Operation and maintenance method and apparatus, system, electronic device, storage medium, and program product

Abstract

The present application belongs to the technical field of communication, and discloses an operation and maintenance method and apparatus, a system, an electronic device, a storage medium, and a program product. The operation and maintenance method of an embodiment of the present application comprises: receiving an external instruction by means of a large language model, the external instruction being used to indicate an operation and maintenance task for performing operation and maintenance on a target network; in response to the external instruction, by means of the large language model, searching for a target operation and maintenance tool capable of matching the operation and maintenance task; using the large language model, calling the target operation and maintenance tool to execute the operation and maintenance task.

Description

Operation and maintenance method, device, system, electronic device, storage medium and program product

[0001] Cross-reference

[0002] The present application claims priority to the Chinese patent application No. 202410901786.8, filed on July 5, 2024, and entitled "Operation and maintenance method, device, system, electronic device, storage medium and program product", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0003] The present application belongs to the field of communication technology, and particularly relates to an operation and maintenance method, device, system, electronic device, storage medium and program product. BACKGROUND

[0004] With the rapid development of wireless communication technology and the continuous improvement of network complexity of wireless communication network, the working environment of operation and maintenance personnel is becoming increasingly complex. With the wide application of emerging technologies such as Fifth-Generation Mobile Networks (5G), Internet of Things, and edge computing, the network data volume of wireless communication network has exploded, and the network architecture of wireless communication network has become more diversified, which directly leads to the intensification of the challenges of wireless communication network operation and maintenance.

[0005] For different operation and maintenance tasks in different scenarios of wireless communication network, such as network performance monitoring tasks, network fault analysis tasks, and network optimization tasks, a large number of tools have appeared in the market, such as network performance monitoring tools, signaling analysis tools, root cause analysis tools, network fault diagnosis tools, alarm analysis tools, and network optimization tools. Although these tools are powerful in their respective applicable scenarios, they often lack effective integration with each other, resulting in fragmentation of operation and maintenance tools.

[0006] In some scenarios, efficient operation and maintenance of wireless communication network is a prerequisite for ensuring the stability and reliability of wireless communication network in the fast-paced operation environment of wireless communication network. However, the current fragmentation of operation and maintenance tools makes it difficult for operation and maintenance personnel to respond quickly in actual operation and maintenance work, especially when dealing with cross-system and cross-level problems. Operation and maintenance personnel need to manually select multiple tools suitable for the current scenario and frequently switch between different tools to complete comprehensive operation and maintenance tasks, which not only wastes time but also requires higher skills from operation and maintenance personnel, as they need to be familiar with the operation interface and logic of each tool, greatly increasing the learning cost, time-consuming and laborious, and reducing the operation and maintenance efficiency, stability and reliability of wireless communication network. SUMMARY

[0007] An embodiment of the present application aims to provide an operation and maintenance method, device, system, electronic device, storage medium and program product.

[0008] In a first aspect, an operation and maintenance method is provided. The method comprises: receiving, by a large language model, an external instruction, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; in response to the external instruction, searching, by the large language model, for a target operation and maintenance tool that can match the operation and maintenance task; and invoking, by the large language model, the target operation and maintenance tool to execute the operation and maintenance task.

[0009] In a second aspect, an operation and maintenance device is provided. The operation and maintenance device comprises: a receiving module configured to receive, by a large language model, an external instruction, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; a searching module configured to search, by the large language model, for a target operation and maintenance tool that can match the operation and maintenance task in response to the external instruction; and an invoking module configured to invoke, by the large language model, the target operation and maintenance tool to execute the operation and maintenance task.

[0010] In a third aspect, an operation and maintenance system is provided. The operation and maintenance system comprises: a terminal device and a tool source module, the terminal device being connected to the tool source module; the tool source module comprising a tool library, the tool library comprising a plurality of operation and maintenance tools; the terminal device being deployed with an invocation service of a large language model, the terminal device invoking the large language model through the invocation service, receiving an external instruction through the large language model, and searching for a target operation and maintenance tool from the tool library of the tool source module according to the external instruction, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; and the large language model being further used to invoke the target operation and maintenance tool to execute the operation and maintenance task.

[0011] In a fourth aspect, an electronic device is provided. The electronic device comprises a memory, a processor, and computer-executable instructions stored on the memory and executable on the processor, the computer-executable instructions being executed by the processor to implement the steps of the method of the first aspect.

[0012] In a fifth aspect, a computer-readable storage medium is provided. The computer-readable storage medium is used to store computer-executable instructions, the computer-executable instructions being executed by a processor to implement the steps of the method of the first aspect.

[0013] In a sixth aspect, a computer program product is provided. The computer program product comprises a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, the program instructions being executed by a computer to implement the steps of the operation and maintenance method of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to make the technical solutions in the present application or the related technical solutions clearer, the drawings needed to be used in the embodiment or the related technical description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0015] FIG. 1 is a flow diagram of an operation and maintenance method according to an example embodiment of the present application.

[0016] FIG. 2 is a flow diagram of an operation and maintenance method according to an example embodiment of the present application.

[0017] FIG. 3 is a structural diagram of an operation and maintenance system according to an example embodiment of the present application.

[0018] FIG. 4 is a structural diagram of an operation and maintenance device according to an example embodiment of the present application.

[0019] FIG. 5 is a structural diagram of an electronic device according to an example embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the technical solutions in the present application or the related technical solutions clearer, the drawings needed to be used in the embodiment or the related technical description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] The technical solutions provided by the embodiments of the present application will be described in detail below in combination with the drawings and some embodiments and their application scenarios.

[0022] FIG. 1 shows a flow diagram of an operation and maintenance method 100 according to an example embodiment of the present application. The method can be executed by an electronic device, such as a terminal device or a server device. In other words, the method can be executed by software or hardware installed in the terminal device or the server device. The server includes but is not limited to a single server, a server cluster, a cloud server, or a cloud server cluster, etc. As shown in FIG. 1, the method can include the following steps.

[0023] Step S101, receiving an external instruction through a large language model.

[0024] The external instruction is used to indicate an operation and maintenance task for operating and maintaining a target network.

[0025] In the embodiments of the present application, the external instruction can be an instruction input by a user in a natural language, which describes an operation and maintenance requirement or an operation and maintenance intention of the user for the target network, and the target network can be a wireless communication network, and the operation and maintenance task includes but is not limited to a network performance monitoring task, a network fault analysis task, and a network optimization task. A large language model is usually used in a natural language interaction scene, such as an intelligent dialogue, a chat robot, intention classification, and emotion recognition. In the present application, the large language model is used to receive an instruction input by a user in a natural language, and the powerful semantic understanding and intention recognition capabilities of the large language model are used to understand the intention of the user, which includes an operation and maintenance task for the target network. When the user inputs the external instruction, the external instruction can be input in an input box of a front-end page of a visual operation and maintenance system, and the external instruction is received by the large language model.

[0026] For example, the user inputs an instruction of "help me analyze the qos flow establishment success rate of the network element 420 and related alarms", which indicates an operation and maintenance task of analyzing the qos flow establishment success rate of the network element 420 and an operation and maintenance task of related alarms in the wireless communication network.

[0027] In step S103, in response to the external instruction, a target operation and maintenance tool that can match the operation and maintenance task is found by using the large language model.

[0028] In the embodiments of the present application, the detailed description information of each operation and maintenance tool can be input into the large language model in the form of a prompt word, and the detailed description information of the operation and maintenance tool introduces detailed information of the operation and maintenance tool, including functions, applicable scenarios, calling methods, and parameter lists. The operation and maintenance tool includes but is not limited to a network performance monitoring tool, a signaling analysis tool, a root cause analysis tool, a network fault diagnosis tool, an alarm analysis tool, and a network optimization tool.

[0029] The large language model identifies the intention of the user by the indication of the external instruction, and the large language model uses the prompt word of the detailed description information of the operation and maintenance tool to select an operation and maintenance tool that can solve the current user requirement.

[0030] In a possible implementation, in response to the external instruction, the target operation and maintenance tool that can match the operation and maintenance task is found by using the large language model, including: inputting the operation and maintenance task and the description information of the operation and maintenance tool in the tool library into the large language model, and using the large language model to find the target operation and maintenance tool that can match the operation and maintenance task from the tool library.

[0031] In an implementation, the operation and maintenance task and the description information of the operation and maintenance tools in the tool library can be input into the large language model at the same time. The large language model first identifies the intention of performing operation and maintenance on the target network in the operation and maintenance task, then performs semantic understanding on the description information of the operation and maintenance tools, and then finds the target operation and maintenance tool that can meet the intention from the operation and maintenance tools.

[0032] The tool library includes various operation and maintenance tools required in operation and maintenance work. The tool source module corresponding to the tool library can uniformly manage the tools in the tool library. The operation and maintenance tools are different in use scenarios, processing tasks, execution efficiency, and other aspects. The tool source module uniformly manages the definition, execution, and update of all operation and maintenance tools in the tool library. In addition, the tool source module can also arrange and define the calling method, parameters, and execution order of various operation and maintenance tools in use.

[0033] For example, the external instruction input by the user is "help me analyze the qos flow establishment success rate of the network element 420 and related alarms." The large language model receives the external instruction, and the detailed description information of each operation and maintenance tool in the related tool library is also input into the large language model as a prompt word. The operation and maintenance tools in the tool library include an index analysis tool, a correlation analysis tool, a root cause analysis tool, an upgrade analysis tool, and an alarm analysis tool. The detailed description information includes the functions, use scenarios, calling methods, and parameter lists of these operation and maintenance tools.

[0034] The large language model first analyzes the problem in the external instruction input by the user, and then performs semantic understanding on the description information of the operation and maintenance tools. After the decision of the large language model, it is found that the function of a certain operation and maintenance tool in the related tool library can solve the user's problem. The large language model selects the tool that can solve the user's problem from the operation and maintenance tools in the tool library. For the problem "help me analyze the qos flow establishment success rate of the network element 420 and related alarms" input by the user, the large language model selects the index analysis tool and the alarm analysis tool to solve the user's problem.

[0035] In step S105, the target operation and maintenance tool is called by the large language model to execute the operation and maintenance task.

[0036] In the embodiments of the present application, after the large language model selects the target operation and maintenance tool that can solve the operation and maintenance task, the large language model can arrange the calling method and the calling order of the target operation and maintenance tool. The target operation and maintenance tool is called and executed according to the arranged calling order and calling method, and the operation and maintenance task is completed.

[0037] The process of arranging the calling order of the target operation and maintenance tool by the large language model and calling the target operation and maintenance tool to execute the operation and maintenance task can be performed in the following manner:

[0038] The calling sequence of the target operation and maintenance tool is arranged by the large language model according to the sequence of the operation and maintenance sub-tasks in the operation and maintenance task; and the target operation and maintenance tool is called according to the calling sequence to execute the operation and maintenance task.

[0039] In the embodiments of the present application, the operation and maintenance sub-tasks can be a plurality of tasks for performing operation and maintenance on the target network described in the external instruction input by the user, and there is a sequence order between these tasks. The sub-task in the front of the sequence order is called first. Or the operation and maintenance task needs to be completed by a plurality of operation and maintenance sub-tasks. The sequence order of the operation and maintenance sub-tasks is the sequence of the operation and maintenance sub-tasks. The sub-task in the front of the sequence order is called first.

[0040] For example, as mentioned in the above embodiment, for the problem of "help me analyze the qos flow establishment success rate of the network element 420 and the related alarms" input by the user, the large language model selects the index analysis tool and the alarm analysis tool to solve the user's problem. In the problem input by the user, there are two operation and maintenance sub-tasks, "analyze the qos flow establishment success rate" and "related alarms". The large language model arranges the calling sequence of the index analysis tool and the alarm analysis tool according to the sequence order of the two operation and maintenance sub-tasks. According to the analysis of the external instruction input by the user, the sequence order of the operation and maintenance sub-task "analyze the qos flow establishment success rate" is in the front, and the sequence order of the operation and maintenance sub-task "related alarms" is in the back. Therefore, when the large language model arranges the calling sequence of the target operation and maintenance tool, the index analysis tool is called first, and then the alarm analysis tool is called. Finally, the large language model calls the index analysis tool and the alarm analysis tool according to the arranged calling sequence to execute the operation and maintenance task "analyze the qos flow establishment success rate of the network element 420 and the related alarms", and obtains the index analysis result of "qos flow establishment success rate" and the result of related alarms.

[0041] For example, the user inputs the question "help me perform network fault analysis on network element 420", which contains the operation and maintenance task of "network fault analysis". To complete this operation and maintenance task, the large language model needs to perform alarm analysis and root cause analysis of the network fault. These two operation and maintenance sub-tasks need to be completed in sequence. Therefore, the large language model selects the alarm analysis tool and the root cause analysis tool, and arranges the calling order of the alarm analysis tool and the root cause analysis tool according to the sequence of the alarm analysis task and the root cause analysis task. First, the alarm analysis tool is called, and then the root cause analysis tool is called. Finally, the large language model calls the alarm analysis tool and the root cause analysis tool in the order arranged, executes the operation and maintenance task of "network fault analysis", and obtains the analysis of "network fault analysis".

[0042] Further, the large language model can use the following process to call the target operation and maintenance tool in sequence according to the calling order to execute the operation and maintenance task: determining the calling mode of the target operation and maintenance tool using the large language model; and calling the target operation and maintenance tool in sequence according to the calling order in the calling mode corresponding to the target operation and maintenance tool to execute the operation and maintenance task.

[0043] In the embodiments of the present application, the calling modes of different operation and maintenance tools can be different, and the calling modes include but are not limited to: command line interface, graphical user interface, Web interface, API, plug-in / extension, etc. The command line interface refers to the command line interface provided by the operation and maintenance tool, which allows users to execute operations by inputting specific commands. The graphical user interface refers to the scenario that needs to interact with the visual interface, such as monitoring system tools and log analysis tools, which usually provide graphical user interfaces. Users can intuitively operate by clicking buttons, dragging icons, or filling in forms, etc. The Web interface refers to the management interface provided by some operation and maintenance tools based on Web, which is convenient for remote access and multi-user collaboration. The API interface is provided by some operation and maintenance tools for integration with other systems or scripts, such as remote procedure calls or other types of API interfaces. Through the API, custom scripts or applications can be written to call the functions of the tool, and automated operation and maintenance processes can be implemented. Plug-ins / extensions refer to some operation and maintenance tools that support plug-in or extension mechanisms, allowing users to extend their functions by installing additional components. For example, Jenkins supports multiple build, test, and deployment tasks through plug-ins. The calling mode can also be other types according to actual conditions, which are not limited in the embodiments of the present application.

[0044] Further, the large language model can determine the calling manner of the target operation and maintenance tool according to the actual scene of the operation and maintenance task, and the corresponding operation and maintenance tool is called according to the calling manner arranged by the large language model when the target operation and maintenance tool is called. In this way, by arranging the calling manner of the operation and maintenance tool by the large language model, the success rate of operation and maintenance tool calling can be improved.

[0045] Through the technical solutions disclosed in the embodiments of the present application, the external instruction is received by the large language model, the external instruction is used to indicate an operation and maintenance task of performing operation and maintenance on a target network; the large language model can automatically select a target operation and maintenance tool suitable for the current operation and maintenance task according to the operation and maintenance task; and the large language model is used to automatically call the target operation and maintenance tool to execute the operation and maintenance task, which saves a lot of time and cost and improves the operation and maintenance efficiency, so that the wireless communication network can be operated and maintained more quickly, and the stability and reliability of the wireless communication network are further improved.

[0046] In a possible implementation manner, after the target operation and maintenance tool is called by the large language model to execute the operation and maintenance task, the operation and maintenance method further includes: integrating, by the large language model, an operation and maintenance result after the operation and maintenance task is executed, and outputting an integrated result.

[0047] In this implementation manner, the large language model integrates the result of the operation and maintenance task executed by the target operation and maintenance tool, so that the description of the operation and maintenance result is more in line with the specifications of natural language, and the final integrated result is output, thereby facilitating the user to more intuitively view the execution result of the operation and maintenance task executed by the operation and maintenance tool, and improving the user experience.

[0048] FIG. 2 shows another flowchart of an operation and maintenance method 200 provided by the embodiments of the present application, which can be executed by an electronic device, such as a terminal device or a server device. In other words, the method can be executed by software or hardware installed in the terminal device or the server device. The server includes but is not limited to a single server, a server cluster, a cloud server, or a cloud server cluster, etc. As shown in FIG. 2, the method can include the following steps.

[0049] Step S201, receiving an external instruction by a large language model.

[0050] The external instruction is used to indicate an operation and maintenance task of performing operation and maintenance on a target network;

[0051] Step S203, in response to the external instruction, finding, by the large language model, a target operation and maintenance tool that can match the operation and maintenance task.

[0052] Step S205, calling, by the large language model, the target operation and maintenance tool to execute the operation and maintenance task.

[0053] It is worth noting that steps S201 to S205 in this embodiment have the same or similar implementation as steps S101 to S105 in the above embodiment, which can be mutually referred to, and the present embodiment will not be described here.

[0054] In step S207, if the target operation and maintenance tool is not found, an operation and maintenance method for performing the operation and maintenance task on the target network is generated by the large language model, and the target network is operated and maintained according to the operation and maintenance method.

[0055] In the present embodiment, if the operation and maintenance tool that can solve the user's problem is not found, that is, there is no operation and maintenance tool in the current tool library that can meet the user's intention, the large language model needs to directly generate an operation and maintenance method and use it to arrange the operation and maintenance task. The operation and maintenance method can be a code directly generated by the large language model according to the operation and maintenance task, which includes the execution flow and execution method of the operation and maintenance task. When the code is executed, the target network is operated and maintained according to the execution flow and execution method in the code. Further, the operation and maintenance task can indicate processing of target data in the target network.

[0056] In one possible implementation, in the case where the target operation and maintenance tool is not found, generating an operation and maintenance method for performing the operation and maintenance task on the target network by the large language model includes: extracting an abstract from the target data corresponding to the operation and maintenance task, the operation and maintenance task being used to indicate processing of the target data; and generating, by the large language model, an operation and maintenance method for the target data according to the abstract, the operation and maintenance method including a data processing flow and a data processing method.

[0057] In this implementation, when the operation and maintenance task indicates processing of target data in the target network, the abstract of the data is first extracted from the target data, and then the abstract of the data is input into the large language model as part of the prompt words. The large language model generates the processing steps and processing method of the target data based on the abstract of the current data, and generates the code meeting the user's demand based on the processing steps and processing method. Finally, the code generated by the large language model is executed to realize the analysis and processing of the data according to the user's demand, and the processing result is obtained. The code generated by the large language model can be a python code.

[0058] For example, the user inputs an external instruction: "Help me calculate the average value of the qos flow establishment success rate on network element 420 on Sunday every week and whether there is a network element change record." The large language model receives this external instruction, and at the same time, the detailed description information of the operation and maintenance tools in the related tool library is also input into the large language model as a prompt word. The tools contained in the related tool library include: index analysis tools, correlation analysis tools, root cause analysis tools, upgrade analysis tools, alarm analysis tools, etc. The detailed description information of the operation and maintenance tools contains the functions, use scenarios, calling methods, parameter lists, etc. of these tools.

[0059] Based on the detailed description information of the tools, the large language model analyzes the user's problem and determines whether the operation and maintenance tools in the current tool library can solve the user's problem. Through the decision of the large language model, it is found that the functions contained in the operation and maintenance tools in the related tool library cannot meet the user's needs.

[0060] Then, the large language model extracts the target data corresponding to the operation and maintenance task. Again, the large language model is used, and the extracted summary is used as a prompt word to arrange the processing flow and processing method of the operation and maintenance task: first, use the index table to calculate the average value of the qos flow establishment success rate on Sunday every week, and then use the operation record table to query whether there is a network element change record on Sunday. According to the above-mentioned processing flow and processing method, the semantic understanding and code generation capabilities of the large language model are used to generate python code, and finally, the python code is executed and the related target data is processed to obtain the processing result.

[0061] Through the technical solutions disclosed in the embodiments of the present application, the large language model receives an external instruction, which is used to indicate an operation and maintenance task for operating and maintaining a target network; the large language model can automatically select a target operation and maintenance tool suitable for the current operation and maintenance task according to the operation and maintenance task; and the large language model automatically calls the target operation and maintenance tool to execute the operation and maintenance task, which saves a lot of time and cost and improves the operation and maintenance efficiency, so that the wireless communication network can be operated and maintained more quickly, and the stability and reliability of the wireless communication network are further improved. In addition, when no operation and maintenance tool is found, the large language model can directly generate an operation and maintenance method of the operation and maintenance task, and operate and maintain the target network according to the operation and maintenance method, which further improves the reliability, success rate and operation and maintenance efficiency of operating and maintaining the target network, and further improves the stability and reliability of the wireless communication network.

[0062] FIG. 3 shows a structural schematic diagram of an operation and maintenance system provided by an embodiment of the present application. The system 300 includes a terminal device 301 and a tool source module 302, the terminal device 301 is connected with the tool source module 302; the tool source module 302 includes a tool library, the tool library includes a plurality of operation and maintenance tools; the terminal device 301 is deployed with a calling service of a large language model, the terminal device 301 calls the large language model through the calling service, receives an external instruction through the large language model, and finds a target operation and maintenance tool from the tool library of the tool source module 302 according to the external instruction, the external instruction is used to indicate an operation and maintenance task of performing operation and maintenance on a target network; the large language model is also used to call the target operation and maintenance tool to perform the operation and maintenance task.

[0063] In the embodiment of the present application, the tool source module uniformly manages the tool library, the tool library includes various operation and maintenance tools needed in operation and maintenance work, and each operation and maintenance tool is different in use scene, processing task, execution efficiency, etc. The tool source module uniformly manages the definition, execution and update of all operation and maintenance tools, and can also arrange and define the calling method, parameters and execution order of various operation and maintenance tools in use.

[0064] The calling service of the large language model is deployed in the terminal device 301, the terminal device 301 can call the large language model through the calling service, the large language model is connected with the tool source module, receives a user's question at the same time, and converts the user's question, demand and description into a call of an operation and maintenance tool by using the powerful semantic understanding ability and intention recognition ability of the large language model, that is, finds a target operation and maintenance tool from the tool library of the tool source module 302 according to the user's demand. Finally, the large language model will arrange and call the corresponding operation and maintenance tool to perform the operation and maintenance task, and return the operation result to the user, realizing the operation and maintenance analysis process of natural language interaction.

[0065] Through the technical scheme disclosed in the embodiment of the present application, an external instruction is received by the large language model, the external instruction is used to indicate an operation and maintenance task of performing operation and maintenance on a target network; the large language model can automatically select a target operation and maintenance tool suitable for the current operation and maintenance task according to the operation and maintenance task; and the large language model automatically calls the target operation and maintenance tool to perform the operation and maintenance task, saving a lot of time and cost, improving the operation and maintenance efficiency, so that the wireless communication network can be maintained more quickly, and the stability and reliability of the wireless communication network are further improved.

[0066] As shown in FIG. 3, further comprising: a data source module 303, the terminal device 301 is connected with the data source module 303; the terminal device 301 is further used for extracting an abstract from target data corresponding to the operation and maintenance task, the operation and maintenance task is used for indicating processing the target data; the large language model is further used for generating an operation and maintenance mode of the target data according to the abstract, obtaining the target data from the data source module, and processing the target data based on the operation and maintenance mode, the operation and maintenance mode including a data processing flow and a data processing mode.

[0067] In the embodiment of the present application, the data source module 303 uniformly manages various types of data to be used in the maintenance and measurement work, and the formats, usage methods, processing methods, and analysis methods of various types of data are not the same. The data source module 303 uniformly stores, updates, and manages the data, and simultaneously generates codes to arrange and define the usage methods, processing sequences, etc. of various types of data in use.

[0068] In this way, the large language model is used to uniformly manage the data source module and the tool source module, and the user only interacts with the large language model, thereby realizing unified management, arrangement, and scheduling of operation and maintenance tools and data.

[0069] It is worth noting that the operation and maintenance system in the embodiment has the same or similar implementation manner as the operation and maintenance method in the above-mentioned embodiments, which can be mutually referred to, and the embodiment of the present application will not be described here again.

[0070] FIG. 4 shows a structural schematic diagram of an operation and maintenance apparatus provided by the embodiment of the present application. The apparatus 400 includes: a receiving module 401, configured to receive an external instruction through a large language model, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; a searching module 402, configured to search for a target operation and maintenance tool capable of matching the operation and maintenance task through the large language model in response to the external instruction; and a calling module 403, configured to call the target operation and maintenance tool to execute the operation and maintenance task by using the large language model.

[0071] The external instruction is received through the large language model, and the external instruction is used to indicate an operation and maintenance task of performing operation and maintenance on a target network. The large language model can automatically select a target operation and maintenance tool suitable for the current operation and maintenance task according to the operation and maintenance task. The large language model is used to automatically call the target operation and maintenance tool to execute the operation and maintenance task, thereby saving a large amount of time and cost and improving operation and maintenance efficiency. Thus, the wireless communication network can be more quickly maintained, and the stability and reliability of the wireless communication network are further improved.

[0072] In a possible implementation manner, the apparatus further includes: a generating module, configured to generate an operation and maintenance mode of the operation and maintenance task of performing operation and maintenance on the target network through the large language model in a case where the target operation and maintenance tool is not searched for; and an operation and maintenance module, configured to perform operation and maintenance on the target network according to the operation and maintenance mode.

[0073] In a possible implementation, the generation module is further configured to extract an abstract from the target data corresponding to the operation and maintenance task, the operation and maintenance task is used to indicate processing of the target data, and the operation and maintenance manner of the target data is generated by using the large language model according to the abstract, the operation and maintenance manner including a data processing flow and a data processing manner.

[0074] In a possible implementation, the finding module 402 is further configured to input the operation and maintenance task and description information of the operation and maintenance tools in the tool library into the large language model, and find the target operation and maintenance tool that can match the operation and maintenance task from the tool library by using the large language model.

[0075] In a possible implementation, the calling module 403 is further configured to arrange a calling sequence of the target operation and maintenance tool by using the large language model, the calling sequence being arranged by the large language model according to the sequence of the operation and maintenance subtasks in the operation and maintenance task, and the target operation and maintenance tool is called in sequence according to the calling sequence to execute the operation and maintenance task.

[0076] In a possible implementation, the calling module 403 is further configured to determine a calling manner of the target operation and maintenance tool by using the large language model, and the target operation and maintenance tool is called in sequence according to the calling sequence and in the calling manner corresponding to the target operation and maintenance tool to execute the operation and maintenance task.

[0077] In a possible implementation, the apparatus further includes an output module configured to integrate an operation and maintenance result after the operation and maintenance task is executed by using the large language model, and output an integrated result.

[0078] The apparatus 400 provided in the embodiments of the present application can execute the methods in the foregoing method embodiments, and achieve the functions and advantages of the methods in the foregoing method embodiments, which will not be described herein again.

[0079] FIG. 5 shows a hardware structure schematic diagram of an electronic device according to an embodiment of the present application. Referring to the figure, at the hardware level, the electronic device includes a processor, and optionally, an internal bus, a network interface, and a memory. The memory can include a memory such as a random-access memory (RAM), and can also include a non-volatile memory such as at least one disk memory. Of course, the electronic device can also include other hardware required by other services.

[0080] The processor, the network interface and the memory can be connected with each other through an internal bus, which can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus or the like. The bus can be divided into an address bus, a data bus, a control bus and the like. For the convenience of representation, only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0081] The memory is configured to store a program. Specifically, the program can include program code including computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provide instructions and data for the processor.

[0082] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs, and forms a device for positioning a specified user at a logical level. The processor executes the program stored in the memory, and specifically is configured to execute the method disclosed in the embodiments shown in FIG. 1-FIG. 2 and realize the functions and beneficial effects of each method described in the foregoing method embodiments, which will not be described herein again.

[0083] The method disclosed in the embodiments of the present application as shown in FIG. 1-2 can be applied to a processor or implemented by the processor. The processor can be an integrated circuit chip having a processing capability of signals. In the implementation, each step of the method can be completed by integrated logic circuits of hardware in the processor or instructions in the form of software. The processor can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; or a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. Each method, step and logic block diagram disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware coding processor for execution, or a combination of hardware and software modules in the coding processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register, etc. The storage medium in the memory is read by the processor, and the hardware thereof is combined to complete the steps of the method.

[0084] The electronic device can also perform the methods described in the foregoing method embodiments, and achieve the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0085] Of course, in addition to the software implementation, the electronic device of the present application does not exclude other implementation manners, such as logic devices or a combination of software and hardware, etc. That is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or a logic device.

[0086] The embodiments of the present application also propose a computer readable storage medium, which stores one or more programs, and when the one or more programs are executed by an electronic device including a plurality of application programs, the electronic device executes the method disclosed in the embodiments of FIG. 1-2 and achieves the functions and beneficial effects of the methods described in the foregoing method embodiments, which will not be repeated here.

[0087] The computer readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0088] Further, the embodiment of the present application further provides a computer program product, which comprises a computer program stored in a non-transitory computer readable storage medium, and the computer program comprises program instructions, and when the program instructions are executed by a computer, the following processes are implemented: the method disclosed in the embodiments shown in FIG. 1 and FIG. 2, and the functions and beneficial effects of the methods described in the foregoing method embodiments, which are not described here again.

[0089] In summary, the above only describes the preferred embodiments of the present application, and is not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0090] The system, device, module or unit disclosed in the above embodiments can be specifically implemented by a computer chip or entity, or by a product with certain functions. A typical implementation device is a computer. Specifically, the computer may, for example, be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0091] The computer readable medium includes permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. According to the definition herein, the computer readable medium does not include transitory computer readable media, such as modulated data signals and carriers.

[0092] It is also to be noted that the terms "comprising", "including", and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element.

[0093] Each of the embodiments in the present specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the description of the method embodiments.

Claims

1. An operation and maintenance method, comprising: receiving, by a large language model, an external instruction, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; in response to the external instruction, finding, by the large language model, a target operation and maintenance tool that can match the operation and maintenance task; calling, by the large language model, the target operation and maintenance tool to execute the operation and maintenance task.

2. The operation and maintenance method of claim 1, wherein, The method further comprises: in the case where the target operation and maintenance tool is not found, generating, by the large language model, an operation and maintenance manner of performing the operation and maintenance task on the target network; performing operation and maintenance on the target network according to the operation and maintenance manner.

3. The operation and maintenance method of claim 2, wherein, The case where the target operation and maintenance tool is not found, and the operation and maintenance manner of performing the operation and maintenance task on the target network is generated by the large language model, comprises: extracting an abstract from target data corresponding to the operation and maintenance task, the operation and maintenance task being used to indicate processing of the target data; generating, by the large language model, an operation and maintenance manner of the target data according to the abstract, the operation and maintenance manner comprising a data processing flow and a data processing manner.

4. The operation and maintenance method according to any one of claims 1 to 3, wherein The case where the target operation and maintenance tool is found by the large language model in response to the external instruction, comprises: inputting the operation and maintenance task and description information of operation and maintenance tools in a tool library into a large language model, and finding, by the large language model, a target operation and maintenance tool that can match the operation and maintenance task from the tool library.

5. The operation and maintenance method of claim 4, wherein, The case where the target operation and maintenance tool is called by the large language model to execute the operation and maintenance task, comprises: arranging, by the large language model, a calling sequence of the target operation and maintenance tool, the calling sequence being arranged by the large language model according to an order of operation and maintenance subtasks in the operation and maintenance task; calling, in sequence, the target operation and maintenance tool according to the calling sequence to execute the operation and maintenance task.

6. The operation and maintenance method of claim 5, wherein, The case where the target operation and maintenance tool is called in sequence according to the calling sequence to execute the operation and maintenance task, comprises: determining, by the large language model, a calling manner of the target operation and maintenance tool; calling, in sequence, the target operation and maintenance tool according to the calling manner corresponding to the target operation and maintenance tool to execute the operation and maintenance task.

7. The operation and maintenance method of claim 1, wherein, After the target operation and maintenance tool is called by the large language model to execute the operation and maintenance task, the operation and maintenance method further comprises: integrating, by the large language model, an operation and maintenance result after the operation and maintenance task is executed, and outputting an integrated result.

8. An operation and maintenance apparatus, comprising: a receiving module configured to receive, by a large language model, an external instruction, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; a finding module configured to find, by the large language model, a target operation and maintenance tool that can match the operation and maintenance task in response to the external instruction; a calling module configured to call, by the large language model, the target operation and maintenance tool to execute the operation and maintenance task.

9. An operations system comprising: a terminal device and a tool source module, the terminal device being connected to the tool source module; the tool source module comprising a tool library, the tool library comprising a plurality of operation and maintenance tools; The terminal device is deployed with a calling service of a large language model, the terminal device calls the large language model through the calling service, receives an external instruction through the large language model, and finds a target operation and maintenance tool from a tool library of the tool source module according to the external instruction, the external instruction being used to indicate an operation and maintenance task of performing operation and maintenance on a target network; The large language model is further used to call the target operation and maintenance tool to execute the operation and maintenance task.

10. The operations and maintenance system of claim 9, wherein, Further comprising a data source module, the terminal device being connected with the data source module; The terminal device is further used to extract an abstract from target data corresponding to the operation and maintenance task, the operation and maintenance task being used to indicate processing of the target data; The large language model is further used to generate an operation and maintenance mode of the target data according to the abstract, The target data is obtained from the data source module, and the target data is processed based on the operation and maintenance mode, the operation and maintenance mode including a data processing flow and a data processing mode.

11. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the operation and maintenance method according to any one of claims 1-7.

12. A computer readable medium, the computer readable storage medium storing a computer program, the computer program, when executed by a processor, implementing the steps of the operation and maintenance method according to any one of claims 1-7.

13. A computer program product, the computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the steps of the operation and maintenance method according to any one of claims 1-7.

Images