Multi-terminal collaborative interaction and rendering method and device of AI content generation platform, and medium

Abstract

The application discloses a multi-terminal collaborative interaction and rendering method and device of an AI content generation platform and a medium, relates to the field of artificial intelligence, and comprises the following steps: acquiring cross-terminal node unified metadata of a target function node; acquiring the terminal type and screen size information of a running terminal; rendering the user interface of the target function node based on the above information, wherein the rendering process reuses the same core rendering logic on different terminals, and the display style, layout mode and interaction mode of the node control are adapted according to the terminal type and screen size information; and generating operation data in response to the operation instruction of the user on the user interface, submitting the operation data to a cloud data center to update a unique data source, and obtaining the latest cloud data. The application realizes the adaptive presentation of the same configuration on different terminals through the cross-terminal node unified metadata, guarantees the consistency of multi-terminal data through the unique data source of the cloud, and improves the unity and rendering efficiency of cross-terminal interaction.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to a multi-terminal collaborative interaction and rendering method, device and medium for an AI content generation platform. Background Technology

[0002] The cross-platform presentation of AI content generation platforms on PCs and mobile devices is a key element in achieving full-scene interaction. Due to fundamental differences between PCs and mobile devices in terms of screen size, input methods, and interaction habits, providing a consistent and efficient user experience on both platforms simultaneously presents significant technical challenges.

[0003] In existing technologies, a common practice is to build separate codebases for PC web interfaces and mobile apps. This development model requires repeatedly writing rendering logic for each function across different platforms, resulting in a large development workload, high maintenance costs, and difficulty in simultaneously advancing feature iterations on both platforms. Another approach is to adopt a responsive layout solution based on a cross-platform framework, attempting to adapt to different screen sizes using the same UI logic. However, this method often requires compromises to accommodate both platforms in practice. For example, complex visual workflow orchestration on PCs, when ported to mobile devices, is often limited by small screens and touch operations, leading to excessively deep core function entry layers, lengthy operation paths, and difficulty in ensuring complete consistency between parameter configuration interfaces and function execution logic on both platforms. Since none of the above solutions fundamentally solve the binary separation between cross-platform operation logic and interactive experience, development teams need to repeatedly perform targeted platform adaptations when dealing with new AI function nodes. This directly leads to a longer product iteration cycle and makes it difficult to ensure complete consistency between business logic and generated effects on both platforms. Furthermore, users often face the dilemma that workflows arranged on computers cannot be quickly operated on mobile phones, which seriously reduces the continuity and efficiency of cross-scenario content creation. Summary of the Invention

[0004] This invention provides a multi-terminal collaborative interaction and rendering method, device and medium for an AI content generation platform. The technical problem it aims to solve is: how to provide a solution that can effectively achieve unified, efficient and consistent interaction and rendering capabilities for an AI content generation platform between PC and mobile terminals.

[0005] In a first aspect, the present invention provides a multi-terminal collaborative interaction and rendering method for an AI content generation platform, comprising: In response to receiving a rendering trigger instruction for a target functional node, the cross-end node unified metadata of the target functional node is obtained, wherein the cross-end node unified metadata includes a first-end rendering configuration and a second-end rendering configuration. Obtain the terminal type and screen size information of the currently running terminal; Based on the unified metadata of the cross-terminal node, the terminal type and the screen size information, the user interface corresponding to the target functional node is rendered. The rendering process reuses the same core rendering logic on different terminals, and adapts the display style, layout and interaction mode of the node controls in the user interface according to the terminal type and the screen size information to obtain the node user interface adapted to the current running terminal. In response to the operation command executed by the user on the node user interface, operation data is generated and submitted to the cloud data center to update the unique data source stored in the cloud data center, so as to obtain the latest data in the cloud.

[0006] Optionally, rendering the user interface corresponding to the target functional node based on the unified metadata of the cross-end node, the end type, and the screen size information includes: When the terminal type is PC, the layout density of the node control is determined based on the rendering configuration of the first terminal and the screen size information, and the node control is presented as a multi-column layout, a floating parameter panel, and adapted to the mouse drag interaction mode based on the layout density. When the terminal type is a mobile terminal, the layout precision of the node control is determined based on the second terminal rendering configuration and the screen size information, and the node control is presented as a single-column flow layout, a full-screen parameter panel, and adapted to the touch interaction mode based on the layout precision.

[0007] Optionally, after submitting the operation data to the cloud data center to update the unique data source stored in the cloud data center and obtaining the latest data in the cloud, the method further includes: The latest data from the cloud is synchronized to each other terminal device currently logged in by the user through a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal.

[0008] Optionally, after synchronizing the latest data from the cloud to each other terminal device currently logged in by the user via a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal, the method further includes: Receive offline operation data uploaded by the mobile device after performing offline editing operations in a network-free environment, in response to the network being restored; The received offline operation data is merged with the data in the cloud data center, and conflict detection is performed during the merging process: If a data conflict is detected, the conflicting modifications that can be automatically merged and those that cannot be automatically merged are determined from the data conflict. The automatically mergeable conflict modifications are merged with the data in the cloud data center to generate merged data; For conflicting modifications that cannot be automatically merged, different modified versions corresponding to the data conflict are displayed, and the selected version is retained in response to the user's selection instruction.

[0009] Optionally, after generating operation data in response to an operation command executed by the user on the node user interface, the method further includes: Obtain the editing operation data of the first collaborator for the target workflow or target project, as well as the permission information of the first collaborator; Determine whether the first collaborator has edit permissions; If the first collaborator's permission information includes the editing permission, the editing operation data is input into the collaborative editing engine, which performs concurrent editing operation conversion and merging processing to generate merged edited content and synchronizes the merged edited content to the terminal devices of all collaborators. If the first collaborator's permission information does not include the required editing permissions, then the editing operation data is rejected.

[0010] Optionally, after synchronizing the merged edited content to the terminal devices of all collaborators, the method further includes: Get the online status, cursor position, and current editing area of ​​each collaborator; The online status, cursor position, and current editing area are synchronized to the terminal devices of all collaborators, and the editing content of each collaborator is marked on the interface of the terminal device to display the editing area identifier of different collaborators.

[0011] Optionally, submitting the operation data to the cloud data center to update the unique data source stored in the cloud data center and obtain the latest data in the cloud includes: The operation data is submitted to the cloud data center, which triggers the cloud data center to perform business logic processing on the operation data. The business logic processing includes rule verification, points deduction and task execution logic. In response to the completion of the business logic processing in the cloud data center, the processing result is obtained and written to the unique data source to obtain the latest data in the cloud.

[0012] Optionally, after generating operation data in response to an operation command executed by the user on the node user interface, the method further includes: Receive mobile-collected material data uploaded by the mobile terminal, and store the mobile-collected material data in the cloud data center; The mobile terminal collects material data, including image data, video data, audio data, or album material data. The mobile terminal collects material data by calling its own camera interface, microphone interface, or album access interface according to the device call command triggered by the user on the mobile terminal.

[0013] Secondly, the present invention also provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0014] Thirdly, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0015] This invention provides a multi-terminal collaborative interaction and rendering method, device, and medium for an AI content generation platform. By unifying metadata across nodes, it integrates rendering configurations for PC and mobile devices into a single structured data structure. This allows the rendering process to reuse the same core rendering logic across different terminals, avoiding the high costs of developing separate rendering code for different terminals and eliminating the potential for inconsistencies caused by independent implementations. Furthermore, during rendering, the display style, layout, and interaction mode of node controls are automatically adapted based on the terminal type and screen size information, ensuring that each terminal device obtains a user interface that matches its operating environment, balancing the richness of information presentation in large-screen scenarios with the ease of operation in small-screen scenarios. Moreover, operational data is uniformly submitted to the cloud data center and updated with a single data source, ensuring that all terminal devices access the same authoritative data version. This provides a data foundation for multi-terminal data consistency and cross-terminal coherent operation, eliminating the need for users to manually save or reload when switching between different terminals. These mechanisms collectively achieve unified, efficient, and consistent interaction and rendering capabilities between PC and mobile terminals, meeting the continuity requirements of content creation across all scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating a multi-terminal collaborative interaction and rendering method for an AI content generation platform provided in an embodiment of the present invention; Figure 2 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0020] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0021] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0022] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0023] Please see Figure 1 This invention provides a multi-terminal collaborative interaction and rendering method for an AI content generation platform. This method achieves adaptive presentation of the same rendering configuration on both PC and mobile devices through unified metadata across cross-terminal nodes, and realizes real-time synchronization and consistent updating of multi-terminal data through a cloud data center. Specifically, the method includes the following steps: S1, in response to receiving a rendering trigger instruction for a target functional node, obtain the cross-end node unified metadata of the target functional node, wherein the cross-end node unified metadata includes a first-end rendering configuration and a second-end rendering configuration.

[0024] In specific implementation, when the AI ​​content generation platform receives a rendering trigger instruction for a target functional node, the platform obtains the cross-platform unified metadata of that target functional node. The rendering trigger instruction can originate from user-initiated clicks on functional nodes, page loading initialization, or automatic triggering during workflow orchestration; this invention is not specifically limited to these. Further, the target functional node refers to an executable unit with specific functions within the AI ​​content generation platform, such as a text generation node, image generation node, or video editing node; this invention is not specifically limited to these. Further, the cross-platform unified metadata is predefined structured configuration data used to describe the presentation of functional nodes on different terminal devices. Specifically, the cross-platform unified metadata includes a first-terminal rendering configuration and a second-terminal rendering configuration. Further, the first-terminal rendering configuration corresponds to rendering parameters for PC devices, including PC control adaptation rules, PC interface layout rules, and PC interaction mode configuration. Further, the second-terminal rendering configuration corresponds to rendering parameters for mobile devices, including mobile control adaptation rules, mobile interface layout rules, and mobile interaction mode configuration. The control adaptation rules define strategies for adjusting the display style of node controls on different screen sizes, such as control size scaling ratios and font size adjustment ranges. The interface layout rules define the layout methods of the node interface, such as switching conditions between multi-column and single-column flow layouts, and panel display methods. The interaction mode configuration defines the interaction methods between the user and the node interface, such as mouse drag and drop, and touch gestures. This unified metadata is stored in a standard structured format, such as JSON or XML, ensuring cross-platform parsing compatibility.

[0025] S2, obtain the terminal type and screen size information of the currently running terminal.

[0026] In specific implementation, while acquiring the unified metadata of the cross-terminal nodes, the platform also acquires the terminal type and screen size information of the currently running terminal. The terminal type identifies whether the currently running terminal is a PC or a mobile terminal, and can be identified through operating system type, user agent string, or hardware characteristics; this invention is not specifically limited to these. The screen size information describes the display area size of the currently running terminal, typically expressed in pixels as width and height values, such as 1920×1080 or 375×812. Specifically, the platform can acquire the above information by calling the application programming interface provided by the operating system; this invention is not specifically limited to this either.

[0027] S3. Based on the unified metadata of the cross-terminal node, the terminal type and the screen size information, render the user interface corresponding to the target functional node. The rendering process reuses the same core rendering logic on different terminals, and adapts the display style, layout and interaction mode of the node controls in the user interface according to the terminal type and the screen size information to obtain the node user interface adapted to the currently running terminal.

[0028] In specific implementation, after obtaining the unified metadata of the cross-platform nodes, the terminal type, and the screen size information, the platform renders the user interface corresponding to the target functional node based on the aforementioned data. Specifically, the rendering process reuses the same core rendering logic across different terminals; that is, the core interface layout calculation, control position calculation, and event handling logic share the same code implementation across different terminals, eliminating the need for separate development for each terminal. Simultaneously, the rendering process adapts the display style, layout method, and interaction mode of the node controls in the user interface according to the terminal type and screen size information. Specifically, the platform selects the corresponding rendering configuration (first-terminal rendering configuration or second-terminal rendering configuration) based on the terminal type and further adjusts the layout parameters based on the screen size information to obtain a node user interface adapted to the currently running terminal. This node user interface is the interface for actual user interaction, including the parameter configuration panel, control components, and operation entry points for the functional node.

[0029] In some preferred embodiments, rendering the user interface corresponding to the target functional node based on the unified metadata of the cross-terminal node, the terminal type, and the screen size information includes: when the terminal type is a PC, determining the layout density of the node control based on the first terminal rendering configuration and the screen size information, and presenting the node control as a multi-column layout, a floating parameter panel, and adapting to the mouse drag-and-drop interaction mode based on the layout density; when the terminal type is a mobile terminal, determining the layout refinement of the node control based on the second terminal rendering configuration and the screen size information, and presenting the node control as a single-column flow layout, a full-screen parameter panel, and adapting to the touch interaction mode based on the layout refinement.

[0030] In practice, this embodiment differentiates the rendering strategies for PC and mobile devices, achieving differentiated presentation of unified metadata for the same cross-platform node on both ends. It also fully utilizes the interactive characteristics of both ends. The specific implementation method is as follows: When the terminal type is a PC, the platform determines the layout density of the node controls based on the first terminal rendering configuration and the screen size information. The layout density reflects the number and compactness of controls that can be displayed simultaneously on the PC screen, and is generated by the platform using a preset density calculation formula based on the screen size information. Specifically, the platform first obtains the preset control baseline size and spacing parameters in the first terminal rendering configuration, then calculates the number of control columns that the current screen can accommodate based on the screen width value in the screen size information, and then calculates the upper limit of the number of controls in each column based on the screen height value in the screen size information, comprehensively determining the layout density of the node controls. Since PC screen sizes are typically large, the layout density is high, meaning more controls and information can be accommodated within the same screen space.

[0031] Furthermore, based on the aforementioned layout density, the platform presents the node controls as a multi-column layout, a floating parameter panel, and is adapted to a drag-and-drop interaction mode. Specifically, the multi-column layout refers to arranging multiple functional nodes or parameter controls in columns, making full use of the horizontal space on the PC to present richer information. The floating parameter panel refers to the parameter configuration panel adopting a floating window format, which users can drag to any position on the screen without affecting the visibility of the main workspace. It also supports opening multiple panels simultaneously, eliminating the need for users to repeatedly switch panels when editing multiple parameters. The drag-and-drop interaction mode allows users to connect nodes, move and adjust parameter panels through mouse drag operations. This interaction method is implemented through mouse event handling, including responses and feedback for three core event stages: mouse press, move, and release, conforming to the operating habits of PC users.

[0032] Furthermore, when the terminal type is a mobile terminal, the platform determines the layout refinement of the node controls based on the second terminal rendering configuration and the screen size information. The layout refinement reflects the compactness of the space allocated to each control on the mobile terminal screen and the fineness of the display granularity. Specifically, the platform first obtains the preset minimum control size and minimum spacing parameters in the second terminal rendering configuration, then determines the number of controls that can be displayed in each row based on the screen width value in the screen size information, and then determines the number of information levels that can be displayed in each screen based on the screen height value in the screen size information, comprehensively determining the layout refinement of the node controls. Furthermore, due to the smaller screen size of mobile terminals, the layout refinement is higher, meaning that the size and spacing of each control are adapted more meticulously. Based on the layout refinement, the platform presents the node controls as a single-column flow layout, a full-screen parameter panel, and adapts to the touch interaction mode. Specifically, the single-column flow layout means arranging all node controls sequentially along the vertical direction, displaying only one main control per row, adapting to the narrow screen characteristics of mobile terminals and reducing the need for horizontal scrolling. A full-screen parameter panel refers to a parameter configuration panel that occupies the entire display area of ​​the mobile screen. Users can scroll up and down to browse all parameter items, avoiding the problem of partial obstruction on small screens. Simultaneously, the parameter controls feature a large touch area design, facilitating precise finger operation. Furthermore, the touch interaction mode refers to users interacting with the interface through touch gestures such as tapping, swiping, and zooming. This interaction method is implemented through touch event handling, including responses to core event stages such as touch start, touch movement, and touch end, and is optimized for touch accuracy on mobile devices. For example, larger touch target areas are provided for buttons and sliders to reduce accidental touches.

[0033] This embodiment differentiates between PC and mobile devices by employing different rendering strategies, such as multi-column layouts versus single-column flow layouts, floating panels versus full-screen panels, and mouse drag-and-drop versus touch interaction. This ensures that the unified metadata for the same cross-platform node provides the best user experience across different screen sizes and interaction methods. The PC version fully utilizes the larger screen space to offer richer information display and more flexible operation methods, while the mobile version simplifies the interface hierarchy through single-column layouts and full-screen panels, highlighting core parameters and reducing the difficulty of touch operation. This differentiated rendering strategy ensures consistency of functionality on both platforms while fully considering their respective operational characteristics, thus improving cross-scene creation efficiency.

[0034] S4. In response to the operation command executed by the user on the node user interface, operation data is generated and submitted to the cloud data center to update the unique data source stored in the cloud data center with the operation data, so as to obtain the latest data in the cloud.

[0035] In practice, after rendering, the platform generates operation data in response to the user's operation commands executed on the node's user interface. This operation data is a record of data changes generated when the user edits or configures functional nodes, such as modifying a parameter value, adjusting workflow node connections, or uploading new materials. The operation data is stored in a structured format, including fields such as operation type identifier, operation object identifier, operation timestamp, and values ​​before and after modification. Further, the platform submits the operation data to the cloud data center to update the unique data source stored in the cloud data center, obtaining the latest data in the cloud. Further, the unique data source is the only authoritative data version stored in the cloud data center, accessible to all terminal devices currently logged in by the user. Further, this unique data source ensures that regardless of which end the user accesses the data from, the obtained data is the same latest version, avoiding inconsistencies across multiple ends. Further, after the cloud data center writes the operation data to the unique data source, it forms the latest data state, i.e., the latest data in the cloud. The latest data in the cloud is the complete data version updated by the unique data source, containing all data changes brought about by the operation data.

[0036] This embodiment unifies the management of rendering configurations for PC and mobile devices through cross-platform unified metadata, enabling the reuse of the same core rendering logic across different platforms and avoiding the high cost of developing separate rendering code for each platform. Furthermore, the rendering process automatically adapts the display style, layout, and interaction mode of node controls based on the platform type and screen size, ensuring users receive an interactive experience tailored to their screen size and operating habits on different devices. Moreover, by submitting operation data to the cloud data center and updating the unique data source, it ensures that all terminal devices access the same authoritative data version, providing a fundamental guarantee for multi-platform data consistency. Finally, this embodiment allows newly added functional nodes to take effect simultaneously on both platforms with only a single configuration, significantly reducing iterative development costs while improving the coherence and efficiency of cross-scenario content creation.

[0037] In some preferred embodiments, submitting the operation data to a cloud data center to update the unique data source stored in the cloud data center and obtain the latest data in the cloud includes: submitting the operation data to the cloud data center, triggering the cloud data center to perform business logic processing on the operation data, the business logic processing including rule verification, points deduction, and task execution logic; in response to the cloud data center completing the business logic processing, obtaining the processing result, and writing the processing result into the unique data source to obtain the latest data in the cloud.

[0038] In practice, this embodiment ensures consistency between PC and mobile terminals in rule verification, points deduction, and task execution by centralizing business logic processing in the cloud. The specific implementation method is as follows: The platform submits the operation data to the cloud data center, triggering the cloud data center to execute business logic processing on the operation data. This business logic processing refers to a series of verification and calculation operations performed to ensure the legality and consistency of the operation data, including rule verification, points deduction, and task execution logic, which are not specifically limited in this invention. Further, rule verification refers to the cloud data center verifying the legality and rationality of the operation data according to preset business rules. Specifically, rule verification includes verifying whether the user's permissions meet the requirements for executing the operation, verifying whether the current state of the operation object allows the operation, and verifying whether the operation parameters are within the legal value range. For example, when a user attempts to delete a node in a workflow, the cloud data center verifies whether the node is depended on by other nodes; if a dependency exists, the operation is rejected. Further, points deduction refers to the cloud data center deducting corresponding points from the user's account according to the operation type and billing rules when the operation involves points consumption. Specifically, the cloud data center first queries the user's current points balance, then calculates the number of points to be deducted according to the operation billing rules, and then determines whether the balance is sufficient. If sufficient, the deduction operation is executed and the points balance is updated; if insufficient, an error message is returned. Furthermore, the task execution logic refers to the process by which the cloud data center initiates the corresponding task execution flow based on task parameters when an operation triggers an AI-generated task or service order. This process includes task scheduling, resource allocation, and progress tracking. The task execution logic ensures that task scheduling and execution are unaffected by the type of terminal device. Whether a task is initiated from a PC or a mobile device, it receives the same execution environment and processing capabilities under unified cloud scheduling.

[0039] Furthermore, after the business logic processing is completed and the processing result is obtained in the cloud data center, the platform writes the processing result into the unique data source to obtain the latest data in the cloud. The processing result includes status information such as whether the rule verification passed, whether the points deduction was successful, and whether the task was successfully scheduled. Specifically, if the rule verification fails, the cloud data center rejects the operation and generates an error message, which is written to the operation log table in the unique data source; if the points deduction is successful, the user's points balance and points transaction record are updated; if the task is successfully executed, the task status table is updated and a task identifier is generated. After the unique data source is updated, the latest data in the cloud is formed, which can be subsequently synchronized to various terminal devices through a real-time communication channel.

[0040] This embodiment centralizes business logic processing in a cloud data center, allowing the PC and mobile terminals to focus solely on interaction and rendering, ensuring complete consistency of business logic across both platforms. Furthermore, rule validation, points deduction, and task execution logic are uniformly processed in the cloud, avoiding rule inconsistencies caused by terminal differences. This guarantees that users receive consistent business feedback and results regardless of which terminal they operate on, improving the consistency of the cross-platform experience.

[0041] In some preferred embodiments, after submitting the operation data to the cloud data center to update the unique data source stored in the cloud data center and obtaining the latest data in the cloud, the method further includes: synchronizing the latest data in the cloud to each other terminal device currently logged in by the user through a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal.

[0042] In practice, this embodiment pushes the latest data from the cloud to all currently logged-in terminal devices through a real-time communication channel, achieving real-time data consistency across multiple devices. The specific implementation method is as follows: After writing operational data to the unique data source in the cloud data center and obtaining the latest data from the cloud, the platform synchronizes the latest cloud data to each other terminal device currently logged in by the user through a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal. Furthermore, the real-time communication channel is a long-connection communication technology, such as the WebSocket protocol. The WebSocket protocol is a protocol for full-duplex communication over a single Transmission Control Protocol connection, characterized by maintaining a persistent connection after it is established, allowing the server to proactively push data to the client without frequent client polling. Furthermore, the platform, as the server, maintains real-time communication connections with each terminal device currently logged in by the user. Specifically, the platform maintains an independent WebSocket connection instance for each terminal device, and each connection instance includes status information such as session identifier, device identifier, and last activity timestamp. Furthermore, when the unique data source is updated, the platform immediately encodes the latest cloud data into frames conforming to the protocol specifications and pushes them to all terminal devices through the real-time communication channel. Furthermore, after receiving the latest data from the cloud, the other terminal devices parse the data content and update their local display content to ensure it is completely consistent with the version displayed on the currently running terminal. This synchronization process is bidirectional, meaning that any operation on one end will trigger the same process, ensuring that the data on all terminals remains synchronized.

[0043] This embodiment pushes the latest data from the cloud to all terminal devices through a real-time communication channel, achieving real-time data synchronization across multiple devices. This allows operations performed by the user on any device to be immediately perceived and updated on other devices. Furthermore, this mechanism avoids editing conflicts or information inconsistencies caused by data synchronization delays, eliminating the need for users to manually save or reload when switching between different devices, providing a seamless cross-device user experience.

[0044] In some preferred embodiments, after synchronizing the latest cloud data to each other terminal device currently logged in by the user via a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal, the method further includes: receiving offline operation data uploaded by the mobile terminal after performing offline editing operations in a network-free environment in response to network recovery; merging the received offline operation data with the data in the cloud data center, and performing conflict detection during the merging process: if data conflicts are detected, determining the conflict modification content that can be automatically merged and the conflict modification content that cannot be automatically merged from the data conflicts; merging the conflict modification content that can be automatically merged with the data in the cloud data center to generate merged data; for the conflict modification content that cannot be automatically merged, displaying different modified versions corresponding to the data conflict, and retaining the selected version in response to the user's selection instruction.

[0045] In practice, this embodiment solves the problem of unsynchronized editing operations on mobile devices in environments without or with weak network coverage by using offline caching, incremental uploading after network recovery, and conflict detection and handling. It also ensures controllable handling of multi-device editing conflicts. The specific implementation method is as follows: The platform receives offline operation data uploaded by a mobile device after performing offline editing operations in a network-free environment, in response to network recovery. Specifically, when the mobile device detects that a user is performing an editing operation in a network-free environment, it caches the operation data corresponding to the offline editing operation in the mobile device's local storage, such as device flash memory or in-memory database. Further, the local storage adopts a structured storage method, using operation timestamps as indexes and storing data sequentially according to the order in which the operations occurred, ensuring the traceability of the offline operation sequence. When the mobile device detects network recovery, it automatically uploads the locally cached operation data to the cloud data center in an incremental synchronization manner. Further, the incremental synchronization method means uploading only the data that has changed since the last synchronization, rather than uploading all data, to reduce network transmission volume and synchronization latency. Specifically, the mobile device first sends a synchronization request to the cloud data center, carrying the latest synchronization version number in the local cache. The cloud data center returns a set of cloud changes since that version number, and the mobile device determines the incremental data that needs to be uploaded based on this. After receiving the offline operation data, the cloud data center prepares the data for subsequent merging and conflict handling.

[0046] Furthermore, the platform merges the received offline operation data with the data in the cloud data center, and performs conflict detection during the merging process. The merging process applies the modifications in the offline operation data to the current data version in the cloud data center while checking for conflicts. Specifically, the conflict detection method compares the modification timestamp or version number in the offline operation data with the current version number of the cloud data to determine if the data version on which the offline operation is based is consistent with the current version in the cloud. If the data version on which the offline operation is based is later than the current version in the cloud, it indicates that the cloud data has been modified by other terminals during the offline operation, and a data conflict is determined. Conflict detection is performed in real-time during the merging process; that is, a conflict determination is performed for each offline operation record merged.

[0047] Furthermore, if a data conflict is detected, the platform determines which conflicting modifications can be automatically merged and which cannot. Specifically, the platform analyzes the fields and content modified by both parties in the conflict to determine if there are overlapping areas. For example, if user A modifies the node name of a workflow and user B modifies the node parameter of the same workflow, but they modify different fields, then the conflicting modifications can be automatically merged. If user A and user B modify the same text or the same parameter value, then the conflicting modifications cannot be automatically merged. The determination process is based on preset conflict resolution rules, which define merging strategies for different field types. For example, numeric fields support cumulative merging, string fields support concatenation merging, and enumerated fields support priority merging, etc., which are not specifically limited in this invention.

[0048] Furthermore, for conflicting modifications that can be automatically merged, the platform merges these modifications with the data in the cloud data center to generate merged data. The merging operation involves combining the modifications in the offline operation data and the modifications in the cloud data field by field, forming a final version that includes the modifications from both sides. For example, if the offline operation modifies the location coordinates of node A, and the cloud data modifies the connection relationship of node B, the merged data will simultaneously contain the new location coordinates of node A and the new connection relationship of node B, without interference between the two.

[0049] Furthermore, for the conflicting modifications that cannot be automatically merged, the platform displays different modified versions corresponding to the data conflict to the user and, in response to the user's selection instruction, retains the selected version. Specifically, the platform displays two or more conflicting versions simultaneously on the interface, for example, in a comparison view, highlighting the differences, and allows the user to choose which version to keep as the final version. After the user makes a selection, the platform, in response to the user's selection instruction, retains the selected version and discards the other versions.

[0050] This embodiment achieves mobile editing capabilities in environments without network coverage by receiving offline editing data performed by the mobile device in a network-free environment, merging the offline data with cloud data, and performing conflict detection. Furthermore, conflicting modifications that can be automatically merged are automatically processed, reducing the need for manual intervention; conflicting modifications that cannot be automatically merged are displayed for the user to choose from, ensuring data accuracy and user control. This mechanism effectively avoids data loss or errors caused by data conflicts while ensuring the flexibility of multi-device collaborative editing.

[0051] In some preferred embodiments, after generating operation data in response to an operation command executed by a user on the node user interface, the method further includes: obtaining editing operation data of a first collaborator for a target workflow or target project, and the permission information of the first collaborator; determining whether the permission information of the first collaborator has editing permissions; if the permission information of the first collaborator has the editing permissions, then inputting the editing operation data into a collaborative editing engine, whereby the collaborative editing engine performs concurrent editing operation conversion and merging processing to generate merged edited content, and synchronizing the merged edited content to the terminal devices of all collaborators; if the permission information of the first collaborator does not have the editing permissions, then rejecting the editing operation data.

[0052] In practice, this embodiment uses a collaborative editing engine to enable the conversion and merging of concurrent editing operations by multiple collaborators on different terminal devices, and ensures collaborative security through permission control. The specific implementation method is as follows: The platform acquires editing operation data of the first collaborator for the target workflow or target project, as well as the first collaborator's permission information. The target workflow refers to an AI content generation process created by the user, consisting of multiple functional nodes connected in a specific order, such as a complete workflow from text input to image generation. The target project refers to a collection containing multiple workflows and related materials. The first collaborator refers to a specific user who initiates the editing operation. The permission information describes the type of operation permission the collaborator possesses for the target workflow or target project, including read-only permission, editing permission, and management permission. The permission information is stored in the cloud data center in a structured manner, including fields such as collaborator identifier, target object identifier, permission type, and authorization time; however, this invention does not specifically limit the scope of the information.

[0053] Furthermore, the platform determines whether the first collaborator's permission information includes edit permissions. Edit permissions refer to the permission level that allows a user to modify the target workflow or target project, including operations such as adding or deleting nodes, configuring parameters, and adjusting connection relationships. If the first collaborator's permission information includes the edit permissions, meaning the collaborator has been granted edit permissions, the platform allows them to perform the editing operation. If the first collaborator's permission information does not include the edit permissions, meaning the collaborator only has read-only permissions or other low-level permissions, the platform rejects the edit operation data and does not execute it.

[0054] Furthermore, when the first collaborator's permission information includes the editing permissions, the platform inputs the editing operation data into the collaborative editing engine. The collaborative editing engine then performs concurrent editing operation transformation and merging processing to generate the merged edited content. The collaborative editing engine is a concurrent editing processing module implemented based on the Operational Transformation (OT) algorithm. The basic principle of the OT algorithm is to convert each user's local editing operations into a series of operation instructions, each instruction containing three core elements: operation type, operation position, and operation content. Further, when multiple users' editing operations occur simultaneously, the collaborative editing engine transforms the operations according to the order and timestamp of the operations. The transformation rule is: when operation A is executed after operation B, the transformation function of operation A adjusts the operation position and operation content of operation A to adapt to the state changes already caused by operation B. Further, through a series of transformation functions, all concurrent operations are ultimately merged into a linearized operation sequence, ensuring that all collaborators' terminal devices ultimately present the same editing state. The collaborative editing engine applies the transformed operation sequence to the initial document state to generate the merged edited content.

[0055] Furthermore, the platform synchronizes the merged edited content to the terminal devices of all collaborators, ensuring that all collaborators' terminal devices display the same merged edited version. This synchronization process also employs a real-time communication channel, consistent with the data synchronization mechanism described in the above embodiments.

[0056] This embodiment utilizes a collaborative editing engine to convert and merge concurrent editing operations from multiple collaborators, enabling multiple users on different devices to simultaneously edit the same workflow or project. A permission control mechanism ensures that collaborators can only operate within their authorized scope, guaranteeing project data security. Furthermore, the OT-based collaborative editing mechanism effectively handles conflicts arising from concurrent editing, ensuring all collaborators ultimately obtain consistent editing results, making it suitable for collaborative content production scenarios involving cross-device and cross-regional collaboration.

[0057] In some preferred embodiments, after synchronizing the merged edited content to the terminal devices of all collaborators, the method further includes: obtaining the online status, cursor position, and current editing area of ​​each collaborator; synchronizing the online status, cursor position, and current editing area to the terminal devices of all collaborators, and marking the edited content of each collaborator in the interface of the terminal devices to display the editing area identifiers of different collaborators.

[0058] In practice, this embodiment visualizes the editing status of each collaborator on the terminal interface, enabling team members to perceive each other's editing activities in real time, thereby improving the efficiency and accuracy of collaborative editing. The specific implementation method is as follows: After the platform synchronizes the merged edited content to the terminal devices of all collaborators, the platform obtains the online status, cursor position, and current editing area of ​​each collaborator. The online status is obtained by the platform maintaining a heartbeat for each collaborator's session. Each collaborator's terminal device periodically sends a heartbeat message to the platform. If the platform does not receive a heartbeat message from a collaborator within a preset timeout period, it determines that the collaborator is offline. The cursor position is the specific location of the collaborator's cursor in the editing interface of the target workflow or target project, including coordinate information and context information. The current editing area is the specific content area that the collaborator is currently editing, such as a specific node in the workflow, a specific field in the parameter configuration panel, or a specific paragraph in the project document.

[0059] Furthermore, the platform synchronizes the online status, cursor position, and current editing area to the terminal devices of all collaborators, and marks the editing content of each collaborator on the interface of the terminal devices to display the editing area identifiers of different collaborators. Specifically, the platform encodes the collaborators' editing status information into structured data and broadcasts it to the terminal devices of all collaborators through a real-time communication channel. Further, after receiving the data, each terminal device marks the editing position of each collaborator on the editing interface with different colors and styles. For example, collaborator A's avatar and colored border are displayed around the node being edited; collaborator B's name tag and highlighted area are displayed in the parameter panel being edited; and a flashing cursor marker is displayed at collaborator C's current cursor position. The editing area identifiers of each collaborator are presented independently and do not interfere with each other, allowing all collaborators to clearly understand who is currently editing which area, thereby effectively avoiding conflicts caused by multiple people simultaneously modifying the same content.

[0060] This embodiment visualizes the online status, cursor position, and current editing area of ​​each collaborator on the terminal interface, enabling team members to perceive each other's editing activities in real time. Furthermore, this visual collaborative feedback mechanism effectively reduces concurrent editing conflicts, improves the smoothness and efficiency of collaborative creation, and is particularly suitable for scenarios where multiple collaborators are simultaneously editing the same workflow or the same project.

[0061] In some preferred embodiments, after generating operation data in response to an operation command executed by the user on the node user interface, the method further includes: receiving mobile-collected material data uploaded by the mobile terminal, and storing the mobile-collected material data in the cloud data center; wherein, the mobile-collected material data includes image data, video data, audio data, or album material data; the mobile-collected material data is obtained by the mobile terminal calling its own camera interface, microphone interface, or album access interface according to a device call command triggered by the user on the mobile terminal.

[0062] In practice, this embodiment enables users to easily capture and upload materials on their mobile devices by calling the camera, microphone, and album interfaces of the mobile terminal, thus meeting the content generation needs in mobile scenarios. The specific implementation method is as follows: After the platform generates operation data in response to the user's operation command executed on the node user interface, the mobile terminal calls its own camera interface, microphone interface, or album access interface to obtain corresponding mobile terminal-captured material data according to the device call command triggered by the user on the mobile terminal. The mobile terminal-captured material data includes image data, video data, audio data, or album material data. The camera interface is an application programming interface provided by the mobile terminal operating system for controlling the camera to capture photos or videos, such as the Camera API on the Android platform or the AVFoundation framework on the iOS platform. Furthermore, by calling the camera interface, the mobile terminal can start camera preview, set shooting parameters, perform shooting operations, and obtain the generated image or video data. The returned result is a compressed image file (such as JPEG format) or video file (such as MP4 format), which is stored in memory or a temporary file as a byte stream. Furthermore, the microphone interface is an interface for recording audio, such as MediaRecorder on Android or AVAudioRecorder on iOS. By calling the microphone interface, the mobile device can set recording parameters, start recording, stop recording, and obtain the audio data generated by the recording. The returned result is a compressed audio file (such as M4A format), also stored as a byte stream. Further, the album access interface is used to read materials already stored in the mobile device's local album, such as Android's MediaStore or iOS's Photos framework. By calling the album access interface, the mobile device can browse the media file list in the album, select files, and read file contents, returning album material data. Further, the mobile device selects the corresponding interface to call based on the type of device call instruction. If the instruction is to take a picture, the camera interface is called to take a photo and generate image data; if the instruction is to take a video, the camera interface is called to record video and generate video data; if the instruction is to record audio, the microphone interface is called to record audio and generate audio data; if the instruction is to select existing materials, the album access interface is called to browse and select materials and obtain album material data. Furthermore, when the mobile device obtains the aforementioned material data, it will automatically associate the material data with the current user session and project context so that it can be correctly categorized after uploading.

[0063] Furthermore, the platform receives the mobile-collected material data uploaded by the mobile terminal and stores the mobile-collected material data in the cloud data center. Specifically, the mobile terminal uploads the acquired image data, video data, audio data, or album material data to the cloud data center via a network channel. The upload process can adopt a block upload method. For larger files, such as video data, it can be divided into several data blocks and uploaded sequentially. Each data block contains a block number and the total number of blocks. After receiving all data blocks, the cloud data center reassembles them according to the block number. It also supports the function of resuming interrupted uploads, that is, if the upload is interrupted, the unfinished blocks can be resumed in the next upload. After receiving and assembling the complete data, the cloud data center stores the mobile-collected material data in the cloud storage space to form cloud material assets. Furthermore, the cloud material assets are assigned a unique resource identifier and associated with the user session and the current project context. The cloud material assets can be accessed and used by all terminal devices of the user. The user can view, edit, and reference these materials simultaneously on PC and mobile devices.

[0064] This embodiment acquires material data and uploads it to the cloud data center by calling the camera interface, microphone interface, and album access interface on the mobile device. This allows mobile users to easily take photos, record videos or audio, select album materials, and immediately use them for AI content generation. Furthermore, after the material data collected by the mobile device is uniformly stored in the cloud data center, users can access and use these materials simultaneously on PC and mobile devices, realizing a creative experience of shooting and generating content on the go, and meeting users' needs to create content anytime, anywhere using their own materials.

[0065] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0066] Please see Figure 2 , Figure 2 This is a schematic block diagram of a computer device provided in an embodiment of this application. The computer device 500 can be a terminal or a server, wherein the server can be a standalone server or a server cluster composed of multiple servers.

[0067] The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0068] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, it enables the processor 502 to execute a multi-terminal collaborative interaction and rendering method for an AI content generation platform.

[0069] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0070] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a multi-terminal collaborative interaction and rendering method of an AI content generation platform.

[0071] The network interface 505 is used for network communication with other devices. Those skilled in the art will understand that the above structure is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. A specific computer device 500 may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements.

[0072] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of a multi-terminal collaborative interaction and rendering method for an AI content generation platform provided in any of the above method embodiments.

[0073] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0074] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0075] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program. When executed by a processor, the computer program causes the processor to perform the steps of a multi-terminal collaborative interaction and rendering method for an AI content generation platform provided in any of the above method embodiments.

[0076] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0077] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0078] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0079] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0080] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0081] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0082] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, this invention is also intended to include these modifications and variations as long as they fall within the scope of the claims of this invention and their equivalents.

[0083] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-terminal collaborative interaction and rendering method for an AI content generation platform, characterized in that, include: In response to receiving a rendering trigger command for a target functional node, obtain the cross-end node unified metadata of the target functional node; Obtain the terminal type and screen size information of the currently running terminal; Based on the unified metadata of the cross-terminal node, the terminal type and the screen size information, the user interface corresponding to the target functional node is rendered. The rendering process reuses the same core rendering logic on different terminals, and adapts the display style, layout and interaction mode of the node controls in the user interface according to the terminal type and the screen size information to obtain the node user interface adapted to the current running terminal. In response to the operation command executed by the user on the node user interface, operation data is generated and submitted to the cloud data center to update the unique data source stored in the cloud data center, so as to obtain the latest data in the cloud.

2. The method according to claim 1, characterized in that, The cross-platform node unified metadata includes a first-platform rendering configuration and a second-platform rendering configuration. The step of rendering the user interface corresponding to the target functional node based on the cross-platform node unified metadata, the platform type, and the screen size information includes: When the terminal type is PC, the layout density of the node control is determined based on the rendering configuration of the first terminal and the screen size information, and the node control is presented as a multi-column layout, a floating parameter panel, and adapted to the mouse drag interaction mode based on the layout density. When the terminal type is a mobile terminal, the layout precision of the node control is determined based on the second terminal rendering configuration and the screen size information, and the node control is presented as a single-column flow layout, a full-screen parameter panel, and adapted to the touch interaction mode based on the layout precision.

3. The method according to claim 1, characterized in that, After submitting the operation data to the cloud data center to update the unique data source stored in the cloud data center and obtaining the latest data in the cloud, the method further includes: The latest data from the cloud is synchronized to each other terminal device currently logged in by the user through a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal.

4. The method according to claim 3, characterized in that, After synchronizing the latest data from the cloud to each other terminal device currently logged in by the user via a real-time communication channel, so that the other terminal devices display the latest content consistent with the currently running terminal, the method further includes: Receive offline operation data uploaded by the mobile device after performing offline editing operations in a network-free environment, in response to the network being restored; The received offline operation data is merged with the data in the cloud data center, and conflict detection is performed during the merging process: If a data conflict is detected, the conflicting modifications that can be automatically merged and those that cannot be automatically merged are determined from the data conflict. The automatically mergeable conflict modifications are merged with the data in the cloud data center to generate merged data; For conflicting modifications that cannot be automatically merged, different modified versions corresponding to the data conflict are displayed, and the selected version is retained in response to the user's selection instruction.

5. The method according to claim 1, characterized in that, After generating operation data in response to an operation command executed by the user on the node user interface, the method further includes: Obtain the editing operation data of the first collaborator for the target workflow or target project, as well as the permission information of the first collaborator; Determine whether the first collaborator has edit permissions; If the first collaborator's permission information includes the editing permission, the editing operation data is input into the collaborative editing engine, which performs concurrent editing operation conversion and merging processing to generate merged edited content and synchronizes the merged edited content to the terminal devices of all collaborators. If the first collaborator's permission information does not include the required editing permissions, then the editing operation data is rejected.

6. The method according to claim 5, characterized in that, After synchronizing the merged edited content to the terminal devices of all collaborators, the method further includes: Get the online status, cursor position, and current editing area of ​​each collaborator; The online status, cursor position, and current editing area are synchronized to the terminal devices of all collaborators, and the editing content of each collaborator is marked on the interface of the terminal device to display the editing area identifier of different collaborators.

7. The method according to claim 1, characterized in that, The step of submitting the operation data to the cloud data center, and updating the unique data source stored in the cloud data center with the operation data to obtain the latest data in the cloud, includes: The operation data is submitted to the cloud data center, which triggers the cloud data center to perform business logic processing on the operation data. The business logic processing includes rule verification, points deduction and task execution logic. In response to the completion of the business logic processing in the cloud data center, the processing result is obtained and written to the unique data source to obtain the latest data in the cloud.

8. The method according to claim 1, characterized in that, After generating operation data in response to an operation command executed by the user on the node user interface, the method further includes: Receive mobile-collected material data uploaded by the mobile terminal, and store the mobile-collected material data in the cloud data center; The mobile terminal collects material data, including image data, video data, audio data, or album material data. The mobile terminal collects material data by calling its own camera interface, microphone interface, or album access interface according to the device call command triggered by the user on the mobile terminal.

9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-8.

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