, wherein the information to be shipped comprises the basic information, the deployment environment, the target picture, the pre-inspection result screenshot and the software deployment authorization file.

2. The method of claim 1, wherein the receiving the software deployment authorization file uploaded after the first auditor passes the audit comprises:

3. The method of claim 1, wherein the basic information comprises at least one of:

A shipping application identifier, a customer name, a deployment type, an order number, a shipping applicant, a shipping address of the shipping applicant, and product information for at least one software product;

4. The method of claim 3, wherein when the to-be-shipped information further includes software deployment configuration information corresponding to each product identifier, the method further comprises, prior to packaging the to-be-shipped information to generate a deployment package:

And acquiring software deployment configuration information corresponding to each product identifier in the basic information from a software service platform based on a second RPA robot, wherein the software deployment configuration information comprises a process image file, a configuration image file, service image information and a model image file.

5. The method of claim 3, wherein the sending the deployment package to the customer corresponding to the order to be shipped for software product deployment comprises:

6. The method of claim 1, wherein prior to packaging the shipment-to-be-shipped information to generate a deployment package, the method further comprises:

And sending the information to be shipped to a second inspector for auditing, and after the auditing is passed, executing the packaging of the information to be shipped to generate a deployment package.

7. The method of any of claims 1-6, wherein after the packaging of the information to be shipped to generate a deployment package, the method further comprises:

8. A software product shipment apparatus based on a robotic process automation RPA and an artificial intelligence AI, the apparatus being applied to a software product shipment platform, the apparatus comprising:

the first acquisition unit is used for acquiring basic information of an order to be sent and a sales contract corresponding to the order to be sent from a customer relationship management CRM system based on the first RPA robot;

an output unit configured to output the basic information;

a third obtaining unit, configured to obtain a target picture and a pre-inspection result screenshot uploaded by the shipping applicant, where the target picture carries client machine information that meets the deployment environment, the pre-inspection result screenshot includes a result of performing a validity inspection on a client machine corresponding to the to-be-shipped order according to a pre-inspection script, where the validity inspection is used to check whether the client machine meets a product deployment requirement;

The receiving unit is used for receiving the software deployment authorization file uploaded after the first auditor passes the audit;

The second sending unit is used for sending the deployment package to a client corresponding to the to-be-sent order for software product deployment, wherein the to-be-sent information comprises the basic information, the deployment environment, the target picture, the front inspection result screenshot and the software deployment authorization file;

the first transmitting unit includes:

The first sending module is used for sending the client machine information identified by the two-dimensional code and the front-end inspection result screenshot to the first auditor for auditing when the target picture is the two-dimensional code;

And the second sending module is used for sending the client machine information recognized by the target picture based on the optical character recognition OCR and the front inspection result screenshot to the first auditor for auditing when the target picture is not the two-dimensional code.

9. The apparatus of claim 8, wherein the receiving unit comprises:

And the receiving module is used for receiving the self-research software deployment authorization file uploaded after the first auditor audits to pass when the third-party provider does not exist, and receiving the third-party software deployment authorization file uploaded after the first auditor audits to pass when the third-party provider exists.

10. An electronic device comprising a processor and a memory, the memory storing instructions that are loaded and executed by the processor to implement the method of any one of claims 1-7.

11. A computer readable storage medium having a computer program stored therein, which when executed by a processor, implements the method according to any of claims 1-7.