A service flow configuration method, device and equipment and storage medium

Abstract

The application discloses a kind of service process configuration method, device, equipment and storage medium, it is related to machine learning technical field.The method includes providing a process configuration interface, it includes process configuration control, in response to process configuration control triggered process configuration operation, determine the business process graph corresponding to target service, business process graph includes multiple model nodes and connecting line.Subsequently according to the first attribute information of each model node, determine multiple target models, and according to the connection attribute information of each connecting line, determine the data processing time sequence between multiple target models.Finally, according to data processing time sequence, the plurality of target models are spliced, and the business model service corresponding to target service is determined.The process configuration of target service is carried out through visual process configuration interface, and when business processing process changes, reconfiguration is carried out by replacing model, applicable in the fast iteration business scene, and the development cycle of business model service can be reduced.

Description

Technical Field

[0001] This invention relates to the field of machine learning technology, and in particular to a business process configuration method, apparatus, device, and storage medium. Background Technology

[0002] As the application of artificial intelligence technology in the industrial field matures, different business operations may need to utilize multiple machine learning-based models. However, existing business models for different business operations are often incompatible, leading to different business departments needing to build their own business architectures and corresponding business models for different application scenarios, significantly reducing the development efficiency of business applications. Summary of the Invention

[0003] In view of the above problems, the present invention is proposed to provide a business process configuration method, apparatus, device and storage medium that overcomes or at least partially solves the above problems.

[0004] According to a first aspect of the present invention, a business process configuration method is provided, the method comprising:

[0005] A process configuration interface is provided, which includes process configuration controls and process editing controls;

[0006] In response to a process configuration operation triggered by the process configuration control, a business processing flowchart corresponding to the target business is determined. The business processing flowchart includes multiple model nodes and connecting lines, which are generated in response to a process editing operation triggered by the process editing control.

[0007] Multiple target models are determined based on the first attribute information of each model node, and the data processing sequence between multiple target models is determined based on the connection attribute information of each connection line.

[0008] Multiple target models are concatenated according to the data processing sequence to determine the business model service corresponding to the target business.

[0009] According to a second aspect of the present invention, a business process configuration apparatus is provided, the apparatus comprising:

[0010] The interface configuration module is used to provide a process configuration interface, which includes model editing controls and component editing controls.

[0011] The flowchart determination module is used to determine the business processing flowchart corresponding to the target business in response to the process configuration operation triggered by the process configuration control. The business processing flowchart includes multiple target nodes and multiple connecting lines, and the target nodes and connecting lines are generated in response to the process editing operation triggered by the process editing control.

[0012] The attribute information determination module is used to determine multiple target models based on the first attribute information of each model node, and to determine the data processing sequence between multiple target models based on the connection attribute information of each connection line.

[0013] The service determination module is used to concatenate multiple target models according to the data processing sequence to determine the business model service corresponding to the target business.

[0014] This invention provides a business process configuration method. The method includes providing a process configuration interface, which includes process configuration controls. Responding to a process configuration operation triggered by the process configuration controls, a business processing flowchart corresponding to a target business is determined. The business processing flowchart includes multiple model nodes and connecting lines. Subsequently, multiple target models are determined based on the first attribute information of each model node, and the data processing sequence between the multiple target models is determined based on the connection attribute information of each connecting line. Finally, the multiple target models are concatenated according to the data processing sequence to determine the business model service corresponding to the target business. Therefore, the process configuration of a target business can be quickly performed through a visual process configuration interface. When the business processing flow changes, only the corresponding model needs to be replaced to reconfigure the business processing flow. This method is applicable to rapidly iterating business scenarios and significantly reduces the development cycle of the corresponding business model service.

[0015] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0017] In the attached diagram:

[0018] Figure 1 This is a flowchart of the steps of a business process configuration method provided in an embodiment of the present invention;

[0019] Figure 2 This is a flowchart of another business process configuration method provided in an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of creating a business processing flowchart in a process configuration interface, provided by an embodiment of the present invention;

[0021] Figure 4 This is a flowchart illustrating the steps of an online evaluation method for business call services provided in an embodiment of the present invention.

[0022] Figure 5 This is a block diagram of a business process configuration device provided in an embodiment of the present invention. Detailed Implementation

[0023] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0024] Reference Figure 1 This diagram illustrates a flowchart of a business process configuration method provided by an embodiment of the present invention, applied to a server. The method may include:

[0025] S101. Provide a process configuration interface, which includes process configuration controls and process editing controls.

[0026] S102. In response to the process configuration operation triggered by the process configuration control, determine the business processing flowchart corresponding to the target business, wherein the business processing flowchart includes multiple model nodes and connecting lines, and the model nodes and connecting lines are generated in response to the process editing operation triggered by the process editing control.

[0027] In this embodiment of the invention, model nodes and connecting lines can be generated based on the user's workflow editing operations on the workflow editing control. Multiple model nodes and connecting lines connecting these nodes are determined based on multiple workflow editing operations by the user, ultimately forming the business processing diagram corresponding to the target business. After the business processing flowchart of the target business is drawn, the user can initiate workflow configuration for the target business by clicking on the workflow configuration control. The server responds to the workflow configuration operation triggered by the workflow configuration control, obtaining the processing flowchart corresponding to the target business. This business processing flowchart represents the complete data processing logic of the corresponding target business.

[0028] S103. Based on the first attribute information of each model node, determine multiple target models, and based on the connection attribute information of each connecting line, determine the data processing sequence between the multiple target models.

[0029] S104. Multiple target models are spliced ​​together according to the data processing sequence to determine the business model service corresponding to the target business.

[0030] In this embodiment of the invention, during the generation of model nodes and connecting lines, the user can also configure the first attribute information of the model nodes and the connection attribute information of the connecting lines based on the process editing control. The first attribute information may include the model type and model version number, which is used to determine the specific target model. The connection attribute information includes the direction information of the connecting lines, which is used to determine the data flow direction between the two nodes forming the connection. Therefore, multiple target models can be determined based on the first attribute information of each model node, and the data processing sequence between the multiple target models can be determined based on the connection attribute information of each connecting line. Following this data processing sequence, the multiple target models are concatenated to determine the business model service corresponding to the target business.

[0031] In one example, target model A and target model B are connected by a connecting line. Based on the connection attribute information of the corresponding connecting line, it is determined that the data processed by target model A will be input into target model B for further processing. Therefore, when concatenating target models A and B, the data output of target model A is connected in series with the data input of target model B. This process continues to determine the business model service corresponding to the target business. Thus, the process configuration of the target business can be quickly performed through a visual process configuration interface. When the business processing flow changes, only the corresponding business model needs to be replaced to reconfigure the business processing flow. This is suitable for rapidly iterating business scenarios and significantly reduces the development cycle of the corresponding business model service.

[0032] Reference Figure 2 The diagram illustrates a flowchart of another business process configuration method provided by an embodiment of the present invention, the method including:

[0033] S201. Provide a process configuration interface, which includes process configuration controls and process editing controls.

[0034] S202. In response to the process configuration operation triggered by the process configuration control, determine the business processing flowchart corresponding to the target business, wherein the business processing flowchart includes multiple model nodes, multiple composite nodes, multiple component nodes and connecting lines, and the model nodes, composite nodes, component nodes and connecting lines are generated in response to the process editing operation triggered by the process editing control.

[0035] In this embodiment of the invention, based on the user's workflow editing operations on the workflow editing control, model nodes, composite nodes, component nodes, and connecting lines can be generated. Furthermore, based on multiple workflow editing operations by the user on the workflow editing control, multiple model nodes, composite nodes, component nodes, and connecting lines connecting two nodes are determined, forming a business processing diagram corresponding to the target business.

[0036] In one example, referencing Figure 3 As shown, the process editing control includes model controls, combination controls, component controls, and connection controls. Based on the user's selection of the model controls, corresponding model nodes are generated, and the first attribute information of the model nodes is configured. This first attribute information is used to determine the specific target model. It may include model type and model version number. During the configuration of the first attribute information, the model type can be determined by selecting the model types displayed in the type control, and the model version number can be determined by selecting the version numbers displayed in the version number control. The model type can be obtained by classifying the model according to its structure, and may include CNN (Convolutional Neural Networks), GNN (Graph Neural Networks), KNN (K-Nearest Neighbor), etc., without limitation. The model version number is used to distinguish models belonging to the same model type but differing in model parameters, etc. The connection attribute information includes the direction information of the connection lines, which is used to determine the data flow direction between the two nodes forming the connection.

[0037] Following the same logic, based on the user's selection of the combined controls, a corresponding combined node is generated, and the second attribute information of the combined node is configured. This second attribute information is used to determine the logical combination method between multiple target models. The logical combination method can be one of the following two: model fusion method and conditional judgment method.

[0038] When the logical combination method is a model fusion method, it means that the data output end of the combination node is connected to the data input ends of multiple model nodes. The corresponding processing logic is that multiple target models process the data output by the target models corresponding to the model nodes connected to the data input ends of the combination node. The processed data output by multiple target models are then combined to form new data for further processing. When the logical combination method is a conditional judgment method, it means that one of the multiple model nodes located at the data output end of the combination node needs to be selected to perform the corresponding data processing.

[0039] In real-world business applications, such as marketing recommendations, risk control, and operational scheduling, a single target business is often accomplished through the collaborative efforts of multiple sub-businesses. For instance, when the target business is vehicle operational scheduling, it may involve sub-businesses such as route planning, driver matching, and risk assessment to determine whether drivers are involved in fraudulent order placement.

[0040] Therefore, different business tags are used to distinguish different business application scenarios, and multiple components can be predefined for each business application scenario, such as through coding or other middleware methods, to generate pluggable, connectable components. For example, the business components corresponding to each business may include feature preprocessing components, feature selection components, result processing components, and feature library components. These multiple components corresponding to each business are stored in a component library according to different business tags. In one embodiment, multiple business components can also be divided according to component categories. These component categories may include preprocessing and result processing categories. Preprocessing business components are used to preprocess the business data input into the target model, and can be appended to the data input end of the corresponding model node during the concatenation process. Preprocessing may include business data transformation, filtering, and other steps. Similarly, result processing business components are used to post-process the business data output from the target model, and can be appended to the data output end of the corresponding model node during the concatenation process. Post-processing may include business result transformation and other steps.

[0041] In response to a selection operation of the various business components displayed in the component control, the corresponding business component is determined, and the third attribute information of the component node is configured based on this business component. Thus, the third attribute information may include the corresponding business tag and component category.

[0042] S203. Based on the first attribute information of each model node, multiple target models are determined.

[0043] S204. Based on the second attribute information of each combination node, determine the logical combination method between multiple target models.

[0044] S205. Based on the third attribute information of each component node, determine the multiple business components corresponding to the target business.

[0045] S206. Based on the connection attribute information of each connection line, determine the data processing sequence between multiple target models and multiple business components.

[0046] S207. According to the data processing sequence and logical combination method, multiple target models and multiple business components are spliced ​​together to determine the business model service corresponding to the target business.

[0047] In this embodiment of the invention, after determining the business processing flowchart corresponding to the target business, the server can determine multiple target models based on the model type and model version number in the first attribute information of each model node. Based on the second attribute information of each combination node, the logical combination method between the multiple target models is determined. Based on the third attribute information of each component node, multiple business components corresponding to the target business are determined. And based on the connection attribute information of each connection line, the data processing sequence between the multiple target models and the multiple business components is determined. Finally, the multiple target models and multiple business components are concatenated according to the data processing sequence and logical combination method.

[0048] During the splicing process, for example, when it is determined that the data input ends of target model A and target model B are simultaneously connected to the combined node a via connecting lines, and the logical combination method corresponding to the combined node is a conditional judgment method, a judgment module matching the conditional judgment method is connected to the data input ends of target model A and target model B. Thus, during the data processing of the target business, the judgment module determines whether to input the data processed by the previous node into target model A or target model B for the next processing step. Therefore, the target business process can be quickly configured through a visual process configuration interface. When the business processing flow changes, only the corresponding business model needs to be replaced to reconfigure the business processing flow. This is applicable to rapidly iterating business scenarios and significantly reduces the development cycle of the corresponding business model service. On the other hand, since the business components corresponding to the target business are directly spliced ​​into the corresponding business model service, they do not require data preprocessing and post-processing for different business scenarios. Therefore, the business model service is a complete service call chain that can be directly used by online businesses.

[0049] In an optional embodiment of the invention, the method may further include:

[0050] Receive model files.

[0051] Based on the model file, determine the model type and model version number of the corresponding model.

[0052] A model management list is generated based on the model type and model version number.

[0053] The model management list is rendered and displayed.

[0054] In this embodiment of the invention, the user uploads the model file corresponding to the trained model to the server. After receiving the model file, the server stores it, for example, by pre-setting a model library and storing the model file in the library. In one embodiment, a naming rule for the model file can be pre-set, thereby automatically identifying the model type and model version number corresponding to the model file based on the detection of the model file's filename. In another embodiment, the process configuration interface also includes a type creation control and / or a model version number creation control, allowing the user to edit the corresponding model type and / or model version number based on the type creation control and / or model version number creation control. Responding to the attribute editing operation triggered by the type creation control and / or model version number creation control, the server determines the model-related information corresponding to the model, which includes at least the model type and model version number.

[0055] Based on the model type and model version number, a model management list is generated. The server renders the model management list and displays it on the process configuration interface. In one embodiment, the type control displays each model type, and the version number control displays each version number of the corresponding model type, thereby determining the corresponding target model in response to the user's selection.

[0056] In another embodiment, it is considered that a target business is often completed through the collaborative efforts of multiple sub-businesses. For example, when the target business is vehicle operation and dispatching, it may involve sub-businesses such as route planning, driver matching, and risk assessment of whether drivers are involved in malicious order fraud. Correspondingly, if a business process flowchart is configured all at once, the corresponding user operation steps will be cumbersome and time-consuming. Therefore, multiple models can be pre-combined according to the business process flow corresponding to each sub-business. The first processing flow refers to the logical steps followed by the sub-business when processing business data. This allows the generation of model sets corresponding to each sub-business, where each model set can completely complete the first processing flow of the corresponding sub-business in terms of business processing logic.

[0057] Correspondingly, the first attribute information of the model node may also include business tags corresponding to each sub-business. During the configuration of the first attribute information, the business tags can be determined by clicking on a set control displaying different business tags. Pre-setting the model sets corresponding to the sub-businesses can avoid situations where the target business has complex business processing logic, leading to confusion in the combination of target models. For example, during the process of assembling a business model service, the model set corresponding to the sub-business can be matched using the business tags in the first attribute information of the model node. Then, according to the data processing sequence and logical combination method, multiple target models, model sets, and multiple business components are assembled to determine the business model service corresponding to the target business.

[0058] In one optional embodiment of the invention, the method may further include:

[0059] S401. In response to the architecture editing operation triggered by the architecture editing control, determine the service architecture information of the business model service.

[0060] S402. In response to the interface editing operation triggered by the interface editing control, determine the language call interface corresponding to the business model service.

[0061] S403. Based on the service architecture information and language call interface, deploy the business model service as an instance to obtain the business call service corresponding to the target business.

[0062] In this embodiment of the invention, after the business model service is determined, it can be quickly deployed as an instance to become a business invocation service on the target business line. Instance deployment may include steps such as service instantiation, service architecture deployment, and service invocation language deployment. For example, the business configuration interface also includes an architecture editing control and an interface editing control. Users can perform click operations on the service architecture information displayed in the architecture editing control and the language invocation interface displayed in the interface editing control. The server responds to the control editing operations triggered by the architecture editing control and the interface editing control, and can determine the service architecture information and language invocation interface corresponding to the business model service. The service architecture information refers to the target architecture type to be converted for the business model service, which may include REST, GRPC, Dubbo, Thrift, etc. The language invocation interface refers to the target language interface that supports calling the business model service. Corresponding language interfaces may include multiple language interfaces such as Java, C++, Python, and Golang, thereby accommodating different technical systems of different business teams, facilitating rapid configuration and deployment of online services, and greatly increasing the flexibility of business process configuration. Based on the service architecture information and language call interface, the business model service is instantiated to obtain a business call service that can be directly called by the business side.

[0063] S404. Collect the service response data of the service call, evaluate the service response data, and determine the corresponding service evaluation result.

[0064] In this embodiment of the invention, when the business call service is invoked by an online business terminal, the online service evaluation of the business call service can also be performed in real time. For example, appropriate evaluation indicators can be selected in advance from the indicator library to evaluate the service, thereby obtaining the service evaluation result. The evaluation indicators may include indicators such as ROC and AUC.

[0065] S405. If the service evaluation results meet the service optimization conditions, obtain training sample data.

[0066] S406. Based on the training sample data, adjust the parameters of the service call to determine the completed service call.

[0067] In this embodiment of the invention, the service evaluation result can be used to determine whether the business call service needs optimization. For example, service optimization conditions can be preset. If the service evaluation result does not meet the service optimization conditions, the business response data of the business call service can continue to be collected and evaluated. If the service evaluation result meets the service optimization conditions, it is determined that the target model involved in the business call service needs parameter adjustment. Training sample data is obtained, wherein the training sample data is pre-labeled with sample tags. The training sample data is input into the business call service for processing to obtain the business response data corresponding to the training sample data. The business response data corresponding to the training sample data is evaluated using the evaluation indicators. Finally, the service evaluation result corresponding to the training sample data is used to tune the parameters of the business call service, for example, adjusting the model parameters involved in the business call service, thereby determining the successfully trained business call service.

[0068] In one example, users can choose a suitable sample collector or code a custom collector to collect online business data corresponding to the target business in real time using methods such as sampling, full collection, and timed collection, and add it to the sample library. The online business data can include business request data and business response data. If the service evaluation results meet the service optimization conditions, the online business data in the sample library can be quickly imported into the training sample library to supplement training and testing samples. Thus, the server can obtain training sample data by querying the training sample library, providing a guarantee for optimizing the service calls of the target business.

[0069] In one optional embodiment of the invention, the method may further include:

[0070] Monitor the resource utilization of the service called by the business.

[0071] If the resource utilization rate reaches the load threshold, the service call will be replicated.

[0072] Distribute the copied business call services to other servers.

[0073] If multiple service calls corresponding to the target service are all running, and the resource utilization rate reaches a combined threshold condition, the number of service calls will be reduced.

[0074] In this embodiment of the invention, since the business call service is directly invoked by the business end, it is a computationally intensive task. To improve the utilization of computing resources, GPU resources can be rationally partitioned and scheduled. For example, the business call service includes Kubernetes-based auto-scaling capabilities. The resource utilization of the business call service is monitored. The resource utilization can be understood as the utilization rate and / or load rate of GPU resources. When the business call volume increases, and the resource utilization reaches a load-sharing threshold, for example, a resource utilization equal to or greater than 80%, the business call service can be replicated. For example, three additional business call services can be replicated, and each business call service can be assigned to a different server. This allows four business call services to be run simultaneously using the GPU resources of four servers to handle the business call volume, improving business response speed and distributing the computational load. Similarly, if the call volume is low, using multiple servers to run multiple business call services would consume excessive computing resources. Therefore, when resource utilization reaches a combined threshold condition, such as the cumulative resource utilization of GPU resources on each server, and the cumulative resource utilization is equal to or less than 70%, if four business call services are running at this time, one or two of the business call services can be stopped. This automatically reduces the number of business call services to a reasonable range, reducing computing resource consumption.

[0075] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of this application.

[0076] Reference Figure 5 This illustration shows a business process configuration device provided by an embodiment of the present invention, the device may include:

[0077] The interface configuration module 501 is used to provide a process configuration interface, which includes model editing controls and component editing controls.

[0078] The flowchart determination module 502 is used to determine the business processing flowchart corresponding to the target business in response to the process configuration operation triggered by the process configuration control. The business processing flowchart includes multiple target nodes and multiple connecting lines, which are generated in response to the process editing operation triggered by the process editing control.

[0079] The attribute information determination module 503 is used to determine multiple target models based on the first attribute information of each model node, and to determine the data processing sequence between multiple target models based on the connection attribute information of each connection line.

[0080] The service determination module 504 is used to concatenate multiple target models according to the data processing sequence to determine the business model service corresponding to the target business.

[0081] In an optional embodiment of the invention, the business processing flowchart further includes multiple combined nodes, and the attribute information determination module 503 may include:

[0082] The target model determination submodule is used to determine multiple target models based on the first attribute information of each model node.

[0083] The combination method determination submodule is used to determine the logical combination method between multiple target models based on the second attribute information of each combination node. The logical combination method includes model fusion method and condition judgment method.

[0084] The timing determination submodule is used to determine the data processing timing between multiple target models based on the connection attribute information of each connection line.

[0085] In an optional embodiment of the invention, the service determination module 504 may be used to:

[0086] According to the data processing sequence and logical combination method, multiple target models are spliced ​​together to determine the business model service corresponding to the target business.

[0087] In an optional embodiment of the invention, the business processing flowchart further includes multiple component nodes, and the processing timing determination submodule may include:

[0088] The business component determination unit is used to determine multiple business components corresponding to the target business based on the third attribute information of each component node. The business components include the following component categories: preprocessing class and result processing class.

[0089] The processing timing determination unit is used to determine the data processing timing between multiple target models and multiple business components based on the connection attribute information of each connection line.

[0090] In an optional embodiment of the invention, the service determination module 504 may further be used for:

[0091] According to the data processing sequence and logical combination method, multiple target models and multiple business components are spliced ​​together to determine the business model service corresponding to the target business.

[0092] In an optional embodiment of the invention, the process configuration interface further includes an architecture editing control and an interface editing control, and the device may further include:

[0093] The architecture information determination module is used to determine the service architecture information of the business model service in response to the architecture editing operation triggered by the architecture editing control.

[0094] The interface call determination module is used to determine the language call interface corresponding to the business model service in response to the interface editing operation triggered by the interface editing control.

[0095] The service invocation determination module is used to deploy instances of the business model service based on the service architecture information and language invocation interface to obtain the business invocation service corresponding to the target business.

[0096] In an optional embodiment of the invention, the service invocation determination module may further include:

[0097] The service call determination submodule is used to deploy instances of the business model service based on the service architecture information and language call interface to obtain the business call service corresponding to the target business.

[0098] The evaluation result determination submodule is used to collect the service response data of the service call, evaluate the service response data, and determine the corresponding service evaluation result.

[0099] The sample data acquisition submodule is used to acquire training sample data when the service evaluation results meet the service optimization conditions.

[0100] The service parameter tuning submodule is used to tune the parameters of the business call service based on the training sample data, and determine the business call service that has been trained.

[0101] In summary, the present invention provides a business process configuration device. The device includes a process configuration interface with process configuration controls. Responding to a process configuration operation triggered by the process configuration controls, a business processing flowchart corresponding to a target business is determined. The business processing flowchart includes multiple model nodes and connecting lines. Subsequently, multiple target models are determined based on the first attribute information of each model node, and the data processing sequence between the multiple target models is determined based on the connection attribute information of each connecting line. Finally, the multiple target models are concatenated according to the data processing sequence to determine the business model service corresponding to the target business. Therefore, the process configuration of a target business can be quickly performed through a visual process configuration interface. When the business processing flow changes, only the corresponding model needs to be replaced to reconfigure the business processing flow. This is applicable to rapidly iterating business scenarios and significantly reduces the development cycle of the corresponding business model service.

[0102] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0103] It will be readily apparent to those skilled in the art that any combination of the above embodiments is feasible, and therefore any combination of the above embodiments is an implementation scheme of the present invention. However, due to space limitations, this specification will not describe them in detail here.

[0104] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0105] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various inventive aspects, features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the above description of exemplary embodiments of the invention. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than expressly recited in each claim. Rather, as reflected in the claims, inventive aspects lie in fewer than all features of the single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0106] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0107] An electronic device, comprising:

[0108] One or more processors;

[0109] Memory;

[0110] One or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs being configured to perform the methods described in the above embodiments.

[0111] A computer-readable storage medium stores a computer program for use in conjunction with an electronic device, the computer program being executable by a processor to perform the methods described in the embodiments above.

[0112] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0113] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0114] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0116] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0117] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0118] The above provides a detailed description of a business process configuration method and a business process configuration device provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A business process configuration method, characterized in that, The method includes: A process configuration interface is provided, which includes process configuration controls and process editing controls; In response to a process configuration operation triggered by the process configuration control, a business processing flowchart corresponding to the target business is determined. The business processing flowchart includes multiple model nodes and connecting lines, which are generated in response to a process editing operation triggered by the process editing control. Multiple target models are determined based on the first attribute information of each model node, and the data processing sequence between multiple target models is determined based on the connection attribute information of each connection line. Multiple target models are spliced ​​together according to the data processing sequence to determine the business model service corresponding to the target business. The business processing flowchart further includes multiple combination nodes. The process involves determining multiple target models based on the first attribute information of each model node, and determining the data processing sequence between the multiple target models based on the connection attribute information of each connecting line, including: Based on the first attribute information of each model node, multiple target models are determined; Based on the second attribute information of each combination node, the logical combination method between multiple target models is determined, and the logical combination method includes model fusion method and condition judgment method; Based on the connection attribute information of each connecting line, the data processing sequence between multiple target models is determined; The model fusion method includes connecting the data output terminal of the combined node to the data input terminals of multiple model nodes; The multiple target models process the input data to obtain multiple output data; The multiple output data are combined to form new data.

2. The business process configuration method according to claim 1, characterized in that, The step of concatenating multiple target models according to the data processing sequence to determine the business model service corresponding to the target business includes: According to the data processing sequence and logical combination method, multiple target models are spliced ​​together to determine the business model service corresponding to the target business.

3. The business process configuration method according to claim 1, characterized in that, The business processing flowchart also includes multiple component nodes. The determination of the data processing sequence between multiple target models based on the connection attribute information of each connection line includes: Based on the third attribute information of each component node, multiple business components corresponding to the target business are determined. The business components include the following component categories: preprocessing class and result processing class. Based on the connection attribute information of each connection line, the data processing sequence between multiple target models and multiple business components is determined.

4. The business process configuration method according to claim 2, characterized in that, The step of concatenating multiple target models according to the data processing sequence and logical combination method to determine the business model service corresponding to the target business includes: According to the data processing sequence and logical combination method, multiple target models and multiple business components are spliced ​​together to determine the business model service corresponding to the target business.

5. The business process configuration method according to claim 1, characterized in that, The process configuration interface also includes architecture editing controls and interface editing controls, and the method further includes: In response to the architecture editing operation triggered by the architecture editing control, the service architecture information of the business model service is determined; In response to the interface editing operation triggered by the interface editing control, determine the language call interface corresponding to the business model service; Based on the service architecture information and language call interface, the business model service is deployed as an instance to obtain the business call service corresponding to the target business.

6. The business process configuration method according to claim 5, characterized in that, The step of deploying instances of the business model service based on the service architecture information and language call interface to obtain the business call service corresponding to the target business includes: Collect the service response data of the service call, evaluate the service response data, and determine the corresponding service evaluation result; If the service evaluation results meet the service optimization criteria, obtain training sample data; Based on the training sample data, the parameters of the business call service are adjusted to determine the business call service that has been trained.

7. A business process configuration device, characterized in that, The device includes: The interface configuration module is used to provide a process configuration interface, which includes process configuration controls and process editing controls. The flowchart determination module is used to determine the business processing flowchart corresponding to the target business in response to the process configuration operation triggered by the process configuration control. The business processing flowchart includes multiple model nodes and connecting lines, which are generated in response to the process editing operation triggered by the process editing control. The attribute information determination module is used to determine multiple target models based on the first attribute information of each model node, and to determine the data processing sequence between multiple target models based on the connection attribute information of each connection line. The service determination module is used to concatenate multiple target models according to the data processing sequence to determine the business model service corresponding to the target business. The business processing flowchart further includes multiple combined nodes, and the attribute information determination module includes: The target model determination submodule is used to determine multiple target models based on the first attribute information of each model node; The combination method determination submodule is used to determine the logical combination method between multiple target models based on the second attribute information of each combination node. The logical combination method includes model fusion method and condition judgment method. The processing timing determination submodule is used to determine the data processing timing between multiple target models based on the connection attribute information of each connection line; The model fusion method includes connecting the data output terminal of the combined node to the data input terminals of multiple model nodes; The multiple target models process the input data to obtain multiple output data; The multiple output data are combined to form new data.

8. An electronic device, comprising: One or more processors; Memory; One or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs being configured to perform the method of any one of claims 1-6.

9. A computer-readable storage medium storing a computer program for use in conjunction with an electronic device, said computer program being executable by a processor to perform the method of any one of claims 1-6.

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