Method and apparatus for displaying component of workflow, electronic device, and product

Abstract

The present application relates to a method and apparatus for displaying a component of a workflow, an electronic device, and a product. The method comprises: during the process of establishing a workflow, acquiring data of a first component that has been established. The method further comprises: acquiring description information related to a requirement of a second component, wherein the description information of the second component is generated by a target model on the basis of the data of the first component. In addition, the method further comprises: on the basis of the description information of the second component, displaying the second component after the first component in the workflow. In the embodiments of the present application, a functional requirement of a next node can be predicted on the basis of a node that has been established in a workflow, so that the next node can be automatically established for display to a user, without requiring the user to manually input a prompt word. Thus, the workflow establishment efficiency is improved, thereby improving user experience.

Description

Method, device, electronic equipment and product for displaying components of a workflow TECHNICAL FIELD

[0001] The present disclosure relates to the field of computers, and more specifically to a method, device, electronic equipment and product for displaying components of a workflow. BACKGROUND

[0002] A workflow is a means of implementing business process automation, which integrates a series of business activities in a computer application environment through a modelized expression. Therefore, the application of workflow can greatly improve the efficiency in the fields of software development, office automation, etc. In the process of establishing a workflow, a user can select the required task nodes and set them at the specified position in the workflow.

[0003] To improve the development efficiency of the workflow, a large language model (LLM) is applied to the establishment process of the workflow. The role of the large language model is to understand the user's intention to assist the user in establishing the workflow. Therefore, in order to improve the development efficiency of the workflow and reduce the development cost, how to apply the large language model to assist the establishment of the workflow becomes an important research direction.

[0004] SUMMARY

[0005] In a first aspect of the present disclosure, a method for displaying components of a workflow is provided. The method comprises, in the process of establishing a workflow, obtaining data of a first component that has been established. The method further comprises obtaining description information related to a requirement of a second component, the description information of the second component being generated by a target model based on the data of the first component. In addition, the method further comprises displaying the second component after the first component in the workflow based on the description information of the second component.

[0006] In a second aspect of the present disclosure, a method for displaying components of a workflow is provided. The method comprises. receiving data of a first component that has been established from a client, the data of the first component being obtained by the client in the process of establishing a workflow. The method further comprises generating, by a target model, description information related to a requirement of a second component based on the data of the first component. In addition, the method further comprises sending the description information of the second component to the client, so that the client displays the second component after the first component in the workflow based on the description information of the second component.

[0007] In a third aspect of the disclosure, an apparatus for displaying components of a workflow is provided. The apparatus includes a first component data obtaining module configured to obtain data of a first component that has been established in a process of establishing a workflow. The apparatus also includes a description information obtaining module configured to obtain description information related to a requirement of a second component, the description information of the second component being generated by a target model based on the data of the first component. In addition, the apparatus also includes a second component displaying module configured to display the second component after the first component in the workflow based on the description information of the second component.

[0008] In a fourth aspect of the disclosure, an apparatus for displaying components of a workflow is provided. The apparatus includes a first component data receiving module configured to receive data of a first component that has been established from a client, the data of the first component being obtained by the client in a process of establishing a workflow. The apparatus also includes a description information generating module configured to generate, by a target model, description information related to a requirement of a second component based on the data of the first component. In addition, the apparatus also includes a description information sending module configured to send the description information of the second component to the client, so that the client displays the second component after the first component in the workflow based on the description information of the second component.

[0009] In a fifth aspect of the disclosure, an electronic device is provided. The electronic device includes a processor; and a memory coupled with the processor, the memory having stored therein instructions which, when executed by the processor, cause the electronic device to perform the method according to any one of the first aspect or the second aspect of the disclosure.

[0010] In a sixth aspect of the disclosure, a computer program product is provided. The computer program product is tangibly stored on a non-transitory computer readable medium and includes machine executable instructions that, when executed, cause a machine to implement the method according to any one of the first aspect or the second aspect of the disclosure.

[0011] The summary is provided to introduce a selection of concepts, in a simplified form, that are further described below in the DETAILED DESCRIPTION. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to limit the scope of the claimed subject matter. BRIEF DESCRIPTION OF DRAWINGS

[0012] FIG. 1 shows a schematic diagram of an example environment in which some embodiments of the disclosure can be implemented;

[0013] FIG. 2 shows a flowchart of a method for displaying components of a workflow according to some embodiments of the disclosure;

[0014] FIG. 3 shows a schematic diagram of a process for updating a displayed workflow, according to some embodiments of the present disclosure;

[0015] FIG. 4A shows a schematic diagram of a workflow before updating, according to some embodiments of the present disclosure;

[0016] FIG. 4B shows a schematic diagram of a workflow after updating, according to some embodiments of the present disclosure;

[0017] FIG. 5 shows a block diagram of an apparatus for displaying components of a workflow, according to some embodiments of the present disclosure; and

[0018] FIG. 6 shows a schematic block diagram of an electronic device, according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0019] It can be understood that all user-related data involved in the technical solution should be obtained and used after authorization by the user. This means that in the technical solution, if the user's personal information needs to be used, the user's explicit consent and authorization are required before obtaining these data, otherwise the relevant data collection and use will not be carried out. It should also be understood that in the implementation of the technical solution, relevant laws and regulations should be strictly followed in the process of data collection, use and storage, and necessary technical and measures should be taken to protect the safety of the user's data and ensure the safe use of the data.

[0020] 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 drawings, it should be understood that the present disclosure can be implemented in various forms and should not be interpreted as being limited to the embodiments set forth herein, but rather these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for exemplary purposes only and are not intended to limit the scope of protection of the present disclosure.

[0021] In the description of embodiments of the present disclosure, the term "comprising" and its similar words are understood to mean "including but not limited to". The term "based on" is understood to mean "based at least in part on". The term "one embodiment" or "the embodiment" is understood to mean "at least one embodiment". The terms "first", "second", and the like can refer to different or the same objects unless explicitly stated otherwise. Other explicit and implicit definitions can also be included below.

[0022] In the process of workflow establishment, a user generally needs to manually add a node in the workflow. To improve the efficiency of workflow establishment, in the related technology, the user can input a piece of natural language, such as voice or text form language, and then call a background large language model to process the natural language to generate a node or a segment of the workflow. However, in the related manner, the user needs to input a piece of natural language to generate the next node every time a node is added, which limits the efficiency of workflow establishment to some extent, and the user experience of establishing the workflow is not high.

[0023] To this end, in an embodiment of the present disclosure, a method for displaying components of a workflow is provided. In the process of establishing a workflow, the data of a node that has been established is first obtained. Then, according to the data of the node that has been established, the description information of the functional requirement of the next node is obtained, wherein the description information of the next node is generated by a target model based on the data of the node that has been established. Further, the next node is selected according to the description information of the next node, and the selected next node is displayed after the node that has been established. In this way, the functional requirement of the next node can be predicted according to the node that has been established in the workflow, and the next node is selected, so that the next node is automatically established to be displayed to the user without the user manually inputting a prompt word. Therefore, the efficiency of workflow establishment is improved, and the user experience is improved.

[0024] FIG. 1 shows a schematic diagram of an example environment 100 in which some embodiments of the present disclosure can be implemented. Referring to FIG. 1, the environment 100 includes a client 102 and a server 104. In some embodiments, the client 102 includes but is not limited to a user terminal, a mobile device, a computer, etc., and the server 104 includes but is not limited to a computing system, a single server, a distributed server, or a cloud-based server, etc. The client 102 and the server 104 are connected through a network to realize the transmission of data.

[0025] In some embodiments, a user can establish a workflow (the workflows 106 and 106' in the example environment 100 are workflows in the establishment process rather than final workflows) in the client 102, and the workflow 106 includes a plurality of nodes that have been established (which can be referred to as a first component that has been established), such as the nodes 1061 and 1062. Then, the client 102 can send the data of the nodes 1061 and 1062 that have been established to the server 104. After receiving, the server 104 can call a language model 110 (which can be referred to as a language model) to process the data of the nodes 1061 and 1062, so as to analyze the functional requirement of the next node (which can be referred to as a second component) and generate corresponding description information 108.

[0026] In some embodiments, after the server 104 invokes the language model 110 to generate the description information 108 of the next node, the description information 108 can be sent to the client 102. After the client 102 receives the description information 108 of the next node, the client 102 searches for the next node, i.e., the node 1063, according to the description information. Then, the client 102 displays the node 1063 after the node 1061 and the node 1062, thereby updating the workflow 106 to obtain the workflow 106'.

[0027] It should be understood that the above is the process of establishing the node 1063 of the workflow, which is one of the links of establishing the final workflow. For the next node of the node 1063 (at this time, the established nodes include the node 1061, the node 1062, and the node 1063), the client 102 can obtain the data of the node 1061, the node 1062, and the node 1063 and send the data to the server 104, and the server 104 invokes the language model 110 to process the received data and determine the description information of the next node, and then the client 102 selects the next node of the node 1063 based on the description information of the next node. By repeating the above process, the next node of the workflow can be continuously established, thereby forming a complete workflow.

[0028] In the embodiments of the present disclosure, in the process of establishing the workflow, the data of the established nodes 1061 and 1062 is first obtained. Then, according to the data of the nodes 1061 and 1062, the description information of the functional requirement of the next node is obtained, wherein the description information of the next node is generated by the language model 110 based on the data of the nodes 1061 and 1062. Further, the node 1063 is selected according to the description information of the next node, and the node 1063 is displayed after the nodes 1061 and 1062. In this way, the functional requirement of the next node can be predicted and the next node can be selected according to the established nodes in the workflow, thereby automatically establishing the next node to display to the user, without the user manually inputting the prompt word, improving the establishment efficiency of the workflow, and further improving the user experience.

[0029] It should be understood that the architecture and functions in the example environment 100 are described for illustrative purposes only, without implying any limitation on the scope of the present disclosure. Embodiments of the present disclosure can also be applied to other environments with different structures and / or functions.

[0030] The process according to the embodiments of the present disclosure will be described in detail below in combination with FIG. 2 to FIG. 6. For ease of understanding, the specific data mentioned in the following description are all exemplary and do not serve to limit the protection scope of the present disclosure. It should be understood that the embodiments described below can also include additional actions not shown and / or can omit the actions shown, and the scope of the present disclosure is not limited in this respect.

[0031] FIG. 2 shows a flowchart of a method 200 for displaying components of a workflow according to some embodiments of the present disclosure. In some embodiments, the method 200 can be performed by the client 102 in the example environment 100 shown in FIG. 1. In some embodiments, the client 102 includes but is not limited to a user terminal, a mobile device, a computer, etc. It should be understood that although the following is described with the client 102 as the performing subject, the method 200 can also be performed by other devices. The method 200 can also include additional actions not shown and / or can omit the actions shown, and the scope of the present disclosure is not limited in this respect.

[0032] At block 202, data of a first component that has been established is obtained in the process of establishing a workflow. In some embodiments, a user can establish a workflow in the client 102, and the workflow 106 includes a plurality of nodes 1061 and 1062 (both can be referred to as the first component) in the establishment process. The client 102 can obtain data of the nodes 1061 and 1062. The data of the nodes 1061 and 1062 may, for example, include description information of functional requirements of the nodes, configuration information for implementing the functional requirements, and logical information between the nodes, etc.

[0033] At block 204, description information related to a requirement of a second component is obtained, and the description information of the second component is generated by a target model based on the data of the first component. In some embodiments, the client 102 obtains the data of the nodes 1061 and 1062 and sends the data to the server 104 to enable the server 104 to call a language model 110 (which can be referred to as a target model) to process the data of the nodes 1061 and 1062, so as to analyze functional requirements of a next node (which can be referred to as a second component) and generate corresponding description information 108. The client 102 can receive the generated description information 108 from the server 104.

[0034] At block 206, the second component is displayed after the first component in the workflow based on the description information of the second component. In some embodiments, after the client 102 obtains the description information 108 of the next node, the client 102 can select the next node, i.e., the node 1063, according to the description information 108. Then, the client 102 displays the node 1063 after the nodes 1061 and 1062, so as to update the workflow 106 to obtain a workflow 106’.

[0035] In embodiments of the present disclosure, in the process of establishing a workflow, data of a node that has been established is first acquired. Then, according to the data of the node that has been established, description information of a functional requirement of a next node is acquired, where the description information of the next node is generated by a language model based on the data of the node that has been established. Further, the next node is selected according to the description information of the next node, and the next node is displayed after the node that has been established. In this way, the functional requirement of the next node can be predicted and the next node can be selected according to the node that has been established in the workflow, so that the next node can be automatically established and displayed to the user without manual input of a prompt word by the user. Therefore, the establishment efficiency of the workflow is improved, and the user experience is improved.

[0036] FIG. 3 shows a schematic diagram of a process 300 for updating a displayed workflow according to some embodiments of the present disclosure. In some embodiments, the process 300 can be performed by the client 102 and the server 104 in the example environment 100 shown in FIG. 1. In some embodiments, the client 102 includes, but is not limited to, a user terminal, a mobile device, a computer, etc., and the server 104 includes, but is not limited to, a computing system, a single server, a distributed server, or a cloud-based server, etc. It should be understood that although the following is described with the client 102 and the server 104 as the execution subject, the process 300 can also be performed by other devices. The process 300 can also include additional actions not shown and / or can omit the actions shown, and the scope of the present disclosure is not limited in this regard.

[0037] In some embodiments, the data of the node that has been established includes workflow description information 302 (which can be referred to as a plurality of description information of a plurality of first components), which can include, for example, the description information of the node 1061 and the description information of the node 1062 that have been established in FIG. 1. After the client 102 acquires the workflow description information 302, the workflow description information 302 is sent to the server 104. After the server 104 receives the workflow description information 302, the large language model 3061 is invoked to process the workflow description information 302, so as to predict the functional requirement of the next node and generate the description information 308 of the functional requirement. For example, the description information 308 of the next node can be “the plug-in of the next node should have map navigation ability or map planning ability, and can calculate the shortest commuting time or the fastest commuting time between two locations according to the input latitude and longitude information between the two locations”.

[0038] Then, the server 104 returns the description information 308 of the next node to the client 102. In this way, the server 104 can use the description information of the previously generated node as prior knowledge to predict the functional requirements of the next node, thereby improving the accuracy of the description information 308 of the next node. Moreover, it can also avoid directly operating on all the data in the established workflow, thereby reducing the computational load of the server 104 and the pressure of the client 102 to collect and transmit data.

[0039] Alternatively or additionally, the data of the established node can also include workflow building information 304, which can be, for example, the logical information between the node 1061 and the node 1062 in FIG. 1. When the server 104 invokes the large language model 3061 to predict the functional requirements of the next node, the workflow description information 302 and the workflow building information 304 can be combined to generate the description information 308 of the next node. In this way, the accuracy of the description information 308 of the next node can be further improved.

[0040] In some embodiments, the memory of the client 102 stores a candidate node set 310 (which can be referred to as a component set). The client 102 can search for a plurality of matched candidate nodes 312 (which can be referred to as a plurality of second components) in the candidate node set 310 according to the description information 308 of the next node. After searching for the plurality of matched candidate nodes 312, the client 102 sends the candidate nodes 312 to the server 104. After receiving the candidate nodes 312, the server 104 invokes the large language model 3062 to further select the next node 314 (such as the node 1063 in the example environment) from the plurality of candidate nodes 312 and returns the next node 314 to the client 102. After receiving the next node 314, the client 102 can display the next node 314 after the established node.

[0041] It should be noted that the large language model 3061 and the large language model 3062 in the present embodiment can be the same language model (which can be implemented as the language model 110), or two different language models, or two sub-models of the same language model (such as the language model 110). In the present embodiment, in the process of establishing the workflow in the client 102, the large language model 3062 can be used to further screen the candidate nodes 312 selected by the client 102 to obtain the next node 314, thereby improving the accuracy of the prediction of the nodes in the workflow, and further improving the success rate of the workflow execution.

[0042] In some embodiments, during the process of searching the candidate nodes 312 from the candidate node set 310 by the client 102, the client 102 can determine the text features of the description information 308 of the next node according to the description information 308, such as the keywords included in the description information 308. Then, according to the text features of the description information 308 and the text features of the nodes in the candidate node set 310, the similarity between the description information 308 of the next node and each node in the candidate node set 310 is determined respectively. Further, the client 102 can sort the calculated similarities, so as to select a plurality of candidate nodes 312 with higher similarities.

[0043] Alternatively or additionally, the client 102 can also use the vector features of the description information 308 of the next node to calculate the similarity between the description information 308 and the nodes in the candidate node set 310, and then select a plurality of candidate nodes 312 with higher similarities. In this way, the client 102 can select the candidate nodes 312 based on the text features or vector features of the description information 308 of the next node, so as to improve the accuracy of the candidate nodes 312, and further improve the accuracy of the next node prediction.

[0044] In some embodiments, after the server 104 selects the next node 314, the large language model 3062 can be continuously invoked to set the configuration information 316 for the next node 314 according to the description information 308 of the next node 314. For example, if the next node 314 is a code node, the server 104 can generate the code writing parameters of the code node. If the next node 314 is a large language model node, the server 104 can generate the prompt words of the large language model node. If the next node 314 is a SQL search node, the server 104 can generate the SQL search statement. In this way, the configuration efficiency of the nodes in the workflow can be improved during the establishment of the workflow.

[0045] Then, the server 104 sends the configuration information 316 to the client 102. The client 102 can display the configuration information 316 in the next node 314, so as to form the updated workflow 318. In some embodiments, before sending the configuration information 316 to the client 102, the server 104 can also perform parameter mapping on the configuration information 316 to associate the configuration information 316 with the current workflow establishment data.

[0046] To facilitate further understanding of the establishment process of the workflow, more specific embodiments of the workflow are provided below. FIG. 4A and FIG. 4B respectively show a schematic diagram of a pre-updated workflow 400A and a post-updated workflow 400B of some embodiments of the present disclosure, which may, for example, respectively implement the workflow 106 and the workflow 106’ in the example environment 100. In some embodiments, the workflow 400A is a workflow that has built part of the nodes, including a start node 402, an extract query node 404, an array node 406, a loop node 408, a search node 410, an extract search result node 412, and an update loop output node 414 (all of which can be referred to as the first components, i.e., the components that have been established).

[0047] It should be understood that each of the above nodes has description information for describing the functional requirements thereof, for example, the description information of the array node 406 is generated by the language model 110 based on the description information of the start node 402 and the description information of the extract query node 404, and the description information of the loop node 408 is generated by the language model 110 based on the description information of the start node 402, the description information of the extract query node 404, and the description information of the array node 406. Therefore, for the description information of the nodes after the update loop output node 414, the client 102 can send the description information of the update loop output node 414 and the description information of the nodes before it to the server 104, and the server 104 can invoke the language model 110 to predict the functional requirements of the next node and generate the corresponding description information according to the received description information.

[0048] Then, based on the description information of the nodes after the update loop output node 414, the client 102 can select a plurality of candidate nodes and send the plurality of candidate nodes to the server 104 for further screening by the server 104. Specifically, the server 104 can invoke the language model 110 to select the node that best meets the functional requirements from the plurality of candidate nodes, i.e., the generate report node 416 in the workflow 400B. Then, the server 104 sends the determined generate report node 416 to the client 102, and the client 102 can display the generate report node 416 after the update loop output node 414.

[0049] In some embodiments, in the process of determining the description information of the next node of the update loop output node 414, the structural information of the update loop output node 414 and the nodes before it can also be combined to determine the next position. As can be seen from FIG. 4B, according to the above structural information, it can be determined that the position of the next node should be outside the loop body instead of inside the loop body. In this way, the description content of the position of the next node can also be included in the description information of the next node, so that the final generate report node 416 is located outside the loop body of the loop node 408.

[0050] In some embodiments, configuration information is further included in the nodes of the workflow 400B, which can be as parameters to fulfill the functional requirements of the nodes. For example, in the extraction query node 404, a large language model needs to be invoked, then the language model 110 can configure the model type for the extraction query node 404 as “XXX4.2”, so that when the workflow executes the extraction query node 404, the XXX4.2 large language model can be invoked. In the loop node 408, for example, the language model 110 can define the index as “index=0” as the initial parameter of the loop body. The configuration parameters can refer to more specific parameters in FIG. 4B, which will not be described one by one in this embodiment.

[0051] After the server 104 selects the report generation node 416, configuration information can also be set for the report generation node 416 according to the description information of the report generation node 416. For example, in the report generation node 416, the model type can be set as “XXX4.2”, and the prompt word can be set as the content corresponding to the {loop_1>results} code, i.e., the final search result determined in the loop node 408. In this way, the server 104 can configure the parameters for the report generation node 416, so as to generate the final report by taking the search result as the prompt word of the language model XXX4.2.

[0052] FIG. 5 shows a block diagram of an apparatus 500 for displaying components of a workflow, according to some embodiments of the present disclosure. In some embodiments, the apparatus 500 includes a first component data acquisition module 502 configured to acquire data of a first component that has been established in a process of establishing a workflow. The apparatus 500 further includes a description information acquisition module 504 configured to acquire description information related to a requirement of a second component, the description information of the second component being generated by a target model based on the data of the first component. In addition, the apparatus 500 further includes a second component display module 506 configured to display the second component after the first component in the workflow based on the description information of the second component.

[0053] In some embodiments, the data of the first component includes a plurality of description information of a plurality of first components, and the description information acquisition module 504 is further configured to: send the plurality of description information of the plurality of first components to a server to enable the server to invoke the target model to generate the description information of the second component based on the plurality of description information of the plurality of first components; and receive the description information of the second component from the server.

[0054] In some embodiments, the second component display module 506 is further configured to: select the second component from a component set based on the description information of the second component; and display the selected second component after the first component in the workflow.

[0055] In some embodiments, the second component display module 506 is further configured to: select a plurality of second components in the component set based on the description information of the second component; send the description information of the second component and the plurality of second components to the server, so that the server invokes the target model to select the second component from the plurality of second components based on the description information of the second component; and receive the selected second component from the server.

[0056] In some embodiments, the second component display module 506 is further configured to: determine a feature of the description information of the second component, the feature of the description information of the second component comprising at least one of a text feature, a vector feature; determine a plurality of similarities between a plurality of components in the component set and the description information of the second component based on the feature of the description information of the second component; and select the plurality of second components based on the plurality of similarities.

[0057] In some embodiments, the second component display module 506 is further configured to: receive configuration information of the second component from the server, the configuration information of the second component being generated by the server invoking the target model based on the description information of the second component; and display the configuration information in the selected second component.

[0058] It can be understood that the apparatus 500 of the present disclosure can achieve at least one of the many advantages that the method or process as described above can achieve. For example, in the process of establishing the workflow, the apparatus 500 first acquires data of the already established node. Then, according to the data of the already established node, the description information of the next node is acquired, wherein the description information of the next node is generated by the target model based on the data of the already established node. Further, the next node is selected according to the description information of the next node, and the next node is displayed after the already established node. In this way, the functional requirements of the next node can be predicted and the next node can be selected according to the already established node in the workflow, so that the next node can be automatically established to be displayed to the user without the user manually inputting the prompt word, thereby improving the establishment efficiency of the workflow and further improving the user experience.

[0059] The present disclosure also provides another apparatus for displaying a component of a workflow. The apparatus comprises a first component data receiving module configured to receive data of a first component that has been established from a client, the data of the first component being acquired by the client in the process of establishing the workflow. The apparatus further comprises a description information generating module configured to generate description information related to a requirement of a second component by a target model based on the data of the first component. In addition, the apparatus further comprises a description information sending module configured to send the description information of the second component to the client, so that the client displays the second component after the first component in the workflow based on the description information of the second component.

[0060] In some embodiments, the data of the first component includes a plurality of description information of the plurality of first components, and the description information generation module is further configured to generate, by the target model, the description information of the second component based on the plurality of description information of the plurality of first components.

[0061] In some embodiments, the apparatus further includes a description information and second component receiving module configured to receive, from the client, the description information of the second component and a plurality of second components, the plurality of second components being selected by the client from the component set based on the description information of the second component; a second component selection module configured to select, by the target model, the second component from the plurality of second components based on the description information of the second component; and a second component sending module configured to send the selected second component to the client.

[0062] In some embodiments, the apparatus further includes a configuration information generation module configured to generate, by the target model, configuration information of the selected second component based on the description information of the second component; and a configuration information sending module configured to send the configuration information of the second component to the client to enable the client to display the configuration information in the selected second component.

[0063] FIG. 6 shows a schematic block diagram of an electronic device 600 according to some embodiments of the present disclosure. The electronic device 600 may, for example, be a processing unit of the client 102 or the server 104 as shown in FIG. 1. As shown in FIG. 6, the electronic device 600 includes a central processing unit (CPU) and / or a graphics processing unit (GPU) 601, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 602 or loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the electronic device 600 can also be stored in the RAM 603. The CPU / GPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604. Although not shown in FIG. 6, the electronic device 600 can also include a coprocessor.

[0064] A plurality of components in the electronic device 600 are connected to the I / O interface 605, including an input unit 606 such as a keyboard, a mouse, etc., an output unit 607 such as various types of displays, a speaker, etc., a storage unit 608 such as a magnetic disk, an optical disk, etc., and a communication unit 609 such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0065] The various methods or processes described above can be performed by the CPU / GPU 601. For example, in some embodiments, a method can be implemented as a computer software program tangibly embodied in a machine readable medium, such as the storage 608. In some embodiments, portions of the computer program or all of the computer program can be loaded onto the electronic device 600 via the ROM 602 and / or the communications unit 609. When a computer program is loaded onto the RAM 603 and executed by the CPU / GPU 601, one or more of the steps or actions of the methods or processes described above can be performed.

[0066] In some embodiments, the methods and processes described above can be tied to a computer program product. The computer program product can include a computer readable storage medium having computer readable program instructions tangibly embodied therein.

[0067] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or punched tape, a

[0068] The computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0069] Computer readable program instructions for carrying out operations of the present disclosure can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including object oriented programming languages and conventional procedural programming languages. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate array (FPGA), or programmable logic array (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0070] These computer readable program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks. These computer readable program instructions can also be stored in a computer readable storage medium that can include a non-transitory computer readable storage medium that can direct a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function / act specified in the flowchart and / or block diagram block or blocks.

[0071] The computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process such that the instructions which execute on the computer, other programmable data processing apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0072] The computer program product of the second aspect can include a computer readable storage medium. The computer readable storage medium can include instructions. The instructions can include one or both of: instructions for causing a computer to enable a user equipment device to receive a configuration message from a base station, the configuration message comprising an indication of a set of one or more parameters for a first type of hybrid automatic repeat request process, the first type of hybrid automatic repeat request process being associated with a first type of data; and instructions for causing a computer to enable a user equipment device to receive a configuration message from a base station, the configuration message comprising an indication of a set of one or more parameters for a first type of hybrid automatic repeat request process, the first type of hybrid automatic repeat request process being associated with a first type of data.

[0073] Embodiments of the present disclosure have been described above, with the understanding that these embodiments are exemplary only, and are not restrictive, and are not limited to the disclosed embodiments. Many modifications and changes to the described embodiments are possible, without departing from the scope and spirit of the described embodiments. The selection of terms to be used herein is intended to best explain the principles of the embodiments, practical application, or technical improvement over the technology in the market, or to enable other ordinary skilled persons in the art to understand the embodiments disclosed herein.

Claims

1. A method for displaying components of a workflow, comprising: acquiring data of a first component that has been established in a process of establishing the workflow; acquiring description information related to a requirement of a second component, the description information of the second component being generated by a target model based on the data of the first component; and displaying the second component after the first component in the workflow based on the description information of the second component. 2.The method of claim 1, wherein the data of the first component includes a plurality of description information of a plurality of first components, and the acquiring the description information related to the requirement of the second component comprises: sending the plurality of description information of the plurality of first components to a server to cause the server to invoke the target model to generate the description information of the second component based on the plurality of description information of the plurality of first components; and receiving the description information of the second component from the server. 3.The method of claim 1, wherein the displaying the second component after the first component in the workflow based on the description information of the second component comprises: selecting the second component in a component set based on the description information of the second component; and displaying the selected second component after the first component in the workflow. 4.The method of claim 3, wherein the selecting the second component in a component set based on the description information of the second component comprises: selecting a plurality of second components in the component set based on the description information of the second component; sending the description information of the second component and the plurality of second components to a server to cause the server to invoke the target model to select the second component among the plurality of second components based on the description information of the second component; and receiving the selected second component from the server. 5.The method of claim 4, wherein the selecting a plurality of second components in the component set based on the description information of the second component comprises: determining a feature of the description information of the second component, the feature of the description information of the second component including at least one of a text feature, a vector feature; determining a plurality of similarities between a plurality of components in the component set and the description information of the second component based on the feature of the description information of the second component; and selecting the plurality of second components based on the plurality of similarities. 6.The method of claim 4, wherein the displaying the second component after the first component in the workflow based on the description information of the second component comprises: receiving configuration information of the second component from a server, the configuration information of the second component being generated by the server invoking the target model based on the description information of the second component; and displaying the configuration information in the selected second component. 7.A method for displaying components of a workflow, comprising: receiving data of a first component that has been established from a client, the data of the first component being acquired by the client in a process of establishing the workflow; receiving configuration information of the second component from a server, the configuration information of the second component being generated by the server invoking the target model based on the description information of the second component; and displaying the configuration information in the selected second component. ​ ​ ​ ​ generating, by a target model, description information related to a requirement of a second component based on the data of the first component; and sending the description information of the second component to the client to enable the client to display the second component after the first component in the workflow based on the description information of the second component.

8. The method of claim 7, wherein the data of the first component comprises a plurality of description information of a plurality of first components, and generating, by a target model, description information related to a requirement of a second component based on the data of the first component comprises: generating, by the target model, the description information of the second component based on the plurality of description information of the plurality of first components.

9. The method of claim 7, further comprising: receiving, from the client, the description information of the second component and a plurality of second components, the plurality of second components being selected by the client in a component set based on the description information of the second component; selecting, by the target model, the second component in the plurality of second components based on the description information of the second component; and sending the selected second component to the client.

10. The method of claim 9, further comprising: generating, by the target model, configuration information of the selected second component based on the description information of the second component; and sending the configuration information of the second component to the client to enable the client to display the configuration information in the selected second component.

11. An apparatus for displaying components of a workflow, comprising: a first component data obtaining module configured to obtain data of a first component that has been established in a process of establishing the workflow; a description information obtaining module configured to obtain description information related to a requirement of a second component, the description information of the second component being generated by a target model based on the data of the first component; and a second component displaying module configured to display the second component after the first component in the workflow based on the description information of the second component.

12. An apparatus for displaying components of a workflow, comprising: a first component data receiving module configured to receive data of a first component that has been established from a client, the data of the first component being obtained by the client in a process of establishing the workflow; a description information generating module configured to generate, by a target model, description information related to a requirement of a second component based on the data of the first component; and a description information sending module configured to send the description information of the second component to the client to enable the client to display the second component after the first component in the workflow based on the description information of the second component.

13. An electronic device, comprising: a processor; and a memory coupled with the processor, the memory having instructions stored therein that, when executed by the processor, cause the electronic device to perform the method of any of claims 1-6 or 7-10. ​ ​ ​ ​ ​ ​ 14. A computer program product, the computer program product being tangibly stored on a non-transient computer readable medium and comprising machine executable instructions that, when executed, cause a machine to implement the method of any one of claims 1 to 6 or claims 7 to 10.

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