Method and device for interacting with large model through visual editor, equipment and medium

Abstract

The invention relates to a method and device for interacting with a large model through a visual editor, equipment and a medium. The method for interacting with the large model through the visual editor comprises the steps that in response to task editing operation of a user, a task flow chart corresponding to the task editing operation is displayed on an interaction interface, and the task flow chart comprises a plurality of nodes; converting the task flow chart into a structured format text through a front-end system, and sending the structured format text to a rear-end system; performing task execution processing on each node through the back-end system according to the structured format text to obtain a corresponding task output result; and displaying the task output result corresponding to each node on the interactive interface through the front-end system. According to the embodiment of the invention, the planning and implementation process of complex tasks can be greatly simplified, and the task processing accuracy is improved.

Description

Technical Field

[0001] The present disclosure relates to the application field of complex multi-process task management technology, and in particular to a method, device, equipment and medium for interacting with a large model through a visual editor. Background Art

[0002] In the field of complex multi-process task management, using large models to generate strategies or support task execution has become a trend, especially for projects with multiple processes, multiple nodes, and interdependencies. However, current technical means mainly rely on plain text prompt word input, and users use text descriptions to express the requirements and relationships of each process node to guide the large model to understand the task structure and output corresponding strategies. This method has the following shortcomings in practice: 1. The description process is cumbersome: In large projects or complex task scenarios, users need to describe the functions, associations, and dependencies of each node one by one so that the large model can understand the entire task chain. This not only requires users to have clear logical organization skills, but also makes the construction of text prompts time-consuming and cumbersome, and it is difficult to ensure the comprehensive and accurate description of task relationships. 2. Information transmission is not intuitive: Multi-process tasks often involve multiple process chains and complex front-to-back dependencies. Relying solely on text to describe these relationships is not only easy to cause misunderstandings, but may also cause the results of large model generation to deviate from task requirements. 3. Inconvenient adjustment and insufficient flexibility: During the execution of tasks, requirements may continue to change or be refined. In the traditional text prompt method, each change requires re-editing or re-describing the node and process relationship. Such an adjustment process often takes a long time and is prone to errors. Especially in complex projects, frequent adjustments will further increase the user burden and the probability of error. 4. Lack of global view support: Complex task management often requires users to maintain a grasp of the overall structure of the task and ensure that the goals and positions of each process node are clear. However, constructing a global view of the task through text description is not intuitive, and it is difficult to ensure that the large model understands the overall picture of the task, resulting in unsatisfactory overall strategy generation results.

[0003] Therefore, how to build an intuitive and flexible interactive method to help users describe complex task processes with lower operating costs and higher accuracy has become a current problem. Summary of the invention

[0004] In order to solve the above technical problems, the present disclosure provides a method, device, equipment and medium for interacting with a large model through a visual editor.

[0005] In a first aspect, the present disclosure provides a method for interacting with a large model through a visual editor, comprising: In response to a task editing operation by a user, a task flow chart corresponding to the task editing operation is displayed on an interactive interface, wherein the task flow chart includes a plurality of nodes; Converting the task flow chart into a structured format text through a front-end system, and sending the structured format text to a back-end system; According to the structured format text, the back-end system performs task execution processing on each node to obtain corresponding task output results; The task output results corresponding to each node are displayed on the interactive interface through the front-end system.

[0006] In a second aspect, the present disclosure provides a device for interacting with a large model through a visual editor, comprising: A first display module, configured to respond to a task editing operation of a user and display a task flow chart corresponding to the task editing operation on an interactive interface, wherein the task flow chart includes a plurality of nodes; A first processing module, used for converting the task flow chart into a structured format text through a front-end system, and sending the structured format text to a back-end system; A second processing module is used to perform task execution processing on each node through the back-end system according to the structured format text to obtain a corresponding task output result; The second display module is used to display the task output results corresponding to each node on the interactive interface through the front-end system.

[0007] In a third aspect, the present disclosure provides a device for interacting with a large model through a visual editor, including: processor; A memory for storing executable instructions; The processor is used to read executable instructions from the memory and execute the executable instructions to implement the first aspect of the method for interacting with a large model through a visual editor.

[0008] In a fourth aspect, the present disclosure provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor implements the method for interacting with a large model through a visual editor according to the first aspect.

[0009] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages: The method, device, equipment and medium for interacting with a large model through a visual editor in the disclosed embodiment can respond to the user's task editing operation, display the task flow chart corresponding to the task editing operation on the interactive interface, and the task flow chart includes multiple nodes, and then convert the task flow chart into a structured format text through the front-end system, and send the structured format text to the back-end system, and then perform task execution processing on each node through the back-end system according to the structured format text to obtain the corresponding task output result, and finally display the task output result corresponding to each node on the interactive interface through the front-end system. Thus, the user performs the task editing operation through the interactive interface, converts the corresponding task flow chart into a structured format text through the front-end system, and performs task execution processing on each node through the back-end system to obtain the corresponding task output result. Thus, through the interactive mode of simply dragging and dropping the flowchart to edit, the context understanding throughout is maintained with the structured format text, which greatly simplifies the planning and implementation process of complex tasks and improves the accuracy of task processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0011] Figure 1 A flowchart of a method for interacting with a large model through a visual editor provided in an embodiment of the present disclosure; Figure 2 A flowchart of another method for interacting with a large model through a visual editor provided by an embodiment of the present disclosure; Figure 3 A schematic diagram of a structure of a device for interacting with a large model through a visual editor provided by an embodiment of the present disclosure; Figure 4 A schematic diagram of the structure of a device for interacting with a large model through a visual editor is provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0012] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0013] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0014] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0015] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0016] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0017] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0018] In order to solve the above problems, the embodiments of the present disclosure provide a method, device, equipment and medium for interacting with a large model through a visual editor. Figure 1 to Figure 2 The method for interacting with a large model through a visual editor provided in an embodiment of the present disclosure is described in detail.

[0019] Figure 1 A flowchart of a method for interacting with a large model through a visual editor provided by an embodiment of the present disclosure is shown.

[0020] In the embodiment of the present disclosure, the method for interacting with the large model through the visual editor can be executed by an electronic device, wherein the electronic device may include but is not limited to devices such as computer devices, cloud servers or cloud server clusters.

[0021] like Figure 1 As shown, the method for interacting with a large model through a visual editor may include the following steps.

[0022] S110. In response to a task editing operation of a user, displaying a task flow chart corresponding to the task editing operation on an interactive interface, wherein the task flow chart includes a plurality of nodes.

[0023] In an embodiment of the present disclosure, the electronic device may display a task flow chart corresponding to the task editing operation on an interactive interface in response to a task editing operation by a user.

[0024] Optionally, the task editing operation may be an editing operation for a user to construct a task flow chart. For example, the task editing operation may include a user dragging and dropping the task flow chart.

[0025] Optionally, the task flow chart may be a flow chart for realizing a specific task function, wherein the task flow chart may include multiple nodes.

[0026] Specifically, the user can create a task flowchart in the editor by dragging and dropping, that is, the electronic device can respond to the user's task editing operation and display the task flowchart corresponding to the task editing operation in the interactive interface, and the task flowchart may include multiple nodes.

[0027] S120: Convert the task flow chart into a structured format text through a front-end system, and send the structured format text to a back-end system.

[0028] In the embodiment of the present disclosure, the electronic device can convert the task flow chart into a structured format text through a front-end system, and send the structured format text to a back-end system.

[0029] Optionally, the structured format text may be a Mermaid format text (or other structured formats).

[0030] Specifically, the electronic device can convert the task flow chart into a structured format text through the front-end system, and send the structured format text to the back-end system. For example, for a four-node flow chart, the following Mermaid text can be generated: "flowchart TDA [data acquisition] --> B [data cleaning] B --> C [model training] C --> D [result output]".

[0031] Among them, the structured format text always serves as the context of the large model in subsequent interactions, ensuring that the large model can understand the overall picture of the entire task when processing each node.

[0032] S130. According to the structured format text, the back-end system performs task execution processing on each node to obtain a corresponding task output result.

[0033] In the disclosed embodiment, the electronic device may perform task execution processing on each node through the back-end system according to the structured format text to obtain corresponding task output results.

[0034] Specifically, the electronic device can perform task execution processing on each node through the back-end system according to the structured format text, that is, the back-end system performs task execution processing on each node in the task flow chart in turn, and combines the context information of the structured format text to obtain the corresponding task output result.

[0035] S140. Displaying the task output results corresponding to each node on the interactive interface through the front-end system.

[0036] In the disclosed embodiment, the electronic device may display the task output results corresponding to each node on the interactive interface through the front-end system.

[0037] Thus, in the disclosed embodiment, in response to the user's task editing operation, the task flow chart corresponding to the task editing operation can be displayed on the interactive interface, the task flow chart includes multiple nodes, and then the task flow chart is converted into a structured format text through the front-end system, and the structured format text is sent to the back-end system, and then according to the structured format text, the task execution processing is performed on each node through the back-end system to obtain the corresponding task output result, and finally the task output result corresponding to each node is displayed on the interactive interface through the front-end system. Thus, the user performs the task editing operation through the interactive interface, the corresponding task flow chart is converted into a structured format text through the front-end system, and the task execution processing is performed on each node through the back-end system to obtain the corresponding task output result. Thus, through the interactive mode of simply dragging and dropping the flowchart to edit, the contextual understanding is maintained throughout with the structured format text, which greatly simplifies the planning and implementation process of complex tasks and improves the accuracy of task processing.

[0038] Optionally, S110 may specifically include: in response to a user's dragging operation, displaying multiple nodes corresponding to the dragging operation in the interactive interface; in response to a user's connection operation, determining the execution order and dependency relationship between multiple nodes; based on the multiple nodes and the execution order and dependency relationship between the multiple nodes, generating and displaying the task flow chart in the interactive interface.

[0039] In an embodiment of the present disclosure, the electronic device may, in response to a drag operation by a user, display a plurality of nodes corresponding to the drag operation in the interactive interface.

[0040] Specifically, the user creates a task flow chart in the editor by dragging and dropping. Each node represents a task step or functional module. The user can freely add, delete, and move nodes, and set the dependencies between nodes through connections to form a complete task flow. The electronic device can respond to the user's drag operation and display multiple nodes corresponding to the drag operation in the interactive interface. For example, a flowchart may include multiple nodes such as data collection, data cleaning, model training, and result output. The user can express the execution order and dependency of each node through connections.

[0041] Furthermore, the electronic device may determine the execution order and dependency relationships among multiple nodes in response to a user's connection operation.

[0042] Specifically, each node can define multiple attributes (such as name, type, task parameters, etc.), and users can express dependencies through connections. The dependencies between nodes not only refer to the execution order, but also represent different types of dependencies such as data flow and control flow. Electronic devices can determine the execution order and dependencies between multiple nodes in response to user connection operations. The attributes of the connection are retained in subsequent conversions and prompt word generation, ensuring that the large model can understand the complex task chain structure.

[0043] Furthermore, the electronic device may generate and display the task flow chart in the interactive interface based on the execution order and dependency relationships among the multiple nodes.

[0044] Optionally, S120 may specifically include: traversing each node through the back-end system to obtain corresponding node information, and sending the node information to the big model; performing task execution processing on each node through the big model according to the structured format text and the node information to obtain corresponding task output results.

[0045] In the disclosed embodiment, the electronic device may traverse each node through the backend system to obtain corresponding node information, and send the node information to the large model.

[0046] Specifically, the electronic device can traverse each node in the flowchart through the back-end system, pass the node information to the big model one by one, and require the big model to think independently about each node and output the corresponding execution strategy or code implementation.

[0047] Furthermore, according to the structured format text and the node information, the large model is used to perform task execution processing on each node to obtain a corresponding task output result.

[0048] Specifically, the big model can automatically combine the context information in the global flow chart based on the structured format text and the node information to understand the role of the node in the task chain, thereby providing accurate suggestions or implementation codes. For example, the big model may generate data acquisition code for the "data collection" node and cleansing logic for the "data cleaning" node.

[0049] The large model generates task outputs independently according to the specific needs of each node, including code implementation, analysis documents, etc. For example: Data collection node: Generates code and documentation for data collection. Data cleaning node: Generates data cleaning code and guidance documents for data normalization. Model training node: Provides code and configuration parameter descriptions for model training. Result output node: Generates formatted code and display reports for output data.

[0050] By keeping the structured text format throughout the entire interaction process, the big model can review the global structure of the task at any time. This mechanism greatly improves the big model's understanding of the task background and reduces the risk of context loss. The big model can not only view the information of the current node, but also combine the context of other nodes to help users optimize the task process.

[0051] Optionally, the method of interacting with the big model through the visual editor may also include: identifying multiple target nodes with the same function among multiple nodes through the big model; and aggregating and executing the multiple target nodes through the big model to obtain corresponding task output results.

[0052] In an embodiment of the present disclosure, the electronic device can identify multiple target nodes with the same function among multiple nodes through the large model, and perform aggregation execution processing on the multiple target nodes through the large model to obtain corresponding task output results.

[0053] Specifically, the electronic device can identify multiple target nodes with the same function in multiple nodes through the large model. For example, if a set of data processing steps should be merged into a data preprocessing module, the large model is used to aggregate and execute multiple target nodes to obtain the corresponding task output results. Generally, the relevant nodes are presented in a box on the flowchart to prompt the user that these nodes can be implemented as a whole function. This automatic aggregation mechanism helps users optimize the flowchart structure and improve the modularity of task execution.

[0054] When the large model determines that some nodes can be aggregated into a functional module, it will mark the relevant nodes in the flowchart and generate a merged implementation plan. This aggregation not only reduces the number of nodes, but also improves the overall execution efficiency of the task. For example, the large model may aggregate the "data cleaning" and "data standardization" nodes into a "data preprocessing" module and output the aggregated code and instruction documents.

[0055] Optionally, the method of interacting with a large model through a visual editor may also include: in response to a user's task modification operation, modifying multiple nodes in the task flow chart to obtain an updated task flow chart; and updating the structured format text through the front-end system according to the updated task flow chart.

[0056] In an embodiment of the present disclosure, the electronic device may modify a plurality of nodes in the task flow chart in response to a task modification operation by a user to obtain an updated task flow chart.

[0057] Specifically, each node can enter an independent prompt word communication dialogue page, where users can view the task output (such as code, analysis documents, etc.) generated by the large model and further communicate with the large model. For example, the user can ask the large model to optimize a certain section of code or further explain the implementation logic of the node. At the same time, the user can modify and adjust the output of the large model to meet actual needs. The electronic device can modify multiple nodes in the task flow chart in response to the user's task modification operation to obtain an updated task flow chart.

[0058] Furthermore, the electronic device may update the structured format text through the front-end system according to the updated task flow chart.

[0059] Specifically, the user can modify the flowchart at any time in the dialogue page, such as adding new nodes, changing the order of nodes, or adjusting dependencies. These changes will automatically update the Mermaid text and regenerate the prompt word context to ensure that the large model can understand the new task structure in real time. The electronic device can update the structured format text through the front-end system according to the updated task flowchart. Therefore, the user can flexibly adjust the task process according to the feedback of the large model and the changes in task requirements, thereby improving the adaptability of task planning.

[0060] Optionally, the method of interacting with the big model through the visual editor may also include: based on the structured format text, optimizing and analyzing the task flow chart through the big model to obtain corresponding optimization suggestions; optimizing the task flow chart according to the optimization suggestions to obtain an optimized task flow chart.

[0061] In the disclosed embodiment, the electronic device may optimize and analyze the task flow chart based on the structured format text through a large model to obtain corresponding optimization suggestions.

[0062] Specifically, the electronic device can optimize and analyze the task flow chart based on the structured format text through the big model. For example, the big model can automatically suggest optimizing the layout and dependency of nodes based on understanding the overall picture of the flow chart. If the big model detects that the dependency of some nodes is redundant or unreasonable, it can automatically generate optimization suggestions to help users simplify the flow chart structure. This greatly enhances the intelligence and adaptability of the big model in task process management.

[0063] Furthermore, the electronic device may optimize the task flow chart according to the optimization suggestion to obtain an optimized task flow chart.

[0064] Optionally, the method of interacting with the large model through the visual editor may also include: generating a corresponding task execution strategy overview through the large model based on the optimized task flow chart.

[0065] In the disclosed embodiment, the electronic device may generate a corresponding task execution strategy overview through the large model based on the optimized task flow chart.

[0066] Specifically, the electronic device can generate a corresponding task execution strategy overview based on the optimized task flow chart through the large model. For example, the large model generates an overall task execution strategy overview based on the optimized flow chart, covering the role, execution order and dependency of each module. This helps users have a clear understanding of the global strategy of task execution, which is convenient for the final deployment and implementation of the project.

[0067] Optionally, the backend system synchronizes the output content of the large model to the front-end interface in real time, and the execution tasks and instructions of each node will be directly displayed on the corresponding flowchart node. Users can intuitively view the specific implementation details of each node and evaluate and adjust the task flow at any time.

[0068] Optionally, after viewing the execution tasks generated by the large model, the user can make further adjustments to the flowchart and node attributes. These adjustments will be automatically updated by the system and fed back to the large model to generate new execution strategies and implementation plans. This cyclic process enables the flowchart to be continuously optimized according to user needs, and ultimately outputs the optimal task execution plan.

[0069] Figure 2 A flowchart of another method for interacting with a large model through a visual editor provided by an embodiment of the present disclosure is shown.

[0070] like Figure 2As shown in the figure, users create task flow charts in the editor by dragging and dropping, and each node represents a task step or functional module. Users can freely add, delete, and move nodes, and set dependencies between nodes through connections to form a complete task flow. For example, a flowchart may include multiple nodes such as data collection, data cleaning, model training, and result output. Users can express the execution order and dependencies of each node through connections. Each node can define multiple attributes (such as name, type, task parameters, etc.) and express dependencies through connections. The dependencies between nodes not only refer to the execution order, but also represent different types of dependencies such as data flow and control flow.

[0071] Then the electronic device can convert the task flow chart into a structured format text through the front-end system, and send the structured format text to the back-end system. For example, for a four-node flow chart, the following Mermaid text can be generated: "flowchart TDA [data acquisition] --> B [data cleaning] B --> C [model training] C --> D [result output]".

[0072] Furthermore, the electronic device can traverse each node in the flowchart through the back-end system, pass the node information to the big model one by one, and require the big model to think independently about each node and output the corresponding execution strategy or code implementation. The big model can automatically combine the context information in the global flowchart according to the structured format text and the node information, understand the role of the node in the task chain, and provide accurate suggestions or implementation codes. For example, the big model may generate data acquisition code for the "data collection" node and generate cleaning logic for the "data cleaning" node. The big model independently generates task outputs according to the specific needs of each node, including code implementation, analysis documents, etc. For example: Data collection node: Generates code and instruction documents for data collection. Data cleaning node: Generates data cleaning code and guidance documents for data normalization. Model training node: Provides code and configuration parameter descriptions for model training. Result output node: Generates formatted code and display reports for output data.

[0073] Furthermore, the electronic device can identify multiple target nodes with the same function in multiple nodes through the large model. For example, if a set of data processing steps should be merged into a data preprocessing module, the large model is used to aggregate and execute the multiple target nodes to obtain the corresponding task output results. Generally, the relevant nodes are presented in a box on the flowchart to prompt the user that these nodes can be implemented as a whole function. This automatic aggregation mechanism helps users optimize the flowchart structure and improve the modularity of task execution.

[0074] When the large model determines that some nodes can be aggregated into a functional module, it will mark the relevant nodes in the flowchart and generate a merged implementation plan. This aggregation not only reduces the number of nodes, but also improves the overall execution efficiency of the task. For example, the large model may aggregate the "data cleaning" and "data standardization" nodes into a "data preprocessing" module and output the aggregated code and instruction documents.

[0075] Furthermore, each node can enter an independent prompt word communication dialogue page, where users can view the task output (such as code, analysis documents, etc.) generated by the large model and further communicate with the large model. For example, the user can ask the large model to optimize a certain section of code or further explain the implementation logic of the node. At the same time, the user can modify and adjust the output of the large model to meet actual needs. The electronic device can modify multiple nodes in the task flow chart in response to the user's task modification operation to obtain an updated task flow chart. The user can modify the flow chart at any time in the dialogue page, such as adding new nodes, changing the order of nodes, or adjusting dependencies. These changes will automatically update the Mermaid text and regenerate the prompt word context to ensure that the large model can understand the new task structure in real time. The electronic device can update the structured format text through the front-end system according to the updated task flow chart. Thus, the user can flexibly adjust the task process according to the feedback of the large model and the changes in task requirements, and improve the adaptability of task planning.

[0076] Furthermore, the electronic device can optimize and analyze the task flow chart through the big model based on the structured format text. For example, the big model can automatically suggest optimizing the layout and dependencies of the nodes based on understanding the overall picture of the flow chart. If the big model detects that the dependencies of some nodes are redundant or unreasonable, it can automatically generate optimization suggestions to help users simplify the flow chart structure. This greatly enhances the intelligence and adaptability of the big model in task process management. The electronic device can generate a corresponding task execution strategy overview based on the optimized task flow chart through the big model. For example, the big model generates an overall task execution strategy overview based on the optimized flow chart, covering the role, execution order and dependencies of each module. This helps users have a clear understanding of the global strategy of task execution, which facilitates the final deployment and implementation of the project.

[0077] Optionally, the backend system synchronizes the output content of the large model to the front-end interface in real time, and the execution tasks and instructions of each node will be directly displayed on the corresponding flowchart node. Users can intuitively view the specific implementation details of each node and evaluate and adjust the task flow at any time.

[0078] Optionally, after viewing the execution tasks generated by the large model, the user can make further adjustments to the flowchart and node attributes. These adjustments will be automatically updated by the system and fed back to the large model to generate new execution strategies and implementation plans. This cyclic process enables the flowchart to be continuously optimized according to user needs, and ultimately outputs the optimal task execution plan.

[0079] Figure 3 A structural schematic diagram of a device for interacting with a large model through a visual editor provided by an embodiment of the present disclosure is shown.

[0080] like Figure 3 As shown, the device 300 for interacting with a large model through a visual editor may include a first display module 310 , a first processing module 320 , a second processing module 330 and a second display module 340 .

[0081] The first display module 310 can be used to respond to a task editing operation of a user and display a task flow chart corresponding to the task editing operation on an interactive interface, wherein the task flow chart includes a plurality of nodes.

[0082] The first processing module 320 can be used to convert the task flow chart into a structured format text through the front-end system, and send the structured format text to the back-end system.

[0083] The second processing module 330 can be used to perform task execution processing on each node through the back-end system according to the structured format text to obtain corresponding task output results.

[0084] The second display module 340 can be used to display the task output results corresponding to each node on the interactive interface through the front-end system.

[0085] Thus, in the disclosed embodiment, in response to the user's task editing operation, the task flow chart corresponding to the task editing operation can be displayed on the interactive interface, the task flow chart includes multiple nodes, and then the task flow chart is converted into a structured format text through the front-end system, and the structured format text is sent to the back-end system, and then according to the structured format text, the task execution processing is performed on each node through the back-end system to obtain the corresponding task output result, and finally the task output result corresponding to each node is displayed on the interactive interface through the front-end system. Thus, the user performs the task editing operation through the interactive interface, the corresponding task flow chart is converted into a structured format text through the front-end system, and the task execution processing is performed on each node through the back-end system to obtain the corresponding task output result. Thus, through the interactive mode of simply dragging and dropping the flowchart to edit, the contextual understanding is maintained throughout with the structured format text, which greatly simplifies the planning and implementation process of complex tasks and improves the accuracy of task processing.

[0086] In some embodiments of the present disclosure, the first display module 310 may specifically include a first display unit, a relationship determination unit and a second display unit.

[0087] The first display unit may be configured to respond to a drag operation by a user and display multiple nodes corresponding to the drag operation in the interactive interface.

[0088] The relationship determination unit may be used to determine the execution order and dependency relationship between multiple nodes in response to a user's connection operation.

[0089] The second display unit can be used to generate and display the task flow chart in the interactive interface based on multiple nodes and the execution order and dependency relationship between the multiple nodes.

[0090] In some embodiments of the present disclosure, the second processing module 330 may specifically include a node traversal unit and an execution processing unit.

[0091] The node traversal unit can be used to traverse each node through the back-end system to obtain corresponding node information, and send the node information to the large model.

[0092] The execution processing unit can be used to perform task execution processing on each node through the large model according to the structured format text and the node information to obtain corresponding task output results.

[0093] In some embodiments of the present disclosure, the device 300 for interacting with a large model through a visual editor may further include a node identification module and a third processing module.

[0094] The node identification module can be used to identify multiple target nodes with the same function among multiple nodes through the large model.

[0095] The third processing module can be used to perform aggregate execution processing on multiple target nodes through the large model to obtain corresponding task output results.

[0096] In some embodiments of the present disclosure, the apparatus 300 for interacting with a large model through a visual editor may further include a first updating module and a second updating module.

[0097] The first updating module can be used to modify multiple nodes in the task flow chart in response to the user's task modification operation to obtain an updated task flow chart.

[0098] The second updating module can be used to update the structured format text through the front-end system according to the updated task flow chart.

[0099] In some embodiments of the present disclosure, the device 300 for interacting with a large model through a visual editor may further include an optimization analysis module and a fourth processing module.

[0100] The optimization analysis module can be used to optimize and analyze the task flow chart based on the structured format text through a large model to obtain corresponding optimization suggestions.

[0101] The fourth processing module can be used to optimize the task flow chart according to the optimization suggestion to obtain an optimized task flow chart.

[0102] In some embodiments of the present disclosure, the apparatus 300 for interacting with a large model through a visual editor may further include a fifth processing module.

[0103] The fifth processing module can be used to generate a corresponding task execution strategy overview through the large model based on the optimized task flow chart.

[0104] It should be noted that Figure 3 The device 300 for interacting with a large model through a visual editor can be executed Figure 1 to Figure 2 The various steps in the method embodiment shown in the figure are implemented Figure 1 to Figure 2 The various processes and effects in the method embodiment shown are not described in detail here.

[0105] Figure 4 A schematic diagram of the structure of a device for interacting with a large model through a visual editor provided by an embodiment of the present disclosure is shown.

[0106] In some embodiments of the present disclosure, Figure 4The device for interacting with the large model through the visual editor shown can be an electronic device. Specifically, the electronic device can include but is not limited to devices such as computer devices, cloud servers or cloud server clusters.

[0107] like Figure 4 As shown, the device for interacting with a large model through a visual editor may include a processor 401 and a memory 402 storing computer program instructions.

[0108] Specifically, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0109] The memory 402 may include a large capacity memory for information or instructions. By way of example and not limitation, the memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 402 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 402 may be inside or outside the integrated gateway device. In a specific embodiment, the memory 402 is a non-volatile solid-state memory. In a specific embodiment, the memory 402 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (Electrically Erasable Programmable ROM, EEPROM), an electrically rewritable ROM (EAROM) or a flash memory, or a combination of two or more of these.

[0110] The processor 401 reads and executes the computer program instructions stored in the memory 402 to perform the steps of the method for interacting with a large model through a visual editor provided in the embodiment of the present disclosure.

[0111] In one example, the device for interacting with a large model through a visual editor may further include a transceiver 403 and a bus 404. Figure 4As shown, the processor 401, the memory 402 and the transceiver 403 are connected via a bus 404 and communicate with each other.

[0112] The bus 404 includes hardware, software or both. For example, but not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a Memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, the bus 404 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0113] The embodiment of the present disclosure also provides a computer-readable storage medium, which can store a computer program. When the computer program is executed by a processor, the processor implements the method for interacting with a large model through a visual editor provided by the embodiment of the present disclosure.

[0114] The above-mentioned storage medium may, for example, include a memory 402 of computer program instructions, and the above-mentioned instructions may be executed by a processor 401 of a device for interacting with a large model through a visual editor to complete the method for interacting with a large model through a visual editor provided in an embodiment of the present disclosure. Optionally, the storage medium may be a non-temporary computer-readable storage medium, for example, a non-temporary computer-readable storage medium may be a ROM, a random access memory (Random Access Memory, RAM), a compact disc read-only memory (Compact Disc ROM, CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0115] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0116] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for interacting with a large model through a visual editor, characterized in that: include: In response to a task editing operation by a user, a task flow chart corresponding to the task editing operation is displayed on an interactive interface, wherein the task flow chart includes a plurality of nodes; Converting the task flow chart into a structured format text through a front-end system, and sending the structured format text to a back-end system; According to the structured format text, the back-end system performs task execution processing on each node to obtain corresponding task output results; The task output results corresponding to each node are displayed on the interactive interface through the front-end system; The step of performing task execution processing on each node through the back-end system according to the structured format text to obtain the corresponding task output result includes: Traversing each node through the backend system to obtain corresponding node information, and sending the node information to the large model; According to the structured format text and the node information, the task execution processing is performed on each node through the large model to obtain the corresponding task output result.

2. The method according to claim 1, characterized in that In response to the task editing operation of the user, displaying the task flow chart corresponding to the task editing operation on the interactive interface includes: In response to a dragging operation by a user, displaying a plurality of nodes corresponding to the dragging operation in the interactive interface; In response to a user's connection operation, determining an execution order and dependency relationship between multiple nodes; Based on the execution order and dependency relationship between the multiple nodes and the multiple nodes, the task flow chart is generated and displayed in the interactive interface.

3. The method according to claim 1, characterized in that The method further comprises: Identify multiple target nodes with the same function among multiple nodes by using the large model; The large model is used to aggregate and execute processing on multiple target nodes to obtain corresponding task output results.

4. The method according to claim 1, characterized in that: The method further comprises: In response to a task modification operation by a user, modifying a plurality of nodes in the task flow chart to obtain an updated task flow chart; The structured format text is updated through the front-end system according to the updated task flow chart.

5. The method according to claim 1, characterized in that The method further comprises: Based on the structured format text, the task flow chart is optimized and analyzed through a large model to obtain corresponding optimization suggestions; The task flow chart is optimized according to the optimization suggestion to obtain an optimized task flow chart.

6. The method according to claim 5, characterized in that The method further comprises: Based on the optimized task flow chart, the corresponding task execution strategy overview is generated through the large model.

7. A device for interacting with a large model through a visual editor, characterized in that: include: A first display module, configured to respond to a task editing operation of a user and display a task flow chart corresponding to the task editing operation on an interactive interface, wherein the task flow chart includes a plurality of nodes; A first processing module, used for converting the task flow chart into a structured format text through a front-end system, and sending the structured format text to a back-end system; A second processing module is used to perform task execution processing on each node through the back-end system according to the structured format text to obtain a corresponding task output result; A second display module, used to display the task output results corresponding to each node on the interactive interface through the front-end system; Wherein, the second processing module includes: A node traversal unit, used for traversing each node through the back-end system to obtain corresponding node information, and sending the node information to the large model; An execution processing unit is used to perform task execution processing on each node through the large model according to the structured format text and the node information to obtain a corresponding task output result.

8. A device for interacting with a large model through a visual editor, characterized in that: include: processor; A memory for storing executable instructions; The processor is used to read the executable instructions from the memory and execute the executable instructions to implement the method for interacting with a large model through a visual editor as described in any one of claims 1 to 6.

9. A non-volatile computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the processor implements the method for interacting with a large model through a visual editor as described in any one of claims 1 to 6.

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