Methods, apparatuses, devices, media, and products for task processing

Abstract

A method, apparatus, device, storage medium, and computer program product for task processing are provided. The method includes receiving a first input. The method also includes displaying first information, where the first information indicates that first content is being generated, the first content corresponding to the first input. The method also includes receiving a second input. The method also includes displaying the first content. The method also includes displaying second information, where the second information indicates that second content is being generated, the second content corresponding to the second input.

Description

Technical Field

[0001] It generally relates to the field of computers, and more specifically to methods, apparatus, devices, computer-readable storage media, and computer program products for task processing. Background Technology

[0002] Machine learning models are currently in a phase of rapid development, and with continuous technological iteration and innovation, their application scenarios and performance boundaries are constantly expanding. Machine learning technology, with language models as a typical example, has formed relatively mature high-level natural language understanding and generation capabilities by relying on large-scale data training and deep neural network architecture.

[0003] In practical applications, this type of model can efficiently handle cross-domain and multi-level user queries, demonstrating outstanding performance in scenarios such as daily consultations and professional Q&A. It is now widely used in fields such as intelligent customer service, educational tutoring, and professional consulting. Taking the programming field as an example, machine learning models, through learning from and logically reasoning about massive amounts of code, can accurately transform natural language descriptions into grammatically correct and logically complete executable code, helping developers efficiently complete feature development. Summary of the Invention

[0004] A method, apparatus, device, computer storage medium, and computer program product for task processing are provided. In a first aspect, a method for task processing is provided, comprising receiving a first input. The method further comprises displaying first information, wherein the first information indicates that first content is being generated, the first content corresponding to the first input. The method further comprises receiving a second input. The method further comprises displaying the first content. The method further comprises displaying second information, wherein the second information indicates that second content is being generated, the second content corresponding to the second input. This method can simultaneously process multiple task flows and rationally schedule and present responses upon output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0005] In a second aspect, an apparatus for task processing is provided, comprising a first receiving module configured to receive a first input. The apparatus also includes a first display module configured to display first information, wherein the first information indicates that first content is being generated, and the first content corresponds to the first input. The apparatus further includes a second receiving module configured to receive a second input. The apparatus also includes a second display module configured to display the first content. Finally, the apparatus includes a third display module configured to display second information, wherein the second information indicates that second content is being generated, and the second content corresponds to the second input. This apparatus can simultaneously process multiple task flows and rationally schedule and present responses during output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0006] In a third aspect, an electronic device is provided, comprising: at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the electronic device to perform a method for task processing, the method including receiving a first input. The method further includes displaying first information, wherein the first information indicates that first content is being generated, the first content corresponding to the first input. The method further includes receiving a second input. The method further includes displaying the first content. The method further includes displaying second information, wherein the second information indicates that second content is being generated, the second content corresponding to the second input. This electronic device is capable of simultaneously processing multiple task flows and rationally scheduling and presenting responses upon output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0007] In a fourth aspect, a computer-readable storage medium is provided having machine-executable instructions stored thereon, which, when executed by a device, cause the device to perform a method for task processing, the method including receiving a first input. The method further includes displaying first information, wherein the first information indicates that first content is being generated, the first content corresponding to the first input. The method further includes receiving a second input. The method further includes displaying the first content. The method further includes displaying second information, wherein the second information indicates that second content is being generated, the second content corresponding to the second input. This computer-readable storage medium is capable of simultaneously processing multiple task streams and rationally scheduling and presenting responses upon output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0008] In a fifth aspect, a computer program product is provided, including computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement a method for task processing, the method including receiving a first input. The method further includes displaying first information, wherein the first information indicates that first content is being generated, the first content corresponding to the first input. The method further includes receiving a second input. The method further includes displaying the first content. The method further includes displaying second information, wherein the second information indicates that second content is being generated, the second content corresponding to the second input. This computer program product can simultaneously process multiple task flows and rationally schedule and present responses during output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0009] The summary section is provided to introduce a series of concepts in a simplified form, which will be further described in the detailed description below. The summary section is not intended to identify key or essential features, nor is it intended to limit the scope. Other features will become readily apparent from the following description. Attached Figure Description

[0010] Figure 1A A schematic diagram of an example environment implemented in one scenario is shown;

[0011] Figure 1B A schematic diagram of the interface used for task processing is shown;

[0012] Figure 2 A flowchart of the method for task processing is shown;

[0013] Figure 3 A schematic diagram of the prompt message is shown;

[0014] Figure 4 A schematic diagram illustrating the process of generating control responses is shown;

[0015] Figure 5 A schematic diagram illustrating the process of adjusting response priorities is shown;

[0016] Figure 6 A schematic diagram showing multiple replies is provided.

[0017] Figure 7 A schematic diagram of the framework for parallel input processing is shown;

[0018] Figure 8 A schematic block diagram of a device for task processing is shown; and

[0019] Figure 9 A block diagram of an electronic device is shown.

[0020] In all the accompanying figures, the same or similar reference numerals denote the same or similar elements. Detailed Implementation

[0021] The names of the messages or information exchanged between multiple devices in each scenario are for illustrative purposes only and are not intended to limit the scope of these messages or information. It is understood that before using the disclosed technical solutions in each scenario, users should be informed of the type, scope of use, and usage scenarios of the personal information involved, and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0022] For example, upon receiving a user's active request, a prompt message can be sent to the user, explicitly informing them that the requested operation will require the acquisition and use of their personal information. This allows the user to choose whether to provide personal information to the software or hardware (electronic device, application, server, or storage medium) performing the operations described herein, based on the prompt message. As an optional but non-limiting implementation, the prompt message can be sent to the user in the form of a pop-up window, which can present the prompt message in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0023] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation method. Other methods that comply with relevant laws and regulations may also be applied in various situations.

[0024] The various scenarios will now be described in more detail with reference to the accompanying drawings. While some scenarios are shown in the drawings, it should be understood that implementations can take many forms and should not be construed as limited to the one scenario described herein. Rather, these scenarios are provided to provide a more thorough and complete understanding of the technical content. It should be understood that the drawings and scenarios are for illustrative purposes only and are not intended to limit the scope of protection.

[0025] In the descriptions of each situation, the term "comprising" and similar expressions should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The terms "a situation" or "the situation" should be understood as "at least one situation". The terms "first", "second", etc., may refer to different or the same objects unless explicitly stated. Other explicit and implicit definitions may also be included below.

[0026] Existing intelligent systems typically operate on a strict single-task processing model. Taking dialogue as an example, a user can only ask one question or issue one instruction (i.e., input) at a time, and the intelligent system must complete the current response before receiving the next input. This sequential interaction method has significant limitations: firstly, if the user asks a new question midway through, the content being generated is interrupted, preventing the task from being fully executed; secondly, users cannot supplement information, add questions, or initiate parallel tasks while the intelligent system is thinking or generating data, forcing the interaction process into segments and reducing task execution efficiency.

[0027] This application identifies the problem as stemming from the fact that users only interact with the intelligent system that directly provides content, and a single intelligent system can only process one input at a time. To address this, a method for task processing is proposed that allows users to continue inputting subsequent questions or instructions while the intelligent system generates content, without interrupting the execution of existing input. This method can simultaneously process multiple task streams and rationally schedule and present responses during output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0028] Figure 1A A schematic diagram of an example environment 100 implemented in one scenario is shown. Example environment 100 includes a user device 130 and a server 140. The server 140 may deploy a model (e.g., a machine learning model). The user device 130 has an application 110 installed. This application 110 can invoke the model on the server 140 by communicating with the server 140, or the application 110 can set up an intelligent system that can invoke the model on the server 140. In one scenario, the method is executed by the application 110 on the user device 130. As an example, a user can converse with the intelligent system or model on the application 110 to perform tasks, but this does not limit the method. In some scenarios, the user can utilize the intelligent system to perform non-conversational tasks. For ease of description, a conversational scenario is used as an example.

[0029] In some scenarios, user 150 can launch application 110 using user device 130. Application 110 can communicate with server 140 via a network. In some scenarios, user 150 operates application 110 on user device 130 to initiate a business request (e.g., a request containing user input sent to the intelligent system); user device 130 encapsulates the request and sends it to server 140 via the network; server 140 parses the received request, uses the intelligent system to execute corresponding business processing operations (such as model invocation, data query, logical operation, content delivery, etc.), and returns the processing result to user device 130; user device 130 visualizes the processing result through application 110 for user 150 to view, thereby completing the interaction between the client and server sides. In some scenarios, application 110 can complete the steps of this method based on communication and cooperation with server 140.

[0030] Figure 1B A schematic diagram of the interface used for task processing is shown. In some cases, user 150 can create a dialogue window in application 110 to communicate with the intelligent system, and provide input 112, "Help me write a website about travel" (i.e., the first input), in the dialogue window. In some cases, application 110 can receive input 112. After receiving input 112, it can be fed into the model, which can generate corresponding response content based on its trained knowledge.

[0031] In some scenarios, if input 112 is received, application 110 can display information 114 (i.e., the first message), where information 114 indicates that content 120 (i.e., an example of the first content) is being generated. This information 114 could be, for example, "Received! The tourism industry is booming lately, so I'm writing a tourism website. By the way, you can adjust your requirements at any time in subsequent conversations..."

[0032] This message 114 is not a final response to input 112, but rather immediate feedback upon receiving input 112. It informs user 150 that input 112 has been successfully received and how to proceed with it, such as immediately starting to generate content for input 112, or waiting a short while before generating content. This immediate feedback, delivered immediately after user 150 enters the question, eliminates user uncertainty about whether their input has been processed, thus improving the user experience.

[0033] In some scenarios, application 110 can acquire input 116 (i.e., a second input) before displaying content 120. For example, after application 110 displays information 114 and before displaying content 120, user 150 can continue typing input 116 through the input component in the same dialog window to provide to application 110. For example, input 116 could be "Help me compare printer 1 and printer 2, which is better?". In some scenarios, application 110 can receive input 116 while generating content 120. For example, application 110 can be configured with a first intelligent system that can acquire input, generate information 114 and subsequent information 118 (i.e., generate immediate feedback), and can also create new intelligent systems or call other preset intelligent systems in application 110, assigning input to a specific intelligent system to generate a corresponding response. In this way, application 110 can receive input 116 while generating content 120.

[0034] In some scenarios, if content 120 is generated, application 110 can display content 120. For example, content 120 could be something like, "Also, the task of writing the travel website is complete! I designed the website like this..." and provide the corresponding deliverables within content 120. It's worth noting that regardless of when the second input is received, the generation and display of the first content proceed according to its own logic and rhythm, undisturbed. This demonstrates that the processing flow of the first task is independent and protected. The final display of content 120 marks the completion of the first parallel task loop.

[0035] In some scenarios, application 110 can display information 118 (i.e., the second information), which indicates that content 122 (i.e., the second content) is being generated. Similarly, information 118 is an immediate confirmation of input 116, informing user 150 that the second input has also been successfully received and entered the parallel processing queue. This design, which provides immediate responses to each input, continuously ensures the user's sense of certainty and control during parallel input, optimizing the overall experience during multi-input interactions.

[0036] In some scenarios, if content 122 is generated, application 110 can display content 122, which is used to respond to input 116. For example, content 122 could be something like, "Regarding printer 1 and printer 2, which you are concerned about, I have found out the details. The comparative analysis of the two can be summarized as follows:..." Ultimately, the responses to the two tasks (content 120 and content 122) are presented sequentially and completely in the dialog window. The user efficiently obtains detailed responses to two independent questions within a continuous dialog session, without repeatedly opening new dialogs or performing a serial "ask-wait-ask again" operation. This scenario significantly improves input processing efficiency and user experience by allowing responses to be generated in parallel.

[0037] Through real-time feedback mechanisms, parallel input reception, and task processing scheduling, users can submit multiple inputs continuously in a single window and simultaneously receive parallel processing and content generation from these inputs. This not only significantly improves the efficiency of the intelligent system in handling multiple inputs but also allows users to interact continuously without waiting, enhancing the user experience.

[0038] User equipment 130 can be any type of mobile computing device, including mobile computers (e.g., personal digital assistants, laptops, notebooks, tablets, netbooks, etc.), mobile phones (e.g., cellular phones, smartphones, etc.), wearable computing devices (e.g., smartwatches, head-mounted devices, including smart glasses, etc.) or other types of mobile devices. In some cases, user equipment 130 can also be a fixed computing device, such as a desktop computer, game console, smart TV, etc. It should be understood that the above operations can be performed jointly by user equipment 130 and server 140.

[0039] It should be understood that the instance of server 140 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. Server 140 can be connected directly or indirectly through wired or wireless communication, and this application does not impose any restrictions.

[0040] It should be understood that the architecture and functionality in the example environment are described for illustrative purposes only and do not imply any limitation on the scope. The scenarios can also be applied to other environments with different structures and / or functionalities.

[0041] The processes of each scenario will be described in detail below with reference to other accompanying drawings. For ease of understanding, the specific data mentioned in the following description are exemplary and are not intended to limit the scope of protection. It is understood that the scenarios described below may also include additional actions not shown and / or the actions shown may be omitted, and their scope is not limited in this respect.

[0042] Figure 2 A flowchart of a method 200 for task processing is shown. In this case, it can be performed by... Figure 1A The application 110 on the user's device executes this method. In box 202, the first input is received. The first input can be the first task or question entered by the user. For example, the user enters in the smart assistant's dialog window: "Help me create a workout plan for this Friday." The application successfully receives and parses this text, thus completing the reception of the first input.

[0043] In box 204, first information is displayed, indicating that first content is being generated, and this first content corresponds to the first input. This first information could be, for example,... Figure 1B Information 114 is used for immediate feedback.

[0044] In box 206, the second input is received. In this step, the second input is entered before the first content is displayed, and the processing flow for the first input is not interrupted. For example, while the application is generating the "Friday Fitness Plan" (the first content) in the background, the user does not have to wait and immediately enters a second question in the same dialog window: "Also, recommend a few healthy meal delivery places nearby." The application can successfully receive this new question before the fitness plan is generated and displayed.

[0045] In box 208, the first content is displayed. Once the application has completed all processing of the first input and generated the final result (the first content), the display operation can be performed. Display can refer to presenting the generated response content to the user. For example, after the application completes the creation of a fitness plan, it outputs in the dialog window: "This is your fitness plan for this Friday: 1. Warm-up... 2. Resistance training... 3. Aerobic exercise...".

[0046] In box 210, a second piece of information is displayed, indicating that second content is being generated, and this second content corresponds to the second input. This second piece of information is similar to the first piece of information; for example, it could be... Figure 1B Information 118 is used for immediate feedback.

[0047] In some cases, the application outputs the result (second content) after processing the second input. In other cases, the display of the second content is independent of the display sequence of the first content, regardless of when the second input is acquired.

[0048] Figure 2 The method shown can process multiple task flows simultaneously and rationally schedule and present responses during output. This improvement not only significantly enhances task execution efficiency but also makes human-computer dialogue closer to the natural, continuous, and parallel communication experience between humans, thereby improving the user experience.

[0049] Figure 3A schematic diagram of the prompt message is shown. In some cases, the first input 314 includes a first sub-input and a second sub-input. That is, the first input 314 can be a composite input, such as "There are two tasks: 1. Help me analyze the performance of computer 3; 2. Help me write a blessing." In some cases, the first information indicates that the first sub-content and the second sub-content are being generated. After obtaining the first input 314, application 310 can perform semantic analysis on the first input 314 to determine that the first input 314 involves multiple sub-inputs (e.g., two sub-inputs), and can generate a corresponding response for each sub-input separately. In some cases, application 310 can be equipped with a first intelligent system for distributing tasks to other intelligent systems. After recognizing the semantic information of the first input 314, the first intelligent system generates task 1 and task 2, where task 1 is to analyze computer performance and task 2 is to write a blessing.

[0050] In some scenarios, application 310 may display suggestion 316 (i.e., the first suggestion), where suggestion 316 indicates that the first sub-input and the second sub-input should be responded to respectively. For example, after receiving the first input 314, application 310 may display a pop-up window with suggestion 316, which could be something like, "These are two tasks, and they are not closely related. Do you need to process these two tasks in parallel? These two tasks are..." In some scenarios, if the user clicks the "Yes" button, application 310 can process the two sub-inputs in parallel. In some scenarios, if the user clicks the "No" button, application 310 can process the two sub-inputs as a single input, rather than processing them in parallel.

[0051] In some scenarios, when processing two sub-inputs in parallel, the first intelligent system can create or invoke two other intelligent systems: a second and a third intelligent system. In some cases, the second intelligent system handles task 1, and the third intelligent system handles task 2. In others, the first intelligent system can obtain response 1 (an example of the first sub-content) and response 2 (an example of the second sub-content) from the second and third intelligent systems. In this scenario, semantic analysis can automatically identify multiple sub-tasks in the input (such as "analyze computer performance" and "write a blessing") and proactively suggest parallel processing to the user, such as generating the first and second sub-contents separately. After user confirmation, different intelligent systems are scheduled to independently process each sub-task, thus achieving true parallel execution of tasks and response generation. This mechanism transforms the traditional serial task queue into a parallel processing flow, significantly improving overall efficiency and system throughput when processing complex inputs. Furthermore, by giving users control over task splitting and providing immediate status feedback, it optimizes the flexibility of interaction and user experience.

[0052] In some scenarios, when processing two sub-inputs in parallel, application 310 can display a third message indicating that the first and second sub-contents are being generated in parallel. This third message can be generated by the model invoked by the first intelligent system, serving as immediate feedback and enhancing the user experience. For example, the first message could be "Received! Processing these two tasks in parallel."

[0053] In some cases, if the first sub-content is generated, it is displayed. In other cases, if the second sub-content is generated, it is displayed. Once the application has finished processing both sub-inputs, it can output the result. The display order of these two sub-contents is independent. For example, whichever sub-content is generated first is displayed first. As mentioned above, these two sub-contents can be the results directly generated by the second and third intelligent systems. In some cases, the first intelligent system can aggregate the results directly generated by the second and third intelligent systems and merge them into the first content for display.

[0054] By performing intelligent semantic analysis on complex user input and identifying multiple independent subtasks, the application can proactively suggest parallel processing to the user, thus transforming the traditional serial task queue into a parallel processing flow. After user confirmation, the application can schedule multiple intelligent systems (such as second and third intelligent systems) to independently process different subtasks, achieving true parallel execution and response generation. This mechanism not only significantly improves the overall processing efficiency and system throughput in complex input scenarios but also empowers the user with control over input splitting by proactively providing processing suggestions (such as pop-up confirmations) and real-time status feedback. This enhances processing efficiency while also optimizing interaction flexibility and user experience.

[0055] Figure 4 A schematic diagram illustrating the process of generating a control response is shown. In some cases, before displaying the first content, application 410 can obtain a stop instruction (i.e., a third input), which instructs the user to stop generating the first content. For example, the first intelligent system can understand the semantics of the stop instruction to identify the user's intent to stop generating the first content. For example, the stop instruction could be "stop writing the website" or "cancel the previous question," etc. Technically, the first intelligent system can use a lightweight intent classification model to determine in real time whether a newly input statement from the user is a "cancel" instruction for a specific task, and can determine which ongoing task the instruction targets through a task index (e.g., the task corresponding to input 112). In some cases, the first intelligent system can send an instruction to other intelligent systems (e.g., a second intelligent system) undertaking the corresponding task, requesting them to stop generating the response. Upon receiving this instruction, the second intelligent system can immediately interrupt its model inference process and release the occupied computing resources (e.g., GPU memory).

[0056] In some cases, after understanding the semantics of the stop command, application 410 can stop displaying the first content. In other cases, after understanding the semantics of the stop command, application 410 can remove content associated with input 112 that has not yet been displayed from the dialog's display queue, thereby stopping the display of the first content. In this way, the user will not see a response to input 112. This mechanism technically implements a "resource circuit breaker," preventing the continued waste of computing resources when the user clearly does not need them.

[0057] In some scenarios, if a pause instruction 412 (i.e., the first instruction) is received before displaying content 120 and content 122, application 410 can pause the generation of content 120 and continue generating content 122. The pause instruction 412 is used to pause processing of input 112. For example, a first intelligent system sends a pause instruction to a second intelligent system. Upon receiving the pause instruction, the second intelligent system does not immediately destroy the task but serializes and saves the current task's state (such as the intermediate state of model inference, generated partial text, task context, etc.) to memory or temporary storage, and then relinquishes computing resources. Meanwhile, the intelligent system responsible for processing input 116 (printer comparison) (such as a third intelligent system) remains completely unaffected and continues running. In this scenario, the execution states of multiple intelligent systems can be managed, and suspending and resuming individual tasks is supported.

[0058] In some scenarios, if instruction 414 (i.e., the second instruction) is received, application 410 can continue generating the first content, where instruction 414 is used to resume processing for input 112. A continue instruction (such as "Continue writing the website") can trigger the first intelligent system to send a request to the second intelligent system, instructing the second intelligent system to resume task execution from the previously saved intermediate state. From the user's perspective, the generation of the response appears to continue seamlessly from the point of interruption. For example, if the website outline had already been generated when the pause occurred, resuming might start from writing specific chapter content, rather than starting from scratch. This pause / continue mechanism enables dynamic task priority adjustment and time-division multiplexing of computing resources in scenarios where users want to temporarily switch to higher-priority but unrelated smaller tasks (such as querying printer information) while handling time-consuming tasks such as generating long documents or complex analyses. This makes multi-task parallel interaction more flexible and user-friendly.

[0059] Figure 5A schematic diagram illustrating the process of adjusting response priorities is shown. In some cases, application 510 may receive instruction 512 from the user, which may indicate the priority of previous inputs. For example, instruction 512 could be "process the printer comparison task first, then process other tasks," assuming that three inputs have been provided to application 510 before instruction 512 is input. Then, upon receiving instruction 512, the first intelligent system can first perform semantic analysis to identify that the user's intent is "adjust task priorities," and clarify the target task ("printer comparison task") and the desired priority ("process first") in the instruction.

[0060] In some scenarios, the first intelligent system can query its maintained task status table, which records information such as the task ID of each ongoing task, the corresponding user input, the intelligent system responsible for processing it, and its current status (e.g., queued, generating, paused). By matching, it locates the "compare printer" task (e.g., this is the second input) and its current status.

[0061] In some scenarios, the first intelligent system can send a priority update instruction to the task scheduler. This scheduler manages the sequence of accesses to computing resources (such as model inference instances) by all generated tasks. In other scenarios, upon receiving the instruction, the scheduler dynamically adjusts its internal task queue order based on a new priority strategy (e.g., elevating the target task to "highest" priority). For low-priority tasks currently being generated, the scheduler can send a "temporarily suspend" instruction, allowing them to preserve their intermediate state and temporarily relinquish computing resources; for tasks that have not yet started or have been suspended, they are rearranged according to the new order. In this scenario, the user can dynamically adjust the priority of specific tasks via natural language instructions during the parallel processing of multiple tasks. This enables flexible scheduling of multi-task interaction processes based on the user's real-time intent, thereby optimizing the allocation of computing resources and improving overall interaction efficiency.

[0062] In some scenarios, computing resources can be prioritized for the "Compare Printers" task to accelerate its generation. Application 510 can send immediate feedback to the user, such as displaying the message: "Instruction accepted, prioritizing the 'Printers Compare' task." Once this task is completed, the scheduler then schedules the remaining tasks in the updated order (e.g., processing the printer task first, then the original first and third tasks in sequence).

[0063] This mechanism empowers users to dynamically manage processes during parallel task execution. When user needs change or the urgency of certain tasks increases, users can flexibly rearrange the processing order within the system without canceling any tasks, thereby optimizing the overall task completion sequence and making the interaction of multiple tasks in parallel more in line with the user's real-time intentions.

[0064] In some scenarios, the first piece of content can be displayed. In other scenarios, if no action is taken on the first piece of content within a preset time period, its display area is reduced. This action can be any explicit user interaction, such as clicking on a reply, selecting text, hovering the mouse pointer over the content area, or interacting with a form element associated with the content (such as a "copy" button). If, when the second piece of content is displayed, the application detects that the user has not performed any of the above actions on the first piece of content within a preset time period (e.g., 3-5 seconds), it triggers interface collapse logic, for example. For instance, the front-end calls a collapse animation function to dynamically adjust the height of the display area containing the first piece of content (such as a container) to only display the title or summary, hiding the detailed content and thus reducing its screen space usage. This mechanism implements an "automatic organization" function for the chat interface. Its core logic is to infer that the user's attention has shifted from a completed old task to a new one, thereby proactively optimizing the limited screen space layout and preventing the interface from becoming lengthy and requiring frequent manual scrolling due to multiple long replies stacked sequentially.

[0065] In some scenarios, if second content is generated, it is highlighted based on the reduced display area. In others, the application can temporarily increase the border width of the container containing the second content and use a high-contrast color (such as a blue border). In still others, the application can briefly change its background color (such as a light yellow highlight). And in some cases, the application can add a dynamic indicator next to the container, such as a "new message" badge or a subtle pulsating animation. Meanwhile, the container for the first content, having been collapsed, is visually "inactive" (e.g., using a lighter font color and a gray border). This dynamic style adjustment based on task status clearly establishes the hierarchy of information visually, automatically drawing the user's attention to the most recently completed task result, thereby enhancing the user experience.

[0066] Figure 6A schematic diagram showing multiple responses is illustrated. The user can provide inputs 612 and 614 in application 610. Application 610 can display responses in the bottom area of ​​the dialog window. In some cases, when a first intelligent system creates or invokes a new intelligent system to handle a task, a unique task ID can be generated for that task, and a "Create New Task View" event can be sent to the front-end interface. Upon receiving this event, the front-end interface (such as a web-based application) can dynamically insert a new sub-area component with the corresponding task ID identifier within a preset display area. In some cases, responses can be displayed in several sub-areas of the bottom area, with the number of sub-areas matching the number of responses being generated. For example, in some cases, the generation process of the first content is displayed in the first area 616 of the interface, and the generation process of the second content is displayed in the second area 618 of the interface.

[0067] Each sub-region can be an independent message stream, with an internal structure similar to the main dialogue history, but containing only content relevant to that specific task: the top displays the corresponding original user input, while the bottom streams partial response text generated by the intelligent system in real time. This design technically achieves stacked management of the dialogue context, making the progress of multiple independent tasks clear at a glance and without interference between them.

[0068] In some scenarios, the application can obtain modification instructions before displaying the initial content, which modify the initial input. This step allows the user to dynamically adjust or refine their requirements during task execution. Users can issue modification instructions through various interactive methods, such as sending a natural language instruction like "Wait, the website I mentioned earlier needs to add mobile adaptation requirements" or "Change the budget in my first question from 5000 to 8000." The application (or its primary intelligent system) needs to parse this new input in real time, recognizing through semantic understanding and contextual association that it is a modification intent for a specific ongoing task (such as one bound to a task ID), rather than a new, independent task. In some scenarios, the application can stop displaying the initial content. This means the user will not see a response to the original input. In some scenarios, the application can display third content, which corresponds to both the modification instruction and the initial input.

[0069] The third content is the final result generated based on a new task description that incorporates the modification instructions. For example, an application can semantically fuse the modification instructions with the original input to construct an updated, complete task instruction. For instance, if the original instruction is "write a travel website" and the modification instruction is "add mobile adaptation," the fused instruction might be "write a travel website that supports mobile adaptation." Once generated, it is displayed in the original "first content" position (or associated sub-region) in the dialog flow. This achieves a "task iteration in place" effect, supporting an efficient and exploratory creative process. Users do not need to initiate a completely independent new dialog due to minor changes in requirements, thus maintaining task coherence and contextual consistency.

[0070] In some scenarios, when multiple inputs are received, the assistant intelligent system in the application can set up a sub-intelligent system for each input, with each sub-intelligent system handling one input. In other scenarios, when processing multiple inputs, the assistant intelligent system can utilize persistent containers to manage historical information. For example, when a user asks the first independent question, "Please explain what ABC is?", the assistant intelligent system can dispatch it to a lightweight question-answering intelligent system, which generates a response 1 in the persistent container: "ABC is a technical architecture that combines information retrieval and a large language model..." and saves this response, associated with the question, to the container. When the user subsequently asks a related follow-up question, "Please write a simple ABC retrieval example code in C++", the assistant intelligent system can handle this new task in the persistent container, dispatching the corresponding intelligent system to generate a response 2 containing example code. After the task is completed, this new dialogue record can also be saved back to the persistent container. In this way, the persistent container acts as a central storage, continuously accumulating and associating dialogue history, enabling the assistant intelligent system to understand the context in subsequent interactions and provide a more coherent experience.

[0071] When a user poses a more comprehensive follow-up question (e.g., "Based on the previous explanations and code, summarize the main advantages of ABC"), the assistant's intelligent system can first analyze the semantics of the input, identifying its relevance to previously saved responses 1 and 2 from the historical dialogue. Subsequently, it retrieves these two responses from a persistent container as the core context for generating a new response. The assistant's intelligent system does not simply piece together the original content; instead, it fuses and abstracts information from the retrieved explanatory text and code instances, ultimately generating a new, more insightful response (e.g., clearly listing ABC's core advantages in accuracy and traceability), thus achieving deep information aggregation and reasoning across multiple rounds of dialogue.

[0072] Figure 7A schematic diagram of a framework for parallel input processing is shown. In some cases, the assistant intelligent system 710 can have a corresponding relationship with a user, with each user having their own assistant intelligent system 710. This assistant intelligent system 710 can be stored in a persistent container, allowing it to store all of the user's historical interactions, inputs, and corresponding responses and outputs. The assistant intelligent system 710 can use this information to enhance its understanding of the user; for example, it can generate user-related information. Each time a user uses the assistant intelligent system 710, it can process the user's input based on this user-related information, making the input more aligned with the user's needs and thus improving the accuracy of the responses.

[0073] In some cases, user requests (i.e., inputs) are submitted through applications (such as various software applications), web pages, or other front-end channels. All these inputs are uniformly aggregated into the Assistant Intelligent System 710. The Assistant Intelligent System 710, acting as the system's unified access and coordination center, is responsible for receiving and initially understanding all concurrent user requests.

[0074] In some scenarios, after initial parsing of the input, the assistant intelligent system 710 passes it to the configuration module 712. At this point, the core resource scheduling and preparation phase begins, where the assistant intelligent system 710 can dynamically configure resources for the tasks required to process the input within the configuration module 712. It reads or writes historical states and configurations from the file system and selects and assembles the necessary capabilities for task execution from the shared resource pool 714 (including toolkits, custom configurations, and skills). In particular, when multiple tasks need to be processed in parallel, the assistant intelligent system 710 can instantiate or invoke different sub-intelligent systems for different tasks and independently configure the dedicated resources required by each sub-intelligent system.

[0075] In some scenarios, after resource configuration is completed, the assistant intelligent system 710 performs task assignment. The assistant intelligent system 710 precisely assigns the specific task instructions (i.e., the processing target) along with the configured resource environment to one or more specialized sub-intelligent systems (sub-intelligent systems 1, 2, and 3 in the figure). This step binds the task to the execution unit, ensuring that each sub-intelligent system can work independently in the correct context, and the responses generated by these sub-intelligent systems will be output.

[0076] In this scenario, a pipeline of input-configuration-dispatch-execution is systematically presented. Its core innovation lies in transforming serial task processing into a parallel intelligent system collaboration process through the dynamic scheduling and resource orchestration of the configuration module 712, thereby efficiently generating multiple responses.

[0077] Figure 8A schematic block diagram of a device 800 for task processing is shown. Device 800 can be implemented via software, hardware, or a combination of both. Figure 8 As shown, the device 800 includes a first receiving module 810, a first display module 820, a second receiving module 830, a second display module 840, and a third display module 850.

[0078] In some cases, the first receiving module 810 can be configured to receive a first input. The first display module 820 can be configured to display first information, wherein the first information indicates that first content is being generated, and the first content corresponds to the first input. The second receiving module 830 can be configured to receive a second input. The second display module 840 can be configured to display the first content. The third display module 850 can be configured to display second information, wherein the second information indicates that second content is being generated, and the second content corresponds to the second input.

[0079] In some cases, the first input includes a first sub-input and a second sub-input, the first information indicates that first sub-content and second sub-content are being generated, and the device 800 further includes: a first sub-content module configured to display the first sub-content in response to the generation of the first sub-content; and a second sub-content module configured to display the second sub-content in response to the generation of the second sub-content.

[0080] In some cases, the device 800 further includes a suggestion module configured to display a first suggestion, wherein the first suggestion indicates the generation of a first sub-content and a second sub-content, respectively.

[0081] In some cases, the device 800 further includes a third information module configured to display third information in response to receiving the first input, wherein the third information indicates that the first sub-content and the second sub-content are being generated in parallel.

[0082] In some cases, the device 800 further includes a region adjustment module configured to display the generation process of the first content in a first region of the interface and the generation process of the second content in a second region of the interface.

[0083] In some cases, the device 800 further includes: a third input module configured to acquire a third input, wherein the third input indicates to stop generating the first content; and a first stop display module configured to stop displaying the first content.

[0084] In some cases, the device 800 further includes: a first instruction module configured to pause the generation of first content and continue generating second content in response to receiving a first instruction, wherein the first instruction is used to pause the processing of the first input; and a second instruction module configured to continue generating the first content in response to receiving a second instruction, wherein the second instruction is used to resume the processing of the first input.

[0085] In some cases, the device 800 further includes: a content display module configured to display first content; an area reduction module configured to reduce the display area of ​​the first content in response to no operation on the first content being received within a preset time period; and a highlighting module configured to highlight the second content based on the reduced display area in response to the generation of the second content.

[0086] In some cases, the device 800 further includes: a modification module configured to acquire a modification instruction, wherein the modification instruction is used to modify the first input; a second stop display module configured to stop displaying the first content; and a third content module configured to display third content, wherein the third content corresponds to the modification instruction and the first input.

[0087] In each scenario, the division of modules or units is illustrative and represents only one logical functional division. In actual implementation, other division methods are possible. Furthermore, functional units can be integrated into one unit, exist as separate physical entities, or combine two or more units into a single unit. The integrated units described above can be implemented in hardware or as software functional units.

[0088] Figure 9 A block diagram of electronic device 900 is shown. It should be understood that... Figure 9 The electronic device 900 shown is merely an example and should not be construed as limiting the functionality and scope of the implementation described herein. For example, the electronic device 900 may correspond to the implementation described herein. Figure 1A The user equipment described above can be used to perform the above-described... Figures 1A to 7 The process. For example, electronic device 900 may correspond to the electronic device of the third aspect of the invention content.

[0089] like Figure 9 As shown, electronic device 900 is in the form of a general-purpose computing device. Components of electronic device 900 may include, but are not limited to, one or more processors or processing units 910, memory 920, storage device 930, one or more communication units 940, one or more input devices 950, and one or more output devices 960. Processing unit 910 may be a physical or virtual processor and is capable of performing various processes according to programs stored in memory 920. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capability of electronic device 900.

[0090] Electronic device 900 typically includes multiple computer storage media. Such media can be any available media accessible to electronic device 900, including but not limited to volatile and non-volatile media, removable and non-removable media. Memory 920 can be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof). Storage device 930 can be removable or non-removable media and can include machine-readable media, such as flash drives, disks, or any other media that can be used to store information and / or data (e.g., training data for training) and can be accessed within electronic device 900.

[0091] Electronic device 900 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not explicitly stated... Figure 9 As shown, disk drives for reading from or writing to removable, non-volatile disks (e.g., "floppy disks") and optical disk drives for reading from or writing to removable, non-volatile optical disks can be provided. In these cases, each drive can be connected to a bus (not shown) via one or more data media interfaces. Memory 920 may include computer program product 925 having one or more program modules configured to perform various methods or actions in various implementations.

[0092] The communication unit 940 enables communication with other computing devices via a communication medium. Additionally, the functionality of the components of the electronic device 900 can be implemented as a single computing cluster or multiple computing machines capable of communicating via communication connections. Therefore, the electronic device 900 can operate in a networked environment using logical connections to one or more other servers, network personal computers (PCs), or another network node.

[0093] Input device 950 can be one or more input devices, such as a mouse, keyboard, trackball, etc. Output device 960 can be one or more output devices, such as a monitor, speaker, printer, etc. Electronic device 900 can also communicate with one or more external devices (not shown) via communication unit 940 as needed. These external devices include storage devices, display devices, etc., and can communicate with one or more devices that enable user interaction with electronic device 900, or with any device that enables electronic device 900 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication can be performed via input / output (I / O) interface (not shown).

[0094] Furthermore, a computer-readable storage medium is provided that stores computer-executable instructions thereon, wherein the computer-executable instructions are executed by a processor to implement the method described above. This computer-readable storage medium may be a non-transitory computer-readable storage medium. Furthermore, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, which are executed by a processor to implement the method described above. Additionally, a computer program product is provided that stores a computer program thereon, which, when executed by a processor, implements the method described above.

[0095] This document describes various aspects of the scenarios with reference to flowcharts and / or block diagrams of methods, apparatuses, devices, and computer program products implemented according to the various scenarios. It should be understood that each block of the flowcharts and / or block diagrams, as well as combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0096] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0097] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions that execute on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0098] The flowcharts and block diagrams in the accompanying figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products based on multiple implementations. In this respect, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the figures. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0099] The implementations have been described above. The foregoing descriptions are illustrative and not exhaustive, nor are they limited to the disclosed implementations. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described implementations. The terminology used herein is chosen to best explain the principles, practical applications, or improvements to technology in the market, or to enable others skilled in the art to understand the various implementations disclosed herein.

Claims

1. A method for task processing, comprising: Receive the first input; Display first information, wherein the first information indicates that first content is being generated, and the first content corresponds to the first input; Receive the second input; Display the first content; as well as Display second information, wherein the second information indicates that second content is being generated, and the second content corresponds to the second input.

2. The method of claim 1, wherein the first input includes a first sub-input and a second sub-input, the first information indicating that first sub-content and second sub-content are being generated, and the method further includes: In response to the generation of the first sub-content, the first sub-content is displayed; as well as In response to the generation of the second sub-content, the second sub-content is displayed.

3. The method according to claim 2, further comprising: Display a first suggestion, wherein the first suggestion instructs the generation of the first sub-content and the second sub-content, respectively.

4. The method according to claim 2, further comprising: In response to receiving the first input, a third message is displayed, wherein the third message indicates that the first sub-content and the second sub-content are being generated in parallel.

5. The method according to claim 1, further comprising: The generation process of the first content is displayed in the first area of ​​the interface, and the generation process of the second content is displayed in the second area of ​​the interface.

6. The method according to claim 1, further comprising: Obtain a third input, wherein the third input indicates to stop generating the first content; as well as Stop displaying the first content.

7. The method according to claim 1, further comprising, before displaying the first content and the second content: In response to receiving a first instruction, the generation of the first content is paused and the generation of the second content continues, wherein the first instruction is used to pause the processing of the first input; as well as In response to receiving a second instruction, the first content continues to be generated, wherein the second instruction is used to resume the processing of the first input.

8. The method according to claim 1, further comprising: Display the first content; In response to the absence of any operation on the first content within a preset time period, the display area of ​​the first content is reduced; as well as In response to the generation of the second content, the second content is highlighted based on the reduced display area.

9. The method according to claim 1, further comprising, before displaying the first content: Obtain a modification instruction, wherein the modification instruction is used to modify the first input; Stop displaying the first content; as well as Display a third piece of content, wherein the third piece of content corresponds to the modification instruction and the first input.

10. An apparatus for task processing, comprising: The first receiving module is configured to receive the first input; A first display module is configured to display first information, wherein the first information indicates that first content is being generated, and the first content corresponds to the first input. The second receiving module is configured to receive the second input; The second display module is configured to display the first content; as well as The third display module is configured to display second information, wherein the second information indicates that second content is being generated, and the second content corresponds to the second input.

11. An electronic device, comprising: At least one processing unit; At least one memory is coupled to the at least one processing unit and stores operations to be performed by the at least one processing unit, which, when performed by the at least one processing unit, cause the electronic device to perform the method according to any one of claims 1 to 9.

12. A computer program product having a computer program stored thereon, which, when executed by a processor, implements the method according to any one of claims 1 to 9.

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