Desktop system construction method and device based on large model and electronic equipment

Abstract

The invention discloses a desktop system construction method and device based on a large model and electronic equipment, and belongs to the technical field of computers. The method comprises the steps of obtaining demand description information input by a user in a user interface; selecting a target development tool according to the desktop system environment; and inputting the demand description information into the large model to obtain a desktop system file generated by the large model based on the target development tool. According to the embodiment of the invention, the personalized demand of the user is obtained through the user-friendly interface, so that the user can customize the desktop system according to personal preference of the user and intelligently select the most suitable development tool according to the target desktop system environment, the adaptability and flexibility of the development process are improved, and the development efficiency is improved. And the desktop system file is generated by using a knowledge base with abundant large models, so that the personalized customization difficulty of the desktop system is reduced, and the desktop system use requirements of different platforms and different application scenes can be met.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and in particular, relates to a desktop system construction method, device and electronic equipment based on a large model. Background Art

[0002] With the rise of open source culture and the development of computer technology, Linux desktop system has become one of the popular choices for personal computers and workstations. With its high degree of customizability, stability and security, Linux desktop system meets the diverse needs of ordinary users to professional developers.

[0003] The diverse ecosystem of Linux desktop systems benefits from its open architecture and rich desktop environments (DesktopEnvironments). These desktop environments, such as GNOME, KDE Plasma, Xfce, and MATE, provide different user experiences and feature sets.

[0004] However, these desktop environments have a certain degree of similarity in style and functionality, which may cause users to feel duplication in interface and functionality. Moreover, due to the continuous iteration of desktop systems, some functions may become redundant or have unreasonable designs, making it difficult to meet the desktop system usage requirements of different platforms and application scenarios. Summary of the invention

[0005] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a desktop system construction method, device and electronic device based on a large model to reduce the difficulty of personalized customization of the desktop system and meet the desktop system usage requirements of different platforms and different application scenarios.

[0006] In a first aspect, the present application provides a method for constructing a desktop system based on a large model, comprising:

[0007] Obtain the requirement description information entered by the user in the user interface;

[0008] Select the target development tool based on the desktop system environment;

[0009] The requirement description information is input into the large model to obtain a desktop system file generated by the large model based on the target development tool.

[0010] According to the desktop system construction method based on the big model of the present application, the requirement description information input by the user in the user interface is obtained; the target development tool is selected according to the desktop system environment; the requirement description information is input into the big model to obtain the desktop system file generated by the big model based on the target development tool. The embodiment of the present application obtains the personalized needs of the user through a user-friendly interface, so that the user can customize the desktop system according to his or her own personal preferences, and intelligently select the most suitable development tool according to the target desktop system environment, thereby improving the adaptability and flexibility of the development process, and using the rich knowledge base of the big model to generate the desktop system file, reducing the difficulty of personalized customization of the desktop system, and being able to meet the desktop system usage requirements of different platforms and different application scenarios.

[0011] According to one embodiment of the present application, the requirement description information includes a functional requirement description and / or an interface design description.

[0012] In this embodiment, by accurately capturing the user's functional requirement description and interface design description, the desktop system file is automatically generated to enable users with different personalities to customize or modify the desktop system interface.

[0013] According to an embodiment of the present application, in the case where the requirement description information includes a functional requirement description, the desktop system file includes a code file;

[0014] In the case where the requirement description information includes an interface design description, the desktop system file includes an image file.

[0015] In this embodiment, the user's functional requirement description and interface design description are captured through the user interface, and the advanced text processing capabilities of the large model are used to automatically generate the code and image files required for the desktop system, thereby enhancing the customizability of the desktop system and allowing users to easily customize functions and interfaces according to their preferences.

[0016] According to an embodiment of the present application, the step of inputting the requirement description information into the large model to obtain a desktop system file generated by the large model based on the target development tool includes:

[0017] Modularize the desktop system;

[0018] Identifying the core modules of the desktop system according to the hardware configuration of the desktop system through the large model, and determining the optional modules of the desktop system according to the requirement description information;

[0019] The desktop system files are generated based on the target development tool through the large model according to the core modules and optional modules.

[0020] In this embodiment, by dividing the desktop system into functional modules, the big model can identify the core modules of the desktop system according to the hardware configuration. These modules are necessary for the operation of the desktop system, and the big model will determine additional optional modules according to the user's specific needs description, so that the generated desktop system can accurately meet the user's hardware conditions and functional requirements, and fully meet the desktop system usage requirements in different platforms and different application scenarios.

[0021] According to an embodiment of the present application, the modules of the desktop system correspond to a module description language, and the module description language describes the functions, dependencies and resource requirements of each module;

[0022] The identifying the core modules of the desktop system according to the hardware configuration of the desktop system through the large model, and determining the optional modules of the desktop system according to the requirement description information, includes:

[0023] Identify the core modules of the desktop system according to the module description language and the hardware configuration through the large model;

[0024] The optional modules of the desktop system are determined through the large model according to the module description language and the requirement description information.

[0025] In this embodiment, through the module description language, the big model will use the information defined in the module description language to identify which are the core modules based on the hardware configuration of the desktop system, so that the basic functions of the desktop system can operate normally. The big model can also further analyze the demand description information input by the user through the user interface, combined with the detailed description in the module description language, to determine which optional modules should be included in the desktop system to meet the user's specific needs. This method not only matches the functions of the desktop system with the hardware resources, but also can customize the system according to the user's personalized needs.

[0026] According to one embodiment of the present application, the method further includes:

[0027] Generate test scripts;

[0028] Using the test script to test the desktop system file;

[0029] When the desktop system file passes the test, the desktop system file is integrated into the configuration file of the desktop system.

[0030] In this embodiment, by automatically creating corresponding test scripts and testing the generated desktop system files, different user interaction scenarios are simulated to verify the stability and responsiveness of the desktop system. When the test script confirms that the desktop system files meet the requirements, the desktop system files will be integrated into the configuration file of the desktop system, completing the entire process from development to deployment, which not only improves development efficiency, but also improves the quality and reliability of the final product.

[0031] According to one embodiment of the present application, the large model is trained in the following manner:

[0032] Collecting first data related to the functional description of the desktop system and collecting second data related to the interface design of the desktop system;

[0033] Constructing a training set according to the first data and the second data;

[0034] The training set is used to train the large model.

[0035] In this embodiment, a comprehensive training data set is constructed by collecting data related to the desktop system functions and interface design, so that the big model can learn to understand the needs of the desktop system and user preferences during training, thereby improving the processing capabilities of the big model in desktop system generation applications.

[0036] In a second aspect, the present application provides a desktop system construction device based on a large model, comprising:

[0037] An acquisition module is used to acquire the demand description information input by the user in the user interface;

[0038] A selection module is used to select a target development tool according to the desktop system environment;

[0039] An input module is used to input the requirement description information into the large model to obtain a desktop system file generated by the large model based on the target development tool.

[0040] According to the desktop system construction device based on the big model of the present application, by obtaining the demand description information input by the user in the user interface; selecting the target development tool according to the desktop system environment; inputting the demand description information into the big model, the desktop system file generated by the big model based on the target development tool is obtained. The embodiment of the present application obtains the personalized needs of the user through a user-friendly interface, so that the user can customize the desktop system according to his or her own personal preferences, and intelligently select the most suitable development tool according to the target desktop system environment, thereby improving the adaptability and flexibility of the development process, and using the rich knowledge base of the big model to generate the desktop system file, reducing the difficulty of personalized customization of the desktop system, and being able to meet the desktop system usage requirements of different platforms and different application scenarios.

[0041] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for constructing a desktop system based on a large model as described in the first aspect above is implemented.

[0042] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the large model-based desktop system construction method as described in the first aspect above.

[0043] In a fifth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the large model-based desktop system construction method as described in the first aspect above.

[0044] In a sixth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the large model-based desktop system construction method as described in the first aspect above.

[0045] The above one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0046] According to the desktop system construction method based on the big model of the present application, the requirement description information input by the user in the user interface is obtained; the target development tool is selected according to the desktop system environment; the requirement description information is input into the big model to obtain the desktop system file generated by the big model based on the target development tool. The embodiment of the present application obtains the personalized needs of the user through a user-friendly interface, so that the user can customize the desktop system according to his or her own personal preferences, and intelligently select the most suitable development tool according to the target desktop system environment, thereby improving the adaptability and flexibility of the development process, and using the rich knowledge base of the big model to generate the desktop system file, reducing the difficulty of personalized customization of the desktop system, and being able to meet the desktop system usage requirements of different platforms and different application scenarios.

[0047] Furthermore, in some embodiments, by accurately capturing the user's functional requirement description and interface design description, the desktop system file is automatically generated to enable users with different personalities to customize or modify the desktop system interface.

[0048] Furthermore, in some embodiments, the user's functional requirement description and interface design description are captured through the user interface, and the advanced text processing capabilities of the big model are used to automatically generate the code and image files required for the desktop system, thereby enhancing the customizability of the desktop system and allowing users to easily customize functions and interfaces according to their preferences.

[0049] Furthermore, in some embodiments, by dividing the desktop system into functional modules, the big model can identify the core modules of the desktop system according to the hardware configuration. These modules are necessary for the operation of the desktop system, and the big model will determine additional optional modules based on the user's specific needs description, so that the generated desktop system can accurately meet the user's hardware conditions and functional requirements, and fully meet the desktop system usage requirements in different platforms and different application scenarios.

[0050] Furthermore, in some embodiments, through the module description language, the big model will use the information defined in the module description language to identify which are the core modules based on the hardware configuration of the desktop system, so that the basic functions of the desktop system can operate normally. The big model can also further analyze the demand description information input by the user through the user interface, combined with the detailed description in the module description language, to determine which optional modules should be included in the desktop system to meet the user's specific needs. This approach not only matches the functions of the desktop system with the hardware resources, but also customizes the system according to the user's personalized needs.

[0051] Furthermore, in some embodiments, by automatically creating corresponding test scripts and testing the generated desktop system files, different user interaction scenarios are simulated to verify the stability and responsiveness of the desktop system. When the test script confirms that the desktop system files meet the requirements, the desktop system files will be integrated into the configuration file of the desktop system, completing the entire process from development to deployment, which not only improves development efficiency, but also improves the quality and reliability of the final product.

[0052] Furthermore, in some embodiments, a comprehensive training data set is constructed by collecting data related to the desktop system functions and interface design, so that the big model can learn to understand the needs of the desktop system and user preferences during training, thereby improving the processing capabilities of the big model in desktop system generation applications.

[0053] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1is a schematic diagram of a Linux desktop system provided in an embodiment of the present application;

[0056] Figure 2 is a schematic diagram of a personalization tool for a desktop system provided in an embodiment of the present application;

[0057] Figure 3 is a schematic diagram of the expansion process of the desktop system provided in an embodiment of the present application;

[0058] Figure 4 It is a flowchart of a desktop system construction method based on a large model provided in an embodiment of the present application;

[0059] Figure 5 It is a schematic diagram of the generation and packaging process of desktop system files provided in an embodiment of the present application;

[0060] Figure 6 It is a schematic diagram of the process of module identification and selection provided by an embodiment of the present application;

[0061] Figure 7 It is a schematic diagram of the large model development process provided by the embodiment of the present application;

[0062] Figure 8 It is a structural schematic diagram of a desktop system construction device based on a large model provided in an embodiment of the present application;

[0063] Fig. 9 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0065] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0066] Mainstream desktop environments such as GNOME, KDE Plasma, Xfce, and MATE all provide unique user experiences and feature sets. These environments meet users' needs for aesthetics, efficiency, and ease of use by providing different interface designs, themes, and applications. However, although this diversity provides users with choices, existing desktop systems still have some drawbacks in terms of homogeneity, difficulty in personalization, and scalability:

[0067] 1. Homogeneity of desktop systems

[0068] Lack of diversity: e.g. Figure 1 As shown, the current mainstream Linux desktop systems are similar in style. Users may feel repetitive and lack of freshness in interface and functions. At the same time, due to the continuous iteration of desktop systems, there may be redundancy and unreasonable designs in functions, but due to years of development habits, this part of the content has not been optimized.

[0069] Software uniformity: Standardization and homogeneity may limit developers' innovation in interface design and function implementation, because new ideas may need to follow existing frameworks and specifications. At the same time, even if the desktop system runs on different hardware specifications, a standard desktop system will still be installed. In application scenarios with insufficient resources and single functions, some modules appear redundant and will affect the overall performance. When resources are sufficient, there are no extra optional functions for users to use.

[0070] 2. User Personalization Difficulty

[0071] Technical threshold: For ordinary users, achieving deep personalized settings may require certain programming knowledge, which constitutes a technical threshold.

[0072] Limited choices: e.g. Figure 2 As shown, although there are some personalization tools, users' choices are still limited to the options provided by the desktop environment, and completely free customization cannot be achieved.

[0073] Difficulty in maintenance: Personalized settings may cause system instability or incompatibility with other software, and users may encounter difficulties in maintaining these customized settings.

[0074] 3. Scalability of desktop systems

[0075] Development difficulty: Figure 3 As shown, during the use process, users may want to have a personal desktop plug-in or some special extension programs, but since the development of new extensions or plug-ins requires developers to have certain programming technical capabilities, this practice is often restricted for users of desktop systems.

[0076] Compatibility issues: There may be compatibility issues between different extensions, or even incompatibility with desktop environment updates, which may cause new problems when users use extensions, leading to functional failures or system crashes.

[0077] According to the above analysis, it is difficult to customize the current desktop environment and it is difficult to meet the desktop system usage requirements of different platforms and different application scenarios.

[0078] In order to solve at least one of the above technical problems, the present application proposes a desktop system construction method, device and electronic device based on a large model. The desktop system construction method, device and electronic device based on a large model provided by the embodiment of the present application are described in detail below through specific embodiments and their application scenarios in conjunction with the accompanying drawings.

[0079] Among them, the desktop system construction method based on the large model can be applied to the terminal, and can be specifically executed by the hardware or software in the terminal.

[0080] Optionally, the terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but a desktop computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). In some embodiments, the terminal may also be an optical receiver, an optical fiber switch, etc. having a processor.

[0081] However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse and joystick.

[0082] The embodiment of the present application provides a desktop system construction method based on a big model. The execution subject of the desktop system construction method based on a big model can be an electronic device or a functional module or functional entity in the electronic device that can implement the desktop system construction method based on a big model. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras and wearable devices. The desktop system construction method based on a big model provided in the embodiment of the present application is explained below using an electronic device as an execution subject as an example.

[0083] like Figure 4 As shown, the desktop system construction method based on the large model includes: step 410, step 420 and step 430.

[0084] Step 410: Obtain the requirement description information input by the user in the user interface.

[0085] In an embodiment of the present application, a desktop customization tool may be developed in advance, and the desktop customization tool may include a user interface that can guide users to clearly and accurately input their needs. The user interface may include elements such as forms, dialog boxes, drop-down menus, sliders, etc., so that users can select or input the functions and design preferences they want.

[0086] The requirement description information is a detailed description of the user's specific requirements and ideas for the desktop system he or she hopes to develop.

[0087] In some embodiments, the requirement description information may include a functional requirement description, which may explain the functions that the user wants the desktop system to have, for example, core functions: basic functions that the user needs the desktop system to have, such as file management, window operations, network connections, system settings, etc.; additional functions: in addition to core functions, users may also need some additional functions, such as email clients, schedule management, multimedia playback, etc.; performance requirements: user expectations for system performance, such as startup time, response speed, processing power, etc.; compatibility requirements: the range of hardware and software that the user expects the desktop system to support, such as a specific processor type, memory size, storage capacity, graphics processing capabilities, network interface, etc.

[0088] The requirement description information may include an interface design description, which may describe the requirements for the visual and interactive design of the desktop interface, for example, visual style: the user's requirements for the visual style of the desktop system, such as color scheme, icon style, window borders, etc.; layout requirements: the user's preferences for desktop layout, including taskbar location, panel layout, shortcut arrangement, etc.; interactive design: the user's requirements for system interaction methods, such as mouse and keyboard operation, touch screen response, voice control, etc.

[0089] In this embodiment, by accurately capturing the user's functional requirement description and interface design description, the desktop system file is automatically generated to enable users with different personalities to customize or modify the desktop system interface.

[0090] In some embodiments, during the process of user inputting information, the user interface can provide real-time feedback and suggestions to help the user refine the requirements. For example, if the user selects a specific function, the interface can recommend corresponding interface design options or prompt the hardware resources that may be required. After the user completes the requirement input, the user interface can also provide a summary or preview to allow the user to confirm whether the requirement is correctly understood and recorded.

[0091] In the embodiment of the present application, the information input by the user in the user interface will be collected and organized into a requirement description document. The document containing the requirement description information is used as the input of the large model for subsequent desktop system file generation.

[0092] Step 420: Select a target development tool according to the desktop system environment.

[0093] In the embodiments of the present application, it is necessary to understand the characteristics of the current desktop system environment, including the operating system type (such as Windows, macOS or Linux), system architecture (such as x86 or ARM), user group and hardware configuration. Then select the appropriate development tool according to the current desktop system environment, for example: GTK+: Suitable for the development of graphical user interface (Graphical UserInterface, GUI) applications, which is part of the GNOME desktop environment. QT: A framework for developing cross-platform applications, supporting multiple programming languages, and designing the layout of the user interface design interface by yourself, such as buttons, selectors, text input boxes, etc. GNOME: GNOME Extensions can be used to integrate gadgets or applications. KDE: It can be integrated into the desktop system through Plasma Widgets or system settings, and the menu layout of the desktop environment can be updated to include custom developed applications. For example, if the current desktop system environment is Linux, GTK+ can be used. If the current desktop system environment is a cross-platform application, QT can be selected.

[0094] Step 430: Input the requirement description information into the large model to obtain the desktop system file generated by the large model based on the target development tool.

[0095] Large Language Model (LLM) is a deep learning model trained with a large amount of text data, which can generate natural language text or understand the meaning of language text. Large models can handle a variety of natural language tasks, such as text classification, question answering, dialogue, etc. In some embodiments, the large model used can be Tongyi Qianwen, ChatGLM, LLaMA, etc., which is not limited in this specification embodiment.

[0096] In some embodiments, the large model is trained according to the following method:

[0097] Collecting first data related to the functional description of the desktop system and collecting second data related to the interface design of the desktop system;

[0098] Constructing a training set based on the first data and the second data;

[0099] The training set is used to train the large model.

[0100] In this embodiment, the first data related to the functional description of the desktop system may be data related to the implementation of the desktop system functions, such as functional requirement documents, user stories, use case descriptions, etc. The first data may be collected from existing project documents, developer forums, open source projects, user feedback, and descriptions of application stores. The data content may include operations that the system should perform, business logic, performance requirements, compatibility requirements, etc.

[0101] The second data related to the interface design of the desktop system may include design drawings, prototypes, user interface flow charts, user feedback, etc. It can be collected from the designer's portfolio, design competitions, user research, usability testing, and user interface design frameworks. The data content may include layout, color scheme, font selection, icons, control style, animation effects, etc.

[0102] In this embodiment, the process of building a training set may include data integration, merging the collected function descriptions and interface design data to form a unified data set. To ensure consistent data formats and facilitate model processing, the data in the data set may be converted into a standardized format. The process of building a training set may also include data cleaning, deleting irrelevant, duplicated or low-quality data, and correcting errors in the data, such as spelling errors, inconsistent terms or format errors. The process of building a training set may also include data annotation, adding labels to the first data related to the function description, such as function type, priority, dependency, etc., and adding labels to the second data related to the interface design, such as design patterns, target user groups, design principles, etc. In some embodiments, the process of building a training set may also include expanding the data set, increasing the diversity and coverage of the data set through data enhancement techniques, such as adding noise, rotation, scaling, etc.

[0103] In this embodiment, after the training set is constructed, the training set can be used to train the large model. Specifically, a large model architecture suitable for processing structured and unstructured data, such as a variant of Transformer or BERT, can be selected, or an existing large model can be selected, and the large model can be trained using the training set, and the optimal hyperparameter combination, such as learning rate, batch size, number of training rounds, etc., can be found through automated search methods such as grid search or random search. Use the validation set to evaluate the performance of the model, such as accuracy, recall rate, F1 score, etc.; use the test set for the final evaluation to ensure the generalization ability of the model; adjust the model structure or training strategy according to the evaluation results to improve the performance of the model.

[0104] In one example, a desktop system builds a dedicated large model development process such as Figure 5 As shown in the figure, it includes two main stages: dataset collection and model building and training.

[0105] The data set collection process includes the collection of programming language and framework data, the collection of requirement description data, and the collection of model training data. The collection of programming language and framework data includes language data collection, which involves collecting code examples of different programming languages, such as Python, Java, C++, etc. The purpose is to summarize the grammatical rules, programming paradigms, and best practices of these languages. These data will be used to train the big model so that it can generate code that conforms to specific language specifications. The collection of programming language and framework data also includes framework data collection. In framework data collection, use cases of mainstream development frameworks, such as Spring, Django, React, etc., are collected to analyze the structure, characteristics, and applicable development scenarios of these frameworks so that the big model can understand how to choose the appropriate framework in different projects.

[0106] The collection of requirement description data includes functional requirement collection. Functional requirement collection collects functional requirement documents of desktop systems. By analyzing user behavior and functional implementation methods, the big model can learn how to generate corresponding codes based on functional requirements. The collection of requirement description data also includes interface design collection. This step includes collecting desktop system interface design examples and studying user interface design principles and trends. These data can help the big model understand the requirements of user interface design and generate an interface that conforms to design trends.

[0107] The collection of model training data includes the collection of source code generation data. This step collects data sets that can be used to train source code generation. These data sets contain code snippets of different granularity, from single functions to complete projects, to support the large model to learn how to generate code of different complexity. The collection of model training data also includes the collection of UI (User Interface) design data. This step includes collecting interface design data for training UI design, such as layout, color, font and other design elements. This data will enable the large model to generate interface designs with good user experience.

[0108] The model building and training process includes data set processing and model training and optimization. Data set processing includes data cleaning and labeling. In this step, invalid or irrelevant data can be removed and data can be labeled to meet the needs of model training. Data cleaning can improve the quality of the data set, while labeling provides the necessary contextual information for the large model. Data set processing can also include data enhancement. This step can expand the data set to increase the generalization ability of the model. The use of data enhancement techniques, such as data shuffling and rotation, can simulate more scenarios and variants and improve the robustness of the model. Data set processing can also include data set segmentation. This step includes dividing the data set into training set, validation set and test set. Reasonable data segmentation enables the model to be exposed to a balanced data distribution during training, validation and testing, thereby evaluating the performance of the model.

[0109] Model training and optimization can include the formulation of training strategies. In this step, appropriate training strategies are applied, such as the use of transfer learning and other techniques. Transfer learning allows the model to use the knowledge learned on other tasks to accelerate the training process and improve the performance of the model. Model training and optimization can also include hyperparameter tuning. This step can include adjusting hyperparameters such as learning rate and batch size. Using automated search methods such as grid search or random search, the optimal hyperparameter combination can be found to optimize the model's training process and final performance.

[0110] Through the above steps, large models can be trained to understand complex programming languages, frameworks, user needs, and design principles, and generate high-quality desktop system code and interface design.

[0111] In this embodiment, a comprehensive training data set is constructed by collecting data related to the desktop system functions and interface design, so that the big model can learn to understand the needs of the desktop system and user preferences during training, thereby improving the processing capabilities of the big model in desktop system generation applications.

[0112] In an embodiment of the present application, the demand description information can be input into the big model, and the big model can parse the input demand description information to identify key technical requirements and user preferences. The big model can use a rich knowledge base, as well as built-in logic and programming knowledge, to understand the demand description information and map the demand description information to specific development tasks. The big model can automatically generate desktop system files based on the development tasks obtained according to the demand description information according to the target development tool. The desktop system files may include code files, configuration files, resource files, etc.

[0113] In some embodiments, the desktop system file can be an executable Linux package suitable for the current platform, such as .deb or .rpm, so that users can install and use it in different systems. In one example, the generation and packaging process of the desktop system file is as follows: Figure 6 shown.

[0114] According to the desktop system construction method based on the big model of the present application, the requirement description information input by the user in the user interface is obtained; the target development tool is selected according to the desktop system environment; the requirement description information is input into the big model, and the desktop system file generated by the big model based on the target development tool is obtained. The embodiment of the present application obtains the personalized needs of the user through a user-friendly interface, so that the user can customize the desktop system according to his or her own personal preferences, and intelligently selects the most suitable development tool according to the target desktop system environment, thereby improving the adaptability and flexibility of the development process, and using the rich knowledge base of the big model to generate the desktop system file, reducing the difficulty of personalized customization of the desktop system, and being able to meet the desktop system usage requirements of different platforms and different application scenarios.

[0115] In some embodiments, when the requirement description information includes a functional requirement description, the desktop system file includes a code file;

[0116] In the case where the requirement description information includes an interface design description, the desktop system file includes an image file.

[0117] In this embodiment, the big model can be trained before deployment so that the big model learns the syntax, programming paradigms and software architecture of different programming languages; model training can also include learning the function implementation methods of specific types of applications so that best practices can be followed when generating code. The big model can automatically generate code files based on the user's functional requirements description. The generated code files can include functional modules such as the core logic, data processing, and user interaction of the application.

[0118] In this embodiment, the big model can be trained before deployment to learn different design styles and best practices for user interfaces. Model training can also include the identification and reorganization of design elements so that a user interface that is both beautiful and practical can be created when a new interface is generated. Based on the user's interface design description, the big model can automatically generate image files, such as icons, buttons, backgrounds, etc. The generated image files can be used directly in the desktop system or as part of the desktop system theme.

[0119] In this embodiment, the user's functional requirement description and interface design description are captured through the user interface, and the advanced text processing capabilities of the large model are used to automatically generate the code and image files required for the desktop system, thereby enhancing the customizability of the desktop system and allowing users to easily customize functions and interfaces according to their preferences.

[0120] In some embodiments, the requirement description information is input into the large model to obtain a desktop system file generated by the large model based on the target development tool, including:

[0121] Modularize the desktop system;

[0122] Identify the core modules of the desktop system according to the hardware configuration of the desktop system through the large model, and determine the optional modules of the desktop system according to the requirement description information;

[0123] The desktop system files are generated based on the target development tools according to the core modules and optional modules through the large model.

[0124] In this embodiment, the desktop system can be modularized according to different functions and components in the desktop system. Specifically, the various functions provided by the desktop system can be identified, the dependencies between the various functions can be analyzed, the modules can be divided according to the dependencies between the functions, and the responsibilities, functions, inputs and outputs, and interfaces of each module can be determined, so that the various modules can work together to form a complete desktop system.

[0125] In this embodiment, the core module is necessary for the operation of the desktop system, and the core module provides basic system functions and user interfaces. For example, the core module may include a system module, a user interface module, and a device driver module. Among them, the system module includes the core library of the operating system, basic system services, and process management, and the system module provides basic functions of the desktop system, such as starting, maintaining, and shutting down the system. The user interface module is responsible for providing a graphical interface, including window management, desktop background, icons, mouse pointers, and themes, and the user interface module is a direct interface for users to interact with the desktop system. The device driver module contains hardware device drivers, which enable the desktop system to recognize and use various hardware, such as displays, keyboards, mice, storage devices, etc.

[0126] Optional modules provide additional functionality and can be selected and customized according to user needs and preferences. Optional modules can include multimedia modules, network management modules, power management modules, game and entertainment modules, etc.

[0127] In this embodiment, the large model analyzes the hardware configuration of the desktop system, such as the type of processor (Central Processing Unit, CPU) (ARM, x86, etc.), memory size, storage capacity, graphics processing capabilities, network interface, etc. to identify the core modules. For example, if the hardware configuration is low, the large model can select a lightweight core module to optimize performance.

[0128] Specifically, Figure 7As shown, the following steps may be included in the process of identifying the required modules (core modules): Determine the desktop system hardware requirements: Evaluate the minimum hardware configuration required for the desktop system, including processor type, memory size, storage capacity, and graphics processing capabilities, etc., to ensure that the basic functions of the system can run; Hardware compatibility check: Check the compatibility between the selected hardware components to ensure that they can work together to avoid potential conflicts and problems; Prepare a list of required modules: List the modules that are necessary for the operation of the desktop system, such as window managers, file managers, system settings, etc. These modules constitute the basic framework of the desktop system; System performance optimization: Optimize system performance, including reducing startup time, improving response speed, and ensuring that the system runs with low resource consumption to provide a smooth user experience.

[0129] In this embodiment, the requirement description information input by the user needs to be analyzed in detail, including analyzing the functional requirement description, such as what additional functions the desktop system is expected to have, and analyzing the interface design description, such as the user's preference for visual style and layout. Based on the requirement description information, possible optional modules are identified. For example, if the user needs to perform video editing, a video editor module may be integrated; if the user needs to perform frequent network operations, an advanced network management module may be selected.

[0130] Specifically, Figure 7 As shown, the optional module identification process may include the following steps: Analyze specific needs: By investigating the user's usage habits and preferences, analyze the additional functions that the user may need, such as multimedia playback, network management, security tools, etc.; Optional module evaluation: Evaluate the functions and performance of the optional modules to determine whether they meet user needs and will not affect the system stability; Module integration testing: Integrate the selected optional modules into the desktop system and test them to ensure that they are compatible with the core modules and will not affect the overall performance and stability of the system; User feedback collection: Collect user feedback on the integrated optional modules to understand their actual performance and user satisfaction for further adjustment and optimization.

[0131] In this embodiment, after determining the core modules and optional modules, the large model can select appropriate development tools based on the desktop system environment. For example, for a Linux desktop system, GTK+ or QT can be selected as a GUI development tool. The software architecture of each module, such as class structure, function interface, and data flow, is designed through the API of the development tool, and the code corresponding to each module is generated. For example, if the user needs a video playback function, the large model can generate a video player module, including video decoding, playback control, and user interface elements.

[0132] In this embodiment, by dividing the desktop system into functional modules, the big model can identify the core modules of the desktop system according to the hardware configuration. These modules are necessary for the operation of the desktop system, and the big model will determine additional optional modules according to the user's specific needs description, so that the generated desktop system can accurately meet the user's hardware conditions and functional requirements, and fully meet the desktop system usage requirements in different platforms and different application scenarios.

[0133] In some embodiments, there is a module description language corresponding to the modules of the desktop system, and the module description language describes the functions, dependencies and resource requirements of each module;

[0134] The core modules of the desktop system are identified based on the hardware configuration of the desktop system through the large model, and the optional modules of the desktop system are determined based on the requirement description information, including:

[0135] Identify the core modules of the desktop system based on the module description language and hardware configuration through the large model;

[0136] The optional modules of the desktop system are determined through the large model according to the module description language and requirement description information.

[0137] In this embodiment, the Module Description Language (MDL) is a language used to describe modules, components or systems, and is intended to provide a clear and standardized way to describe the structure, interface and functions of these modules. Through MDL, developers can define the interface, function and dependency of the module, and how they affect the overall performance of the system.

[0138] The big model can identify these core modules by analyzing the MDL description and hardware configuration. For example, if a desktop system needs to support multi-window operation, the big model will determine to include an efficient window manager as a core module based on the MDL and hardware configuration information.

[0139] Optional modules provide additional functionality and can be selected and customized based on the user's needs and preferences. For example, if the user needs to perform video editing, the big model may identify "Video Editor" as an optional module. The big model will evaluate the functionality and performance of the optional modules based on the user's requirement description information and MDL, and determine whether the optional modules meet the user's needs and will not affect system stability.

[0140] In this embodiment, through the module description language, the big model will use the information defined in the module description language to identify which are the core modules based on the hardware configuration of the desktop system, so that the basic functions of the desktop system can operate normally. The big model can also further analyze the demand description information input by the user through the user interface, combined with the detailed description in the module description language, to determine which optional modules should be included in the desktop system to meet the user's specific needs. This method not only matches the functions of the desktop system with the hardware resources, but also can customize the system according to the user's personalized needs.

[0141] In some embodiments, the method further comprises:

[0142] Generate test scripts;

[0143] Use test scripts to test desktop system files;

[0144] When the desktop system file test passes, the desktop system file is integrated into the configuration file of the desktop system.

[0145] In this embodiment, the test script is a series of automated commands used to simulate user operations and verify whether the response and behavior of the application are as expected. The test script may include the following aspects: Functional testing: verify whether the basic functions of the desktop system, such as window management, file operations, system settings, etc., work as expected; Performance testing: check the performance of the system under high load or long-term operation to ensure that there are no memory leaks or performance bottlenecks; User interface testing: ensure that user interface elements such as buttons, menus, dialog boxes, etc. are displayed correctly and respond to user operations; Compatibility testing: verify the compatibility of the desktop system on different hardware configurations and operating system versions. Test scripts can be generated and executed by automated testing tools such as WinAppDriver, Appium, etc.

[0146] In some embodiments, the big model can use the API and library of the target development tool to write automated test scripts. The test script can simulate user operations, such as clicking, entering text, dragging, etc., and verify whether the system response is as expected. For example, if the desktop system includes a text editor module, the big model can generate a test script to verify the functions of text insertion, deletion, formatting, etc.

[0147] When the desktop system files pass the test, the desktop system files need to be integrated into the desktop system's configuration files. Configuration files usually contain all the settings and parameters required for system startup, operation, and maintenance. For example, you can place the desktop system files in a specified system directory, update the system path, or modify the registry entries to ensure that the system can recognize and load these files.

[0148] In this embodiment, by automatically creating corresponding test scripts and testing the generated desktop system files, different user interaction scenarios are simulated to verify the stability and responsiveness of the desktop system. When the test script confirms that the desktop system files meet the requirements, the desktop system files will be integrated into the configuration file of the desktop system, completing the entire process from development to deployment, which not only improves development efficiency, but also improves the quality and reliability of the final product.

[0149] The following describes the method for building a desktop system based on a large model provided in an embodiment of the present application through scenario examples.

[0150] Scenario example 1: User A develops a screenshot software and integrates it into the DeltaOS desktop system. This scenario example includes the following steps:

[0151] Users input requirements into the large model. For example, users can input requirements through the user interface, such as screenshot area selection (full screen, custom area, window), shortcut key support, screenshot delay, image format, editing functions (such as adding text, marking), etc.

[0152] The large model automatically selects the QT framework for development and uses Qt Designer to design the user interface. Create an interface that includes a screenshot button, options (such as selecting the screenshot area, delay, etc.) and a screenshot result display area. Use the QPixmap class to capture the screen image, use QApplication::screens() to get the screen list, then select the appropriate screen for screenshot, use the QPainter class to draw the screenshot area, and finally use the QImage class to save the screenshot to a file, providing options for users to choose the save format (such as PNG, JPEG, etc.).

[0153] Generate a Linux executable file, place it in the main menu of the desktop environment, and create a desktop icon. The large model automatically writes test scripts for testing to ensure integration and functionality (normal operation, screenshots, save and exit operations, etc.).

[0154] In this way, user A developed a screenshot software that can run on the desktop of the DeltaOS system.

[0155] Scenario 2: User B loves Chinese style, so he wants to change all icons on the desktop system to Chinese style with one click. This scenario includes the following steps:

[0156] The user inputs the icon style and type to be replaced in the user interface, such as the traditional style.

[0157] According to the input requirements of the large model, the size, color, output format, etc. of the output icon are output, and a request is sent to the large model to generate an icon that meets the application.

[0158] Back up the original icons, and download the generated Chinese-style icons to the local DeltaOS system desktop icon storage location such as / usr / share / icons to overwrite them, and restart the desktop system to take effect.

[0159] The desktop system construction method based on a large model provided in the embodiment of the present application can be executed by a desktop system construction device based on a large model. In the embodiment of the present application, the desktop system construction device based on a large model performs the desktop system construction method based on a large model as an example to illustrate the desktop system construction device based on a large model provided in the embodiment of the present application.

[0160] The embodiment of the present application also provides a desktop system construction device based on a large model.

[0161] like Figure 8 As shown, the desktop system construction device based on the large model includes:

[0162] An acquisition module 810 is used to acquire the demand description information input by the user in the user interface;

[0163] A selection module 820, for selecting a target development tool according to a desktop system environment;

[0164] The input module 830 is used to input the requirement description information into the large model to obtain the desktop system file generated by the large model based on the target development tool.

[0165] According to the desktop system construction device based on the big model of the present application, by obtaining the demand description information input by the user in the user interface; selecting the target development tool according to the desktop system environment; inputting the demand description information into the big model, the desktop system file generated by the big model based on the target development tool is obtained. The embodiment of the present application obtains the personalized needs of the user through a user-friendly interface, so that the user can customize the desktop system according to his or her own personal preferences, and intelligently selects the most suitable development tool according to the target desktop system environment, thereby improving the adaptability and flexibility of the development process, and using the rich knowledge base of the big model to generate the desktop system file, reducing the difficulty of personalized customization of the desktop system, and being able to meet the desktop system usage requirements of different platforms and different application scenarios.

[0166] The desktop system construction device based on the large model in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or it can be other devices other than the terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a handheld computer, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., and the embodiment of the present application is not specifically limited.

[0167] The desktop system construction device based on the large model in the embodiment of the present application can be a device with an operating system. The operating system can be a Microsoft (Windows) operating system, an Android (Android) operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0168] In some embodiments, Fig. 9 As shown, an embodiment of the present application also provides an electronic device 900, including a processor 901, a memory 902, and a computer program stored in the memory 902 and executable on the processor 901. When the program is executed by the processor 901, each process of the above-mentioned large-model-based desktop system construction method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0169] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0170] An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned large-model-based desktop system construction method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0171] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0172] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned desktop system construction method based on a large model when executed by a processor.

[0173] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0174] The embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned large model-based desktop system construction method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0175] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0176] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0177] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0178] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0179] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0180] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A desktop system construction method based on a large model, characterized in that: include: Obtain the requirement description information entered by the user in the user interface; Select the target development tool based on the desktop system environment; The requirement description information is input into the large model to obtain a desktop system file generated by the large model based on the target development tool.

2. The method according to claim 1, characterized in that The requirement description information includes a functional requirement description and / or an interface design description.

3. The method according to claim 2, wherein when the requirement description information includes a functional requirement description, the desktop system file includes a code file; In the case where the requirement description information includes an interface design description, the desktop system file includes an image file.

4. The method according to claim 1, characterized in that: The step of inputting the requirement description information into the large model to obtain a desktop system file generated by the large model based on the target development tool includes: Modularize the desktop system; Identifying the core modules of the desktop system according to the hardware configuration of the desktop system through the large model, and determining the optional modules of the desktop system according to the requirement description information; The desktop system files are generated based on the target development tool through the large model according to the core modules and optional modules.

5. The method according to claim 4, characterized in that The modules of the desktop system correspond to a module description language, and the module description language describes the functions, dependencies and resource requirements of each module; The identifying the core modules of the desktop system according to the hardware configuration of the desktop system through the large model, and determining the optional modules of the desktop system according to the requirement description information, includes: Identify the core modules of the desktop system according to the module description language and the hardware configuration through the large model; The optional modules of the desktop system are determined through the large model according to the module description language and the requirement description information.

6. The method according to claim 1, characterized in that The method further comprises: Generate test scripts; Using the test script to test the desktop system file; When the desktop system file passes the test, the desktop system file is integrated into the configuration file of the desktop system.

7. The method according to claim 1, characterized in that The large model is trained according to the following method: Collecting first data related to the functional description of the desktop system and collecting second data related to the interface design of the desktop system; Constructing a training set according to the first data and the second data; The training set is used to train the large model.

8. A desktop system construction device based on a large model, characterized in that: include: An acquisition module is used to acquire the demand description information input by the user in the user interface; A selection module is used to select a target development tool according to the desktop system environment; An input module is used to input the requirement description information into the large model to obtain a desktop system file generated by the large model based on the target development tool.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method according to any one of claims 1 to 7.

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