Joint debugging service method and system based on fusion of AI large model and automatic testing technology

Abstract

The invention relates to a joint debugging service method and system based on fusion of an AI large model and an automatic testing technology, and the method specifically comprises the steps: building a knowledge base based on historical question and answer data, a system operation manual, an interface document and the like, carrying out the rewriting and retrieval of question data through the AI large model, generating a question answer according to the knowledge base, and carrying out the step splitting of the answer, the steps are subjected to keyword extraction through an auxiliary execution instruction and an AI large model and matched with preset key information, an automatic test execution tool is called to form script steps, and the script steps are compared with an existing automatic case library to execute corresponding operation. According to the scheme, the problem data are input into the large model to be subjected to multi-stage splitting and keyword extraction, requirements can be comprehensively known, a three-party automatic tool can be called to assist flow operation, the service efficiency of guiding problems is improved, and the system application threshold is lowered.

Description

Technical Field

[0001] The present invention relates to the field of merchant joint debugging services in the financial technology industry, and in particular to a joint debugging service method and system based on the integration of AI big models and automated testing technology, so as to improve the efficiency and quality of merchant joint debugging services and meet complex and changeable joint debugging needs. Background Art

[0002] Banks face many challenges in the merchant joint debugging service in the financial technology industry. Although the emergence of joint debugging intelligent customer service has provided some help in solving problems, the existing intelligent customer service system mainly relies on a preset question and answer library for conversational communication, which has obvious limitations.

[0003] When dealing with complex business scenarios, existing intelligent customer service systems often require a lot of manual remote guidance and operation, resulting in low overall joint debugging efficiency. In addition, the intelligent customer service system can only communicate based on the preset question and answer library, lacks flexibility and adaptability, and cannot effectively respond to changing joint debugging needs. For system usage issues, the existing intelligent customer service system cannot provide effective automated solutions and relies entirely on manual remote guidance of customer operations, which increases labor and time costs.

[0004] Therefore, the present invention proposes a joint debugging service method based on the integration of AI big model and automated testing technology to improve the efficiency and quality of the joint debugging service. By combining the big language model and UI automation technology, an in-depth understanding of user intentions can be achieved, and external tools can be automatically called to assist users in process operations, thereby improving the overall level of bank merchant joint debugging services. Summary of the invention

[0005] In order to solve the deficiencies of the prior art, the present invention proposes a joint debugging service method and system based on the integration of AI big model and automated testing technology.

[0006] To achieve the above objectives, the technical solutions adopted by the present invention include:

[0007] A joint debugging service method based on the integration of AI big model and automated testing technology, characterized by comprising the following steps:

[0008] S1. Collect the first data and crawl the second data, import the first data and the second data into the vector database to establish a knowledge base based on a preset algorithm, the first data is the joint debugging history data, and the second data is the menu name and function name;

[0009] S2. Receive question data, the AI ​​big model processes the question data based on the first data and matches it with the data in the knowledge base, and if there is similar question data with a similarity exceeding a preset threshold, use the similar question data to generate corresponding answer data based on the knowledge base;

[0010] S3. The AI ​​big model splits the answer data into steps to generate step data;

[0011] S4. Receive auxiliary execution information, extract keywords from the step data through the AI ​​big model, and match them with preset key information;

[0012] S5. If the match is successful, the automated test execution tool is called to form script steps according to the step data, compare them with the existing automated case library, obtain a consistent process script and execute it automatically.

[0013] Furthermore, the step S2 also includes: if there is no similar question data with a similarity exceeding a preset threshold, sending the matching result and the data to be supplemented.

[0014] Furthermore, the step splitting is to split the answer data into step data in which each step only includes one operation.

[0015] Furthermore, the step S5 further includes:

[0016] If there is no consistent process script, the preset UI script is called to complete the necessary steps, and manual operation information is sent for the remaining steps.

[0017] Furthermore, the method further comprises:

[0018] S6. Record the execution result of the guidance process and output the execution result.

[0019] In addition, the present invention also relates to a joint debugging service system based on the integration of AI big model and automated testing technology, which is characterized by comprising:

[0020] A knowledge base construction module, used to collect first data and crawl second data, and import the first data and the second data into a vector database to establish a knowledge base based on a preset algorithm, wherein the first data is joint debugging history record data, and the second data is a menu name and a function name;

[0021] A question matching module, for receiving question data, wherein the AI ​​big model processes the question data based on the first data and matches the question data with the data in the knowledge base, and if there is similar question data with a similarity exceeding a preset threshold, the similar question data is used to generate corresponding answer data based on the knowledge base;

[0022] A step splitting module, used to split the answer data into steps based on the AI ​​big model to generate step data;

[0023] A keyword extraction module, used to receive auxiliary execution information, extract keywords from the step data through the AI ​​big model, and match them with preset key information;

[0024] The automatic execution module is used to call the automated test execution tool when the match is successful, form script steps according to the step data, compare with the existing automated case library and execute corresponding operations.

[0025] Furthermore, it also includes:

[0026] The recording module is used to record the execution result of the guidance process and output the execution result.

[0027] In addition, the present invention also relates to an electronic device, characterized in that it comprises a processor and a memory;

[0028] The memory is used to store operation instructions;

[0029] The processor is used to execute the above method by calling the operation instruction.

[0030] In addition, the present invention also relates to a computer-readable storage medium, characterized in that a computer program is stored on the storage medium, and the computer program implements the above method when executed by a processor.

[0031] By adopting the solution provided in this application, a knowledge base is built based on historical question and answer data, system operation manuals, interface documents, etc. The AI ​​big model rewrites and retrieves the question data, generates answers to the questions according to the knowledge base, and splits the answers into steps. By assisting in executing instructions, the AI ​​big model extracts keywords from the steps and matches them with preset key information, calls the automated test execution tool to form script steps, and compares them with the existing automated case library to perform corresponding operations. Therefore, this case can fully understand the needs by inputting the question data into the big model for multi-level splitting and keyword extraction, and can call third-party automation tools to assist in process operations, thereby improving the service efficiency of guidance-type questions and lowering the threshold for system application. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flowchart of a joint debugging service method based on the integration of AI big model and automated testing technology provided in an embodiment of the present application;

[0033] Figure 2 A step-by-step instruction diagram of a joint debugging service method based on the integration of an AI big model and automated testing technology provided in an embodiment of the present application;

[0034] Figure 3 A structural diagram of a joint debugging service system based on the integration of AI big model and automated testing technology provided in an embodiment of the present application;

[0035] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be interpreted as limiting the present invention.

[0037] Those skilled in the art can understand that, unless otherwise stated, the singular forms "one", "an", "said" and "the" used herein may also include plural forms, and the "first", "second", etc., are only used to distinguish and define objects for the purpose of introducing the scheme clearly, and do not limit the objects themselves. Of course, the objects defined by "first" and "second" may be the same terminal, device, user, etc., or the same type of terminal, device and user. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0038] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0039] The present application embodiment provides a joint debugging service method based on the integration of AI big model and automated testing technology, such as Figure 1 , Figure 2 As shown, specifically including:

[0040] S1. Collect the first data and crawl the second data, import the first data and the second data into the vector database to establish a knowledge base based on a preset algorithm, the first data is the joint debugging history data, system operation manual, etc., the second data is the menu name and function name, and the preset algorithm is the bge-large-zh algorithm;

[0041] S2. Receive question data, the AI ​​big model processes the question data based on the first data and matches it with the data in the knowledge base. If there is similar question data with a similarity of more than 90%, the similar question data is used to generate corresponding answer data based on the knowledge base. If there is no similar question data with a similarity exceeding a preset threshold, the matching result and the data to be supplemented are sent, waiting for further supplementation;

[0042] S3. The AI ​​big model organizes the answer data and splits the answer into steps in the prompt, wherein the step splitting is to split the answer data into step data in which each step only includes one operation, and return the step data for display;

[0043] S4. Receive auxiliary execution information, extract keywords from the step data through the AI ​​big model, form {{operation 1: operated object 1}{operation 2: operated object 2}…}, and match it with preset key information, the preset key information is system name, menu function name, operation name, operated object name, etc.;

[0044] S5. If the match is successful, use the Function Call function of the AI ​​big model to call up the execution end interface, send all step data to the execution end, call the automated test execution tool, form script steps according to the step data, and compare with the existing automated case library. If there is a consistent process script, call the script and directly initiate automated execution (the existing UI automated test assets are saved in the form of keywords). If there is no consistent process script, call the preset UI script to complete the necessary steps, and send manual operation information for the remaining steps;

[0045] S6. Record the execution result of the guidance process and output the execution result.

[0046] By adopting the solution provided in this application, a knowledge base is built based on historical question and answer data, system operation manuals, interface documents, etc. The AI ​​big model rewrites and retrieves the question data, generates answers to the questions according to the knowledge base, and splits the answers into steps. By assisting in executing instructions, the AI ​​big model extracts keywords from the steps and matches them with preset key information, calls the automated test execution tool to form script steps, and compares them with the existing automated case library to perform corresponding operations. Therefore, this case can fully understand the needs by inputting the question data into the big model for multi-level splitting and keyword extraction, and can call third-party automation tools to assist in process operations, thereby improving the service efficiency of guidance-type questions and lowering the threshold for system application.

[0047] based on Figure 1 , Figure 2The invention relates to a joint debugging service method based on the integration of AI big model and automated testing technology, and also relates to a joint debugging service system based on the integration of AI big model and automated testing technology, the structure of which is as follows: Figure 3 As shown, including:

[0048] A knowledge base construction module 301 is used to collect first data and crawl second data, and import the first data and the second data into a vector database to establish a knowledge base based on a preset algorithm, wherein the first data is joint debugging history record data, and the second data is a menu name and a function name;

[0049] The question matching module 302 is used to receive question data. The AI ​​big model processes the question data based on the first data and matches it with the data in the knowledge base. If there is similar question data with a similarity exceeding a preset threshold, the similar question data is used to generate corresponding answer data based on the knowledge base. If there is no similar question data with a similarity exceeding the preset threshold, the matching result and the data to be supplemented are sent.

[0050] A step splitting module 303 is used to perform step splitting on the answer data based on the AI ​​big model to generate step data, wherein the step splitting is to split the answer data into step data in which each step only includes one operation;

[0051] A keyword extraction module 304 is used to receive auxiliary execution information, extract keywords from the step data through the AI ​​big model, and match them with preset key information;

[0052] The automatic execution module 305 is used to call the automated test execution tool when the match is successful, form script steps according to the step data, compare with the existing automated case library and perform corresponding operations. If there is no consistent process script, call the preset UI script to complete the necessary steps, and send manual operation information for the remaining steps;

[0053] The recording module 306 is used to record the execution result of the guidance process and output the execution result.

[0054] By using this system, the above method can be executed and the corresponding technical effects can be achieved.

[0055] An embodiment of the present invention further provides an electronic device for executing the above method, as an implementation device of the method, comprising a processor and a memory;

[0056] A memory, used for storing operation instructions;

[0057] The processor is used to execute the joint debugging service method based on the integration of AI big model and automated testing technology provided in any embodiment of the present application by calling operation instructions.

[0058] As an example, Figure 4 A schematic diagram of the structure of an electronic device applicable to an embodiment of the present application is shown, and the electronic device 400 includes: a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, such as being connected through a bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that in actual applications, the transceiver 404 is not limited to one. It is understandable that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the specific structure of the electronic device 400. In other embodiments of the present application, the electronic device 400 may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware. Optionally, the electronic device may also include a display screen 405 for displaying images, or receiving user operation instructions when necessary.

[0059] The processor 401 is applied in the embodiment of the present application to implement the method shown in the above method embodiment. The transceiver 404 may include a receiver and a transmitter. The transceiver 404 is applied in the embodiment of the present application to implement the function of the electronic device of the embodiment of the present application communicating with other devices when executed.

[0060] Processor 401 may be a CPU (Central Processing Unit), a general purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0061] The processor 401 may also include one or more processing units, for example: the processor 401 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), a controller, a memory, a video codec, a digital signal processor (digital signal processor, DSP), a baseband processor, and / or a neural network processor (Neural-network Processing Unit, NPU), etc. Different processing units can be independent devices or integrated into one or more processors. Among them, the controller can be the nerve center and command center of the electronic device 400. The controller can generate an operation control signal according to the instruction opcode and the timing signal to complete the control of fetching and executing instructions. A memory can also be set in the processor 401 for storing instructions and data. In some embodiments, the memory in the processor 401 is a cache memory. The memory can save instructions or data that the processor 401 has just used or circulated.

[0062] Processor 401 can run the joint debugging service method based on the integration of AI big model and automated testing technology provided in the embodiment of the present application. Processor 401 may include different devices. For example, when integrating CPU and GPU, the CPU and GPU can cooperate to execute the joint debugging service method based on the integration of AI big model and automated testing technology provided in the embodiment of the present application. Some algorithms are executed by the CPU, and other algorithms are executed by the GPU to obtain faster processing efficiency.

[0063] The bus 402 may include a path to transmit information between the above components. The bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0064] The memory 403 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or may include a high-speed random access memory, or may include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to this.

[0065] Optionally, the memory 403 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the joint debugging service method based on the integration of AI big model and automated testing technology provided in any embodiment of the present application.

[0066] The memory 403 can be used to store computer executable program codes, which include instructions. The processor 401 executes various functional applications and data processing of the electronic device 400 by running the instructions stored in the memory 403. The memory 403 may include a program storage area and a data storage area. Among them, the program storage area may store the code of the operating system, application program, etc. The data storage area may store data created during the use of the electronic device 400 (such as images, videos, etc. collected by the camera application), etc.

[0067] The memory 403 may also store one or more computer programs corresponding to the joint debugging service method based on the integration of AI big model and automated testing technology provided in the embodiment of the present application. The one or more computer programs are stored in the above-mentioned memory 403 and are configured to be executed by the one or more processors 401. The one or more computer programs include instructions, and the above-mentioned instructions can be used to execute each step in the above-mentioned corresponding embodiment.

[0068] Of course, the code of the joint debugging service method based on the integration of AI big model and automated testing technology provided in the embodiment of the present application can also be stored in an external memory.

[0069] The display screen 405 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a Miniled, a MicroLed, a Micro-oLed, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the electronic device 400 may include 1 or N display screens 405, where N is a positive integer greater than 1. The display screen 405 may be used to display information input by a user or information provided to a user and various graphical user interfaces (GUIs). For example, the display screen 405 may display photos, videos, web pages, or files, etc.

[0070] The electronic device provided in the embodiment of the present application is applicable to any embodiment of the above method. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, which will not be repeated here.

[0071] An embodiment of the present invention also provides a computer-readable storage medium capable of implementing all the steps in the method in the above embodiment, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, all the steps in the method in the above embodiment are implemented.

[0072] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or multiple boxes.

[0074] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps of the functions specified in a box or multiple boxes. Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the attached claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0076] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A joint debugging service method based on the integration of AI big model and automated testing technology, characterized in that: The following steps are involved: S1. Collect the first data and crawl the second data, import the first data and the second data into the vector database to establish a knowledge base based on a preset algorithm, the first data is the joint debugging history data, and the second data is the menu name and function name; S2. Receive question data, the AI ​​big model processes the question data based on the first data and matches it with the data in the knowledge base, and if there is similar question data with a similarity exceeding a preset threshold, use the similar question data to generate corresponding answer data based on the knowledge base; S3. The AI ​​big model splits the answer data into steps to generate step data; S4. Receive auxiliary execution information, extract keywords from the step data through the AI ​​big model, and match them with preset key information; S5. If the match is successful, the automated test execution tool is called to form script steps according to the step data, compare them with the existing automated case library, obtain a consistent process script and execute it automatically.

2. The method according to claim 1, characterized in that The step S2 also includes: if there is no similar question data with a similarity exceeding a preset threshold, sending the matching result and the data to be supplemented.

3. The method according to claim 1 or 2, characterized in that: The step splitting is to split the answer data into step data in which each step only includes one operation.

4. The method according to claim 3, characterized in that The step S5 further comprises: If there is no consistent process script, the preset UI script is called to complete the necessary steps, and manual operation information is sent for the remaining steps.

5. The method according to claim 1, characterized in that: Also includes: S6. Record the execution result of the guidance process and output the execution result.

6. A joint debugging service system based on the integration of AI big model and automated testing technology, characterized in that: include: A knowledge base construction module, used to collect first data and crawl second data, and import the first data and the second data into a vector database to establish a knowledge base based on a preset algorithm, wherein the first data is joint debugging history record data, and the second data is a menu name and a function name; A question matching module, for receiving question data, wherein the AI ​​big model processes the question data based on the first data and matches the question data with the data in the knowledge base, and if there is similar question data with a similarity exceeding a preset threshold, the similar question data is used to generate corresponding answer data based on the knowledge base; A step splitting module, used to split the answer data into steps based on the AI ​​big model to generate step data; A keyword extraction module, used to receive auxiliary execution information, extract keywords from the step data through the AI ​​big model, and match them with preset key information; The automatic execution module is used to call the automated test execution tool when the match is successful, form script steps according to the step data, compare with the existing automated case library and execute corresponding operations.

7. The system according to claim 6, characterized in that The system further comprises: The recording module is used to record the execution result of the guidance process and output the execution result.

8. An electronic device, characterized in that: including a processor and a memory; The memory is used to store operation instructions; The processor is used to execute the method according to any one of claims 1 to 5 by calling the operation instruction.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

Images