Large model search engine method and device for processing computer tasks
By designing a large model search engine method, the search system automatically combines the task model, which solves the problem that existing search engines cannot directly solve complex computer tasks, and achieve fast and efficient task processing.
Patent Information
- Application Number
- CN202411387086.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-30
- Publication Date
- 2025-01-28
AI Technical Summary
Existing search engines cannot directly help users solve complex computer tasks or problems, and can only provide solutions.
A large model search engine method is designed to define the basic task model of the computer and establish a search system described by the matching problem. Users can search the system to search the system to automatically combine the task model to solve the problem.
When users encounter complex computer tasks or problems, they can quickly handle them without their own hands, which improves the efficiency of searching and solving problems.
Smart Images
Figure CN119377474A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of computer technology, and more specifically, to a large model search engine method and device for processing computer tasks. Background Art
[0002] The development of search engines began in the early days of the Internet. As the content of the web exploded, the need to effectively manage this information increased. In the early 1990s, systems such as Archie, Gopher, and WAIS began to appear, but they were mainly based on directory or file name searches. By the mid-1990s, with the popularity of web browsers, web content-based search engines such as Yahoo!, AltaVista, and Lycos came out one after another. After entering the 21st century, search engine technology has made significant progress. Google stands out with its unique PageRank algorithm, which measures the importance of web pages based on the link relationship between web pages. In addition, search engines have begun to incorporate more artificial intelligence technologies, such as natural language processing, to better understand and respond to user query intent.
[0003] Search engines can help us find solutions to problems quickly, but so far famous search engines at home and abroad such as Google Search, Yahoo Search, Baidu Search, etc. cannot help users directly solve problems. Even the new generation of text generation search engines such as Chatgpt, Gemini, Copilot, etc. can only provide solutions to problems when encountering computer problems but cannot directly help users solve problems. Summary of the invention
[0004] In response to at least one defect or improvement need in the prior art, the present invention provides a large model search engine method and device for processing computer tasks, which solves the problem that existing search engines can only provide solutions to problems but cannot directly solve specific user problems. When users encounter complex computer tasks or problems, they can handle complex computer tasks and problems conveniently and quickly without having to do it themselves, thereby achieving high efficiency in searching for problems and solving problems.
[0005] To achieve the above-mentioned purpose, according to the first aspect of the present invention, a large model search engine method for processing computer tasks is provided, the method comprising: defining a basic computer task model, wherein the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation; establishing a search system for retrieving matching problem descriptions, wherein the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model; when the task problem description matching the target problem description is retrieved in the search system, determining the entered task model, wherein the task model consists of input parameters, the processing task model and output parameters; after receiving a confirmation execution instruction, executing the task model to automatically complete the task.
[0006] In an exemplary embodiment, the establishing of a search system for retrieving matching problem descriptions includes: entering the task problem description and the associated problem solution into the search system; and entering the processing task model associated with the task problem description into the search system.
[0007] In an exemplary embodiment, after establishing a search system for retrieving matching problem descriptions, the method further includes: upon receiving the input target problem description, performing retrieval matching in the search system; determining at least one task problem description in the search system that matches the target problem description; and determining the task problem description that has the highest degree of matching with the target problem description among at least one task problem description.
[0008] In an exemplary embodiment, after determining the task problem description that has the highest degree of match with the target problem description in at least one of the task problem descriptions, the method further includes: outputting at least one of the processing task models associated with the task problem description; and selecting and determining one of the processing task models from the at least one processing task model for executing the task.
[0009] In an exemplary embodiment, when the task problem description matching the target problem description is retrieved in the search system, determining the task model to be entered includes: when the problem answer corresponding to the task problem description includes multiple solution steps, determining the task model corresponding to each of the multiple solution steps to obtain multiple task models; and entering the multiple task models into the retrieval system.
[0010] In an exemplary embodiment, after entering the plurality of task models into the retrieval system, the method further includes: pausing execution of the task model when inputting parameters until completion of the input parameters is detected and the task model is re-executed; and after the task model is executed to automatically complete the task, evaluating the task execution result.
[0011] In an exemplary embodiment, the method further includes: executing the plurality of task models in an order corresponding to the plurality of solution steps, and issuing an execution exception prompt when one of the plurality of task models fails to execute, wherein the execution exception prompt is used to prompt manual execution or terminate execution.
[0012] According to the second aspect of the present invention, there is also provided a large model search engine device for processing computer tasks, comprising: a definition unit, for defining a basic computer task model, wherein the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation; an establishment unit, for establishing a search system for retrieving matching problem descriptions, wherein the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model; an entry unit, for determining an entered task model when the task problem description matching the target problem description is retrieved in the search system, wherein the task model consists of input parameters, the processing task model and output parameters; a first execution unit, for executing the task model to automatically complete the task after receiving a confirmation execution instruction.
[0013] According to a third aspect of the present invention, there is also provided a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the above-mentioned large model search engine method for processing computer tasks when running.
[0014] According to a fourth aspect of the present invention, there is also provided an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the large model search engine method for processing computer tasks through the computer program.
[0015] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:
[0016] (1) The present invention provides a large model search engine method for processing computer tasks, which defines multiple computer task models and establishes a search system. When a user searches for a problem through the search system, the search system can help the user directly solve the problem by finding and freely combining the established task models. By establishing a computer task model, when a user encounters a complex computer task or problem, the user can conveniently and quickly handle the complex computer tasks and problems without having to do it himself.
[0017] (2) By adopting a large model search engine method for processing computer tasks provided by the present invention, task models can be freely combined as basic task units to implement more complex computer tasks and solve more complex computer problems. After a large number of task models are entered, when processing a computer task, the task models will be freely combined in the black box based on the input parameters and output parameters to provide the user with the most effective processing model. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0019] Figure 1 A schematic flow chart of an optional large model search engine method for processing computer tasks provided in an embodiment of the present application;
[0020] Figure 2 A schematic diagram of the structure of an optional large model search engine device for processing computer tasks provided in an embodiment of the present application;
[0021] Figure 3 A schematic diagram of the structure of an optional electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0022] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.
[0023] The terms "first", "second", "third", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.
[0024] According to one aspect of the embodiments of the present application, a large model search engine method for processing computer tasks is provided. Figure 1 The invention describes a large model search engine method for processing computer tasks provided by an embodiment of the present application.
[0025] Figure 1 is a flow chart of an optional large model search engine method for processing computer tasks provided by an embodiment of the present application, such as Figure 1 As shown, the process of the method may include the following steps:
[0026] S102, defining a basic computer task model, wherein the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation;
[0027] S104, establishing a search system for retrieving matching problem descriptions, wherein the search system stores a matching relationship between the task problem description and the target problem description, and the task problem description is associated with a processing task model;
[0028] S106, when a task problem description matching the target problem description is retrieved in the search system, determining an entered task model, wherein the task model is composed of input parameters, a processing task model, and output parameters;
[0029] S108, after receiving the confirmation execution instruction, executing the task model to automatically complete the task.
[0030] The embodiment of the present application provides a large model search engine method for processing computer tasks, which can be used to collect a large amount of text data, train the text data to obtain a training model, and then use the training model to detect the text to be detected to obtain the detection results and feed them back to the user.
[0031] Optionally, multiple computer task models can be defined first and a search system can be established. The system can input problems and their corresponding solutions, and when a user makes a query, a matching task model can be provided for the user to select and execute. When a user searches for a problem through the search system, the search system can help the user directly solve the problem by finding and freely combining the established task models. By establishing a computer task model, when a user encounters a complex computer task or problem, he or she can easily and quickly handle complex computer tasks and problems without having to do it himself or herself.
[0032] Furthermore, a basic task model of a computer can be defined, and the basic task model can include mouse operations (e.g., left click, right click, scroll, etc.) and keyboard operations (e.g., press, single click, double click, etc.). A search system for retrieving matching problem descriptions is provided, and the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model. In the initial stage, the search system can enter questions and provide answers, including the problem description, the problem answer, and the problem processing task model. When a user uses the search system to search for a problem, the search system can retrieve and match the user's problem description with the problem that has been entered into the system, and provide the best processing task model for the user to choose. After the user selects the task model, he can choose to execute the task model with one click, which automatically helps the user solve computer problems or process computer tasks.
[0033] When a task problem description matching the target problem description is retrieved in the search system, it is necessary to determine the entered task model. Here, the task model can be composed of input parameters, processing task models, and output parameters. After receiving the confirmation execution instruction, the task model can be executed to automatically complete the task. For example, execute left click of mouse -> input user name on keyboard -> click enter on keyboard -> input password on keyboard -> left click of mouse, and automatically complete the task by simulating the user interface operation.
[0034] Through the above steps S102 to S108, by defining the basic computer task model, the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation; a search system for retrieving matching problem descriptions is established, wherein the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model; when the task problem description matching the target problem description is retrieved in the search system, the entered task model is determined, wherein the task model is composed of input parameters, a processing task model and output parameters; after receiving the confirmation execution instruction, the task model is executed to automatically complete the task, so that when the user encounters complex computer tasks or problems, the user can easily and quickly handle complex computer tasks and problems without having to do it by himself, thereby achieving high efficiency in searching and solving problems.
[0035] In one exemplary embodiment, establishing a search system for retrieving matching problem descriptions includes:
[0036] S11, entering the task problem description and the associated problem solution into the search system;
[0037] S12, entering the processing task model associated with the task problem description into the search system.
[0038] In an embodiment of the present application, when establishing a search system for retrieving matching problem descriptions, the task problem description and the associated problem answers can be entered into the search system in the initial stage, and the processing task model associated with the task problem description can be entered into the search system.
[0039] For example, the input problem description may be: How do I change the resolution of my computer? The problem answer associated with the problem description may be: Open Settings -> Display Settings -> Change Resolution. The processing task model corresponding to the answer question may include a series of subtask models, that is, a series of basic task models.
[0040] Through this embodiment, when solving more complex computer problems, after entering a large number of task models, when processing a computer task, the task models will be freely combined in the black box according to the input parameters and output parameters to provide the user with the most effective processing model.
[0041] In an exemplary embodiment, after establishing a search system for retrieving matching problem descriptions, the method further includes:
[0042] S21, upon receiving the input target problem description, performing retrieval matching in the search system;
[0043] S22, determining at least one task problem description matching the target problem description in the search system;
[0044] S23, determining a task problem description that has the highest matching degree with the target problem description in at least one task problem description.
[0045] In the embodiment of the present application, after defining the basic computer task model, a search system can be established. When the user searches for a problem, the system searches and matches the user's problem description with the problems entered into the system, and provides the best processing task model for the user to choose. After the user selects the task model, he can choose to execute the task model with one click, automatically helping the user solve computer problems or process computer tasks.
[0046] First, you can define basic mouse and keyboard actions that will become the basis for building more complex tasks, including:
[0047] LEFT_CLICK(x,y): Left click on the coordinates (x,y) on the screen.
[0048] RIGHT_CLICK(x,y): Right click on the coordinates (x,y) on the screen.
[0049] SCROLL_UP(n): Scroll up n times.
[0050] SCROLL_DOWN(n): Scroll down n times.
[0051] KEY_PRESS(key): Press the specified key key.
[0052] TYPE_TEXT(text): Input text text.
[0053] DOUBLE_CLICK(x,y): Double-click at coordinates (x,y).
[0054] SCREENSHOT(): Get a screenshot of the current screen.
[0055] SCREENSHOT_COMPARE(s1,s2): Screen shot comparison.
[0056] After the definition is completed, a search system can be established and provided, which can include: entering problems and solutions. The problem description here can be: How do I change the resolution of my computer? The problem solution can be: Open Settings->Display Settings->Change Resolution, and enter a problem handling task model including a series of subtask models. Then, the problem search can be performed. When the user searches for something like "How do I change the resolution of my computer", the system will match the problem description with the entered problem, find the most relevant solution, and provide it to the user. The user can choose "One-click Execution", and the system will automatically execute the task model.
[0057] In an exemplary embodiment, after determining the task problem description with the highest matching degree with the target problem description in at least one task problem description, the method further includes:
[0058] S31, outputting at least one processing task model associated with the task problem description;
[0059] S32, selecting and determining a processing task model from at least one processing task model for executing the task.
[0060] In the embodiment of the present application, during the execution of a task model, when the user selects to execute a task model, the system can simulate mouse and keyboard events according to a defined operation sequence to execute each task model.
[0061] When the user searches for a problem or task, the system will output the solution steps of the problem or task after searching and matching the problem, and provide a task model for the user to choose to execute. When the task model is executed, the same operation is performed according to the entered mouse and keyboard operation sequence.
[0062] In an exemplary embodiment, when a task problem description matching the target problem description is retrieved in the search system, determining the entered task model includes:
[0063] S41, when the problem solution corresponding to the task problem description includes multiple solution steps, determining a task model corresponding to each of the multiple solution steps to obtain multiple task models;
[0064] S42, entering multiple task models into the retrieval system.
[0065] In an embodiment of the present application, when entering questions and answers, there may be n steps to solve a problem, and a task model is established for each step. The task model consists of input parameters, a combination of basic task models, and output parameters. It should be noted that the input parameters here are used to provide the parameters required for the execution of the basic task model (such as the user name and password of the task model for logging into the website; the application name of the task model for opening the program). The basic task model combination is a combination of mouse and keyboard operations (such as left click of the mouse -> keyboard input of the user name -> keyboard single click of enter -> keyboard input of the password -> left click of the mouse). The output parameters are the basis for judging whether a task model is successfully executed or as the input of the next task model (such as screenshots, screen prompts).
[0066] Specifically, question answering can be split into multiple task models, including:
[0067] 1. Open Settings
[0068] Input parameters: None
[0069] Basic task model combination:
[0070] KEY_PRESS('win') (Press the Windows key)
[0071] TYPE_TEXT('settings')
[0072] KEY_PRESS('enter')
[0073] settings_window_opened=SCREENSHOT()
[0074] Output parameter: settings_window_opened (check if the settings window is open)
[0075] 2. Open Display Settings
[0076] Input parameters: None
[0077] Basic task model combination:
[0078] SCROLL_DOWN(3)
[0079] LEFT_CLICK(200,300) (Click the display settings button)
[0080] display_settings_opened=SCREENSHOT()
[0081] Output parameter: display_settings_opened (checks whether the display settings window is open)
[0082] 3. Change the resolution
[0083] Input parameter: resolution (e.g. "1920x1080")
[0084] Basic task model combination:
[0085] LEFT_CLICK(400,500) (Click the resolution drop-down menu)
[0086] TYPE_TEXT(resolution)
[0087] KEY_PRESS('down')
[0088] KEY_PRESS('enter')
[0089] resolution_changed=SCREENSHOT()
[0090] Output parameter: resolution_changed (checks if the resolution has changed).
[0091] In an exemplary embodiment, after entering the plurality of task models into the retrieval system, the method further includes:
[0092] S51, pausing the execution of the task model when inputting parameters, until it is detected that the input parameters are completed and then re-executing the task model;
[0093] S52, after the execution task model automatically completes the task, the task execution result is evaluated.
[0094] In an embodiment of the present application, when the task model is executed, the same operation can be performed according to the recorded mouse and keyboard operation sequence. During this period, if a task model requires input of parameters, the task model will suspend execution until it detects that the user has entered the parameters and can continue execution. After execution is completed, the execution correctness is automatically evaluated (comparing the screenshot of the entered task model with the screenshot of the user executing the task model).
[0095] Specifically, when the user selects to execute a task model, the system will simulate mouse and keyboard events according to the defined operation sequence to execute each task model. For example:
[0096] Open Settings
[0097] ①Press the Windows key.
[0098] KEY_PRESS('win')
[0099] ②Enter “Settings”.
[0100] TYPE_TEXT('settings')
[0101] ③Press the Enter key.
[0102] KEY_PRESS('enter')
[0103] ④The system checks whether the settings window is open.
[0104] SCREENSHOT_COMPARE(settings_window_opened,SCREENSHOT())
[0105] Open Display Settings
[0106] SCROLL_DOWN(3)
[0107] LEFT_CLICK(200,300) (Click the display settings button)
[0108] ①Scroll down three times.
[0109] SCROLL_DOWN(3)
[0110] ②Click the Display Settings button.
[0111] LEFT_CLICK(200,300)
[0112] ③The system checks whether the display settings window is open.
[0113] SCREENSHOT_COMPARE(display_settings_opened,SCREENSHOT())
[0114] Change the resolution
[0115] ①Click the Resolution drop-down menu.
[0116] LEFT_CLICK(400,500)
[0117] ②Enter the new resolution.
[0118] TYPE_TEXT(resolution)
[0119] ③ Use the keyboard to select the appropriate resolution.
[0120] KEY_PRESS('down')
[0121] ④Press the Enter key to confirm your selection.
[0122] KEY_PRESS('enter')
[0123] ⑤The system checks whether the resolution has been changed.
[0124] SCREENSHOT_COMPARE(resolution_changed,SCREENSHOT())
[0125] If the user needs to confirm certain operations during execution (such as a dialog box to confirm changing the resolution), the system will pause execution and wait for user confirmation before continuing.
[0126] In an exemplary embodiment, the method further comprises:
[0127] S61, executing multiple task models in the order corresponding to the multiple solution steps, and issuing an execution exception prompt when one of the multiple task models fails to execute, wherein the execution exception prompt is used to prompt manual execution or termination of execution.
[0128] In an embodiment of the present application, when a user searches for a problem or task, the system will output the solution steps for the problem or task after searching and matching the problem, and provide a task model for the user to choose to execute, and simulate mouse and keyboard operations to execute the task model.
[0129] Optionally, the task model can provide a learning optimization mechanism. If a task includes n steps, then there will be n corresponding task models. The task models are executed in sequence. When any task model fails to execute, the user will be prompted to execute manually or terminate. If the user executes manually and clicks Continue, the program will continue to execute subsequent task models until the execution is completely successful. At the same time, the task model will be learned and updated according to the keyboard and mouse sequence manually executed by the user.
[0130] For example, if a task model fails to execute, the system will prompt the user to complete the task manually. After the user completes the task manually, he can click "Continue" and the system will continue to execute the subsequent task model. At the same time, the system will record the user's manual operation and add it to the corresponding task model for future optimization. If the user needs to confirm a dialog box to continue to change the resolution, the system will record this step and automatically handle similar confirmation operations in the future. Optionally, as a basic task unit, the task model can be freely combined to achieve more complex computer tasks and solve more complex computer problems as long as the output of one task model is consistent with the output of another task. After a large number of task models are entered, when processing a computer task, the task model will be freely combined in the black box based on the input parameters and output parameters to provide the user with the most effective processing model. Task models can be freely combined to solve more complex computer problems. For example, after changing the resolution, the user may need to adjust other display settings, which can be achieved by combining multiple task models.
[0131] According to another aspect of the embodiments of the present application, a large model search engine method and a large model search engine device for implementing the above-mentioned large model search engine for processing computer tasks are also provided. Figure 2 is a schematic diagram of the structure of an optional large model search engine device for processing computer tasks according to an embodiment of the present application, such as Figure 2 As shown, the device may include:
[0132] A definition unit 202 is used to define a basic computer task model, wherein the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation;
[0133] An establishing unit 204 is used to establish a search system for retrieving matching problem descriptions, wherein the search system stores a matching relationship between a task problem description and a target problem description, and the task problem description is associated with the processing task model;
[0134] An input unit 206 is used to determine an input task model when the task problem description matching the target problem description is retrieved in the search system, wherein the task model is composed of input parameters, the processing task model and output parameters;
[0135] The first execution unit 208 is used to execute the task model to automatically complete the task after receiving the confirmation execution instruction.
[0136] It should be noted that the definition unit 202 in this embodiment can be used to execute the above step S102, the establishment unit 204 in this embodiment can be used to execute the above step S104, the entry unit 206 in this embodiment can be used to execute the above step S106, and the first execution unit 208 in this embodiment can be used to execute the above step S108.
[0137] Through the above modules, by defining the basic computer task model, the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation; a search system for retrieving matching problem descriptions is established, wherein the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model; when a task problem description matching the target problem description is retrieved in the search system, the entered task model is determined, wherein the task model is composed of input parameters, a processing task model and output parameters; after receiving the confirmation execution instruction, the execution task model automatically completes the task, so that when the user encounters complex computer tasks or problems, he can easily and quickly handle complex computer tasks and problems without having to do it himself, and achieves high efficiency in searching and solving problems.
[0138] In an exemplary embodiment, the establishing unit includes:
[0139] A first input module, used for inputting the task problem description and the associated problem answer into the search system;
[0140] The second input module is used to input the processing task model associated with the task problem description into the search system.
[0141] In an exemplary embodiment, the apparatus further comprises:
[0142] A retrieval matching unit, configured to perform retrieval matching in the search system upon receiving the input target problem description;
[0143] A first determining unit, configured to determine at least one task problem description in the search system that matches the target problem description;
[0144] The second determining unit is used to determine the task problem description that has the highest matching degree with the target problem description among at least one of the task problem descriptions.
[0145] In an exemplary embodiment, the apparatus further comprises:
[0146] An output unit, configured to output at least one of the processing task models associated with the task problem description;
[0147] A selection unit is used to select and determine a processing task model from at least one of the processing task models for executing the task.
[0148] In an exemplary embodiment, the input unit comprises:
[0149] A determination module, configured to determine the task model corresponding to each of the multiple solution steps, to obtain multiple task models, when the problem solution corresponding to the task problem description includes multiple solution steps;
[0150] The third input module is used to input the plurality of task models into the retrieval system.
[0151] In an exemplary embodiment, the apparatus further comprises:
[0152] A second execution unit, used for suspending the execution of the task model when inputting parameters, and re-executing the task model after detecting that the input parameters are completed;
[0153] After executing the task model to automatically complete the task, the evaluation unit evaluates the task execution result.
[0154] In an exemplary embodiment, the apparatus further comprises:
[0155] A prompt unit is used to execute the multiple task models in the order corresponding to the multiple solution steps, and issue an execution exception prompt when one of the multiple task models fails to execute, wherein the execution exception prompt is used to prompt manual execution or termination of execution.
[0156] It should be noted here that the examples and scenarios implemented by the above-mentioned modules and corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned embodiments. It should be noted that the above-mentioned modules as part of the device can run in a hardware environment and can be implemented by software or hardware, wherein the hardware environment includes a network environment.
[0157] According to another aspect of the embodiment of the present application, a storage medium is also provided. Optionally, in this embodiment, the storage medium can be used to execute the program code of any of the above-mentioned large model search engine methods for processing computer tasks in the embodiment of the present application.
[0158] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps:
[0159] S1, define the basic task model of the computer. The basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation.
[0160] S2, establishing a search system for retrieving matching problem descriptions, wherein the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model.
[0161] S3, when a task problem description matching the target problem description is retrieved in the search system, an input task model is determined, wherein the task model is composed of input parameters, a processing task model, and output parameters.
[0162] S4, after receiving the confirmation execution instruction, the execution task model automatically completes the task.
[0163] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, which will not be described in detail in this embodiment.
[0164] Among them, computer-readable storage media may include, but are not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.
[0165] According to another aspect of the embodiments of the present application, an electronic device for implementing the above-mentioned large model search engine method for processing computer tasks is also provided. The electronic device can be a server, a terminal, or a combination thereof.
[0166] Figure 3 is a schematic diagram of the structure of an optional electronic device according to an embodiment of the present application, such as Figure 3 As shown, it includes a processor 302, a communication interface 304, a memory 306 and a communication bus 308, wherein the processor 302, the communication interface 304, and the memory 306 communicate with each other through the communication bus 308, wherein:
[0167] Memory 306, used for storing computer programs;
[0168] The processor 302 is used to implement the following steps when executing the computer program stored in the memory 306:
[0169] S1, define the basic task model of the computer. The basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation.
[0170] S2, establishing a search system for retrieving matching problem descriptions, wherein the search system saves the matching relationship between the task problem description and the target problem description, and the task problem description is associated with the processing task model.
[0171] S3, when a task problem description matching the target problem description is retrieved in the search system, an input task model is determined, wherein the task model is composed of input parameters, a processing task model, and output parameters.
[0172] S4, after receiving the confirmation execution instruction, the execution task model automatically completes the task.
[0173] Optionally, the communication bus may be a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The communication interface is used for communication between the electronic device and other devices.
[0174] The memory may include RAM, or may include nonvolatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.
[0175] As an example, the memory 306 may include, but is not limited to, the definition unit 202, the establishment unit 204, the input unit 206, and the first execution unit 208 in the large model search engine device for processing computer tasks. In addition, it may also include, but is not limited to, other module units in the large model search engine device for processing computer tasks, which will not be repeated in this example.
[0176] The above-mentioned processor can be a general-purpose processor, which can include but not be limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be DSP (Digital Signal Processing), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
[0177] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.
[0178] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.
[0179] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0180] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.
[0181] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0182] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0183] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program code.
[0184] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.
[0185] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of the implementation scheme of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.
[0186] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0187] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A large model search engine method for processing computer tasks, characterized in that: include: Define a computer basic task model, wherein the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation; Establishing a search system for retrieving matching problem descriptions, wherein the search system stores a matching relationship between a task problem description and a target problem description, wherein the task problem description is associated with the processing task model; In the case where the task problem description matching the target problem description is retrieved in the search system, determining an entered task model, wherein the task model is composed of input parameters, the processing task model, and output parameters; After receiving the confirmation execution instruction, the task model is executed to automatically complete the task.
2. The large model search engine method for processing computer tasks according to claim 1, characterized in that: The establishment of a search system for retrieving matching problem descriptions includes: Entering the task problem description and the associated problem answer into the search system; The processing task model associated with the task problem description is entered into the search system.
3. The large model search engine method for processing computer tasks as claimed in claim 1, characterized in that: After establishing the search system for retrieving matching problem descriptions, the method further includes: Upon receiving the input target problem description, performing retrieval matching in the search system; Determining at least one of the task problem descriptions in the search system that matches the target problem description; Determine the task problem description that has the highest matching degree with the target problem description among at least one of the task problem descriptions.
4. The large model search engine method for processing computer tasks as claimed in claim 3, characterized in that: After determining the task problem description having the highest matching degree with the target problem description among at least one of the task problem descriptions, the method further includes: Outputting at least one of the processing task models associated with the task problem description; A processing task model is selected from at least one of the processing task models to be used for executing the task.
5. The large model search engine method for processing computer tasks according to claim 1 or 2, characterized in that: In the case where the task problem description matching the target problem description is retrieved in the search system, determining the entered task model includes: In the case where the problem solution corresponding to the task problem description includes multiple solution steps, determining the task model corresponding to each of the multiple solution steps to obtain multiple task models; A plurality of the task models are entered into the retrieval system.
6. The large model search engine method for processing computer tasks as claimed in claim 5, characterized in that: After entering the plurality of task models into the retrieval system, the method further includes: When inputting parameters, the execution of the task model is suspended until the completion of the input parameters is detected and the task model is re-executed; After the task model is executed to automatically complete the task, the task execution result is evaluated.
7. The automatic variable magnification adjustment method according to any one of claims 1 to 6, characterized in that: The method further comprises: The multiple task models are executed in the order corresponding to the multiple solution steps, and when one of the multiple task models fails to execute, an execution exception prompt is issued, wherein the execution exception prompt is used to prompt manual execution or termination of execution.
8. A large model search engine device for processing computer tasks, characterized in that: include: A definition unit, used for defining a basic computer task model, wherein the basic task model is freely combined to form a processing task model, wherein the basic task model includes mouse operation and keyboard operation; An establishing unit, configured to establish a search system for retrieving matching problem descriptions, wherein the search system stores a matching relationship between a task problem description and a target problem description, and the task problem description is associated with the processing task model; An input unit, configured to determine an input task model when the task problem description matching the target problem description is retrieved in the search system, wherein the task model is composed of input parameters, the processing task model and output parameters; The first execution unit is used to execute the task model to automatically complete the task after receiving a confirmation execution instruction.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 7 when executed.
10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 7 through the computer program.