Construction method and device of agent application, equipment, medium and program product

Abstract

The invention discloses an agent application construction method and device, equipment, a medium and a program product, and relates to the technical field of agent development, and the method comprises the steps: carrying out the arrangement of each component node and the flow of each component node, and obtaining a to-be-debugged agent; debugging each component node of the to-be-debugged agent to obtain a target agent; and monitoring the target agent according to the log information of the target agent and the parameter information of each component node so as to ensure the operation of the target agent. According to the invention, the arranged and designed agent application can run stably and efficiently.

Description

Technical Field

[0001] The present application relates to the field of intelligent agent development technology, and in particular to an intelligent agent application construction method, an intelligent agent application construction device, an intelligent agent application construction equipment, a storage medium and a computer program product. Background Art

[0002] In the existing technical solutions for the current intelligent agent application processing, the focus is often only on the design of the intelligent agent application orchestration. Although the preliminary construction of the intelligent agent application process has been achieved to a certain extent, work nodes can be created through visual interfaces and other means, and then the application execution process can be planned. However, in actual application scenarios, the operation of the intelligent agent may encounter various complex situations, such as data transmission errors, algorithm execution deviations, etc., and the coherence of the intelligent agent application is poor, resulting in the inability of the orchestrated intelligent agent application to run stably and efficiently. Summary of the invention

[0003] The main purpose of this application is to provide an intelligent application construction method, an intelligent application construction device, an intelligent application construction equipment, a storage medium and a computer program product, aiming to solve the technical problem that the choreographed intelligent application cannot run stably and efficiently.

[0004] To achieve the above objectives, the present application proposes a method for constructing an intelligent agent application, the method comprising: By arranging each component node and the process of each component node, the intelligent agent to be debugged is obtained; Debugging each component node of the agent to be debugged to obtain a target agent; The target intelligent agent is monitored according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

[0005] In one embodiment, the step of debugging each component node of the agent to be debugged to obtain a target agent includes: Debugging each component node of the agent to be debugged in sequence according to a predetermined execution order; Record the exceptions generated during the debugging process of each component node and generate a debugging log; The abnormality of the agent to be debugged is repaired according to the debugging log to obtain the target agent.

[0006] In one embodiment, the step of debugging the component nodes of the agent to be debugged in sequence according to a predetermined execution order includes: When encountering a breakpoint set at a designated component node of the agent to be debugged, pausing execution at the breakpoint to check the running state and running parameters of the designated component node; During the period when the execution is suspended at the breakpoint, when a running instruction to continue the execution at the breakpoint is received, the subsequent component nodes are continued to be executed from the breakpoint.

[0007] In one embodiment, the step of debugging the component nodes of the agent to be debugged in sequence according to a predetermined execution order includes: When encountering a breakpoint set at a designated component node of the agent to be debugged, pausing execution at the breakpoint to check the running state and running parameters of the designated component node; During the period when the execution is suspended at the breakpoint, when a running instruction to continue the execution at the breakpoint is received, the subsequent component nodes are continued to be executed from the breakpoint.

[0008] In one embodiment, after the step of collecting the log information of the target agent during operation and the parameter information of each component node in the target agent in real time, the method further includes: According to the log information and the parameter information, an abnormality prediction is performed on the running state of the intelligent agent through a preset abnormality prediction model to obtain a target time period in which the abnormality will occur; During the target period, preventive measures are taken in advance to deal with abnormalities that will occur.

[0009] In one embodiment, before the step of performing abnormal prediction on the running state of the agent according to the log information and the parameter information by using a preset abnormal prediction model to obtain a target time period in which the abnormality will occur, the method includes: Based on historical log information, historical parameter information and historical anomaly periods, a prediction model for anomaly prediction is trained.

[0010] In addition, to achieve the above-mentioned purpose, the present application also proposes a device for constructing an intelligent agent application, the device for constructing an intelligent agent application comprising: an orchestration module, for obtaining an intelligent agent to be debugged by orchestrating each component node and the process of each component node; A debugging module, used to debug each component node of the agent to be debugged to obtain a target agent; The monitoring module is used to monitor the target intelligent agent according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

[0011] In addition, to achieve the above-mentioned objectives, the present application also proposes a device for constructing an intelligent application, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the method for constructing an intelligent application as described above.

[0012] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the method for constructing the intelligent application as described above are implemented.

[0013] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the method for constructing an intelligent agent application as described above.

[0014] One or more technical solutions proposed in this application have at least the following technical effects: Since the existing intelligent agent application processing only focuses on the design link of the intelligent agent application choreography, it is impossible to accurately locate the root cause of the problem in actual application and it is difficult to fully grasp the running status and performance of the intelligent agent. The coherence of the intelligent agent application is poor, resulting in the inability of the choreography-designed intelligent agent application to run stably and efficiently. This application provides a one-stop capability of design, debugging, and monitoring when processing intelligent agent applications. It not only includes the choreography design link, but also performs debugging operations and monitoring operations on each component node of the intelligent agent to be debugged. During the debugging process, each component node will be debugged and the detailed information of its execution will be recorded. When the intelligent agent has problems during operation, the specific component node or operation step can be accurately located. By monitoring the target intelligent agent, using log information and parameter information of each component node, the running status of the intelligent agent can be grasped from multiple dimensions. After the choreography design is completed, potential problems are eliminated through debugging, and then stability during operation is guaranteed through monitoring, thereby improving the overall performance and operation efficiency of the intelligent agent application. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flowchart of an embodiment of a method for constructing an intelligent agent application of the present application is provided; Figure 2 A schematic diagram of the component node content provided for an embodiment of a method for constructing an intelligent agent application of the present application; Figure 3A schematic diagram of the operation mode selection provided in an embodiment of the method for constructing an intelligent agent application of the present application; Figure 4 A schematic diagram of log information provided for another embodiment of the method for constructing an intelligent agent application of the present application; Figure 5 A schematic diagram of the module structure of a construction device for an intelligent agent application of this application; Figure 6 A schematic diagram of the device structure of the hardware operating environment involved in the method for constructing the intelligent application of this application.

[0018] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0020] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0021] In the existing technology, the main focus is to build a logically coherent intelligent agent workflow, and we are used to treating intelligent agent application orchestration as a relatively independent process, rather than a system that needs to be continuously optimized and guaranteed. It is just to enable intelligent agent applications to perform basic tasks, that is, how to combine various components and processes to achieve specific intelligent agent tasks.

[0022] In addition, the orchestration of intelligent agent applications is already a challenging task in itself, which requires the integration of multiple components, complex logic processes, and different algorithm modules. Within limited resources and development cycles, developers tend to focus on the implementation of orchestration, and do not have sufficient resources to develop additional debugging and monitoring tools and functions. They believe that simple testing and basic functional implementation are sufficient, and do not realize the importance of subsequent debugging and monitoring for long-term stable operation.

[0023] Even if it is easy to think of adding debugging and monitoring links based on existing technologies, it is difficult to achieve: in terms of debugging, it is necessary to record data on the execution process of a large number of component nodes in the intelligent application, and it is necessary to collect multi-dimensional data such as input parameters, output parameters, internal status, etc. of different components at different stages; the existing debugging only supports one-time running debugging, does not support single-step debugging and breakpoint debugging capabilities, and cannot fine-tune the input and output parameter information of component nodes. In terms of monitoring, real-time collection and analysis of the running status of the intelligent agent involves complex logging and performance indicator calculations. Furthermore, adding debugging and monitoring links may have an impact on the existing intelligent application orchestration architecture. Adding debugging and monitoring functions involves a lot of modifications to the original code, and requires redesigning interfaces and modules. It is difficult to ensure that the modified system can run stably.

[0024] It should be noted that the execution subject of this embodiment can be a device for constructing an intelligent agent application, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a processor, etc. that can realize the above functions. The following takes the device for constructing an intelligent agent application as an example to illustrate this embodiment and the following embodiments.

[0025] Based on this, the present application embodiment provides a method for constructing an intelligent agent application, referring to Figure 1 , Figure 1 A flowchart of an embodiment of a method for constructing an intelligent agent application of the present application.

[0026] In this embodiment, the method for constructing the intelligent agent application includes steps S10 to S30: Step S10, obtaining the intelligent agent to be debugged by arranging each component node and the process of each component node; In one embodiment, the intelligent agent application is orchestrated by dragging and dropping each component node on the canvas to quickly and flexibly adjust the process and components, configure the process component information, and obtain the intelligent agent to be debugged, wherein the intelligent agent application refers to various application programs developed using the intelligent agent.

[0027] In one embodiment, Figure 2 As shown, the component nodes include large models, knowledge bases, intelligent algorithms, event processing and script execution, as well as data conversion components, message queue components, application connector components, content security, and data cleaning.

[0028] Step S20, debugging each component node of the agent to be debugged to obtain a target agent; It should be noted that in addition to providing conventional choreography design, this application also takes into account the debugging operation after the intelligent agent design is completed; specifically, after the intelligent agent application choreography design is completed, the intelligent agent to be debugged is debugged to obtain the target intelligent agent. During debugging, it supports one-time debugging mode or single-step debugging mode, and can perform debugging on each component node one by one. Detailed log information and input and output parameter information of component nodes can be viewed during debugging. Figure 3 As shown, after the test parameters are passed in, you can choose the running mode, perform one-time running debugging or single-step debugging, and view the real-time log information and the input or output parameter information of the component node, namely the debugging log. Single-step debugging can provide breakpoint settings and can run to the next step or breakpoint position. At the same time, it also provides the functions of terminating debugging and re-debugging.

[0029] In one embodiment, in step S20, the method for constructing the intelligent agent application further includes steps A10 to A30: Step A10, debugging each component node of the debugged intelligent agent in turn according to a predetermined execution order; It should be noted that the order in which each component node is debugged is pre-set based on the design architecture and functional logic of the agent. According to its workflow, each component node is debugged in turn to ensure that each component functions normally in the entire agent application. This sequential debugging can ensure that each component is tested under the correct input conditions, avoiding interference with the debugging judgment of the subsequent components due to problems with the previous components.

[0030] In one embodiment, step A10 includes: When encountering a breakpoint set at a specified component node of the agent to be debugged, pausing execution at the breakpoint to check the running status and running parameters of the specified component node; During the breakpoint suspension period, when a running instruction to continue execution at the breakpoint is received, the subsequent component nodes are continued to be executed from the breakpoint.

[0031] It should be noted that a breakpoint is first set at the specified component node of the agent to be debugged. When the agent to be debugged reaches the breakpoint, it will pause execution to check the running status and running parameters of the specified component node. The running status includes the current activity status of the component (for example, whether it is waiting for input, whether it is in a busy calculation process), etc. The running parameters are the values ​​of various variables involved in the running process of this component, such as the value of the input data, the intermediate results generated in the internal calculation process, etc.

[0032] During the breakpoint suspension period, if a running instruction to continue execution at the breakpoint is received, the debugged agent will continue to execute subsequent component nodes from the breakpoint and check the running status and running parameters of the subsequent component nodes.

[0033] In this embodiment, a breakpoint is set at a specified component node and execution is paused. By checking the current state and parameter values, the agent is troubleshooted, which helps to troubleshoot problems step by step according to the logical order of the agent, making the debugging process more organized. After optimizing or modifying the agent, it can be easily tested again. By pausing and continuing execution at the same breakpoint, it can be quickly verified whether the previously discovered problems have been solved, and it will not affect the normal operation of the component nodes that have been tested, and the operation of the entire agent can be efficiently tested.

[0034] Step A20, recording the exceptions generated during the debugging process of each component node and generating a debugging log; It should be noted that when debugging each component node, due to the complexity of the component, the interaction with other components or the external environment, exceptions may occur. The exceptions may be program crashes, output results that do not meet expectations, running too slowly, etc. Record the relevant information when these exceptions occur in detail, such as the time when the exception occurred, the name of the component node, the input value of the component at that time, the error prompts that appeared, etc., and organize the exception records to obtain the debugging log.

[0035] Step A30, repair the abnormality of the agent to be debugged according to the debugging log to obtain the target agent.

[0036] It should be noted that the debug log records the abnormal conditions of each component node in detail. By analyzing these records, we can accurately find the component nodes with problems in the agent to be debugged, as well as the specific manifestations and possible causes of the problems; then we can fix these problems, such as modifying the algorithm parameters in the component, fixing the vulnerabilities in the code, adjusting the interaction logic between components, etc. When all the abnormalities found according to the debug log are fixed, the normally running agent to be debugged is the target agent.

[0037] In this embodiment, each component node is debugged in turn according to a predetermined execution order, and a debug log is generated, which can better follow the operation logic of the intelligent body, ensure that each component node of the entire intelligent body to be debugged is checked, and more accurately locate problems that occur during data transmission and processing, thereby improving the overall performance and reliability of the intelligent body. The logs generated during the entire debugging process and the repair operations based on the logs enhance the maintainability of the intelligent body. In the subsequent use process, if a problem occurs again, the debug log and repair method can be referred to to more efficiently solve the new problem.

[0038] Step S30, monitoring the target intelligent agent according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

[0039] It should be noted that the target agent's log information and the parameter information of each component node can be generated during debugging or during actual operation. Since the agent's operating environment may be complex and changeable, if the parameters of the component nodes exceed the normal range, the parameters can be adjusted in time; if the agent frequently encounters communication errors from the log, the network connection and other related factors can be checked to ensure that the agent can run continuously and stably and perform its due functions.

[0040] In this embodiment, when processing the intelligent agent application, a one-stop capability of design, debugging, and monitoring is provided, which not only includes the choreography design link, but also performs debugging operations and monitoring operations on each component node of the intelligent agent to be debugged. During the debugging process, each component node will be debugged, and detailed information during its execution will be recorded. When a problem occurs during the operation of the intelligent agent, the specific component node or operation step can be accurately located. By monitoring the target intelligent agent, using log information and parameter information of each component node, the operating status of the intelligent agent can be grasped from multiple dimensions. After the choreography design is completed, potential problems are eliminated through debugging, and stability during operation is guaranteed through monitoring, thereby improving the overall performance and operating efficiency of the intelligent agent application.

[0041] Based on the above embodiments of the present application, in another embodiment of the present application, the same or similar contents as those of the above embodiments can be referred to the above introduction and will not be repeated later.

[0042] In this embodiment, the method for constructing the intelligent agent application includes steps D10 to D30: Step D10, real-time collection of log information of the target agent during operation and parameter information of each component node in the target agent; It should be noted that the real-time collection of log information and parameter information is to be able to grasp the dynamic situation of the intelligent agent in a timely and accurate manner. The log information includes timestamps, operation records and event information, among which the timestamp records the specific time when each operation or event occurs, and is used to track the operation trajectory of the intelligent agent and the order of events. For example, the time when the intelligent agent starts to execute the task, the time when the task is completed, the start and end time of each subtask, the specific measures taken when abnormal events occur, etc.; the operation record is the specific operation performed by the intelligent agent, such as which functions are called, which data processing is performed, which external services are called, etc.; event information includes interaction events with other systems or services, events caused by user operations, etc. For example, Figure 4As shown, the log information may also include the total number of runs, the number of successes, the number of failures, and the number of errors. The parameter information of each component node includes input parameters and output parameters, such as input parameters may be input data received by each component node, and output parameters may be output results after the component node completes the operation.

[0043] In one embodiment, after step D10, the following steps are included: According to the log information and parameter information, the abnormality prediction of the running state of the intelligent agent is carried out through the preset abnormality prediction model to obtain the target time period when the abnormality will occur; During the target period, take preventive measures in advance to deal with abnormalities that will occur.

[0044] It should be noted that after the anomaly prediction model analyzes and infers the input log information and parameter information, it obtains the target period when the anomaly will occur, where the target period can be a time interval or the running stage of the agent (such as the number of task execution cycles). Preventive measures are taken before the target period when the anomaly is predicted to occur. Preventive measures can include: adjusting the parameters of the agent, increasing resources, temporarily repairing or replacing components of the agent that may fail, etc.

[0045] In one embodiment, before the step of predicting the abnormality of the running state of the agent by using a preset abnormality prediction model according to the log information and parameter information and obtaining the target time period in which the abnormality will occur, the method includes: Based on historical log information, historical parameter information and historical anomaly periods, a prediction model for anomaly prediction is trained.

[0046] It should be noted that a prediction model for anomaly prediction is constructed based on historical log information, historical parameter information and historical time periods of historical anomalies; during the training process, the prediction model will find out the intrinsic relationship between historical log information, historical parameter information and the corresponding historical time periods of historical anomalies, so that it can predict the time period when the intelligent agent will have anomalies in the future based on the current log information and parameter information, so that preventive measures such as adjusting its own parameters can be taken in advance.

[0047] In this embodiment, by predicting the target time period when anomalies will occur and taking preventive measures in advance, it helps to ensure the normal operation of various functions of the intelligent body, reduce the need for emergency repairs, and make the operation of the intelligent body more reliable.

[0048] Step D20, calculating the performance index of the target agent according to the log information and parameter information and referring to the preset calculation rules; It should be noted that the performance indicators of the target intelligent agent may be one or more of the average response time, the task completion rate and the output result accuracy, wherein the average response time calculation rule may be: divide the total time for the intelligent agent to complete a set of tasks by the number of tasks (obtained based on the log information and parameter information) to obtain the average response time of each task; the task completion rate calculation rule may be: calculate the ratio of the number of successfully completed tasks to the total number of tasks (obtained based on the log information and parameter information); the output result accuracy calculation rule may be: calculate the accuracy based on its output results (obtained based on the log information and parameter information) and the expected results (pre-given results). For example, in an image recognition intelligent agent, the accuracy indicator is obtained by dividing the number of correctly recognized images (i.e., the number of output results that match the expected results) by the total number of recognized images.

[0049] As described above, in this embodiment, there is no limitation on the method of obtaining, for example, the total time for an agent to complete a set of tasks divided by the number of tasks, the number of successfully completed tasks and the total number of tasks based on log information and parameter information.

[0050] Step D30, when it is detected that the performance indicator exceeds the preset indicator range, the alarm mechanism is triggered and an abnormal notification is sent.

[0051] It should be noted that when the calculated performance index exceeds the preset range, the alarm mechanism is triggered and an abnormal notification is sent. For example, when the average response time exceeds 3 seconds, the alarm mechanism is triggered and an abnormal notification is sent.

[0052] In this embodiment, by collecting the log information of the target intelligent agent during operation and the parameter information of each component node in real time, comprehensive monitoring of the intelligent agent can be achieved, and then the performance indicators of the target intelligent agent are calculated based on the collected log information and parameter information and with reference to preset calculation rules. This allows the performance of the intelligent agent to be quantified, and the operating effect of the intelligent agent can be intuitively understood, which helps to accurately locate the abnormal components of the intelligent agent, trigger the alarm mechanism and send abnormal notifications, thereby achieving a rapid response to abnormal situations and making the operation of the intelligent agent more stable.

[0053] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the method for constructing the intelligent application of the present application. More forms of simple transformations based on this technical concept, such as the interaction and combination of various embodiments, are all within the scope of protection of the present application.

[0054] This application also provides a device for constructing an intelligent agent application, please refer to Figure 5 , the construction device of the intelligent agent application includes: The orchestration module 10 is used to obtain the intelligent agent to be debugged by orchestrating each component node and the process of each component node; The debugging module 20 is used to debug each component node of the agent to be debugged to obtain a target agent; The monitoring module 30 is used to monitor the target intelligent agent according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

[0055] Optionally, the debugging module 20 is further used to debug each component node of the agent to be debugged in sequence according to a predetermined execution order; Record the exceptions generated during the debugging process of each component node and generate a debugging log; The abnormality of the agent to be debugged is repaired according to the debugging log to obtain the target agent.

[0056] Optionally, the debugging module 20 is further configured to, when encountering a breakpoint set at a specified component node of the agent to be debugged, suspend execution at the breakpoint to check the operating state and operating parameters of the specified component node; During the period when the execution is suspended at the breakpoint, when a running instruction to continue the execution at the breakpoint is received, the subsequent component nodes are continued to be executed from the breakpoint.

[0057] Optionally, the monitoring module 30 is further used to collect log information of the target agent during operation and parameter information of each component node in the target agent in real time; Calculating the performance index of the target agent according to the log information and the parameter information and referring to the preset calculation rules; When it is detected that the performance indicator exceeds the preset indicator range, an alarm mechanism is triggered and an abnormal notification is sent.

[0058] Optionally, the monitoring module 30 is further used to perform abnormal prediction on the running state of the intelligent body through a preset abnormal prediction model according to the log information and the parameter information, and obtain a target time period in which the abnormality will occur; During the target period, preventive measures are taken in advance to deal with abnormalities that will occur.

[0059] Optionally, the monitoring module 30 is further used to train a prediction model for abnormality prediction based on historical log information, historical parameter information and historical time periods of historical abnormalities.

[0060] The construction device of the intelligent agent application provided by the present application adopts the construction method of the intelligent agent application in the above embodiment, which can solve the technical problem that the intelligent agent application designed by the arrangement cannot run stably and efficiently. Compared with the prior art, the beneficial effects of the construction device of the intelligent agent application provided by the present application are the same as the beneficial effects of the construction method of the intelligent agent application provided by the above embodiment, and the other technical features in the construction device of the intelligent agent application are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0061] The present application provides a device for constructing an intelligent agent application, the device for constructing an intelligent agent application includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for constructing the intelligent agent application in the first embodiment described above.

[0062] Reference below Figure 6 , which shows a schematic diagram of the structure of a device for constructing an intelligent agent application suitable for implementing the embodiment of the present application. The device for constructing an intelligent agent application in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The construction device of the intelligent agent application shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0063] like Figure 6As shown, the construction device of the intelligent agent application may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the construction device of the intelligent agent application are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the construction device of the intelligent agent application to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows the construction device of the intelligent agent application with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0064] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0065] The construction device of the intelligent agent application provided by the present application adopts the construction method of the intelligent agent application in the above embodiment, which can solve the technical problem that the intelligent agent application designed by the arrangement cannot run stably and efficiently. Compared with the prior art, the beneficial effects of the construction device of the intelligent agent application provided by the present application are the same as the beneficial effects of the construction method of the intelligent agent application provided by the above embodiment, and the other technical features in the construction device of the intelligent agent application are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0066] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0067] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0068] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the method for constructing an intelligent agent application in the above-mentioned embodiment.

[0069] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0070] The computer-readable storage medium mentioned above may be included in the construction device of the intelligent agent application; or may exist independently without being assembled into the construction device of the intelligent agent application.

[0071] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the construction device of the intelligent agent application, the construction device of the intelligent agent application: arranges each component node and the process of each component node to obtain the intelligent agent to be debugged; Debugging each component node of the agent to be debugged to obtain a target agent; The target intelligent agent is monitored according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

[0072] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0073] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0074] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0075] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned method for constructing an intelligent agent application, and can solve the technical problem that the intelligent agent application designed by the arrangement cannot run stably and efficiently. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the method for constructing an intelligent agent application provided by the above-mentioned embodiment, and will not be repeated here.

[0076] The present application also provides a computer program product, including a computer program, which implements the steps of the method for constructing an intelligent agent application as described above when executed by a processor.

[0077] The computer program product provided by this application can solve the technical problem that the intelligent agent application designed by the arrangement cannot run stably and efficiently. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the method for constructing the intelligent agent application provided by the above embodiment, which will not be repeated here.

[0078] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for constructing an intelligent agent application, characterized in that: The method comprises: By arranging each component node and the process of each component node, the intelligent agent to be debugged is obtained; Debugging each component node of the agent to be debugged to obtain a target agent; The target intelligent agent is monitored according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

2. The method for constructing an intelligent agent application as claimed in claim 1, characterized in that: The step of debugging each component node of the agent to be debugged to obtain the target agent includes: Debugging each component node of the agent to be debugged in sequence according to a predetermined execution order; Record the exceptions generated during the debugging process of each component node and generate a debugging log; The abnormality of the agent to be debugged is repaired according to the debugging log to obtain the target agent.

3. The method for constructing an intelligent agent application as claimed in claim 2, characterized in that: The step of debugging the component nodes of the agent to be debugged in sequence according to a predetermined execution order comprises: When encountering a breakpoint set at a designated component node of the agent to be debugged, pausing execution at the breakpoint to check the running state and running parameters of the designated component node; During the period when the execution is suspended at the breakpoint, when a running instruction to continue the execution at the breakpoint is received, the subsequent component nodes are continued to be executed from the breakpoint.

4. The method for constructing an intelligent agent application as claimed in claim 1, characterized in that: The step of monitoring the target intelligent agent according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent includes: Collecting log information of the target agent during operation and parameter information of each component node in the target agent in real time; Calculating the performance index of the target agent according to the log information and the parameter information and referring to the preset calculation rules; When it is detected that the performance indicator exceeds the preset indicator range, an alarm mechanism is triggered and an abnormal notification is sent.

5. The method for constructing an intelligent agent application as claimed in claim 4, characterized in that: After the step of collecting the log information of the target agent during operation and the parameter information of each component node in the target agent in real time, the method further includes: According to the log information and the parameter information, an abnormality prediction is performed on the running state of the intelligent agent through a preset abnormality prediction model to obtain a target time period in which the abnormality will occur; During the target period, preventive measures are taken in advance to deal with abnormalities that will occur.

6. The method for constructing an intelligent agent application as claimed in claim 5, characterized in that: Before the step of predicting the abnormality of the running state of the intelligent agent by a preset abnormality prediction model according to the log information and the parameter information to obtain the target time period in which the abnormality will occur, the method includes: Based on the historical log information, historical parameter information and historical anomaly periods, a prediction model for anomaly prediction is trained.

7. A device for constructing an intelligent agent application, characterized in that: The constructing device of the intelligent agent application comprises: The orchestration module is used to obtain the intelligent agent to be debugged by orchestrating each component node and the process of each component node; A debugging module, used to debug each component node of the agent to be debugged to obtain a target agent; The monitoring module is used to monitor the target intelligent agent according to the log information of the target intelligent agent and the parameter information of each component node to ensure the operation of the target intelligent agent.

8. A device for constructing an intelligent agent application, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for constructing an intelligent agent application as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for constructing an intelligent agent application as described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the method for constructing an intelligent agent application as claimed in any one of claims 1 to 6 are implemented.

Images