Task processing method and task processing collaboration system

Abstract

The embodiment of the present specification provides a task processing method and a task processing collaboration system, wherein the task processing method comprises: determining a target task in response to a processing request associated with a target service; splitting the target task into a plurality of subtasks by using a scheduling intelligent module; creating a work unit corresponding to each subtask through a command line interface tool, and adding the work unit corresponding to each subtask to a to-do management panel; polling the to-do management panel to determine a to-be-processed work unit by using an execution intelligent module, and migrating the to-be-processed work unit to an execution management panel through the command line interface tool, and executing a target subtask corresponding to the to-be-processed work unit by using a task processing intelligent module; and in the case where the target subtask is executed, migrating the to-be-processed work unit to an archive management panel through the command line interface tool.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of artificial intelligence technology, and in particular to task processing methods and task processing collaborative systems. Background Technology

[0002] With the rapid development of large language model technology, intelligent agent tools can now support long-term planning and autonomous execution modes. Users only need to provide macro-level business objectives, and the tool can automatically complete multi-step cyclical operations such as file reading, tool invocation, command execution, result verification, and error correction within minutes to hours. This capability integrates micro-processes that originally required manual step-by-step operation into delegated long-term tasks, significantly reducing the burden on workers. However, when workers attempt to run multiple intelligent agent tasks simultaneously to improve productivity, new bottlenecks emerge. Users must frequently switch between multiple task contexts, and each switch requires re-acquiring task status information, including task progress, current execution stage, and whether manual intervention is needed. This repetitive context retrieval process severely offsets the theoretical benefits of parallel tasks. Furthermore, there is a lack of passive notification mechanisms for task completion or exceptions; users can only confirm the status by continuously polling the terminal window, making it easy to miss tasks due to oversight. Therefore, an effective solution is urgently needed to address these issues. Summary of the Invention

[0003] In view of this, embodiments of this specification provide a task processing method. One or more embodiments of this specification also relate to a task processing apparatus, a task processing cooperative system, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0004] According to a first aspect of the embodiments of this specification, a task processing method is provided, applied to a task processing collaborative system, comprising: In response to the processing request of the associated target business, the target task is determined, and the target task is divided into multiple sub-tasks using the scheduling intelligence module; Create a work unit corresponding to each subtask using the command-line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The task management panel is polled using the execution intelligence module to determine the work units to be processed, and the work units to be processed are migrated to the execution management panel through the command line interface tool. The target sub-tasks corresponding to the work units to be processed are executed using the task processing intelligence module. Once the target subtask is completed, the pending work unit is migrated to the archive management panel via the command-line interface tool.

[0005] According to a second aspect of the embodiments of this specification, a task processing collaborative system is provided, including an operation terminal and a processing terminal, comprising: The operating terminal is used to receive processing requests related to the target service and send the processing requests to the processing terminal. The processing terminal is used to determine the target task in response to the processing request, and to use the scheduling intelligence module to split the target task into multiple sub-tasks; The operation terminal is used to create a work unit corresponding to each subtask through a command-line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The processing end is used to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and use the task processing intelligence module to execute the target sub-task corresponding to the work unit to be processed. The operation terminal is used to migrate the work unit to be processed to the execution management panel through the command line interface tool; and when the target subtask is completed, to migrate the work unit to be processed to the archive management panel through the command line interface tool.

[0006] According to a third aspect of the embodiments of this specification, another task processing collaborative system is provided, including a scheduling intelligent module, an execution intelligent module, and a task processing intelligent module, comprising: The scheduling intelligence module is used to determine the target task in response to the processing request of the associated target business, split the target task into multiple sub-tasks, create a work unit corresponding to each sub-task through the command line interface tool, and add the work unit corresponding to each sub-task to the to-do management panel. The execution intelligence module is used to poll the to-do management panel to determine the work units to be processed, and to migrate the work units to be processed to the execution management panel through the command line interface tool; The task processing intelligent module is used to execute the target subtask corresponding to the work unit to be processed; when the target subtask is completed, the work unit to be processed is migrated to the archive management panel through the command line interface tool.

[0007] According to a fourth aspect of the embodiments of this specification, another task processing method is provided, applied to a task processing collaborative system, comprising: In response to processing requests from related R&D business, project tasks are determined, and the project tasks are broken down into multiple sub-tasks using a scheduling intelligence module; Create a work unit corresponding to each subtask using the command-line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The execution intelligence module polls the to-do management panel to determine the work units to be processed, and migrates the work units to be processed to the execution management panel through the command line interface tool, and executes the target sub-tasks corresponding to the work units to be processed using the programming intelligence module; Once the target subtask is completed, the pending work unit is migrated to the archive management panel via the command-line interface tool.

[0008] According to a fifth aspect of the embodiments of this specification, a task processing apparatus is provided, applied to a task processing collaborative system, comprising: The determination module is configured to determine the target task in response to the processing request of the associated target business, and to use the scheduling intelligence module to split the target task into multiple sub-tasks; The creation module is configured to create work units corresponding to each subtask via a command-line interface tool and add the work units corresponding to each subtask to the to-do management panel; The execution module is configured to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and to migrate the work unit to be processed to the execution management panel through the command line interface tool, and to use the task processing intelligence module to execute the target subtask corresponding to the work unit to be processed; The migration module is configured to migrate the pending work unit to the archive management panel via the command-line interface tool after the target subtask has been completed.

[0009] According to a sixth aspect of the embodiments of this specification, another task processing apparatus is provided, applied to a task processing collaborative system, comprising: The task determination module is configured to determine project tasks in response to processing requests from related R&D business, and to use the scheduling intelligence module to break down the project tasks into multiple sub-tasks. The Create Unit module is configured to create work units corresponding to each subtask via a command-line interface tool and add the work units corresponding to each subtask to the to-do management panel; The unit determination module is configured to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and to migrate the work unit to be processed to the execution management panel through the command line interface tool, and to use the programming intelligence module to execute the target subtask corresponding to the work unit to be processed; The migration unit module is configured to migrate the work unit to be processed to the archive management panel via the command-line interface tool after the target subtask has been completed.

[0010] According to a seventh aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the above-described task processing method.

[0011] According to an eighth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the task processing method described above.

[0012] According to a ninth aspect of the embodiments of this specification, a computer program product is provided, including a computer program or instructions that, when executed by a processor, implement the steps of the task processing method described above.

[0013] The task processing method provided in this embodiment determines the target task in response to the processing request of the associated target business, and uses a scheduling intelligence module to split the target task into multiple subtasks; creates a work unit corresponding to each subtask through a command-line interface tool, and adds each work unit to the to-do management panel; uses an execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and uses the command-line interface tool to migrate the work unit to be processed to the execution management panel, and uses the task processing intelligence module to execute the target subtask corresponding to the work unit to be processed; when the target subtask is completed, uses the command-line interface tool to migrate the work unit to be processed to the archive management panel. This method achieves automated task status flow by determining tasks, splitting subtasks, creating work units, and using the to-do management panel, execution management panel, and archive management panel in response to business requests. It effectively solves the problems of lack of centralized monitoring of task status and insufficient expression of workflow sequence, achieving centralized monitoring and process management of task status, effectively reducing the context switching burden on users in multi-task processing, and improving task processing efficiency. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating a task processing method provided in one embodiment of this specification; Figure 2a This is a schematic diagram of a management panel in a task processing method provided in one embodiment of this specification; Figure 2b This is a schematic diagram of the content displayed on the secondary screen in a task processing method provided in one embodiment of this specification; Figure 2c This is a schematic diagram of the content displayed on the secondary screen in a second task processing method provided in one embodiment of this specification; Figure 2d This is a schematic diagram of the content displayed on the secondary screen in a third task processing method provided in one embodiment of this specification; Figure 2e This is a schematic diagram of a task processing page in a task processing method provided in one embodiment of this specification; Figure 3 This is a schematic diagram of the structure of a task processing collaborative system provided in one embodiment of this specification; Figure 4 This is a schematic diagram of the structure of another task processing collaborative system provided in one embodiment of this specification; Figure 5 This is a flowchart of another task processing method provided in one embodiment of this specification; Figure 6 This is a flowchart of a task processing collaborative system provided in one embodiment of this specification; Figure 7 This is a schematic diagram of the structure of a task processing device provided in one embodiment of this specification; Figure 8 This is a schematic diagram of another task processing device provided in one embodiment of this specification; Figure 9 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0015] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0016] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0017] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0018] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0019] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0020] Large Language Model (LLM) is a type of neural network model trained on massive amounts of natural language text and possessing general generation and reasoning capabilities.

[0021] The Large Language Model Coding Assistant (hereinafter referred to as "the Coding Assistant") is an intelligent agent program that uses a large language model as its inference kernel and performs code reading and writing, command execution, and file operations interactively in the terminal. This article uses Claude Code as a typical example.

[0022] An intelligent agent is a software entity that possesses autonomous perception, decision-making, and execution capabilities.

[0023] A workspace is an independent unit of work, bound together by a name, a file system directory, and a set of associated contexts. Each workspace hosts an independently running programming assistant process.

[0024] A control board is a visual interface that intuitively displays the status distribution of work units in a "card + group" format. For example, a control board for a programming assistant's workspace can be implemented in a webpage, presented as a "multi-panel sidebar," emphasizing three main capabilities: "grouping by status + drag-and-drop reordering + procedural operation."

[0025] Sidebar Panel: A vertically divided area in the sidebar of the main interface, organized by status. For example, by default, there are two active panels (in progress and to-do) and one collapsed archived panel; the number of panels can be expanded as needed for deployment.

[0026] The Terminal Session Isolation Layer (PSI) is an intermediary layer between the browser and the command interpreter. It decouples the lifecycle of the terminal session from the lifecycle of the browser page and provides two unified capabilities: "content sampling" and "remote interactive injection." For example, an industry-standard terminal multiplexer can be used as one of the implementation carriers for this intermediary layer.

[0027] Remote Interaction Injection (RII) is a technique where another process (such as an auxiliary display interface or a higher-level intelligent agent) asynchronously injects a piece of text into a programming assistant session and triggers a Enter key, so that the session receives input equivalent to that of the user typing locally.

[0028] The Sidecar Status Dashboard, or "secondary screen" for short, is an auxiliary interface that is relatively independent of the main control board. It is used to centrally observe the real-time status of all "in progress" work areas on another physical display screen (or a separate browser window) and supports light intervention.

[0029] Status Self-Perception is the ability of an external system to automatically determine the current working status (running / idle) of each workspace without modifying the programming assistant's core code, and to inform the user through both visual (indicator color) and auditory (prompt sound) signals.

[0030] Urgency is an integer value ranging from 0 to 100, derived from the status map. It is used to sort multiple workspaces on the secondary screen, so that the workspaces that are most worthy of the user's attention appear at the top of the list.

[0031] Priority Workspace is the workspace with the highest urgency and the greatest need for user intervention. It is automatically selected by the secondary screen based on its status and highlighted in a prominent manner.

[0032] Command Line Interface Tool (CLIP), which can be named board-cli, is a command-line program that communicates with backend services and inputs and outputs data in a structured data format. It facilitates programming assistants or other external scripts to perform programmed operations on the control panel (adding, moving, archiving, querying workspaces, etc.).

[0033] This specification provides a task processing method. One or more embodiments of this specification also relate to a task processing apparatus, a task processing cooperative system, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail in the following embodiments.

[0034] In agent-based tools that support long-term planning and autonomous execution, users face high cognitive costs when multiple agent tasks run in parallel, due to the high cost of switching between multi-task contexts. Specifically, the lack of a centralized management view prevents unified monitoring of task states; the order of task execution cannot be systematically expressed; there is a lack of proactive notification mechanisms when task states change; and upper-layer agents struggle to programmatically orchestrate lower-layer agents. This issue forces users to frequently retrieve task context information during task processing, resulting in low task execution efficiency and a high risk of omissions, thus impacting overall system reliability and user productivity. Furthermore, the inherent sequential logic of user workflows—such as task startup priority, subsequent task connection, and temporary storage of unstarted tasks—cannot be uniformly expressed in existing systems. Users are forced to rely on external tools such as note-taking or to-do software for management, leading to high costs and errors in cross-platform synchronization. Existing engineering practices include multi-window concurrent solutions, session retention tools, and cloud-based integrated development environments (IDEs). However, all of these solutions suffer from fundamental flaws: multi-window solutions isolate each terminal, preventing users from intuitively grasping the real-time status distribution of all tasks; session retention tools only provide passive maintenance of background processes, failing to reflect the logical order between tasks; and cloud-based IDEs focus on code environment management rather than the full lifecycle collaboration of agent tasks. It's important to note that none of these solutions address issues such as the lack of centralized monitoring of task status, insufficient expression of workflow sequence, and a lack of proactive notification mechanisms for anomalies. They are particularly inadequate for supporting the programmatic orchestration needs of upper-layer agents for lower-layer agents, such as task splitting, work unit migration, and archiving operations. Furthermore, the separation between the context document and the terminal operation area further exacerbates the burden of switching between task planning and execution, making it difficult to effectively improve the efficiency of multi-task collaboration.

[0035] In view of this, the task processing method provided in this embodiment determines the target task in response to the processing request of the associated target business, and uses the scheduling intelligence module to split the target task into multiple sub-tasks; creates a work unit corresponding to each sub-task through a command-line interface tool, and adds the work unit corresponding to each sub-task to the to-do management panel; uses the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and uses the command-line interface tool to migrate the work unit to be processed to the execution management panel, and uses the task processing intelligence module to execute the target sub-task corresponding to the work unit to be processed; when the target sub-task is completed, uses the command-line interface tool to migrate the work unit to be processed to the archive management panel. This achieves automated task status flow by determining tasks, splitting sub-tasks, creating work units, and using the to-do management panel, execution management panel, and archive management panel in response to business requests. It effectively solves the problems of lack of centralized monitoring of task status and insufficient expression of workflow sequence, realizing centralized monitoring and process management of task status, effectively reducing the context switching burden on users in multi-task processing, and improving task processing efficiency.

[0036] See Figure 1 , Figure 1 A flowchart of a task processing method according to an embodiment of this specification is shown. The method is applied to a task processing collaborative system and specifically includes the following steps.

[0037] Step S102: In response to the processing request of the associated target business, the target task is determined, and the target task is split into multiple sub-tasks using the scheduling intelligence module.

[0038] Step S104: Create a work unit corresponding to each subtask through the command line interface tool, and add the work unit corresponding to each subtask to the to-do management panel.

[0039] Step S106: Use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and use the command line interface tool to migrate the work unit to be processed to the execution management panel, and use the task processing intelligence module to execute the target subtask corresponding to the work unit to be processed.

[0040] Step S108: After the target subtask is completed, the work unit to be processed is migrated to the archive management panel through the command line interface tool.

[0041] The task processing method provided in this embodiment can be applied to any business scenario where intelligent agent-type tools carry out long-term delegated tasks, such as R&D business (multiple projects in parallel, fixing defects, performing experiments, and writing documents, with each project executed by a programming assistant for a long time), editing / content production business (multiple material processing tasks in parallel, with each task executed by a content generation intelligent agent for a long time), and writing business (multiple creative themes in parallel, with each theme drafted and revised by a creative intelligent agent for a long time). It is used to automatically split tasks into multiple sub-tasks, and multiple sub-tasks can be automatically managed and coordinated with user operations, thereby realizing centralized monitoring and process management of task status, effectively reducing the context switching burden on users in multi-task processing, and improving task processing efficiency.

[0042] This embodiment uses the application of the task processing method in the R&D business scenario as an example to illustrate the task processing method. The same or corresponding descriptions in other scenarios can be found in the description in this embodiment, and will not be elaborated on further here.

[0043] Specifically, the task processing collaboration system is an integrated platform designed to coordinate and manage the execution of tasks by multiple intelligent agents. It provides a unified interface and mechanism, enabling users to monitor, schedule, and interact with multiple parallel tasks from a centralized view, thereby improving work efficiency and task controllability. The target business refers to the business scenario or requirement related to a specific task processing flow. For example, in the software development field, the associated target business could be new feature development, defect fixing, or performance optimization; in the content creation field, it could be article writing, video editing, or image processing. The scheduling intelligence module is an intelligent agent responsible for receiving and parsing the processing requests of the target business, and then intelligently decomposing a macro-level target task into a series of smaller, more specific, and independently executable subtasks. Its core function lies in the automated decomposition and preliminary planning of tasks. Subtasks are the smallest executable units with clear boundaries and execution logic, decomposed from the target task by the scheduling intelligence module. Each subtask represents a specific step or operation required to complete the target task.

[0044] Correspondingly, the command-line interface tool provides a standardized set of commands for interacting with the backend services of the task processing collaboration system. Through this tool, operations such as creating, querying, moving, and archiving work units can be performed in a structured data format, facilitating programmatic calls and result parsing by the intelligent agent. A work unit is an abstract representation of a subtask in the task processing collaboration system. Each work unit encapsulates the execution context, status information, and related operation interfaces of the corresponding subtask, serving as the basic carrier for task management and workflow. The to-do management panel is a visual area in the task processing collaboration system, used to centrally display all created but not yet executed work units. It carries the task queue and shows the task priority order.

[0045] Correspondingly, the execution intelligence module is an intelligent agent responsible for continuously monitoring the task management panel, identifying and selecting work units to be processed, and transitioning them from the pending state to the execution state. Its main functions are automatic task selection and state transition. A work unit to be processed refers to a work unit currently selected by the execution intelligence module and about to be or currently being executed by it. The execution management panel is another visual area in the task processing collaboration system, used to centrally display all work units currently being executed by the task processing intelligence module. It provides a real-time monitoring view of active tasks. The task processing intelligence module is an intelligent agent responsible for receiving work units to be processed and, based on their encapsulated subtask information, calling the corresponding tools or execution logic to complete the specific operation of the target subtask. It is the core driver of task execution. The target subtask refers to the specific operation or step represented by the work unit to be processed that the task processing intelligence module is currently executing. The archive management panel is a visual area in the task processing collaboration system, used to centrally display all work units that have been successfully executed and archived. It provides a view of task history and completion status.

[0046] Based on this, firstly, in response to processing requests related to the target business, the target task is determined, and the scheduling intelligence module is used to break down the target task into multiple sub-tasks. In practical applications, when a user submits a macro-level business requirement in the task processing collaboration system, such as "complete the development of a new feature," the system receives a processing request. Subsequently, the scheduling intelligence module is activated, which can analyze and understand the macro-level target task using a preset rule base or based on a machine learning model. For example, this module can break down "complete the development of a new feature" into multiple independent sub-tasks such as "designing the database structure," "writing the backend API," "developing the frontend interface," and "conducting integration testing." As another implementation method, the scheduling intelligence module can also interact with the user, guiding the user to manually confirm or adjust the granularity of the task breakdown, thereby generating a series of sub-tasks.

[0047] Secondly, this method creates a work unit corresponding to each subtask through a command-line interface tool and adds each work unit to the to-do management panel. After the subtasks are determined, the system generates an independent work unit for each subtask. For example, for the subtask "Design database structure," a work unit named "Database Design" is created. The creation of work units can be accomplished through the command-line interface tool, which receives the description information of the subtask and encapsulates it into a data structure that can be recognized and managed by the system. After creation, the work unit is automatically placed in the to-do management panel. The to-do management panel can simply display work units in a list format, and users can manually adjust their order by dragging and dropping, or the system can arrange them according to their creation time.

[0048] Furthermore, this method utilizes the execution intelligence module to poll the to-do list management panel to determine pending work units, migrates these work units to the execution management panel via a command-line interface tool, and executes the target subtasks corresponding to the pending work units using the task processing intelligence module. Once a work unit exists in the to-do list management panel, the execution intelligence module periodically scans the panel. For example, the execution intelligence module can check the to-do list management panel at fixed intervals (e.g., 30 seconds) and select one work unit as the pending work unit. The selection strategy can be the work unit that entered the queue first, or a random selection. After selection, the execution intelligence module sends a command via the command-line interface tool to remove the pending work unit from the to-do list management panel and add it to the execution management panel. Simultaneously, the task processing intelligence module is activated, receives the target subtask represented by the pending work unit, and begins execution. For example, if the pending work unit is "write backend API," the task processing intelligence module will call the corresponding programming tools or scripts to begin writing code.

[0049] Finally, upon completion of the target subtask, the method migrates the pending work unit to the archive management panel via a command-line interface tool. When the task processing intelligent module successfully completes the execution of a target subtask, such as when the code for "writing the backend API" is completed and passes preliminary testing, the task processing intelligent module sends a completion signal to the system. Upon receiving this signal, the system executes the corresponding operation via the command-line interface tool, removing the pending work unit currently in the execution management panel from that panel and moving it to the archive management panel. The archive management panel can be simply presented as a list of completed tasks, recording all completed work units.

[0050] For example, suppose user A has a macro-level goal in a task processing collaboration system: "Release a new version of the software product." First, when user A submits a request to "Release a new version of the software product" in the system, the system responds and identifies the target task. Then, the scheduling intelligence module is activated, intelligently breaking down the macro-level goal into a series of specific sub-tasks based on preset rules or models, such as: "Update dependency libraries," "Execute unit tests," "Generate release package," "Deploy to the test environment," and "Update user documentation." The system creates a corresponding work unit for each sub-task through a command-line interface tool. For example, a "Dependency Update" work unit is created for "Update dependency libraries," a "Unit Test" work unit is created for "Execute unit tests," and so on. The newly created work units are then automatically added to the to-do management panel. At this point, the to-do management panel clearly displays all pending work units, for example, arranged in a list in the order of creation. Subsequently, the execution intelligence module continuously polls the to-do management panel. For example, the execution intelligence module checks the to-do list panel every minute and finds that the "Dependency Update" work unit is in a pending state. The execution intelligence module selects this "Dependency Update" work unit as the pending work unit and migrates it from the to-do list panel to the execution management panel via the command-line interface tool. Simultaneously, the task processing intelligence module is activated, receives the target subtask represented by the "Dependency Update" work unit, and begins execution. The task processing intelligence module calls the appropriate tools to automatically perform the dependency library update operation. Once the "Dependency Update" target subtask is completed, the task processing intelligence module sends a completion signal. Upon receiving this signal, the system migrates the "Dependency Update" work unit from the execution management panel to the archive management panel via the command-line interface tool. At this point, the "Dependency Update" work unit disappears from the execution management panel, while it is added to the archive management panel. Finally, the execution intelligence module continues to poll the to-do list panel, finds the "Unit Test" work unit, and repeats the migration and execution process. In this way, each subtask is automatically circulated from pending, execution, to archiving by the system, forming a complete task processing loop. User A doesn't need to frequently switch terminal windows or manually check the progress of each task; they only need to focus on the status of the work units on the management panel. The entire process demonstrates the close collaboration between the various intelligent modules and the management panel, achieving automated task scheduling, execution, and management.

[0051] In summary, by responding to business requests to determine tasks, break down subtasks, create work units, and utilize the to-do management panel, execution management panel, and archive management panel to automate the flow of task status, the system effectively solves the problems of lack of centralized monitoring of task status and insufficient expression of workflow sequence. It achieves centralized monitoring and process management of task status, effectively reduces the context switching burden on users in multi-task processing, and improves task processing efficiency.

[0052] Furthermore, how to achieve orderly scheduling of multiple subtasks during execution and automatic adaptation to the working environment to ensure the continuity and accuracy of task execution remains a problem to be solved. In this embodiment, the step of using the execution intelligence module to poll the to-do management panel to determine the work units to be processed, migrating the work units to be processed to the execution management panel through the command-line interface tool, and using the task processing intelligence module to execute the target subtasks corresponding to the work units to be processed, includes: The execution intelligence module polls the to-do management panel and selects work units as pending work units in sequence according to the polling results. The pending work units are migrated to the execution management panel through the command line interface tool, and the work directory corresponding to the previous polling cycle is switched to the work directory corresponding to the pending work unit. The task processing intelligence module executes the target subtask corresponding to the pending work unit according to the switched work directory.

[0053] Specifically, the execution intelligence module is an automation component whose main function is to monitor and manage the task processing flow. This module periodically checks the to-do list panel to identify and retrieve work units in a pending state. When multiple work units exist in the to-do list panel, the execution intelligence module determines and selects the next work unit to be processed based on preset scheduling strategies, such as the first-in-first-out (FIFO) principle, priority, or task type. This aims to ensure the orderly processing of tasks, avoid potential problems caused by disordered task execution, and provide a clear and stable target for subsequent task execution. As a specific implementation method, the execution intelligence module can maintain a task queue, selecting tasks according to the order in which they were added to the to-do list panel; alternatively, each work unit can be assigned a priority upon creation, and the execution intelligence module will always prioritize processing the highest priority task.

[0054] Correspondingly, a command-line interface (CLI) tool is a text-based, interactive interface that allows automation programs or users to interact with the system or application by entering specific commands. In this step, the tool executes specific migration commands to update the status of a pending work unit from the to-do management panel to the execution management panel. This typically involves updating the work unit's metadata or its logical state internally to reflect its current processing stage. Specifically, the CLI tool can encapsulate calls to a backend application programming interface (API) to update the work unit's status and associated panel by sending API requests; alternatively, it can execute pre-defined scripts that directly manipulate the underlying database or file system to modify the work unit's panel ownership information.

[0055] Correspondingly, the working directory refers to the specific file system path where the files and resources the current task depends on reside. The core of this step is that before starting a new unit of work, the system automatically adjusts the working directory of the current operating environment to the path specified by that unit of work. The working directory corresponding to the previous polling cycle refers to the file path used when the previous unit of work was executed. This switching mechanism ensures that each unit of work runs in its independent and correct context, effectively avoiding problems caused by file path conflicts or resource confusion between different tasks, and guaranteeing the accuracy and isolation of task execution. For example, the working directory of a newly started process can be specified by setting or modifying the process's environment variables; or, in command-line interface tools, shell commands such as `cd` (changedirectory) can be used to dynamically change the working directory of the current session.

[0056] Correspondingly, the task processing intelligent module is the core component responsible for the actual execution of the target subtask. Upon receiving a work unit to be processed, this module first verifies whether the current operating environment's working directory has been correctly switched to the path specified by that work unit. Once the working directory is confirmed to be correct, the task processing intelligent module will start and run the target subtask in this correct working directory. The accuracy of this module's execution directly affects the success of the entire task and is a key link in the task processing flow. As one implementation method, the task processing intelligent module can call a corresponding script interpreter (such as a Python interpreter or a Bash interpreter) to execute the script or program defined in the target subtask; alternatively, it can also call external services or internal APIs to complete specific operations based on the definition of the target subtask.

[0057] Based on this, by introducing an ordered polling mechanism and automated working directory switching logic, the automated flow and environment configuration of multiple subtasks in the task processing collaboration system are realized. Specifically, after responding to the processing request of the associated target business and determining the target task, the scheduling intelligence module breaks down the target task into multiple subtasks, creates a corresponding work unit for each subtask through a command-line interface tool, and adds it to the to-do management panel. On this basis, the execution intelligence module periodically polls the to-do management panel and selects work units as pending work units in sequence according to a preset scheduling strategy. Once a pending work unit is determined, the system migrates it from the to-do management panel to the execution management panel through the command-line interface tool, thereby updating its status on the visual interface. During the migration, the system automatically switches the current working environment, i.e., the working directory corresponding to the previous polling cycle, to the working directory specified by the pending work unit. The automatic switching mechanism ensures that each subtask executes in its independent and correct context, effectively avoiding path conflicts or resource confusion that may occur when multiple tasks run in parallel. Subsequently, the intelligent task processing module will accurately execute the target subtasks corresponding to the work units to be processed, based on the switched work directory. In this way, the solution of this application not only ensures the logical order of task execution and avoids errors caused by disordered execution order, but also guarantees the accuracy and consistency of task execution through automatic environmental adaptation, thereby significantly improving the automation level and execution efficiency of the task processing collaboration system in handling complex multi-task scenarios.

[0058] For example, suppose a developer needs to handle multiple programming tasks in parallel, each corresponding to an independent programming assistant session. First, when a developer submits a macro-level development task, the scheduling intelligence module breaks it down into multiple independent subtasks, such as "implement user login functionality" or "optimize database queries." Each subtask is encapsulated as a work unit and added to the to-do list panel. Next, the execution intelligence module continuously polls the to-do list panel. For example, following a first-in, first-out (FIFO) principle, it selects the first work unit from the to-do list panel, let's say it's the work unit corresponding to "implement user login functionality." Once selected, the command-line interface tool executes the corresponding command, moving the work unit from the to-do list panel to the execution panel. Simultaneously, the system automatically switches the current working directory to the project directory corresponding to the "implement user login functionality" work unit. For example, if the previous task's working directory was / projects / old_feature, it will now automatically switch to / projects / user_login. Subsequently, the task processing intelligent module (e.g., a programming assistant running in a separate process) will start in the / projects / user_login directory and begin executing the target subtask of "implementing user login functionality". Once this subtask is completed, the work unit will be further migrated to the archive management panel. This ensures that each programming assistant works in its own dedicated project environment, avoiding interference between different project files and greatly improving the efficiency and accuracy of multi-task parallel processing.

[0059] In summary, the above-mentioned methods effectively improve the automation level and execution efficiency of the task processing collaboration system in handling complex multi-task scenarios, enabling knowledge workers to manage and execute multiple intelligent agent tasks more efficiently and reducing the cost of manual intervention and context switching.

[0060] Furthermore, existing task processing methods, when utilizing intelligent task processing modules to execute target sub-tasks, make it difficult for users to intuitively understand the real-time execution status of each task at different stages such as pending, execution, and archiving. This leads to users being unable to keep track of task progress in a timely manner when processing multiple tasks in parallel, easily resulting in omissions or management chaos. To address this, in this embodiment, after the execution of the target sub-task steps corresponding to the work unit to be processed using the intelligent task processing module, the method further includes: The execution status of the work units contained in the to-do management panel, the execution management panel, and the archive management panel is detected; and the status prompt information of the corresponding work units is displayed in the to-do management panel, the execution management panel, and the archive management panel according to the execution status.

[0061] Specifically, the to-do management panel, the execution management panel, and the archive management panel are logical areas in the task processing collaboration system used to organize and display task status. The to-do management panel stores work units that have not yet started execution or are waiting to be processed; the execution management panel stores work units that are currently executing or paused; and the archive management panel stores work units that have been completed or terminated. Together, they constitute a visual task lifecycle management interface, allowing users to clearly understand the overall progress of tasks. A work unit is an abstract representation of a subtask in the task processing collaboration system, with each work unit corresponding to a specific subtask. It carries relevant information about the subtask, such as its name, description, current status, and possible operation options. The work unit is the basic carrier for user interaction with the system, management, and monitoring of subtasks. The execution status refers to the real-time running status of the subtask represented by the work unit in the task processing collaboration system. This status can reflect whether the subtask is running, paused, completed, has encountered an error, or is waiting for user input, etc. Execution status detection can be achieved in various ways, such as monitoring the process activity corresponding to subtasks, analyzing the log output of subtasks, or sampling and analyzing the terminal display content through a session isolation layer. Displaying the status prompt information for the corresponding work unit means presenting the current status of the work unit to the user in an intuitive and easy-to-understand manner in the corresponding management panel based on the detected execution status. This can be achieved through various visual or auditory means, such as using indicator lights of different colors (e.g., green for running, gray for idle or stopped), displaying specific icons (e.g., play, pause, complete, error icons), or directly displaying the status description in text form (e.g., "Running," "Waiting for input," "Completed"). The aim is to provide immediate feedback, allowing users to quickly grasp the task overview without needing to delve deeper.

[0062] Based on this, a status monitoring and visual feedback mechanism is introduced to achieve dynamic tracking of the entire task lifecycle. After the task processing intelligent module executes the target subtask corresponding to the pending work unit, the system continuously or periodically monitors the execution status of all work units in the to-do management panel, execution management panel, and archive management panel. This monitoring mechanism can capture the latest progress of each subtask in real time, such as determining whether it is still running actively, whether it has stopped, whether an anomaly has occurred, or whether it has been successfully completed. Based on the detected execution status, the system will display corresponding status prompts in the corresponding management panel. For example, an executing work unit will be marked as "Running," while a completed work unit will be marked as "Archived." This design transforms the abstract background execution logic into intuitive visual feedback, allowing users to clearly identify which tasks are in the pending, execution, or archive stage through a unified interface view. This effectively reduces the cognitive load on users during multi-task switching and improves the transparency and collaborative efficiency of task management. By integrating status detection and display functions into the task processing flow, users can keep track of task progress in a timely manner, avoiding the problem of frequently manually polling and checking task status in traditional solutions, and significantly improving the efficiency of multi-task parallel processing and user experience.

[0063] like Figure 2a The diagram illustrates a scenario where, for example, the To-Do panel includes items A and B, and the DOING panel includes items X and Y. Item X is in the execution state, indicated by a green indicator light. When the agent encounters item A as the first item in the To-Do panel, it can move it to the DOING panel; before execution, its indicator light is gray. Simultaneously, the Archive panel (Archived / Collapsed) manages completed items and can be displayed in a collapsed state for easier user browsing, reducing the amount of information displayed.

[0064] For example, in a research and development scenario, when a programming assistant executes a target sub-task in a task processing collaboration system, the system can continuously monitor the execution status of the corresponding work unit. For instance, when the programming assistant continuously outputs content to its terminal, the status self-aware module can detect the continuous changes in the screen, thus determining the execution status of the work unit as "running" and displaying a status prompt in the form of a green indicator light in the execution management panel. Conversely, if the programming assistant stops outputting updates, the screen becomes static, or the session does not exist, has exited, is waiting for user input, or an error occurs—in other "non-running" situations—the status self-aware module will determine the execution status of the work unit as "idle" or "stopped," displaying a status prompt in the form of a gray indicator light in the execution management panel. Furthermore, the system can also display work units in a "pending start" state in the to-do management panel or a work unit in a "completed" state in the archive management panel based on the detected status. This visual status indicator allows developers to easily observe the current working status of multiple programming assistant tasks without having to switch between terminal windows one by one or manually query. For example, the system can inform the user that "the programming assistant has stopped running in project A and is waiting for user input" or "the programming assistant has encountered an error in project B", thereby achieving effective management and timely intervention of tasks.

[0065] In summary, the above approach effectively solves the problem of users finding it difficult to intuitively understand the real-time execution status of multiple tasks in traditional task processing methods. By monitoring the execution status of work units in the to-do list, execution management, and archive management panels in real time after the intelligent task processing module executes subtasks, and displaying corresponding status prompts based on the status, users can obtain clear and immediate feedback on task progress. This significantly improves the transparency of task management and reduces the cognitive burden and context switching costs for users when processing multiple tasks in parallel. Users no longer need to frequently manually poll or guess the task status; they can quickly identify which tasks are in progress, which have been completed, and which require attention or intervention through a unified interface view. This not only avoids task omissions and management chaos but also allows users to allocate attention and resources more efficiently, thereby greatly improving the efficiency of multi-task parallel processing and the overall user experience of the collaborative system.

[0066] In practice, when task execution encounters abnormalities or stalls, the system lacks a proactive monitoring and alerting mechanism, preventing users from promptly obtaining the real-time status of the task. This often necessitates frequent manual intervention, resulting in a waste of human resources and a reduction in task processing efficiency. Therefore, in this embodiment, before the step of migrating the pending work unit to the archive management panel via the command-line interface tool after the target subtask has been completed, the following further steps are included: The execution visualization information corresponding to the work unit to be processed is determined; if the target subtask is in a stopped state and exceeds a set time threshold based on the execution visualization information, a reminder message is sent to the operation terminal of the task processing collaboration system according to a preset reminder strategy, and the work unit card corresponding to the work unit to be processed is displayed on the external operation device of the task processing collaboration system.

[0067] Specifically, during task execution, it is necessary to determine the execution visualization information corresponding to the work unit to be processed. This execution visualization information aims to reflect the running status and progress of the task in real time. Its implementation methods may include, but are not limited to: capturing dynamic data such as terminal output, log information, and UI screenshots by sampling the session isolation layer in the task processing collaboration system; or, obtaining the task's internal status variables, progress indicators, error codes, etc. in real time by integrating the task execution environment's application programming interface (API) or software development kit (SDK).

[0068] Based on this, the system determines whether the target subtask is in a stopped state according to the acquired execution visualization information, and further confirms whether the stopped state has exceeded a preset time threshold. This judgment mechanism can effectively distinguish between normal task execution pauses and abnormal freezes or blockages. For example, by analyzing the timestamp sequence in the execution visualization information, if no new output or status update is detected within the set time threshold, it is determined to be in a stopped state; or, by comparing the current execution visualization information with the execution visualization information at the previous moment, if both remain unchanged within the set time threshold, it can also be determined to be in a stopped state. Once it is determined that the target subtask is in a stopped state and has exceeded the set time threshold, the system will send a reminder message to the operation terminal in the task processing collaboration system according to a preset reminder strategy. This reminder strategy can be diversified, for example, by using the system's internal message notification mechanism to pop up a prompt box on the operation terminal interface or send an internal message; or by using an external communication interface to send SMS or email notifications to the mobile phone or email address bound to the operation terminal, ensuring that the user can receive the notification of task abnormality as soon as possible. At the same time, in order to provide a more intuitive and convenient interactive entry point, the system will display the work unit card corresponding to the work unit to be processed on the external operation device in the task processing collaboration system. The external operating device can be a user's mobile terminal, tablet, or a dedicated web dashboard. Work unit cards can be presented as cards in a web interface or mobile application, or as desktop widgets or floating windows, intuitively displaying key task information and possible operation options.

[0069] Based on this, an intelligent and proactive management of task execution status is achieved by introducing a monitoring and analysis mechanism for execution visualization information. After the task processing collaboration system responds to processing requests, schedules and splits the target task into multiple subtasks, and creates work units through the command-line interface tool and adds them to the to-do management panel, the execution intelligence module polls the to-do management panel to identify the work units to be processed and migrates them to the execution management panel. Subsequently, the task processing intelligence module executes the target subtask. During this execution process, the execution visualization information of the work units to be processed is continuously determined. By intelligently analyzing the visualization information, the system can accurately determine whether the target subtask has entered a stopped state, and by combining it with preset time thresholds, it can effectively filter out brief and normal pauses, thereby accurately identifying real task anomalies. Once an abnormal stoppage is confirmed, the system will immediately send a reminder message to the operator according to the preset reminder strategy, and simultaneously display the work unit card corresponding to the work unit to be processed on the external operating device. This series of steps are closely linked, forming a closed-loop monitoring and feedback mechanism, which allows users to know the real-time status of tasks in a timely manner without passively polling, and can quickly locate problems and intervene through an intuitive card interface. This proactive monitoring and alerting mechanism greatly enhances the robustness and user experience of the task processing collaboration system when handling long-term or complex tasks, effectively making up for the shortcomings of traditional solutions in task status awareness and anomaly handling.

[0070] For example, suppose a developer is using a task processing collaboration system to process multiple code review tasks in parallel. One subtask is running a complex static code analysis tool. When the execution intelligence module migrates the work unit corresponding to this static analysis subtask to the execution management panel and starts execution by the task processing intelligence module, the system continuously collects execution visualization information such as the terminal output stream, CPU and memory usage of the static analysis tool. If the system detects that the terminal output stream has not been updated for five consecutive minutes (a set time threshold) and the CPU usage remains low, the system will determine that the static analysis subtask has stopped. At this time, the system will immediately send a pop-up reminder to the developer's desktop client (operation terminal) and simultaneously display a "Static Code Analysis Task Stalled" work unit card on the developer's mobile phone (external operating device). This card includes the subtask name, the stop time, and operation buttons such as "View Log" and "Restart". The developer can quickly understand the task status and perform corresponding operations through the card on their mobile phone without actively switching to the terminal window.

[0071] In summary, the above approach effectively solves the problem of the lack of proactive monitoring and alerting mechanisms in traditional task processing when task execution encounters anomalies or stalls. Users no longer need to frequently intervene manually to check task status; instead, they can promptly and accurately learn about task anomalies and quickly locate the problem through system-proactive alerts and intuitively displayed work unit cards on external operating devices. This significantly improves the efficiency and reliability of task processing, reduces the waste of human resources, and provides users with a more convenient and efficient task management experience. Based on this, when the target subtask is in a stopped state and requires manual intervention, the system lacks an effective interaction mechanism, preventing the operator from obtaining the task status in a timely manner and providing targeted instruction feedback. This leads to an interruption in task processing continuity and makes it difficult to achieve closed-loop management of long-running tasks. Therefore, in this embodiment, the method further includes: The system receives operation instructions submitted via the external operating device for the work unit card and sends the operation instructions to the task processing intelligent module. The work unit card displays the execution status information corresponding to the work unit to be processed. The task processing intelligent module then continues to execute the target subtask according to the operation instructions.

[0072] Specifically, the system receives operation instructions submitted via external operating devices for work unit cards, aiming to provide a way for users to interact with the task processing collaboration system, allowing users to intervene in specific work units during task execution. The external operating device can be a standalone hardware device, such as a smartphone, tablet, dedicated control panel, or a client application running on the user's computer. The work unit card is a graphical interface element on the external operating device used for display and interaction, visually presenting key information about the work unit to be processed to the user. Users generate operation instructions on the work unit card by clicking, entering text, or selecting preset options. These instructions are then sent to the task processing intelligent module, ensuring that the instructions submitted by the user on the external operating device can be received and understood by the core processing unit of the task processing collaboration system. The sending of operation instructions can be achieved through various communication protocols, such as RESTful API calls based on HTTP / HTTPS, real-time WebSocket communication, or asynchronous transmission via message queue services. The task processing intelligent module is the core component responsible for parsing and executing instructions; it can transform user-friendly operation instructions into task control commands that the system can recognize and execute internally. Work unit cards display the execution status information of the work units to be processed. This feature provides users with real-time feedback on the task execution process, forming the basis for effective user decision-making. Execution status information can include the current stage of the task (e.g., "Running," "Paused," "Waiting for Input," "Error"), progress percentage, elapsed time, key output summaries, and any prompts or warnings requiring user attention. This information is presented intuitively through work unit cards in the form of text, icons, progress bars, or color coding, allowing users to understand the latest status of the task without delving into the system's internals. Utilizing the intelligent task processing module to continue executing the target subtask according to operation instructions is key to achieving dynamic task intervention and recovery. After receiving an operation instruction, the intelligent task processing module parses the user's intent based on the instruction's content and translates it into a corresponding operation on the target subtask. For example, if the instruction is "Continue," the module will unsuspend the subtask; if the instruction is "Retry," the module will restart a failed step of the subtask; if the instruction contains new input, the module will inject it into the subtask's execution flow. In this way, the intelligent task processing module can ensure that the target subtask can smoothly and accurately recover or adjust its execution path after manual intervention.

[0073] Based on this, this solution addresses the problem of task interruption caused by the lack of an effective interaction mechanism when manual intervention is required during long-term task execution using traditional task processing methods. This solution achieves dynamic intervention and recovery of the task execution process by introducing interaction between external operating devices and the intelligent task processing module. Specifically, in the task processing collaboration system, after determining the target task in response to the processing request of the associated target business, the scheduling intelligent module breaks down the target task into multiple subtasks. A work unit corresponding to each subtask is created through a command-line interface tool and added to the to-do management panel. Subsequently, the execution intelligent module polls the to-do management panel to determine the work units to be processed, migrates them to the execution management panel through the command-line interface tool, and executes the target subtasks corresponding to the work units to be processed using the task processing intelligent module. During this process, a user interaction mechanism is introduced to handle situations where the target subtasks are stopped or require manual input. First, during the execution of the target subtasks, the system determines the execution visualization information corresponding to the work units to be processed. When the system determines, based on the visualization information, that a target subtask is in a stopped state and has exceeded a set time threshold, it will send a reminder message to the operator terminal in the task processing collaboration system according to a preset reminder strategy. The system will also display the corresponding work unit card on the external operating device within the task processing collaboration system. This work unit card visually presents the execution status information of the work unit, including the task's running status, progress, and any prompts requiring user attention. By observing the real-time status information, users can promptly understand the task's progress and potential problems. When a user needs to intervene in a stopped or pending subtask, they can directly submit an operation command to that work unit card through the external operating device. The operation command can be a simple "continue," "pause," or "retry," or a text command containing specific input content. The external operating device will then send the operation command to the task processing intelligent module. As the core control unit of the system, the task processing intelligent module is responsible for receiving, parsing, and executing the commands. It converts the user-submitted commands into control signals or data inputs that the system can recognize and applies them to the corresponding target subtask. Finally, the task processing intelligent module continues to execute the target subtask based on the received operation command. For example, if the instruction requires continued execution, the intelligent task processing module will unsuspend the subtask, resuming its execution from the point of interruption. If the instruction provides new input, the module will inject that input into the subtask's execution flow, thus propelling the task forward. Through this process, the previously passive task processing is transformed into a human-machine collaborative interaction. The combination of external operating devices and the intelligent task processing module allows users to directly perform fine-grained control over specific tasks, resolving the problem of tasks stalling due to anomalies or waiting for input during execution.The real-time status information provided by the work unit cards offers users intuitive decision-making support, ensuring the relevance and effectiveness of instructions. The intelligent task processing module resumes task execution based on instructions, achieving an automated closed loop from receiving instructions to resuming task execution. This enhances the robustness and flexibility of the task processing collaboration system when handling complex, long-duration tasks. This human-machine collaborative model effectively compensates for the shortcomings of purely automated processing when facing uncertainty or requiring subjective judgment, making the entire task processing workflow smoother and more efficient.

[0074] In a research and development scenario, assuming the highest priority work unit is as follows: Figure 2b The illustrated content can then display corresponding confirmation information to the user, such as "Phase 0 engine reconstruction in progress, introducing context state, modifying the link to support streaming filtering and usage accumulation"; it can also provide user-accessible input commands, such as "Complete Phase 0 reconstruction," "Reconstruct Provider," and "Run equivalence test," and can also support user-defined input information; when the user selects the "Complete Phase 0 reconstruction" command via the secondary screen, such as... Figure 2c The diagram shown can display a prompt box to the user to prevent accidental operation; if the user selects a custom option, such as... Figure 2d The diagram shown illustrates an input pop-up window that allows users to input more complex commands. This ensures that remote injection and local user input are completely equivalent through proper delay settings.

[0075] For example, suppose a developer is using a task processing collaboration system for code development, and one of the target sub-tasks is "writing unit tests." When the task processing intelligent module executes this sub-task, the programming assistant may pause after completing part of the code, waiting for user confirmation or further instructions. At this time, the status awareness module in the task processing collaboration system will detect that the output of the workspace (i.e., the work unit to be processed) has not been updated for a long time, and determine that it is in a stopped state. The work unit card displayed on the external operating device will be updated immediately, showing the execution status of the sub-task as "waiting for user input" or "paused," and prompting the user through a color change (e.g., from green to gray) or flashing. The developer observes the status prompt of the work unit card through the external operating device (e.g., a dedicated control panel on their desktop or a mobile application). They can click on the card and enter an operation instruction such as "continue, and ensure all edge cases are covered" in the pop-up input box. This operation instruction is then sent to the task processing intelligent module through a secure communication link. After receiving the instruction, the task processing intelligent module will parse the text content and identify the two intentions: "continue" and "ensure all edge cases are covered." The intelligent task processing module translates the "continue" command into a command to resume the programming assistant's execution, and injects "ensure all edge cases are covered" as new input or contextual information into the programming assistant's session flow. Upon receiving the command and input, the programming assistant resumes execution from its pause point and continues writing unit test code based on the new instructions, paying particular attention to edge case coverage. In this way, developers can intervene and guide tasks on external operating devices without switching to a command-line interface, achieving seamless task integration and efficient progress.

[0076] In summary, the above approach effectively solves the problem of task interruption caused by the lack of an effective interaction mechanism when manual intervention is required during long-running tasks in traditional task processing methods. By adopting a human-machine collaborative interaction model, the originally passive task processing process is transformed into proactive and efficient closed-loop management. This improves the robustness, flexibility, and user experience of the task processing collaboration system when handling complex and long-running tasks, and avoids decreased work efficiency and context switching costs caused by task stagnation.

[0077] Furthermore, when a target task is interrupted or restarted, the system lacks persistent records of the task execution status and layout information, making it impossible to quickly restore the execution environment to its pre-interruption state after a task restart, increasing the burden on users to reconfigure the task context. To address this, in this embodiment, the step of creating a work unit corresponding to each subtask through a command-line interface tool and adding the work unit corresponding to each subtask to the to-do management panel after execution further includes: Obtain global layout information corresponding to each work unit, wherein the global layout information includes at least one of name information, panel information, archive status information, and size information; store the global layout information corresponding to each work unit in a local configuration file, wherein the global layout information stored in the local configuration file is updated according to a real-time update strategy; in the event that the target task is restarted, read the global layout information sequence from the local configuration file, and resume execution of the target task according to the global layout information sequence.

[0078] Specifically, obtaining the global layout information for each work unit refers to the system automatically capturing and aggregating the work unit's name, its current panel (e.g., to-do management panel, execution management panel, archive management panel), its archive status indicator, and its display size on the interface (e.g., width, height) through internal APIs or event listening mechanisms when creating or updating a work unit. Alternatively, when a user operates on a work unit on the task processing collaboration system interface (e.g., dragging, resizing, moving to different panels), the front-end interface can trigger corresponding events, reporting the layout change information (name, panel, archive status, size) to the back-end service in real time for collection. The global layout information for each work unit is stored in a local configuration file. This local configuration file is updated according to a real-time update strategy, meaning it can use structured text formats such as JSON, YAML, or XML and be stored in a preset directory on the task processing collaboration system's server or client. When any change occurs in the global layout information, the system can immediately trigger a write operation to overwrite or append the latest layout information to the local configuration file. In addition, the system can also be configured with a background daemon or scheduled task to check for layout information updates at fixed time intervals (e.g., every 5 or 10 seconds) and write all updates to the local configuration file in batches. A complete layout information write operation will also be forced before the system shuts down normally. When the target task restarts, reading the global layout information sequence from the local configuration file and resuming execution of the target task based on this sequence means that when the task processing collaboration system starts, its initialization module first checks if a local configuration file exists. If it does, the file is parsed, and the global layout information sequence stored within is extracted. Based on this information, the system recreates or repositions the corresponding work units and places them on the corresponding panels and positions, restoring their archived state and size. Alternatively, after system startup, a configuration management service will be loaded. This service is responsible for reading the global layout information from the local configuration file and converting it into an in-memory data structure. Subsequently, the interface rendering module or task management module subscribes to the layout information and dynamically constructs the user interface based on this information, including the display, position, and status of each work unit.

[0079] Based on this, by introducing a persistent storage and recovery mechanism for global layout information, the problem of context loss after task interruption is effectively solved, achieving seamless connection of the task execution environment. Specifically, in the task processing collaboration system, after determining the target task in response to the processing request of the associated target business, the intelligent scheduling module is used to split the target task into multiple subtasks. Subsequently, a work unit corresponding to each subtask is created through a command-line interface tool, and each work unit is added to the to-do management panel. During this process, the system obtains the global layout information corresponding to each work unit. This information comprehensively describes the spatial distribution and state characteristics of the work unit in the collaboration system, providing data support for subsequent accurate recovery. The global layout information is stored in a local configuration file and adopts a real-time update strategy to ensure that the system can continuously record the latest execution snapshot during task execution, avoiding the lag of state information caused by system anomalies or active restarts. When the target task restarts, the system can read the global layout information sequence from the local configuration file and automatically reconstruct the task execution environment based on the information, accurately restoring the work unit to the panel position and state before the restart. This approach, combined with basic task management methods, ensures that the user's work context is fully preserved throughout the entire process of task decomposition, work unit creation, and transition between the to-do, execution, and archive panels, even if the system is interrupted or restarted, thereby greatly improving the continuity and stability of task processing.

[0080] For example, suppose a user is managing a complex software development project using a task-processing collaboration system. One "target task" is "implementing user login functionality." The scheduling intelligence module breaks this target task down into multiple "subtasks," such as "designing the login interface," "developing the backend authentication API," and "writing unit tests." Through a command-line interface tool, the system creates corresponding work units for each subtask, such as "UI design work unit," "API development work unit," and "testing work unit," and adds them to the to-do management panel. When a work unit is created and placed in the to-do management panel, the system immediately retrieves its global layout information. For example, the global layout information for the "UI design work unit" includes its name "UI design work unit," its panel information as "to-do management panel," its archive status information as "not archived," and its default size information on the interface. This global layout information is then stored in a local configuration file, such as a plain text file named layout.json in the user's home directory. If a user drags an "API Development Workbench" from the To-Do panel to the Execution panel, or adjusts the display size of a "UI Design Workbench," the corresponding global layout information in the local configuration file will be updated immediately according to a real-time update strategy. Now, suppose the user's computer unexpectedly restarts, or the task processing collaboration system needs a maintenance restart. When the system restarts, it automatically reads the layout.json file. Based on the sequence of global layout information stored in the file, the system can accurately restore the original positions and sizes of the "UI Design Workbench" and "Test Workbench" in the To-Do panel, and restore the "API Development Workbench" to its corresponding position in the Execution panel. In this way, the user does not need to remember the previous state of each task unit or manually reorganize them; the system can automatically restore the system to its precise working state before the interruption.

[0081] In summary, the above approach effectively solves the problem of the system lacking persistent records of task execution status and layout information after task interruption or restart. This solution reduces the burden on users of reconfiguring task contexts after task restarts by storing and restoring the global layout information of work units in real time, ensuring the continuity and stability of the task processing flow. This frees users from tedious context switching and state restoration work, thereby improving work efficiency and user experience.

[0082] In practical applications, relying solely on simple visual information to determine whether a task has stopped can easily lead to false alarms due to normal pauses or brief periods of unresponsiveness during task execution. This results in the system frequently sending invalid alerts, interfering with the user's accurate assessment of the task status. Therefore, in this embodiment, determining the execution visual information corresponding to the work unit to be processed includes: The execution visualization information corresponding to the work unit to be processed is collected through the content sampling rules of the session isolation layer in the task processing collaboration system. Specifically, when the execution visualization information determines that the target subtask is in a stopped state and has exceeded a set time threshold, a reminder message is sent to the operation terminal in the task processing collaboration system according to a preset reminder strategy. This includes: comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed; and, if the execution visualization information is the same as the historical execution visualization information, and the stopped state time of the target subtask exceeds the set time threshold, executing the step of sending a reminder message to the operation terminal in the task processing collaboration system according to the preset reminder strategy.

[0083] Specifically, the session isolation layer refers to a logical or physical isolation mechanism inserted between the terminal session and the command interpreter in a task processing collaboration system. This isolation layer can hold the terminal session independently of the user interface (such as a browser page) lifecycle, remaining active even if the browser is closed or the system restarts. Its core function is to provide non-intrusive monitoring and interaction capabilities. The content sampling rule of the session isolation layer is a processing capability provided by this layer, allowing the system to periodically read the content of the currently visible area of ​​the session without interfering with the normal input / output flow of the session. This can be achieved by implementing a screen buffer capture module within the session isolation layer or by utilizing the virtual terminal API provided by the underlying operating system. Collecting the execution visualization information corresponding to the work unit to be processed refers to obtaining the visual presentation content of the currently executing subtask on the terminal interface by calling the sampling interface provided by the session isolation layer. This can be a direct capture of the terminal screen text content or a capture of rendered images. Its purpose is to obtain the real-time visual state of task execution as an objective basis for judging whether the task is running normally. Comparing the executed visualization information with the historical executed visualization information corresponding to the work unit to be processed refers to comparing the currently collected visualization information with the visualization information collected at a previous point in time. The purpose of this comparison is to identify whether the content of the task interface has changed, thereby determining whether the task is in an active or inactive state. The comparison method can include calculating the string similarity of text content (e.g., by calculating hash values ​​or edit distance), or feature matching or pixel difference analysis of image content. The target subtask's stopped state time exceeding a set time threshold means that when the executed visualization information is detected to be continuously identical to the historical executed visualization information (i.e., the interface content has not changed for a long time), the system maintains a timer to record the duration of this inactive state. Only when this duration exceeds the preset time threshold is the task determined to be in an abnormal stopped state. The time threshold is introduced to filter out normal short pauses or waits during task execution and avoid false alarms. Sending reminder information to the operation terminal of the task processing collaboration system according to a preset reminder strategy means that when it is confirmed that the target subtask is in an abnormal stopped state for a long time, the system sends a notification to the user according to a pre-configured strategy. Alert strategies can take many forms, such as popping up notifications on the user interface of a task processing collaboration system, sending messages via email or instant messaging tools, or highlighting abnormal tasks on a specific monitoring panel.

[0084] Based on this, by introducing a content sampling mechanism and historical state comparison logic of the session isolation layer, accurate monitoring of task execution status is achieved. In the task processing collaboration system, when the scheduling intelligence module breaks down the target task into multiple subtasks and creates a corresponding work unit for each subtask through the command-line interface tool and adds it to the to-do management panel, the execution intelligence module polls the to-do management panel to determine the work unit to be processed, migrates it to the execution management panel through the command-line interface tool, and executes the target subtask using the task processing intelligence module. In this process, to avoid false alarms caused by normal pauses or brief periods of unresponsiveness during task execution in traditional solutions, this application uses the content sampling rules of the session isolation layer to periodically collect the execution visualization information corresponding to the work unit to be processed. The collected real-time visualization information is compared with the previously collected historical execution visualization information. If the current visualization information is the same as the historical visualization information, it indicates that the task interface content has not been updated for a period of time, and the system will start timing. Only when this static state lasts for more than a preset time threshold will the system determine that the target subtask is in an abnormal stop state and send a reminder message to the operation terminal of the task processing collaboration system according to the preset reminder strategy. This mechanism, based on state consistency verification and time threshold judgment, can effectively distinguish whether a task is in a true abnormal stop state or merely in a normal running interval or repetitive output phase, thereby reducing the false alarm rate and ensuring that alerts are only sent when user intervention is truly necessary. Combined with the aforementioned task processing methods, this solution enables the entire task processing flow to not only execute automatically but also intelligently monitor task status, promptly detect and handle anomalies, and significantly improve the efficiency and reliability of task processing.

[0085] For example, suppose a developer starts a complex code compilation task in a task processing collaboration system. This task is broken down into multiple subtasks, one of which is "compiling the core module." Once the task unit corresponding to "compiling the core module" is selected by the execution intelligent module and moved to the execution management panel, the task processing intelligent module begins executing the subtask. At this time, the session isolation layer in the task processing collaboration system collects execution visualization information from the terminal interface corresponding to this task unit every 5 seconds according to its content sampling rules. For example, the session isolation layer can capture text content on the terminal screen. The system compares the currently collected text content with historical text content collected 5 seconds ago. If, at some point, the currently collected text content is exactly the same as the historical text content, and this identical state continues for 30 seconds (assuming a time threshold of 15 seconds), the system will determine that the "compiling the core module" subtask has stopped or is stuck. At this point, the system will follow a preset reminder strategy, such as popping up a notification window on the developer's interface displaying "'Compile core module' task has stopped, please check," and simultaneously displaying a card containing the status information of the work unit on the developer's external operating device (such as a mobile application), allowing the developer to perform further operations.

[0086] In summary, the above-described approach effectively addresses the false alarm problem caused by simply judging task termination in traditional solutions. By introducing a content sampling mechanism within a session isolation layer, combined with comparisons between current and historical execution visualizations, and the application of time thresholds, the system can more accurately identify the true termination status of target subtasks. This reduces the sending of invalid alerts, avoids unnecessary interference and context switching costs for users, and thus improves the accuracy of users' task status judgments. Users only receive alerts when task intervention is truly necessary, enabling knowledge workers to manage multiple parallel tasks more efficiently, further amplifying their output and enhancing the intelligence level and user experience of the task processing collaboration system.

[0087] In practice, because the execution visualization information contains a large amount of redundant, noisy, or non-critical dynamically changing data, direct comparison can easily lead to inaccurate comparison results, resulting in misjudgment of task status or failure to detect task anomalies in a timely manner. Therefore, in this embodiment, comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed includes: Determine the historical execution visualization information corresponding to the work unit to be processed, wherein the historical execution visualization information is collected by the session isolation layer in the previous sampling period; filter the execution visualization information and the historical execution visualization information respectively; compare the filtered execution visualization information with the filtered historical execution visualization information.

[0088] Specifically, determining the historical execution visualization information corresponding to the work unit to be processed refers to establishing a benchmark for comparison. Historical execution visualization information is a snapshot of the visual state of the work unit to be processed, captured and stored by the session isolation layer at a previous point in time (e.g., the previous sampling period). Its function is to provide a reference point for comparison with the currently collected execution visualization information, thereby detecting changes or stagnation in the task state. The session isolation layer can periodically take snapshots of the terminal output, screenshots, or key UI element states of the currently executing work unit to be processed, and store the snapshot data in memory or persistent storage as historical execution visualization information. For example, the complete text content of the terminal can be automatically captured every preset sampling period. Alternatively, the session isolation layer can monitor the output stream of the work unit to be processed and record the visualization state at each output event. When a preset sampling period is reached, the last recorded visualization state within that period is saved as historical execution visualization information.

[0089] Correspondingly, filtering the execution visualization information and historical execution visualization information separately refers to preprocessing the original execution visualization information and historical execution visualization information to remove redundant, noisy, or dynamically changing parts that do not affect the judgment of task status. Its purpose is to improve the accuracy and efficiency of comparison and avoid misjudgments caused by non-substantial changes. Text content filtering can be used, for example, removing terminal control sequences (such as ANSI escape codes), whitespace characters (such as spaces, tabs, and newlines), and dynamic but meaningless information such as timestamps. In addition, visual noise such as cursor blinking and scroll bar position changes can be identified and removed. As another implementation method, structured data filtering can be used. If the visualization information is structured (such as JSON or XML), filtering rules can be defined to retain only specific fields or attributes and ignore data that changes frequently but is irrelevant to the core task status. For example, for visualization information of graphical user interface (GUI) interfaces, non-core content such as background animations and pop-up ads can be filtered out.

[0090] Correspondingly, comparing the filtered execution visualization information with the filtered historical execution visualization information involves comparing the filtered current execution visualization information with the historical execution visualization information to determine if there are any substantial differences. The aim is to accurately identify whether a task is in a stopped state or has made substantial progress after eliminating interfering factors. String comparison algorithms can be used; for example, calculating the hash values ​​of two filtered text contents, and considering the content identical if the hash values ​​are the same. Alternatively, the Levenshtein distance algorithm can be used to quantify the degree of difference between the two, considering the content identical when the difference is less than a preset threshold. Another implementation method is structured data comparison. If the filtered information is structured, field-level comparisons can be performed, such as comparing the values ​​of key status variables or the presence or absence of specific log entries. When all key fields remain unchanged, the two are considered identical.

[0091] Based on this, a filtering mechanism was introduced to optimize the accuracy of task status monitoring. After determining the execution visualization information corresponding to the work unit to be processed, in order to more accurately determine whether the target subtask is in a stopped state, the historical execution visualization information corresponding to the work unit to be processed is first determined. This historical execution visualization information is collected and stored by the session isolation layer in the previous sampling period, providing a reliable benchmark for comparison of the current state. Subsequently, the currently collected execution visualization information and the historical execution visualization information are subjected to fine-grained filtering processing. This aims to systematically remove interference items from the original data that do not reflect the substantial progress or state changes of the task, such as visual noise such as terminal control sequences, blank characters, and cursor blinking. In this way, the comparison process can focus on the truly meaningful feature data that reflects the core state of the task. Finally, the filtered current execution visualization information is compared with the filtered historical execution visualization information. This comparison mechanism, after eliminating various interference factors, can more accurately identify whether there are substantial differences between the two. If the comparison results show that the two are the same, and the stop time of the target subtask exceeds the preset time threshold, the system can accurately determine that the task has stopped, thereby triggering a subsequent reminder strategy, sending a reminder message to the operator, and displaying the work unit card on the external operating device. Through the above scheme, this application, in the task processing collaboration system, utilizes the execution visualization information collected by the session isolation layer, combined with a filtering mechanism, to ensure the accuracy of task status judgment. This allows the system to effectively avoid misjudging that the task is still busy due to non-substantial changes in terminal output (such as cursor blinking), thereby improving the reliability of task anomaly detection. In the basic scheme, although visualization information can be collected and compared, there is a lack of effective noise processing, which can easily lead to false alarms or missed alarms. By introducing a filtering step, the comparison results more realistically reflect the actual execution status of the task, thus enabling more timely and accurate detection of task stoppage or anomalies, thereby triggering an effective reminder mechanism and improving the user's monitoring efficiency and experience of parallel tasks.

[0092] For example, suppose a work unit is executing a compilation task, and its execution visualization is mainly represented by the terminal's text output. First, the session isolation layer periodically collects the terminal output of this work unit. For instance, in the previous sampling period (e.g., 5 seconds ago), the session isolation layer collected the complete text content of the terminal and stored it as historical execution visualization information. In the current sampling period, the session isolation layer again collects the complete text content of the terminal as the current execution visualization information. Then, the system filters these two original terminal text contents separately. Specifically, the filtering module performs the following operations: It strips terminal control sequences, removing all ANSI escape codes (codes used to control text color, cursor position, etc., but unrelated to the actual progress of the task); it removes whitespace characters, deleting all spaces, tabs, and consecutive newlines from the text, compressing multiple consecutive whitespace characters into one or removing them completely to eliminate differences caused by formatting changes rather than content changes; it removes timestamps and dynamic log IDs; if the terminal output contains automatically generated timestamps or log IDs that change with each run, these are also identified and removed because they are dynamically changing noise; and it standardizes the text, converting all text to lowercase and unifying the encoding format to ensure consistency in the comparison. After the above filtering, the original terminal output text, which contains a lot of noise, is converted into a concise text string containing only the core visible characters. Finally, the system compares the filtered current execution visualization with the filtered historical execution visualization. For example, it can calculate the hash values ​​(such as MD5 or SHA-256) of the two filtered text strings; if the two hash values ​​are exactly the same, it is considered that the terminal output content has not changed substantially after noise removal. If the hash values ​​are different, it indicates that a substantial change has occurred. Only when the comparison results show that the filtered content is the same, and this unchanged state lasts for more than a preset time threshold (e.g., 30 seconds), will the system determine that the target subtask is in a stopped state and trigger the corresponding reminder mechanism.

[0093] In summary, the above processing improves the accuracy and reliability of task status monitoring. In a collaborative task processing system, when it's necessary to determine whether a target subtask needs an alert due to stopping, introducing filtering processing for execution visualization information and historical execution visualization information effectively eliminates redundant information and dynamic noise in the terminal output that doesn't reflect the substantial progress of the task, such as cursor blinking, terminal control sequences, or non-critical log timestamps. This allows subsequent comparison processes to focus on the core state changes of the task, thus avoiding misjudgments caused by non-substantial changes. Therefore, the system can more accurately identify the true stopping state of the task, reducing unnecessary alerts or delays in detecting task anomalies, ensuring the timeliness and effectiveness of the alert strategy. This not only improves the accuracy of alert information received by the operator but also allows the work unit cards displayed on external operating devices to more accurately reflect the current state of the task, thereby significantly improving the user's monitoring efficiency and management experience for parallel tasks.

[0094] In practical implementation, in scenarios where multiple tasks are executed in parallel, the system often lacks a proactive and intelligent filtering mechanism. This prevents users from promptly identifying which tasks are in a critical state or require manual intervention. Consequently, when faced with a large number of executing work units, users struggle to quickly identify the key tasks from a massive amount of information, leading to a contradiction between information overload and delayed response to critical tasks. To address this, in this embodiment, displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system includes: The status information corresponding to at least one execution work unit contained in the execution management panel is read by the backend aggregator, wherein the at least one execution work unit includes the work unit to be processed; the priority mapping table is queried according to the status information corresponding to each execution work unit to determine the execution priority information corresponding to each execution work unit; if the work unit to be processed meets the display conditions according to the execution priority information, the work unit card corresponding to the work unit to be processed is displayed on the external operating device of the task processing collaboration system.

[0095] Specifically, a backend aggregator refers to a module or service located in the backend of a task processing collaboration system, responsible for collecting, integrating, and processing data from different sources. Its role is to unify and aggregate the status information scattered across various execution work units, forming a global, real-time view of the task status. This aggregator can be an independent microservice that subscribes to status updates from each work unit via a message queue; or it can be a data processing layer that periodically polls the API interfaces of each work unit to obtain status data. The execution management panel is a user interface or logical area within the task processing collaboration system, used to display the currently executing work unit and its related information. As the platform for a work unit to transition from the pending state to the execution state, it is the main window for users to monitor task execution progress. This panel can be a specific area on a web interface or an independent view in a desktop application. At least one execution work unit refers to the smallest operational entity corresponding to and currently executing a subtask in the task processing collaboration system. Each execution work unit represents an independent execution instance that can be scheduled and monitored by the system. A work unit can be an independent process, thread, container instance, or a task session within a virtual machine. Status information refers to data describing the current running status of the execution work unit. Information may include, but is not limited to, task running status (e.g., "Running," "Paused," "Error," "Completed"), progress percentage, last update time, resource usage, and key log summaries. A priority mapping table is a predefined set of rules or data structure used to convert the raw status information of execution work units into quantifiable execution priority information. This table defines the correspondence between different status characteristics (e.g., task type, error code, stop duration, resource consumption, etc.) and priority values ​​or levels. Execution priority information is a quantifiable indicator or level derived by evaluating the status information of execution work units according to the priority mapping table. It reflects the importance, urgency, or degree of user attention required for the current work unit among all executing tasks. Display conditions refer to the set of logical rules used to determine whether a work unit to be processed needs to display its work unit card on an external operating device. Based on execution priority information, for example, when the execution priority information reaches a preset threshold, or when the work unit is identified as a "priority work area," the display conditions are met. External operating devices in the task processing collaboration system refer to user terminal devices that interact with the task processing collaboration system and are capable of displaying work unit cards. This can be a standalone monitor (such as a secondary screen), a mobile device (such as a smartphone or tablet), or an auxiliary display area integrated into a workstation. A work unit card refers to an interface element on an external operating device that displays key information about the work unit to be processed in a graphical and summary format.It includes core information such as task name, current status, execution priority, brief progress, and possible error messages.

[0096] Based on this, an intelligent filtering and proactive push system for multi-task execution status was constructed by introducing a backend aggregator and a priority mapping mechanism. After the task processing collaboration system responds to the processing request of the associated target business and determines the target task, the scheduling intelligence module breaks down the target task into multiple subtasks, creates a corresponding work unit for each subtask through a command-line interface tool, and adds it to the to-do management panel. Subsequently, the execution intelligence module polls the to-do management panel to determine the work units to be processed, migrates them to the execution management panel through the command-line interface tool, and executes the corresponding target subtasks using the task processing intelligence module. On this basis, the backend aggregator continuously reads the status information corresponding to at least one execution work unit (including the work units to be processed) contained in the execution management panel. This achieves unified aggregation of task statuses scattered across various execution processes, ensuring that the system can obtain task execution data from a global perspective. For example, the backend aggregator can obtain simplified two-state codes and auxiliary metadata, such as "time since the last state flip," from the bee module of each execution work unit, thereby comprehensively grasping the real-time dynamics of the task. After obtaining the status information, the system queries a pre-defined priority mapping table based on the status information corresponding to each execution work unit to determine the execution priority information for each work unit. The priority mapping table transforms the abstract execution status into quantifiable priority indicators, enabling the system to distinguish the urgency and importance of different tasks. For example, the priority mapping table can map the status information to urgency values ​​from 0 to 100 based on factors such as task error status, stop duration, and resource consumption. Subsequently, the system determines whether the work unit to be processed meets the pre-defined display conditions based on the determined execution priority information. When the execution priority information of the work unit to be processed reaches a specific threshold or is identified as a "priority work area," the system displays the work unit card corresponding to that work unit on the external operating device in the task processing collaboration system. This priority-triggered display mechanism realizes a shift from passive querying to proactive reminders, ensuring that users only receive reminders when a task reaches a specific priority threshold.

[0097] For example, a task processing collaboration system can be deployed on a server cluster, where the backend aggregator can be an independent microservice, such as an aggregation service built on the Spring Cloud framework. This aggregation service subscribes to status update events published by each execution unit through a message queue (such as Kafka), or periodically polls the health check interface of each execution unit through a RESTful API to obtain its status information. The execution management dashboard can be a web frontend application developed based on React or Vue.js, which connects to the backend aggregator via WebSocket to receive and display the status of the executing units in real time. Each execution unit can be a Docker container running an independent agent instance, responsible for executing specific subtasks. During execution, the container periodically publishes its current status information to the message queue, such as "Running," "Waiting for user input," or "An error has occurred (error code: XXX)." The priority mapping table can be stored in a NoSQL database (such as Redis), and its structure can be defined by a series of rules, such as: if the status information contains the keyword "error", the urgency is increased by 50; if the "time since the last status flip" exceeds 5 minutes and the status is "running", the urgency is increased by 30; if the status is "waiting for user input", the urgency is increased by 40; if the task type is "critical business", the base urgency is 60. After receiving the status information of the work unit, the backend aggregator calculates an urgency value from 0 to 100 as the execution priority information according to the rules. The display condition can be set as follows: when the execution priority information (urgency) is greater than or equal to 70, or when the work unit is identified by the backend aggregator as the "priority work area" with the highest urgency among all currently executing tasks, the display condition is met. The external operating device in the task processing collaboration system can be a second monitor (secondary screen) connected to the user's workstation, or a dedicated tablet computer. When the display condition is met, a work unit card will be displayed on this device. The card can be a simple UI component, for example, displaying "Priority Workspace: [Task Name]" in large font at the top of the secondary screen, with its current status (e.g., "Waiting for user input, 10 minutes have passed") and urgency value below. Users can trigger further actions by clicking the card or through specific gestures on an external device, such as navigating to the main interface to view detailed logs or sending commands to the task processing intelligence module.

[0098] In summary, the above-described approach effectively addresses the challenges of users struggling to quickly identify key tasks from massive amounts of information in multi-task parallel execution scenarios, as well as the issues of information overload and delayed response to critical tasks. It enables more accurate identification of abnormal task pauses and highlights them through a prioritization mechanism, further enhancing the system's intelligence and the timeliness of user response. Users can quickly identify the most critical work area requiring intervention with just a glance at the work unit card on the external operating device, significantly improving the efficiency and accuracy of human-machine collaborative task processing.

[0099] In practical implementation, there is a lack of an effective interaction mechanism to accurately and efficiently transmit unstructured operation instructions generated by external devices to the background running intelligent agent task, and to ensure that the instructions can be correctly recognized and executed by the task processing intelligent module. This results in a communication gap between the external operation instructions and the background task execution environment. To address this, in this embodiment, receiving the operation instructions submitted by the external operation device for the work unit card and sending the operation instructions to the task processing intelligent module includes: The operation text is determined based on the operation instructions submitted by the external operation device to the work unit card; the operation text is written to the session stream corresponding to the work unit to be processed using the session isolation layer, as an operation to send the operation instructions to the task processing intelligent module. Specifically, external operating devices can refer to any computing device used to interact with the task processing collaboration system, such as, but not limited to, tablets, smartphones, auxiliary displays with touchscreens, or remote desktop clients. Their main function is to provide a user interface to display task information and receive user input. A work unit card is a graphical user interface element in the task processing collaboration system used to visually represent a work unit to be processed. It can be a standalone window, an item in a panel, or an interactive component, displaying information such as the name, status, and progress of the work unit to be processed, and providing an entry point for user operation. Operation instructions refer to the intentions expressed by the user when interacting with the work unit card through the external operating device. These instructions can take various forms, such as text typed in a text input box, clicking a button, selecting a menu item, or performing a specific gesture. Operation text refers to the structured text information obtained after parsing and transforming the original operation instructions submitted by the user. For example, if the user clicks a "pause" button, the operation text is "pause"; if the user types text in an input box, that text itself serves as the operation text. The session isolation layer is middleware or a software module whose role is to manage and isolate execution sessions of different tasks within the task processing collaboration system. It ensures that the input and output streams of each task are independent, avoiding mutual interference, and provides the ability to inject content into specific sessions. A pending work unit refers to a work unit created but not yet completed in the task processing collaboration system; it is waiting to be executed, is executing, or is paused for some reason. A session stream refers to the input / output channel associated with a specific pending work unit. The task processing intelligence module receives instructions and outputs execution results through this channel. It can be a standard command-line input stream (stdin), a message queue, or a specific API interface. The task processing intelligence module is the core component of the task processing collaboration system, responsible for parsing and executing target subtasks and performing corresponding operations based on received instructions.

[0100] Based on this, a precise remote control of long-running tasks is achieved by constructing an instruction mapping and injection mechanism from external operating devices to the background task execution environment. Specifically, when a user interacts with a work unit card and submits operation instructions through an external operating device, the system first converts the user's intuitive interaction into standardized operation text that can be processed by the computer. This ensures the standardization and transmissibility of instructions; regardless of the form of external device input used by the user, it can ultimately be uniformly represented as text information. Subsequently, using the session isolation layer middleware, the operation text is accurately written into the session stream corresponding to the specific work unit to be processed. The session isolation layer plays a crucial role in this process. It not only ensures that external instructions can be accurately injected into the execution context of the target task, but also effectively avoids instruction misalignment or mutual interference in a multi-task parallel processing environment through its isolation mechanism. Writing the operation text as part of the session stream allows the task processing intelligent module to process remote instructions as if they were local input, thereby achieving seamless intervention and dynamic adjustment of the running target subtask. This approach not only solves the problem of remote instruction transmission but also ensures the stability and security of multi-task collaborative processing through the session stream isolation mechanism. This processing method enables the efficient and accurate transmission of operation instructions from external devices to the task processing intelligent module upon receipt of such instructions. This allows the task processing intelligent module to continue executing the target sub-task based on the instructions, effectively solving the communication gap problem between external operation instructions and the background task execution environment.

[0101] For example, when an agent task is running on the main display and its corresponding work unit card is displayed on the auxiliary display, the developer doesn't need to switch back to the main display. They can directly type instructions, such as "Please continue to the next step," into the text input box provided below the work unit card on the auxiliary display. At this time, the external operating device (the auxiliary display and its input components) receives this text input as an operation instruction and identifies it as the operation text. Subsequently, the backend service in the task processing collaboration system sends this operation text to the session isolation layer. After receiving the operation text, the session isolation layer writes it into the terminal session input stream corresponding to the work unit. To simulate a user's "long paste" and press Enter on their local terminal, the session isolation layer introduces a brief delay, such as several hundred milliseconds, after writing the operation text, and then simulates a single Enter press. This delay mechanism ensures that the task processing intelligent module (e.g., a programming assistant) has sufficient time to recognize and process the pasted content, avoiding skipping the existing secondary confirmation mechanism due to a too-fast Enter press. Simultaneously, the session isolation layer can also impose length limits and non-empty checks on the injected text to prevent abnormal or malicious requests. In this way, the task processing intelligent module can continue to execute its target subtask based on the injected "please continue to the next step" instruction, just as if it had received local user input.

[0102] In summary, the aforementioned remote interaction mechanism enables users to perform fine-grained control over multiple parallel tasks without frequently switching contexts, thereby avoiding efficiency losses and task omissions caused by high context switching costs and poor instruction transmission. Furthermore, users often need to simultaneously monitor the task execution status, terminal output information, and historical execution records. If this information is scattered across different interfaces or areas, users will frequently need to switch perspectives or windows while processing tasks, making it difficult to intuitively and comprehensively obtain the task execution context information within a unified collaborative page, thereby reducing the efficiency of task monitoring and management. To address this, in this embodiment, the to-do management panel, the execution management panel, and the archive management panel are located in the control area of ​​the collaborative task processing page. The collaborative task processing page also includes an operation area, which comprises a first operation sub-area and a second operation sub-area. The first operation sub-area displays the terminal display information corresponding to the work unit to be processed, and the second operation sub-area displays the task execution record information corresponding to the work unit to be processed.

[0103] Specifically, the to-do list panel displays task units that have not yet started or are awaiting further user action. It can be presented as a list, card, or icon, allowing users to clearly understand the current task queue. The execution panel displays task units that are currently executing or paused. This panel can update the task execution status in real time, such as displaying progress bars, status indicators, or brief execution logs, so users can monitor the task's real-time progress. The archive panel displays completed, canceled, or archived task units. This panel stores historical task records, allowing users to review and query processed tasks. The collaborative task processing page is an integrated user interface designed to provide a unified platform for managing, monitoring, and interacting with multiple tasks and their related information. This page can be a standalone application window, a web page, or a specific view within an integrated development environment (IDE). The control area is a section of the collaborative task processing page specifically designed to centrally display and manage task status, flow, and overview information. This area is located in the sidebar, top, or bottom of the page, and its design goal is to provide a macro view of tasks and quick navigation. The operation area refers to the portion of the collaborative task processing page used to display detailed information, real-time output, and interactive interfaces of the selected task unit. This area occupies the main part of the page, and its content updates dynamically based on the different task units selected by the user in the control area. The first operation sub-area refers to the portion of the operation area specifically used to display real-time terminal output or an interactive command-line interface. This sub-area can be an embedded terminal emulator, a log output window, or an interactive console, used to present immediate feedback information during task execution. The second operation sub-area refers to the area within the operation area specifically used to display the task's historical execution records, documents, notes, or related contextual information. This sub-area can be a text editor, a Markdown renderer, or a file browser, used to provide background information and historical trajectory of the task. Terminal display information refers to the text output generated in the command-line interface or terminal during task execution, including program execution logs, error messages, user interaction prompts, and other standard output content. This information directly reflects the task's execution status and progress. Task execution record information refers to historical operations, execution results, key event logs, user notes, or any persistent data related to a specific task unit that helps understand the task context, allowing users to trace the complete lifecycle of the task.

[0104] Based on this, by organically integrating the core functions of task management with detailed task execution information into a single collaborative task processing page, the problems of scattered information and frequent context switching in traditional solutions are solved. Specifically, the collaborative task processing page is divided into a control area and an operation area. The control area centrally hosts the to-do management panel, execution management panel, and archive management panel, which can intuitively display the macro-status and workflow of all task work units. When a user selects a specific work unit to be processed in the control area, the operation area dynamically updates and displays the detailed information of that work unit. The operation area is further subdivided into a first operation sub-area and a second operation sub-area. The first operation sub-area is specifically used to display the terminal display information corresponding to the selected work unit to be processed, which allows users to view the task's execution output, progress, and any potential errors or interactive prompts in real time without switching to a separate terminal window. At the same time, the second operation sub-area is used to display the task execution record information corresponding to the work unit to be processed, which provides users with the task's historical context, key operation logs, and any related documents or notes, thereby helping users to fully understand the ins and outs of the task. This layout design allows users to view the overall status of all tasks within a unified interface, while also providing in-depth access to the real-time execution details and historical records of individual tasks. For example, in the task processing method described above, after the scheduling intelligence module breaks down the target task into multiple subtasks and creates work units via the command-line interface tool, adding them to the to-do management panel, the user can see these work units in the to-do management panel of the control area. When the execution intelligence module pollutes the to-do management panel and migrates pending work units to the execution management panel, and the task processing intelligence module executes the target subtask, the user can see the changes in the task status in the execution management panel of the control area. At this time, by selecting the executing work unit, the first operation sub-area of ​​the operation area will display the terminal output of the task processing intelligence module executing the target subtask in real time, while the second operation sub-area will display the historical execution record of that subtask. This tight integration avoids frequent switching between multiple applications or windows, reduces cognitive load and context switching costs, and enables users to monitor, manage, and intervene in the task execution process more efficiently. Furthermore, combined with the aforementioned task execution status detection and reminder mechanisms, as well as the reception of operation instructions, this unified page layout further enhances the user's control over the task, making exception handling and manual intervention more timely and convenient.

[0105] For example, such as Figure 2eThe diagram illustrates that the collaborative task processing page can be designed as a left-right layout application interface. The left side of the page serves as a control area, vertically divided into multiple panels. For example, a panel named "TODO" displays tasks yet to be started, a panel named "DOING" displays currently executing tasks, and a collapsible "Archived" panel stores completed or archived tasks. Each task can be presented as a card within the panel, displaying its name and a circular status indicator light before it. For instance, the light is green when the internal terminal session is running and gray when the session is idle. The right side of the page serves as the operation area, further divided into upper and lower sub-areas. The upper part serves as the first operation sub-area, embedding a real terminal simulator to display real-time terminal output information from the programming assistant running the user-selected task in the control area (e.g., a workspace named "audiopp"). The lower half can serve as a second sub-area for operations, displaying a Markdown notes panel to show task execution history information related to the work unit to be processed, such as task plans, logs, user notes, or any historical documents. Additionally, the bottom of the collaborative task processing page can include a "+New Workspace" button for creating new task work units, and a notification volume slider for adjusting the volume of system notifications. This layout allows users to intuitively manage the task lifecycle and obtain real-time execution details and historical context from a unified interface.

[0106] In summary, the above layout centralizes the to-do management panel, execution management panel, and archive management panel within the control area of ​​the collaborative task processing page. This page also integrates an operation area, comprising a first sub-area displaying terminal information and a second sub-area displaying task execution records. This effectively solves the problems of scattered task information and frequent context switching required by traditional solutions. Users can gain a comprehensive understanding of the overall status and flow of all tasks within a unified collaborative task processing page, while also deeply viewing the real-time execution output and historical records of specific pending work units. This integrated view reduces the cognitive load and operational complexity for users, avoiding the tedious switching between different windows or applications, thus significantly improving the efficiency and convenience of task monitoring and management. Especially when handling multiple parallel tasks, users can quickly locate, understand, and intervene in tasks, ensuring the continuity and timeliness of task processing, thereby optimizing the overall workflow. Corresponding to the above method embodiments, this specification also provides embodiments of a task processing collaborative system. Figure 3 A schematic diagram of the structure of a task processing collaborative system provided in one embodiment of this specification is shown. Figure 3 As shown, the task processing collaboration system 300 includes an operation terminal 310 and a processing terminal 320, including: The operation terminal 310 is used to receive processing requests related to the target service and send the processing requests to the processing terminal; The processing terminal 320 is used to determine the target task in response to the processing request, and to use the scheduling intelligence module to split the target task into multiple sub-tasks; The operation terminal 310 is used to create a work unit corresponding to each subtask through the command line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The processing terminal 320 is used to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and use the task processing intelligence module to execute the target sub-task corresponding to the work unit to be processed. The operation terminal 310 is used to migrate the work unit to be processed to the execution management panel through the command line interface tool; and when the target subtask is completed, to migrate the work unit to be processed to the archive management panel through the command line interface tool.

[0107] In an optional embodiment, the step of using the execution intelligence module to poll the to-do management panel to determine the work units to be processed, migrating the work units to be processed to the execution management panel via the command-line interface tool, and using the task processing intelligence module to execute the target sub-tasks corresponding to the work units to be processed includes: using the execution intelligence module to poll the to-do management panel and selecting work units as work units to be processed in sequence according to the polling results; migrating the work units to be processed to the execution management panel via the command-line interface tool and switching the working directory corresponding to the previous polling cycle to the working directory corresponding to the work unit to be processed; and using the task processing intelligence module to execute the target sub-tasks corresponding to the work units to be processed according to the switched working directory.

[0108] In an optional embodiment, after the task processing intelligent module executes the target sub-task steps corresponding to the work unit to be processed, the method further includes: detecting the execution status of the work units contained in the to-do management panel, the execution management panel, and the archive management panel respectively; and displaying the status prompt information of the corresponding work unit in the to-do management panel, the execution management panel, and the archive management panel according to the execution status.

[0109] In an optional embodiment, before the step of migrating the work unit to be processed to the archive management panel via the command-line interface tool after the target subtask has been completed, the method further includes: determining the execution visualization information corresponding to the work unit to be processed; if the target subtask is in a stopped state and exceeds a set time threshold according to the execution visualization information, sending a reminder message to the operation terminal of the task processing collaboration system according to a preset reminder strategy, and displaying the work unit card corresponding to the work unit to be processed on the external operation device of the task processing collaboration system.

[0110] In an optional embodiment, the method further includes: receiving an operation instruction submitted by the external operating device for the work unit card, and sending the operation instruction to the task processing intelligent module, wherein the work unit card displays execution status information corresponding to the work unit to be processed; and using the task processing intelligent module to continue executing the target subtask according to the operation instruction.

[0111] In an optional embodiment, after the step of creating a work unit corresponding to each subtask via a command-line interface tool and adding the work unit corresponding to each subtask to the to-do management panel, the method further includes: obtaining global layout information corresponding to each work unit, wherein the global layout information includes at least one of name information, panel information, archive status information, and size information; storing the global layout information corresponding to each work unit in a local configuration file, wherein the global layout information stored in the local configuration file is updated according to a real-time update strategy; and, in the event that the target task restarts, reading the global layout information sequence from the local configuration file and resuming the execution of the target task according to the global layout information sequence.

[0112] In an optional embodiment, determining the execution visualization information corresponding to the work unit to be processed includes: collecting the execution visualization information corresponding to the work unit to be processed through the content sampling rules of the session isolation layer in the task processing collaboration system; wherein, when it is determined from the execution visualization information that the target subtask is in a stopped state and exceeds a set time threshold, sending reminder information to the operation terminal in the task processing collaboration system according to a preset reminder strategy includes: comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed; when the execution visualization information is the same as the historical execution visualization information, and the stopped state time of the target subtask exceeds the set time threshold, performing the step of sending reminder information to the operation terminal in the task processing collaboration system according to the preset reminder strategy.

[0113] In an optional embodiment, comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed includes: determining the historical execution visualization information corresponding to the work unit to be processed, wherein the historical execution visualization information is collected by the session isolation layer in the previous sampling period; filtering the execution visualization information and the historical execution visualization information respectively; and comparing the filtered execution visualization information with the filtered historical execution visualization information.

[0114] In an optional embodiment, displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system includes: reading the status information corresponding to at least one execution work unit contained in the execution management panel through a backend aggregator, wherein the at least one execution work unit includes the work unit to be processed; querying a priority mapping table according to the status information corresponding to each execution work unit to determine the execution priority information corresponding to each execution work unit; and displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system when the execution priority information determines that the work unit to be processed meets the display conditions.

[0115] In an optional embodiment, receiving the operation instruction submitted by the external operating device for the work unit card and sending the operation instruction to the task processing intelligent module includes: determining the operation text based on the operation instruction submitted by the external operating device for the work unit card; and using the session isolation layer to write the operation text into the session stream corresponding to the work unit to be processed, as an operation to send the operation instruction to the task processing intelligent module. In one optional embodiment, the to-do management panel, the execution management panel, and the archive management panel are located in the control area of ​​the collaborative task processing page. The collaborative task processing page further includes an operation area, which includes a first operation sub-area and a second operation sub-area. The first operation sub-area displays the terminal display information corresponding to the work unit to be processed, and the second operation sub-area displays the task execution record information corresponding to the work unit to be processed.

[0116] The above is an illustrative scheme of a task processing collaborative system according to this embodiment. It should be noted that the technical solution of this task processing collaborative system and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the task processing collaborative system, please refer to the description of the technical solution of the task processing method described above.

[0117] Corresponding to the above method embodiments, this specification also provides another embodiment of a task processing collaborative system. Figure 4 A schematic diagram of another task processing collaborative system provided in one embodiment of this specification is shown. Figure 4 As shown, the task processing collaborative system 400 includes a scheduling intelligent module 410, an execution intelligent module 420, and a task processing intelligent module 430, comprising: The scheduling intelligence module 410 is used to determine the target task in response to the processing request of the associated target business, split the target task into multiple sub-tasks, create a work unit corresponding to each sub-task through the command line interface tool, and add the work unit corresponding to each sub-task to the to-do management panel. The execution intelligence module 420 is used to poll the to-do management panel to determine the work units to be processed, and to migrate the work units to be processed to the execution management panel through the command line interface tool. The task processing intelligent module 430 is used to execute the target subtask corresponding to the work unit to be processed; when the target subtask is completed, the work unit to be processed is migrated to the archive management panel through the command line interface tool.

[0118] In an optional embodiment, the step of using the execution intelligence module to poll the to-do management panel to determine the work units to be processed, migrating the work units to be processed to the execution management panel via the command-line interface tool, and using the task processing intelligence module to execute the target sub-tasks corresponding to the work units to be processed includes: using the execution intelligence module to poll the to-do management panel and selecting work units as work units to be processed in sequence according to the polling results; migrating the work units to be processed to the execution management panel via the command-line interface tool and switching the working directory corresponding to the previous polling cycle to the working directory corresponding to the work unit to be processed; and using the task processing intelligence module to execute the target sub-tasks corresponding to the work units to be processed according to the switched working directory.

[0119] In an optional embodiment, after the task processing intelligent module executes the target sub-task steps corresponding to the work unit to be processed, the method further includes: detecting the execution status of the work units contained in the to-do management panel, the execution management panel, and the archive management panel respectively; and displaying the status prompt information of the corresponding work unit in the to-do management panel, the execution management panel, and the archive management panel according to the execution status.

[0120] In an optional embodiment, before the step of migrating the work unit to be processed to the archive management panel via the command-line interface tool after the target subtask has been completed, the method further includes: determining the execution visualization information corresponding to the work unit to be processed; if the target subtask is in a stopped state and exceeds a set time threshold according to the execution visualization information, sending a reminder message to the operation terminal of the task processing collaboration system according to a preset reminder strategy, and displaying the work unit card corresponding to the work unit to be processed on the external operation device of the task processing collaboration system.

[0121] In an optional embodiment, the method further includes: receiving an operation instruction submitted by the external operating device for the work unit card, and sending the operation instruction to the task processing intelligent module, wherein the work unit card displays execution status information corresponding to the work unit to be processed; and using the task processing intelligent module to continue executing the target subtask according to the operation instruction.

[0122] In an optional embodiment, after the step of creating a work unit corresponding to each subtask via a command-line interface tool and adding the work unit corresponding to each subtask to the to-do management panel, the method further includes: obtaining global layout information corresponding to each work unit, wherein the global layout information includes at least one of name information, panel information, archive status information, and size information; storing the global layout information corresponding to each work unit in a local configuration file, wherein the global layout information stored in the local configuration file is updated according to a real-time update strategy; and, in the event that the target task restarts, reading the global layout information sequence from the local configuration file and resuming the execution of the target task according to the global layout information sequence.

[0123] In an optional embodiment, determining the execution visualization information corresponding to the work unit to be processed includes: collecting the execution visualization information corresponding to the work unit to be processed through the content sampling rules of the session isolation layer in the task processing collaboration system; wherein, when it is determined from the execution visualization information that the target subtask is in a stopped state and exceeds a set time threshold, sending reminder information to the operation terminal in the task processing collaboration system according to a preset reminder strategy includes: comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed; when the execution visualization information is the same as the historical execution visualization information, and the stopped state time of the target subtask exceeds the set time threshold, performing the step of sending reminder information to the operation terminal in the task processing collaboration system according to the preset reminder strategy.

[0124] In an optional embodiment, comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed includes: determining the historical execution visualization information corresponding to the work unit to be processed, wherein the historical execution visualization information is collected by the session isolation layer in the previous sampling period; filtering the execution visualization information and the historical execution visualization information respectively; and comparing the filtered execution visualization information with the filtered historical execution visualization information.

[0125] In an optional embodiment, displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system includes: reading the status information corresponding to at least one execution work unit contained in the execution management panel through a backend aggregator, wherein the at least one execution work unit includes the work unit to be processed; querying a priority mapping table according to the status information corresponding to each execution work unit to determine the execution priority information corresponding to each execution work unit; and displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system when the execution priority information determines that the work unit to be processed meets the display conditions.

[0126] In an optional embodiment, receiving the operation instruction submitted by the external operating device for the work unit card and sending the operation instruction to the task processing intelligent module includes: determining the operation text based on the operation instruction submitted by the external operating device for the work unit card; and using the session isolation layer to write the operation text into the session stream corresponding to the work unit to be processed, as an operation to send the operation instruction to the task processing intelligent module. In one optional embodiment, the to-do management panel, the execution management panel, and the archive management panel are located in the control area of ​​the collaborative task processing page. The collaborative task processing page further includes an operation area, which includes a first operation sub-area and a second operation sub-area. The first operation sub-area displays the terminal display information corresponding to the work unit to be processed, and the second operation sub-area displays the task execution record information corresponding to the work unit to be processed.

[0127] The above is an illustrative scheme of another task processing collaborative system in this embodiment. It should be noted that the technical solution of this task processing collaborative system and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the task processing collaborative system, please refer to the description of the technical solution of the task processing method described above.

[0128] See Figure 5 , Figure 5 A flowchart of another task processing method according to an embodiment of this specification is shown. The method is applied to a task processing collaborative system and specifically includes the following steps.

[0129] Step S502: In response to the processing request of the related R&D business, determine the project task and use the scheduling intelligence module to split the project task into multiple sub-tasks.

[0130] Step S504: Create a work unit corresponding to each subtask through the command line interface tool, and add the work unit corresponding to each subtask to the to-do management panel.

[0131] Step S506: Use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and use the command line interface tool to migrate the work unit to be processed to the execution management panel, and use the programming intelligence module to execute the target subtask corresponding to the work unit to be processed.

[0132] Step S508: After the target subtask is completed, the work unit to be processed is migrated to the archive management panel through the command line interface tool.

[0133] Another task processing method provided in this embodiment is applied to R&D business scenarios. For any content not described in detail, please refer to the same or corresponding descriptions in the above embodiments. This embodiment will not elaborate further here.

[0134] The following is in conjunction with the appendix Figure 6 Taking the application of the task processing collaboration system provided in this specification in a collaborative writing scenario as an example, the task processing collaboration system will be further explained. Among other things, Figure 6 A flowchart of a task processing collaborative system provided in one embodiment of this specification is shown.

[0135] Collaborative writing scenarios include scheduling agents, execution agents, dashboard services, and user interfaces. The user interface refers to a client that integrates a main screen and a secondary screen for user browsing and operation. The dashboard service specifically refers to a control panel that displays the execution progress and details of multiple subtasks to the user. Figure 6 As shown, the specific implementation method is as follows: Step 1, Task Release: The scheduling agent receives the writing task submitted by the user, breaks it down into multiple sub-tasks, creates a work unit corresponding to each sub-task through the command line interface tool, and adds the work unit to the to-do panel.

[0136] Step 2, execute the agent to retrieve: The agent will poll the to-do panel, determine the work unit to be processed based on the polling results, call the command line interface tool to move the work unit to be processed to the execution panel, and switch the working directory to execute the writing subtask corresponding to the work unit to be processed.

[0137] Step 3, Continuous execution (state = running): The execution agent outputs the writing content corresponding to the writing subtask. The state self-aware module continuously identifies the work unit to be processed as running, while the secondary screen sets its urgency to medium.

[0138] Step 4, completion reminder trigger: When the intelligent module completes a certain stage and pauses to wait for user confirmation, the status self-sensing module recognizes that the screen is still and the secondary filter determines that the work unit to be processed has been in a stopped state for more than the set time, triggering a completion reminder. The status indicator light turns gray, the bell rings once, and the secondary screen adjusts the work unit to be processed to the top of the list and recommends it as a priority work unit.

[0139] Step 5, User's secondary screen one-click reply: The operation terminal receives the input command from the user from the corresponding priority work unit on the secondary screen. The remote interaction injection mechanism sequentially transmits the text corresponding to the command and the confirmation instruction to the execution agent, which then continues to process the writing sub-task.

[0140] Step 6, Archiving: Once the agent has completed all writing tasks, invoke the archiving command to move the work units in the execution panel to the archiving panel and clear the cards on the secondary screen.

[0141] In summary, by responding to business requests to identify tasks, break down subtasks, create work units, and utilize the to-do management panel, execution management panel, and archive management panel to automate the flow of task status, the system effectively solves the problems of lack of centralized monitoring of task status and insufficient expression of workflow sequence. It achieves centralized monitoring and process management of task status, effectively reduces the context switching burden on users in multi-task processing, and improves task processing efficiency.

[0142] Corresponding to the above method embodiments, this specification also provides embodiments of a task processing device. Figure 7 A schematic diagram of a task processing apparatus according to one embodiment of this specification is shown. Figure 7 As shown, this device is applied to a task processing collaborative system and includes: The determination module 702 is configured to determine the target task in response to the processing request of the associated target service, and to use the scheduling intelligence module to split the target task into multiple sub-tasks; Module 704 is configured to create work units corresponding to each subtask via the command-line interface tool and add the work units corresponding to each subtask to the to-do management panel. The execution module 706 is configured to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and to migrate the work unit to be processed to the execution management panel through the command line interface tool, and to use the task processing intelligence module to execute the target subtask corresponding to the work unit to be processed. The migration module 708 is configured to migrate the work unit to be processed to the archive management panel via the command-line interface tool when the target subtask is completed.

[0143] In an optional embodiment, the step of using the execution intelligence module to poll the to-do management panel to determine the work units to be processed, migrating the work units to be processed to the execution management panel via the command-line interface tool, and using the task processing intelligence module to execute the target sub-tasks corresponding to the work units to be processed includes: using the execution intelligence module to poll the to-do management panel and selecting work units as work units to be processed in sequence according to the polling results; migrating the work units to be processed to the execution management panel via the command-line interface tool and switching the working directory corresponding to the previous polling cycle to the working directory corresponding to the work unit to be processed; and using the task processing intelligence module to execute the target sub-tasks corresponding to the work units to be processed according to the switched working directory.

[0144] In an optional embodiment, after the task processing intelligent module executes the target sub-task steps corresponding to the work unit to be processed, the method further includes: detecting the execution status of the work units contained in the to-do management panel, the execution management panel, and the archive management panel respectively; and displaying the status prompt information of the corresponding work unit in the to-do management panel, the execution management panel, and the archive management panel according to the execution status.

[0145] In an optional embodiment, before the step of migrating the work unit to be processed to the archive management panel via the command-line interface tool after the target subtask has been completed, the method further includes: determining the execution visualization information corresponding to the work unit to be processed; if the target subtask is in a stopped state and exceeds a set time threshold according to the execution visualization information, sending a reminder message to the operation terminal of the task processing collaboration system according to a preset reminder strategy, and displaying the work unit card corresponding to the work unit to be processed on the external operation device of the task processing collaboration system.

[0146] In an optional embodiment, the method further includes: receiving an operation instruction submitted by the external operating device for the work unit card, and sending the operation instruction to the task processing intelligent module, wherein the work unit card displays execution status information corresponding to the work unit to be processed; and using the task processing intelligent module to continue executing the target subtask according to the operation instruction.

[0147] In an optional embodiment, after the step of creating a work unit corresponding to each subtask via a command-line interface tool and adding the work unit corresponding to each subtask to the to-do management panel, the method further includes: obtaining global layout information corresponding to each work unit, wherein the global layout information includes at least one of name information, panel information, archive status information, and size information; storing the global layout information corresponding to each work unit in a local configuration file, wherein the global layout information stored in the local configuration file is updated according to a real-time update strategy; and, in the event that the target task restarts, reading the global layout information sequence from the local configuration file and resuming the execution of the target task according to the global layout information sequence.

[0148] In an optional embodiment, determining the execution visualization information corresponding to the work unit to be processed includes: collecting the execution visualization information corresponding to the work unit to be processed through the content sampling rules of the session isolation layer in the task processing collaboration system; wherein, when it is determined from the execution visualization information that the target subtask is in a stopped state and exceeds a set time threshold, sending reminder information to the operation terminal in the task processing collaboration system according to a preset reminder strategy includes: comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed; when the execution visualization information is the same as the historical execution visualization information, and the stopped state time of the target subtask exceeds the set time threshold, performing the step of sending reminder information to the operation terminal in the task processing collaboration system according to the preset reminder strategy.

[0149] In an optional embodiment, comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed includes: determining the historical execution visualization information corresponding to the work unit to be processed, wherein the historical execution visualization information is collected by the session isolation layer in the previous sampling period; filtering the execution visualization information and the historical execution visualization information respectively; and comparing the filtered execution visualization information with the filtered historical execution visualization information.

[0150] In an optional embodiment, displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system includes: reading the status information corresponding to at least one execution work unit contained in the execution management panel through a backend aggregator, wherein the at least one execution work unit includes the work unit to be processed; querying a priority mapping table according to the status information corresponding to each execution work unit to determine the execution priority information corresponding to each execution work unit; and displaying the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system when the execution priority information determines that the work unit to be processed meets the display conditions.

[0151] In an optional embodiment, receiving the operation instruction submitted by the external operating device for the work unit card and sending the operation instruction to the task processing intelligent module includes: determining the operation text based on the operation instruction submitted by the external operating device for the work unit card; and using the session isolation layer to write the operation text into the session stream corresponding to the work unit to be processed, as an operation to send the operation instruction to the task processing intelligent module. In one optional embodiment, the to-do management panel, the execution management panel, and the archive management panel are located in the control area of ​​the collaborative task processing page. The collaborative task processing page further includes an operation area, which includes a first operation sub-area and a second operation sub-area. The first operation sub-area displays the terminal display information corresponding to the work unit to be processed, and the second operation sub-area displays the task execution record information corresponding to the work unit to be processed.

[0152] The above is an illustrative scheme of a task processing device according to this embodiment. It should be noted that the technical solution of this task processing device and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the task processing device, please refer to the description of the technical solution of the task processing method described above.

[0153] Corresponding to the above method embodiments, this specification also provides another embodiment of a task processing apparatus. Figure 8 A schematic diagram of another task processing apparatus provided in one embodiment of this specification is shown. Figure 8 As shown, the device includes: The task determination module 802 is configured to determine project tasks in response to processing requests from related R&D business, and to use the scheduling intelligence module to break down the project tasks into multiple sub-tasks. The Create Unit module 804 is configured to create work units corresponding to each subtask via the command-line interface tool and add the work units corresponding to each subtask to the to-do management panel; The unit determination module 806 is configured to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and to migrate the work unit to be processed to the execution management panel through the command line interface tool, and to use the programming intelligence module to execute the target subtask corresponding to the work unit to be processed. The migration unit module 808 is configured to migrate the work unit to be processed to the archive management panel via the command-line interface tool when the target subtask is completed.

[0154] The above is an illustrative scheme of another task processing device in this embodiment. It should be noted that the technical solution of this task processing device and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the task processing device, please refer to the description of the technical solution of the task processing method described above.

[0155] Figure 9 A structural block diagram of a computing device 900 according to one embodiment of this specification is shown. The components of the computing device 900 include, but are not limited to, a memory 910 and a processor 920. The processor 920 is connected to the memory 910 via a bus 930, and a database 950 is used to store data.

[0156] The computing device 900 also includes an access device 940, which enables the computing device 900 to communicate via one or more networks 960. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 940 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0157] In one embodiment of this specification, the above-described components of the computing device 900 and Figure 9 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 9 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0158] The computing device 900 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 900 can also be a mobile or stationary server.

[0159] The processor 920 is configured to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the above-described task processing method.

[0160] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the task processing method described above.

[0161] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described task processing method.

[0162] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the task processing method described above.

[0163] An embodiment of this specification also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described task processing method.

[0164] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the task processing method described above belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the task processing method described above.

[0165] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or advantageous.

[0166] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0167] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0168] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0169] The preferred embodiments disclosed above are merely illustrative of this specification. Optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described in this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification.

Claims

1. A task processing method, characterized in that, Applications in task processing collaborative systems include: In response to the processing request of the associated target business, the target task is determined, and the target task is divided into multiple sub-tasks using the scheduling intelligence module; Create a work unit corresponding to each subtask using the command-line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The task management panel is polled using the execution intelligence module to determine the work units to be processed, and the work units to be processed are migrated to the execution management panel through the command line interface tool. The target sub-tasks corresponding to the work units to be processed are executed using the task processing intelligence module. Once the target subtask is completed, the pending work unit is migrated to the archive management panel via the command-line interface tool.

2. The task processing method according to claim 1, characterized in that, The process of using the execution intelligence module to poll the to-do management panel to determine the work units to be processed, migrating the work units to be processed to the execution management panel via the command-line interface tool, and using the task processing intelligence module to execute the target subtasks corresponding to the work units to be processed includes: The intelligent execution module polls the to-do management panel, and selects work units as pending work units in sequence according to the polling results. The command-line interface tool is used to migrate the work unit to be processed to the execution management panel, and to switch the working directory corresponding to the previous polling cycle to the working directory corresponding to the work unit to be processed. The task processing intelligent module executes the target subtask corresponding to the work unit to be processed according to the switched working directory.

3. The task processing method according to claim 1, characterized in that, After the task processing intelligent module executes the target sub-task steps corresponding to the work unit to be processed, the method further includes: Detect the execution status of the work units contained in the to-do management panel, the execution management panel, and the archive management panel respectively; Based on the execution status, the status prompt information of the corresponding work unit is displayed in the to-do management panel, the execution management panel, and the archive management panel.

4. The task processing method according to claim 1, characterized in that, Before the step of migrating the work unit to be processed to the archive management panel via the command-line interface tool after the target subtask has been completed, the following steps are also included: Determine the execution visualization information corresponding to the work unit to be processed; If the target subtask is determined to be in a stopped state and has exceeded a set time threshold based on the execution visualization information, a reminder message is sent to the operation terminal of the task processing collaboration system according to a preset reminder strategy, and the work unit card corresponding to the work unit to be processed is displayed on the external operation device of the task processing collaboration system.

5. The task processing method according to claim 4, characterized in that, The method further includes: The system receives operation instructions submitted by the external operating device for the work unit card and sends the operation instructions to the task processing intelligent module, wherein the work unit card displays the execution status information corresponding to the work unit to be processed; The target subtask is then executed using the task processing intelligent module according to the operation instructions.

6. The task processing method according to claim 1, characterized in that, After the step of creating a work unit corresponding to each subtask through the command-line interface tool and adding the work unit corresponding to each subtask to the to-do management panel is executed, it also includes: Obtain the global layout information corresponding to each work unit, wherein the global layout information includes at least one of name information, panel information, archive status information, and size information; The global layout information corresponding to each work unit is stored in a local configuration file, wherein the global layout information stored in the local configuration file is updated according to a real-time update strategy. If the target task restarts, the global layout information sequence is read from the local configuration file, and the target task is resumed execution according to the global layout information sequence.

7. The task processing method according to claim 5, characterized in that, The step of determining the execution visualization information corresponding to the work unit to be processed includes: The execution visualization information corresponding to the work unit to be processed is collected by the content sampling rules of the session isolation layer in the task processing collaboration system. Wherein, when it is determined from the execution visualization information that the target subtask is in a stopped state and has exceeded a set time threshold, sending reminder information to the operation terminal of the task processing collaboration system according to a preset reminder strategy includes: The execution visualization information is compared with the historical execution visualization information corresponding to the work unit to be processed; If the execution visualization information is the same as the historical execution visualization information, and the stop time of the target subtask exceeds a set time threshold, then the step of sending a reminder message to the operation terminal of the task processing collaboration system according to a preset reminder strategy is executed.

8. The task processing method according to claim 7, characterized in that, The step of comparing the execution visualization information with the historical execution visualization information corresponding to the work unit to be processed includes: Determine the historical execution visualization information corresponding to the work unit to be processed, wherein the historical execution visualization information is collected by the session isolation layer in the previous sampling period; The execution visualization information and the historical execution visualization information are filtered separately. The filtered execution visualization information is compared with the filtered historical execution visualization information.

9. The task processing method according to claim 7 or 8, characterized in that, The display of the work unit card corresponding to the work unit to be processed on the external operating device of the task processing collaboration system includes: The status information corresponding to at least one execution work unit contained in the execution management panel is read by the backend aggregator, wherein the at least one execution work unit includes the work unit to be processed; The priority mapping table is queried based on the status information corresponding to each execution work unit to determine the execution priority information corresponding to each execution work unit; If the pending work unit meets the display conditions based on the execution priority information, the work unit card corresponding to the pending work unit is displayed on the external operating device of the task processing collaboration system.

10. The task processing method according to claim 9, characterized in that, The step of receiving the operation instruction submitted by the external operating device for the work unit card and sending the operation instruction to the task processing intelligent module includes: The operation text is determined based on the operation instructions submitted by the external operation device to the work unit card. The operation text is written to the session stream corresponding to the work unit to be processed using the session isolation layer, which serves as the operation to send the operation instruction to the task processing intelligent module.

11. The task processing method according to any one of claims 1 to 8, characterized in that, The to-do management panel, the execution management panel, and the archive management panel are located in the control area of ​​the collaborative task processing page. The collaborative task processing page also includes an operation area, which includes a first operation sub-area and a second operation sub-area. The first operation sub-area displays the terminal display information corresponding to the work unit to be processed, and the second operation sub-area displays the task execution record information corresponding to the work unit to be processed.

12. A task processing collaborative system, characterized in that, Includes the operation end and the processing end, including: The operating terminal is used to receive processing requests related to the target service and send the processing requests to the processing terminal. The processing terminal is used to determine the target task in response to the processing request, and to use the scheduling intelligence module to split the target task into multiple sub-tasks; The operation terminal is used to create a work unit corresponding to each subtask through a command-line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The processing end is used to use the execution intelligence module to poll the to-do management panel to determine the work unit to be processed, and use the task processing intelligence module to execute the target sub-task corresponding to the work unit to be processed. The operation terminal is used to migrate the work unit to be processed to the execution management panel through the command line interface tool; and when the target subtask is completed, to migrate the work unit to be processed to the archive management panel through the command line interface tool.

13. A task processing collaborative system, characterized in that, It includes a scheduling intelligence module, an execution intelligence module, and a task processing intelligence module, including: The scheduling intelligence module is used to determine the target task in response to the processing request of the associated target business, split the target task into multiple sub-tasks, create a work unit corresponding to each sub-task through the command line interface tool, and add the work unit corresponding to each sub-task to the to-do management panel. The execution intelligence module is used to poll the to-do management panel to determine the work units to be processed, and to migrate the work units to be processed to the execution management panel through the command line interface tool; The task processing intelligent module is used to execute the target subtask corresponding to the work unit to be processed; when the target subtask is completed, the work unit to be processed is migrated to the archive management panel through the command line interface tool.

14. A task processing method, characterized in that, Applications in task processing collaborative systems include: In response to processing requests from related R&D business, project tasks are determined, and the project tasks are broken down into multiple sub-tasks using a scheduling intelligence module; Create a work unit corresponding to each subtask using the command-line interface tool, and add the work unit corresponding to each subtask to the to-do management panel; The execution intelligence module polls the to-do management panel to determine the work units to be processed, and migrates the work units to be processed to the execution management panel through the command line interface tool, and executes the target sub-tasks corresponding to the work units to be processed using the programming intelligence module; Once the target subtask is completed, the pending work unit is migrated to the archive management panel via the command-line interface tool.

15. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 11 or 14.

16. A computer-readable storage medium, characterized in that, It stores computer-executable instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 11 or 14.

17. A computer program product, characterized in that, Includes a computer program or instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 11 or 14.

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