AI-based weekly report processing method, apparatus and device, and medium

Abstract

The invention provides an AI-based weekly report processing method and device, equipment and a medium, and the method comprises the steps: responding to a first triggering operation, and displaying a first input control in a target document; the user determines creation requirements through selection operation and provides input content through input operation; and after the input content is confirmed, generating corresponding first target content by utilizing the AI, and inserting the first target content into the target document after the user confirms the first target content. The weekly report processing efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence, and in particular to an AI-based weekly report processing method, device, equipment and medium. Background Art

[0002] In the modern business operation environment, the efficiency and quality of teamwork are directly related to the overall operation effect and market competitiveness of the enterprise.

[0003] Traditional team collaboration methods, such as communication and task allocation through email, instant messaging tools or traditional project management software, have many shortcomings. For example, these methods often lack intelligent processing capabilities, causing team members to spend a lot of time and energy in writing weekly reports, organizing project progress and reporting work status. At the same time, these tools also have certain limitations in terms of personalized customization, real-time updates, knowledge sharing, and data-driven decision-making. Summary of the invention

[0004] In view of this, the embodiments of the present application provide an AI-based weekly report processing method, device, equipment and medium, which can improve the efficiency of weekly report processing.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides an AI-based weekly report processing method, the method comprising:

[0007] In response to a first triggering operation on a target control, displaying a first input control in a target document;

[0008] In response to a selection operation in the first input control, determining a first creation requirement from at least one creation requirement;

[0009] In response to an input operation in the first input control, displaying first input content, and after confirming the first input content, displaying first target content generated by AI under the first creation requirement;

[0010] In response to a confirmation operation on the first target content, the first target content is inserted into the target document.

[0011] In a second aspect, an embodiment of the present application further provides an AI-based weekly report processing device, the device comprising:

[0012] A first display module, configured to display a first input control in a target document in response to a first trigger operation on a target control;

[0013] A selection module, configured to determine a first creation requirement from at least one creation requirement in response to a selection operation in the first input control;

[0014] A second display module, configured to respond to an input operation in the first input control, display a first input content, and after confirming the first input content, display a first target content generated by AI under the first creation requirement;

[0015] The inserting module is used for inserting the first target content into the target document in response to a confirmation operation on the first target content.

[0016] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium through the bus, and the processor executes the machine-readable instructions to execute the AI-based weekly report processing method described in any one of the first aspects.

[0017] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the AI-based weekly report processing method described in any one of the first aspects is executed.

[0018] The embodiments of the present application have the following beneficial effects:

[0019] (1) Significantly improve work efficiency: Through intelligent processing and the use of AI big model capabilities, weekly reports are automatically generated, which greatly reduces the time and labor intensity of manual weekly report preparation, allowing team members to devote more energy to core business, thereby significantly improving overall work efficiency.

[0020] (2) Meeting personalized needs: The AI ​​assistant can generate personalized weekly reports based on user input. This not only meets the personalized needs of different team members, but also enhances the pertinence and practicality of the weekly reports, making it easier for team members to accept and recognize the content of the weekly reports.

[0021] (3) Promote real-time communication and collaboration: Real-time updated task management and reporting management functions enable team members to understand project progress and personal work status at any time, promote real-time communication and collaboration among team members, and reduce the possibility of information lag and misunderstanding.

[0022] (4) Improve team knowledge level: The integrated knowledge base management function provides team members with a convenient knowledge sharing platform, promotes the accumulation and inheritance of knowledge within the team, and improves the overall knowledge level and professional quality of the team.

[0023] (5) The user interface is user-friendly and easy to operate, allowing team members to quickly get started, lowering the usage threshold and increasing the popularity and utilization of the system.

[0024] (6) Support data-driven decision-making: Through AI intelligent summary, team managers can quickly obtain the overall situation of the team's work, including key data such as project progress and member performance, providing strong support for decision-making and improving the accuracy and timeliness of decision-making.

[0025] (7) Enhance team collaboration and cohesion: The embodiments of the present application enhance information sharing and communication among team members by providing a series of efficient and convenient collaboration tools, promote the improvement of team collaboration and cohesion, and lay a solid foundation for building an efficient and harmonious team culture.

[0026] In summary, the embodiment of the present application not only improves the efficiency and quality of team collaboration by integrating AI technology, but also promotes knowledge sharing and communication within the team, providing a modern enterprise with an efficient and intelligent team collaboration solution. This helps to improve the overall operational efficiency and market competitiveness of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] 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.

[0028] Figure 1a It is a flowchart of steps S101-S104 provided in an embodiment of the present application;

[0029] Figure 1b This is a diagram of the intelligent weekly report generation function interface provided by an embodiment of the present application;

[0030] Figure 2a It is a flowchart of steps S201-S203 provided in an embodiment of the present application;

[0031] Figure 2b This is a diagram of the content intelligent summary function interface provided by an embodiment of the present application;

[0032] Figure 3a It is a flowchart of steps S301-S304 provided in an embodiment of the present application;

[0033] Figure 3b This is a diagram of the reporting AI assistant management function interface provided in an embodiment of the present application;

[0034] Figure 4aIt is a flowchart of steps S401-S403 provided in an embodiment of the present application;

[0035] Figure 4b This is an interface diagram of the AI ​​intelligent summary function provided in an embodiment of the present application;

[0036] Figure 5 It is a structural schematic diagram of an AI-based weekly report processing device provided in an embodiment of the present application;

[0037] Figure 6 It is a schematic diagram of the composition structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0038] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0039] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0040] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0041] In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0042] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0044] See also Figure 1a , Figure 1a This is a flowchart of steps S101-S104 of the AI-based weekly report processing method provided in the embodiment of the present application, which will be combined with Figure 1a Steps S101-S104 are shown for explanation.

[0045] In step S101, in response to a first trigger operation on a target control, a first input control is displayed in a target document.

[0046] In step S102, in response to a selection operation in the first input control, a first creation requirement is determined from at least one creation requirement.

[0047] In step S103, in response to the input operation in the first input control, the first input content is displayed, and after the first input content is confirmed, the first target content generated by AI under the first creation requirement is displayed.

[0048] In step S104, in response to a confirmation operation on the first target content, the first target content is inserted into the target document.

[0049] Here, when a user (such as an employee) performs a first trigger operation (such as clicking a button or link) in the target document, the system will display a first input control in the document. This control can be a drop-down menu, a text box, or other forms of input interfaces.

[0050] The user performs a selection operation in the first input control to determine one of at least one preset creation requirement as the first creation requirement. These creation requirements may include different parts of the weekly report (such as work summary, next week's plan, problem feedback, etc.) or specific content formats (such as lists, charts, etc.). Figure 1b As shown, users can choose from the creation needs such as "work summary", "daily assistant", "meeting minutes", "micro headline creation", "public account articles", and "writing marketing copy".

[0051] The user continues to input content related to the first creation requirement in the first input control, such as keywords for the work summary, specific items planned for next week, etc. After the input is completed, the user confirms the input content.

[0052] The system generates first target content that matches the first creation requirement based on the first input content confirmed by the user using AI technology. This content may be text that has been processed by natural language, extracted and reorganized, or it may be a chart or list generated based on the user input.

[0053] When the user confirms the first target content, the system will automatically insert the content into the corresponding position of the target document. In this way, the user does not need to manually write or copy and paste the weekly report content.

[0054] The above method uses AI to automatically generate weekly report content, greatly shortening the creation time of weekly reports. AI technology can ensure that the generated weekly report content is more accurate in grammar, logic and format. Users can choose different creation requirements and input content according to their needs, so as to generate weekly reports that meet personal or team requirements.

[0055] In some embodiments, see Figure 2a , Figure 2a It is a flowchart of steps S201-S203 provided in an embodiment of the present application. The method also includes steps S201-S203, which will be described in combination with each step.

[0056] In step S201, after determining the designated content in the target document, in response to a second trigger operation on the target control, the at least one creation requirement is displayed; wherein the designated content is determined by selecting in the target document.

[0057] In step S202, in response to determining a second creation requirement from the at least one creation requirement, a second target content generated by AI under the second creation requirement is displayed; wherein the second creation requirement is a summary and / or generalization requirement; and the second target content is a summary and / or generalization content of the specified content.

[0058] In step S203, in response to a confirmation operation on the second target content, the second target content is inserted into the target document.

[0059] Here, the user selects one or more sections of content in the target document as designated content, and confirms the selection by, for example, clicking a confirmation button.

[0060] After determining the specified content, the user performs a second trigger operation on the target control. In response to this operation, the system displays at least one creation requirement for the user to select. These creation requirements include summary and general requirements, as well as other requirements related to weekly report creation.

[0061] The user selects one of at least one creation requirement as the second creation requirement. This requirement is summary or generalization, and is used to refine and generalize the specified content. Based on the user's selection and specified content, the system uses AI technology to generate the second target content, which is a summary and / or generalization of the specified content.

[0062] The user confirms the generated second target content. If satisfied, the system automatically inserts the content into the appropriate position of the target document, usually near the designated content or at a designated insertion point.

[0063] For examples, see Figure 2b ,like Figure 2b As shown, the original content is summarized by collaborative AI to obtain the second target content. The user can click Add to add the second target content to the target document, or click the Replace Selected button to replace the specified content with the second target content. If the user is not satisfied with this summary, he can click the Retry button to ask AI to answer again, or click the Discard button to abandon the current answer.

[0064] The above method, by supporting the summary and generalization of specified content in the document, makes the creation of weekly reports more flexible and can meet the user's needs for the extraction and presentation of specific content. AI technology can ensure that the generated summary and generalization content is consistent with the original text in terms of semantics and logic, reducing errors in manual extraction. Automatically generating summary and generalization content greatly shortens the creation time of weekly reports and improves work efficiency.

[0065] In some embodiments, see Figure 3a , Figure 3a It is a flowchart of steps S301-S304 provided in an embodiment of the present application. The method also includes steps S301-S304, which will be described in combination with each step.

[0066] In step S301, in response to a report request, a report interface is displayed in a human-computer interaction interface; wherein the report interface includes at least one report item.

[0067] In step S302, in response to a third trigger operation on the target control, a second input control is displayed; wherein the second input control includes a target template that matches the at least one reporting item.

[0068] In step S303, in response to the input operation in the target template, the second input content is displayed, and after the second input content is confirmed, the third target content generated by AI is displayed; wherein the third target content includes at least one sub-content corresponding to the target template.

[0069] In step S304, in response to a confirmation operation on the designated content in the at least one sub-content, the designated content is inserted into a corresponding report item in the at least one report item.

[0070] Here, when the user makes a report request, the system displays a report interface in the human-computer interaction interface. This interface includes at least one report item for displaying different parts or topics of the weekly report.

[0071] The user performs a third trigger operation on the target control, and the system responds to this operation by displaying a second input control. This control includes a target template that matches at least one report item in the report interface. The target template includes a text template, a chart template, or other forms of templates, which are used to guide the user to input and generate corresponding content.

[0072] The user performs input operation in the target template, fills in or selects the corresponding content. After the input is completed, the user confirms the second input content.

[0073] The system generates third target content using AI technology based on the second input content confirmed by the user and the target template. This content usually includes at least one sub-content corresponding to the target template, such as multiple paragraphs, charts or list items.

[0074] The user browses and selects the designated content (a sub-content or a fragment of a sub-content) to be inserted in the third target content. After confirming the designated content, the system automatically inserts the content into the position of the corresponding report item in the report interface.

[0075] For examples, see Figure 3b ,like Figure 3b As shown, users can call AI in the reporting interface, and AI will provide a template that matches the reporting interface. Users only need to fill in the corresponding template to generate the corresponding third target content through AI, and the generated corresponding sub-content will be filled in the corresponding reporting item.

[0076] In addition, users can also fill in the report content they need to generate without using a template. Users can choose whether to insert the document into the current report item based on the analysis results.

[0077] The above method not only supports the automatic generation of weekly report content, but also introduces functions such as report request processing and target template matching, providing comprehensive support for the creation and reporting of weekly reports. Through the matching of target templates and the confirmation and insertion of sub-content, users can freely combine and adjust the content of weekly reports as needed to meet different reporting needs. The use of AI technology has greatly shortened the creation and reporting time of weekly reports and improved work efficiency.

[0078] In some embodiments, see Figure 4a , Figure 4a It is a flowchart of steps S401-S403 provided in an embodiment of the present application. The method also includes steps S401-S403, which will be described in combination with each step.

[0079] In step S401, in response to a trigger operation on a summary control, report information is obtained.

[0080] In step S402, statistical processing is performed based on the report information to obtain statistical results.

[0081] In step S403, a summary interface is displayed in the human-computer interaction interface; wherein the summary interface includes summary information, and the summary information is determined based on the statistical results.

[0082] Here, the user submits a report request through the human-computer interaction interface, the system displays the report interface, and allows the user to input or select the report content. The system uses AI technology to generate the detailed part of the weekly report based on the report content input and selected by the user. When the user needs to summarize and analyze the information in the weekly report, the summary control is triggered (such as clicking the summary button). The system responds to the trigger operation of the summary control and obtains the report information from the weekly report or the data source specified by the user. This information may include text, charts, data, etc. in the weekly report. The system performs statistical processing on the obtained report information, such as calculating the total data, average, proportion, etc., to obtain statistical results. Specific summary information such as Figure 4b shown.

[0083] The system displays a summary interface in the human-computer interaction interface, which includes summary information determined based on statistical results. The summary information is displayed in the form of charts, tables, text, etc., so that users can intuitively understand the key data and trends in the weekly report.

[0084] The above method not only supports the automatic generation and reporting of weekly report content, but also introduces summary analysis functions, providing users with a comprehensive weekly report management solution. Through the use of AI technology, the system can automatically generate weekly report content and perform statistical processing, reducing manual intervention and errors. The summary interface can display statistical results in the form of charts, tables, etc., allowing users to intuitively understand the key information and trends in the weekly report. Users can freely combine and adjust the content and format of the weekly report as needed to meet different reporting needs.

[0085] In some embodiments, the target control and related components of the target control are built based on Vue2, and the input content sent by the target control is sent to the Egg.js server based on the HTTP client.

[0086] Here, developers use the Vue2 framework to build the target control and its related components by writing Vue components. These components include input boxes, buttons, selectors, etc., which are used to receive user input and trigger corresponding operations. When the user enters content in the target control and triggers the corresponding operation (such as clicking the submit button), the Vue component captures the input content. Then, the Vue component uses the HTTP client (such as Axios or Fetch) to encapsulate these input contents into HTTP requests and send them to the backend server through the network. After receiving the HTTP request, the backend server (built on Egg.js) will execute the corresponding business logic according to the URL, method (such as GET, POST, etc.) of the request, and the request body (that is, the input content sent by the front end). During the processing, the Egg.js framework will provide support such as route matching, middleware processing, and controller logic to ensure that the request can be processed and responded to correctly. After the backend server processes the request, it will encapsulate the processing results into an HTTP response and send it back to the front end through the network. After receiving the response, the front-end Vue component will update the interface or perform other operations according to the content of the response.

[0087] In some embodiments, a target interface for receiving input content is predefined in the Egg.js server, and the Egg.js server obtains the AI-generated content by sending an HTTP request to the large model API.

[0088] Here, one or more target interfaces for receiving front-end input content are predefined in the Egg.js server. These interfaces are usually defined by routes (router) and the corresponding processing methods (controller) are specified. When the front-end sends requests to these interfaces through HTTP clients (such as Axios, Fetch, etc.), the Egg.js server will match the corresponding routes according to the URL and method of the request, and call the specified processing method to process the request. In the processing method, the Egg.js server will parse the HTTP request sent by the front-end and extract the input content (such as text, pictures, files, etc.) from it. These input contents may be input by users through the target controls and related components built by Vue2, or they may be sent by other front-end pages or components. After processing the request sent by the front-end, the Egg.js server may need to call the big model API to obtain AI-generated content. The big model API is usually provided by cloud service providers or AI companies, and is used to perform tasks such as natural language processing, image recognition, and recommendation algorithms. The Egg.js server sends the necessary parameters (such as input content, model ID, API key, etc.) to the big model API through an HTTP request (such as a POST request). After receiving the request, the Big Model API will perform the corresponding AI task according to the provided parameters and generate results. These results may be AI-generated content in the form of text, pictures, audio, etc. The Big Model API will encapsulate the generated results into an HTTP response and send it back to the Egg.js server. After receiving the response from the Big Model API, the Egg.js server will parse the AI-generated content. According to business needs, the Egg.js server may further process or convert the AI-generated content (such as formatting, filtering, storage, etc.). After processing the AI-generated content, the Egg.js server will encapsulate the processing results into an HTTP response and send it back to the front end through the network. After receiving the response, the front-end Vue component will update the interface or perform other operations (such as displaying AI-generated content, prompting the user that the operation is successful, etc.) according to the content of the response.

[0089] In some embodiments, the AI ​​preconfigures at least one scene template corresponding to the creation requirements; the method further includes:

[0090] In response to the modification / replacement / addition / deletion operations on the scene template, the scene template is adjusted so that the AI ​​meets the business needs.

[0091] Here, the AI ​​system is pre-configured with at least one scenario template. These scenario templates are designed based on common creative needs or business needs, and are intended to provide a starting point or framework so that AI can generate content that meets the requirements more quickly. The scenario template depends on the application scenario and creative needs of the AI ​​system.

[0092] When an existing scenario template does not fully meet business needs, users or developers can modify the template. This includes adjusting elements such as text, images, audio, etc. in the template, or changing the structure and layout of the template. If a scenario template is no longer applicable or needs to be replaced by a more advanced template, users or developers can choose to replace the template. This usually involves selecting a new template and applying it to the AI ​​system. As business needs change or new scenarios emerge, users or developers may need to add new scenario templates. This can be achieved by creating a completely new template and adding it to the template library of the AI ​​system. For scenario templates that are no longer used or redundant, users or developers can choose to delete them to simplify the management and maintenance of the AI ​​system.

[0093] After adjusting the scene templates, the AI ​​system can adapt to different business needs more flexibly. This helps improve the usability and practicality of the AI ​​system, enabling it to better serve users and businesses. The adjusted scene templates can be used by the AI ​​system to generate content that better meets business needs, thereby improving creation efficiency and quality.

[0094] In summary, the embodiments of the present application have the following beneficial effects:

[0095] (1) Significantly improve work efficiency: Through intelligent processing and the use of AI big model capabilities, weekly reports are automatically generated, which greatly reduces the time and labor intensity of manual weekly report preparation, allowing team members to devote more energy to core business, thereby significantly improving overall work efficiency.

[0096] (2) Meeting personalized needs: The AI ​​assistant can generate personalized weekly reports based on user input. This not only meets the personalized needs of different team members, but also enhances the pertinence and practicality of the weekly reports, making it easier for team members to accept and recognize the content of the weekly reports.

[0097] (3) Promote real-time communication and collaboration: Real-time updated task management and reporting management functions enable team members to understand project progress and personal work status at any time, promote real-time communication and collaboration among team members, and reduce the possibility of information lag and misunderstanding.

[0098] (4) Improve team knowledge level: The integrated knowledge base management function provides team members with a convenient knowledge sharing platform, promotes the accumulation and inheritance of knowledge within the team, and improves the overall knowledge level and professional quality of the team.

[0099] (5) The user interface is user-friendly and easy to operate, allowing team members to quickly get started, lowering the usage threshold and increasing the popularity and utilization of the system.

[0100] (6) Support data-driven decision-making: Through AI intelligent summary, team managers can quickly obtain the overall situation of the team's work, including key data such as project progress and member performance, providing strong support for decision-making and improving the accuracy and timeliness of decision-making.

[0101] (7) Enhance team collaboration and cohesion: The embodiments of the present application enhance information sharing and communication among team members by providing a series of efficient and convenient collaboration tools, promote the improvement of team collaboration and cohesion, and lay a solid foundation for building an efficient and harmonious team culture.

[0102] In summary, the embodiment of the present application not only improves the efficiency and quality of team collaboration by integrating AI technology, but also promotes knowledge sharing and communication within the team, providing a modern enterprise with an efficient and intelligent team collaboration solution. This helps to improve the overall operational efficiency and market competitiveness of the enterprise.

[0103] Based on the same inventive concept, the embodiment of the present application also provides an AI-based weekly report processing device corresponding to the AI-based weekly report processing method in the first embodiment. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned AI-based weekly report processing method, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0104] like Figure 5 As shown, Figure 5 : is a structural diagram of an AI-based weekly report processing device 500 provided in an embodiment of the present application. The AI-based weekly report processing device 500 includes:

[0105] A first display module 501, configured to display a first input control in a target document in response to a first trigger operation on a target control;

[0106] A selection module 502, configured to determine a first creation requirement from at least one creation requirement in response to a selection operation in the first input control;

[0107] The second display module 503 is used to respond to the input operation in the first input control, display the first input content, and after confirming the first input content, display the first target content generated by AI under the first creation requirement;

[0108] The inserting module 504 is configured to insert the first target content into the target document in response to a confirmation operation on the first target content.

[0109] Those skilled in the art should understand that Figure 5 The implementation functions of each unit in the AI-based weekly report processing device 500 shown can be understood by referring to the relevant description of the aforementioned AI-based weekly report processing method. Figure 5 The functions of each unit in the AI-based weekly report processing device 500 shown can be implemented by a program running on a processor, or by a specific logic circuit.

[0110] In a possible implementation, the insertion module 504 further includes:

[0111] After determining the designated content in the target document, in response to a second trigger operation on the target control, displaying the at least one creation requirement; wherein the designated content is determined by selecting in the target document;

[0112] In response to determining a second creation requirement from the at least one creation requirement, displaying a second target content generated by the AI ​​under the second creation requirement; wherein the second creation requirement is a summary and / or generalization requirement; and the second target content is a summary and / or generalization content of the specified content;

[0113] In response to a confirmation operation on the second target content, the second target content is inserted into the target document.

[0114] In a possible implementation, the insertion module 504 further includes:

[0115] In response to the report request, displaying a report interface in the human-computer interaction interface; wherein the report interface includes at least one report item;

[0116] In response to a third trigger operation on the target control, displaying a second input control; wherein the second input control includes a target template matching the at least one reporting item;

[0117] In response to an input operation in the target template, display a second input content, and after confirming the second input content, display a third target content generated by AI; wherein the third target content includes at least one sub-content corresponding to the target template;

[0118] In response to a confirmation operation on the specified content in the at least one sub-content, the specified content is inserted into a corresponding report item in the at least one report item.

[0119] In a possible implementation, the insertion module 504 further includes:

[0120] Respond to trigger operations on summary controls and obtain report information;

[0121] Performing statistical processing based on the reported information to obtain statistical results;

[0122] A summary interface is displayed in the human-computer interaction interface; wherein the summary interface includes summary information, and the summary information is determined based on the statistical results.

[0123] In a possible implementation, the target control and related components of the target control are built based on Vue2, and the input content sent by the target control is sent to the Egg.js server based on an HTTP client.

[0124] In a possible implementation, a target interface for receiving input content is predefined in the Egg.js server, and the Egg.js server obtains the AI-generated content by sending an HTTP request to the large model API.

[0125] In a possible implementation, the AI ​​preconfigures at least one scene template corresponding to the creation requirement; the method further includes:

[0126] In response to the modification / replacement / addition / deletion operations on the scene template, the scene template is adjusted so that the AI ​​meets the business needs.

[0127] The above-mentioned AI-based weekly report processing device has the following beneficial effects:

[0128] (1) Significantly improve work efficiency: Through intelligent processing and the use of AI big model capabilities, weekly reports are automatically generated, which greatly reduces the time and labor intensity of manual weekly report preparation, allowing team members to devote more energy to core business, thereby significantly improving overall work efficiency.

[0129] (2) Meeting personalized needs: The AI ​​assistant can generate personalized weekly reports based on user input. This not only meets the personalized needs of different team members, but also enhances the pertinence and practicality of the weekly reports, making it easier for team members to accept and recognize the content of the weekly reports.

[0130] (3) Promote real-time communication and collaboration: Real-time updated task management and reporting management functions enable team members to understand project progress and personal work status at any time, promote real-time communication and collaboration among team members, and reduce the possibility of information lag and misunderstanding.

[0131] (4) Improve team knowledge level: The integrated knowledge base management function provides team members with a convenient knowledge sharing platform, promotes the accumulation and inheritance of knowledge within the team, and improves the overall knowledge level and professional quality of the team.

[0132] (5) The user interface is user-friendly and easy to operate, allowing team members to quickly get started, lowering the usage threshold and increasing the popularity and utilization of the system.

[0133] (6) Support data-driven decision-making: Through AI intelligent summary, team managers can quickly obtain the overall situation of the team's work, including key data such as project progress and member performance, providing strong support for decision-making and improving the accuracy and timeliness of decision-making.

[0134] (7) Enhance team collaboration and cohesion: The embodiments of the present application enhance information sharing and communication among team members by providing a series of efficient and convenient collaboration tools, promote the improvement of team collaboration and cohesion, and lay a solid foundation for building an efficient and harmonious team culture.

[0135] In summary, the embodiment of the present application not only improves the efficiency and quality of team collaboration by integrating AI technology, but also promotes knowledge sharing and communication within the team, providing a modern enterprise with an efficient and intelligent team collaboration solution. This helps to improve the overall operational efficiency and market competitiveness of the enterprise.

[0136] like Figure 6 As shown, Figure 6 The present invention provides a schematic diagram of the structure of an electronic device 600, wherein the electronic device 600 includes:

[0137] A processor 601, a storage medium 602 and a bus 603, wherein the storage medium 602 stores machine-readable instructions executable by the processor 601. When the electronic device 600 is running, the processor 601 communicates with the storage medium 602 via the bus 603, and the processor 601 executes the machine-readable instructions to perform the steps of the AI-based weekly report processing method described in the embodiment of the present application.

[0138] In actual application, the components in the electronic device 600 are coupled together via the bus 603. It is understood that the bus 603 is used to realize the connection and communication between these components. In addition to the data bus, the bus 603 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 6 Various buses are labeled as bus 603.

[0139] The electronic device has the following beneficial effects:

[0140] (1) Significantly improve work efficiency: Through intelligent processing and the use of AI big model capabilities, weekly reports are automatically generated, which greatly reduces the time and labor intensity of manual weekly report preparation, allowing team members to devote more energy to core business, thereby significantly improving overall work efficiency.

[0141] (2) Meeting personalized needs: The AI ​​assistant can generate personalized weekly reports based on user input. This not only meets the personalized needs of different team members, but also enhances the pertinence and practicality of the weekly reports, making it easier for team members to accept and recognize the content of the weekly reports.

[0142] (3) Promote real-time communication and collaboration: Real-time updated task management and reporting management functions enable team members to understand project progress and personal work status at any time, promote real-time communication and collaboration among team members, and reduce the possibility of information lag and misunderstanding.

[0143] (4) Improve team knowledge level: The integrated knowledge base management function provides team members with a convenient knowledge sharing platform, promotes the accumulation and inheritance of knowledge within the team, and improves the overall knowledge level and professional quality of the team.

[0144] (5) The user interface is user-friendly and easy to operate, allowing team members to quickly get started, lowering the usage threshold and increasing the popularity and utilization of the system.

[0145] (6) Support data-driven decision-making: Through AI intelligent summary, team managers can quickly obtain the overall situation of the team's work, including key data such as project progress and member performance, providing strong support for decision-making and improving the accuracy and timeliness of decision-making.

[0146] (7) Enhance team collaboration and cohesion: The embodiments of the present application enhance information sharing and communication among team members by providing a series of efficient and convenient collaboration tools, promote the improvement of team collaboration and cohesion, and lay a solid foundation for building an efficient and harmonious team culture.

[0147] In summary, the embodiment of the present application not only improves the efficiency and quality of team collaboration by integrating AI technology, but also promotes knowledge sharing and communication within the team, providing a modern enterprise with an efficient and intelligent team collaboration solution. This helps to improve the overall operational efficiency and market competitiveness of the enterprise.

[0148] The embodiment of the present application also provides a computer-readable storage medium, which stores executable instructions. When the executable instructions are executed by at least one processor 601, the AI-based weekly report processing method described in the embodiment of the present application is implemented.

[0149] In some embodiments, the storage medium can be a magnetic random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a magnetic surface storage, an optical disk, or a compact disc read-only memory (CDROM); it can also be various devices including one or any combination of the above memories.

[0150] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0151] As an example, executable instructions may, but do not necessarily, correspond to a file in a file system, may be stored as part of a file that stores other programs or data, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (for example, files storing one or more modules, subroutines, or code portions).

[0152] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0153] The computer-readable storage medium has the following advantages:

[0154] (1) Significantly improve work efficiency: Through intelligent processing and the use of AI big model capabilities, weekly reports are automatically generated, which greatly reduces the time and labor intensity of manual weekly report preparation, allowing team members to devote more energy to core business, thereby significantly improving overall work efficiency.

[0155] (2) Meeting personalized needs: The AI ​​assistant can generate personalized weekly reports based on user input. This not only meets the personalized needs of different team members, but also enhances the pertinence and practicality of the weekly reports, making it easier for team members to accept and recognize the content of the weekly reports.

[0156] (3) Promote real-time communication and collaboration: Real-time updated task management and reporting management functions enable team members to understand project progress and personal work status at any time, promote real-time communication and collaboration among team members, and reduce the possibility of information lag and misunderstanding.

[0157] (4) Improve team knowledge level: The integrated knowledge base management function provides team members with a convenient knowledge sharing platform, promotes the accumulation and inheritance of knowledge within the team, and improves the overall knowledge level and professional quality of the team.

[0158] (5) The user interface is user-friendly and easy to operate, allowing team members to quickly get started, lowering the usage threshold and increasing the popularity and utilization of the system.

[0159] (6) Support data-driven decision-making: Through AI intelligent summary, team managers can quickly obtain the overall situation of the team's work, including key data such as project progress and member performance, providing strong support for decision-making and improving the accuracy and timeliness of decision-making.

[0160] (7) Enhance team collaboration and cohesion: The embodiments of the present application enhance information sharing and communication among team members by providing a series of efficient and convenient collaboration tools, promote the improvement of team collaboration and cohesion, and lay a solid foundation for building an efficient and harmonious team culture.

[0161] In summary, the embodiment of the present application not only improves the efficiency and quality of team collaboration by integrating AI technology, but also promotes knowledge sharing and communication within the team, providing a modern enterprise with an efficient and intelligent team collaboration solution. This helps to improve the overall operational efficiency and market competitiveness of the enterprise.

[0162] In the several embodiments provided in the present application, it should be understood that the disclosed methods and electronic devices can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units 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 can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0163] The modules described as separate components may or may not be physically separated, and the components shown as modules 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.

[0164] 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.

[0165] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a platform server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, or optical disks.

[0166] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A weekly report processing method based on AI, characterized in that: The method comprises: In response to a first triggering operation on a target control, displaying a first input control in a target document; In response to a selection operation in the first input control, determining a first creation requirement from at least one creation requirement; In response to an input operation in the first input control, displaying first input content, and after confirming the first input content, displaying first target content generated by AI under the first creation requirement; In response to a confirmation operation on the first target content, the first target content is inserted into the target document.

2. The method according to claim 1, characterized in that: The method further comprises: After determining the designated content in the target document, in response to a second trigger operation on the target control, displaying the at least one creation requirement; wherein the designated content is determined by selecting in the target document; In response to determining a second creation requirement from the at least one creation requirement, displaying a second target content generated by the AI ​​under the second creation requirement; wherein the second creation requirement is a summary and / or generalization requirement; and the second target content is a summary and / or generalization content of the specified content; In response to a confirmation operation on the second target content, the second target content is inserted into the target document.

3. The method according to claim 1, characterized in that The method further comprises: In response to the report request, displaying a report interface in the human-computer interaction interface; wherein the report interface includes at least one report item; In response to a third trigger operation on the target control, displaying a second input control; wherein the second input control includes a target template matching the at least one reporting item; In response to an input operation in the target template, display a second input content, and after confirming the second input content, display a third target content generated by AI; wherein the third target content includes at least one sub-content corresponding to the target template; In response to a confirmation operation on the specified content in the at least one sub-content, the specified content is inserted into a corresponding report item in the at least one report item.

4. The method according to claim 3, characterized in that The method further comprises: Respond to trigger operations on summary controls and obtain report information; Performing statistical processing based on the reported information to obtain statistical results; A summary interface is displayed in the human-computer interaction interface; wherein the summary interface includes summary information, and the summary information is determined based on the statistical results.

5. The method according to any one of claims 1 to 4, characterized in that: The target control and related components of the target control are built based on Vue2, and the input content sent by the target control is sent to the Egg.js server based on the HTTP client.

6. The method according to claim 5, characterized in that The Egg.js server predefines a target interface for receiving input content, and the Egg.js server obtains the AI-generated content by sending an HTTP request to the large model API.

7. The method according to any one of claims 1 to 4, characterized in that: The AI ​​pre-configures at least one scene template corresponding to the creation requirements; the method further includes: In response to the modification / replacement / addition / deletion operations on the scene template, the scene template is adjusted so that the AI ​​meets the business needs.

8. An AI-based weekly report processing device, characterized in that: The device comprises: A first display module, configured to display a first input control in a target document in response to a first trigger operation on a target control; A selection module, configured to determine a first creation requirement from at least one creation requirement in response to a selection operation in the first input control; A second display module, configured to respond to an input operation in the first input control, display a first input content, and after confirming the first input content, display a first target content generated by AI under the first creation requirement; The inserting module is used to respond to a confirmation operation on the first target content and insert the first target content into the target document.

9. An electronic device, characterized in that: include: A processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to execute the AI-based weekly report processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the AI-based weekly report processing method according to any one of claims 1 to 7 is executed.

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