A method and device for rapid abstract modeling of business applications

Abstract

The present invention relates to the technical field of automatic business processing, and is a method and device for rapid abstract modeling of business applications, comprising: determining the business application domain of the business to be modeled, obtaining a business abstract application library based on the business application domain, constructing a target business application group based on the business abstract application library and application scenarios, arranging a business scenario application model based on the target business application group, utilizing the business scenario application model to obtain a business execution result, performing intelligent analysis on the business execution result based on a case library and a large language model to obtain an executable confidence level, manually correcting the business execution result to obtain a business correction result, and recording the business correction result as an executable result, obtaining a current case based on original business data, and adding the current case to the case library. The present invention can improve the intelligence and flexibility of business processing and improve the efficiency of business processing.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic business processing, and in particular to a method and device for rapid abstract modeling of business applications. Background Art

[0002] With the diversified development of financial business scenarios, the operational paths of business personnel are becoming increasingly complex. For some frequently occurring business processing processes, it is hoped that the system will be used for automation and to assist business personnel in locating process risks.

[0003] In traditional solutions, business personnel need to sort out the business processes for automation, describe them using BPMN and other methods, and deploy them to the workflow engine. Necessary business rules also need to be coded and embedded in the BPMN process. Since BPMN describes business flows closer to technical implementation, the element symbols it contains are difficult for business personnel to understand. BPMN emphasizes neat process paths and predefined rules, but there are a large number of unstructured scenarios in real business. At the same time, the background service nodes of this method have almost no business display capabilities, which means that the intelligence and flexibility of this method need to be improved, and the automation tasks of this method are executed inefficiently in the workflow engine. Summary of the Invention

[0004] The present invention provides a method and device for rapid abstract modeling of business applications, the main purpose of which is to improve the intelligence and flexibility of business processing and improve the efficiency of business processing.

[0005] To achieve the above objectives, the present invention provides a method for rapid abstract modeling of business applications, comprising:

[0006] Receive application modeling instructions, and determine the business to be modeled and original business data based on the application modeling instructions;

[0007] Determine the business application domain of the business to be modeled, and obtain a business abstract application library based on the business application domain, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is set with a parameter interface;

[0008] Dividing the business to be modeled into business units to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface;

[0009] Based on the business abstract application library and the unit business group, a valid business application group is constructed, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library;

[0010] Determine the application scenario of the business to be modeled, and based on the application scenario, perform exclusive parameter setting on the valid business application group to obtain the target business application group;

[0011] Orchestrate business scenario application models based on target business application groups;

[0012] Perform business automation processing based on original business data and business scenario application models to obtain business execution results;

[0013] Based on a pre-built case library, intelligent analysis is performed on the business execution results to obtain an executable confidence level, wherein the intelligent analysis refers to analysis using a large language model;

[0014] If the executable confidence is not greater than the confidence threshold, manually correcting the business execution result to obtain a business correction result, and recording the business correction result as an executable result;

[0015] If the confidence level of the business execution is greater than the confidence threshold, the business execution result is recorded as an executable result;

[0016] Based on the original business data and the executable results, case data is merged to obtain the current case, and the current case is added to the case library to complete the rapid abstract modeling of the business application.

[0017] Optionally, obtaining a business abstract application library based on the business application field includes:

[0018] Constructing a business application process of the business application field, wherein the business application process includes a plurality of business process nodes;

[0019] Extracting business process nodes in sequence from a plurality of business process nodes of a business application process, defining node interfaces of the business process nodes, and obtaining programmable business nodes, wherein the node interfaces include: an input parameter interface and an output parameter interface;

[0020] Performing application development on the programmable service node to obtain a service abstract application, wherein the application development includes language programming;

[0021] The business abstract applications are aggregated to obtain a business abstract application library.

[0022] Optionally, constructing a valid business application group based on the business abstract application library and the unit business group includes:

[0023] Extracting unit businesses in the unit business group in sequence and determining flow data of the unit businesses, wherein the flow data includes: input data and output data;

[0024] Based on the flow data, determine whether there is a business abstract application matching the unit's business in the business abstract application library;

[0025] If there is a business abstract application matching the unit's business in the business abstract application library, extract the public business application from the business abstract application library;

[0026] If there is no business abstract application matching the unit business in the business abstract application library, then construct a proprietary business application for the unit business;

[0027] The public business applications or proprietary business applications are aggregated to obtain a valid business application group.

[0028] Optionally, determining whether there is a business abstract application matching the unit business in the business abstract application library includes:

[0029] Extracting business abstract applications from the business abstract application library in sequence, identifying the business node interface of the business abstract application, and determining whether the unit business matches the business abstract application based on the flow data and the business node interface;

[0030] If it is confirmed that the unit business does not match the business abstract application, the business abstract application is recorded as a non-matching application;

[0031] Aggregate the non-matching applications to obtain a non-matching application set;

[0032] If the number of non-matching applications in the non-matching application set is equal to the number of business abstract applications in the business abstract application library, then there is no business abstract application matching the unit business in the business abstract application library;

[0033] Otherwise, there is a business abstract application matching the unit business in the business abstract application library.

[0034] Optionally, performing exclusive parameter setting on the valid business application group based on the application scenario to obtain the target business application group includes:

[0035] Extracting valid business applications in the valid business application group in sequence, and confirming configuration options in the valid business applications;

[0036] Obtaining exclusive configuration parameters for the application scenario, and using the exclusive configuration parameters to update configuration options in the valid business application to obtain the target business application;

[0037] Summarize the target business applications to obtain a target business application group.

[0038] Optionally, arranging the business scenario application model based on the target business application group includes:

[0039] Determining a target business process of the business to be modeled, wherein the target business process includes a plurality of target business nodes, and each target business node corresponds to a target business application in a target business application group;

[0040] Based on the target business process, determining the application connection relationship of each target business application in the target business application group to obtain an application connection relationship group, wherein the application connection relationship group includes: a series relationship and a parallel relationship;

[0041] According to the application connection relationship group, each target business application in the target business application group is integrated to obtain a business scenario application model, wherein the integration method includes: API interface call.

[0042] Optionally, performing intelligent analysis on the business execution results based on a pre-built case library to obtain executable confidence includes:

[0043] Based on the business application field, search for case collections in the case library. Case collections in the same field include multiple cases in the same field, and cases in the same field are cases in the business application field.

[0044] Extracting cases in the same field from the case set in the same field in sequence, determining a case business application group of the cases in the same field, and obtaining case configuration parameters corresponding to each case business application in the case business application group to obtain a case configuration parameter group;

[0045] Determine case input data for the case in the same field;

[0046] Based on the case input data and case configuration parameter group, similarity analysis is performed on cases in the same field and the business to be modeled to obtain business similarity;

[0047] If the business similarity is greater than a preset similarity threshold, the business similarity is recorded as a valid business similarity;

[0048] Summarize the effective business similarities to obtain an effective business similarity group;

[0049] If the valid business similarity group is a preset empty set, the executable confidence is recorded as 0;

[0050] If the valid business similarity group is not an empty set, extracting a similar case group corresponding to the valid business similarity group from the case set in the same field;

[0051] Use similar case groups to evaluate business execution results and obtain executable confidence.

[0052] Optionally, the use of a similar case group to evaluate the business execution results to obtain the executable confidence level includes:

[0053] Sequentially extract similar cases from the similar case group and obtain case execution results of the similar cases;

[0054] Use the large language model to evaluate the similarity between case execution results and business execution results to obtain action similarity;

[0055] The action similarities are summarized to obtain an action similarity group, and the executable confidence is calculated based on the action similarity group and the effective business similarity group, where the executable confidence is expressed as:

[0056]

[0057] in, Indicates the confidence level of execution. Indicates the number of action similarities in the action similarity group or the number of valid business similarities in the valid business similarity group. and Respectively represent the first The similarity of effective business and Effective business similarity, Indicates the first Action similarity.

[0058] Optionally, manually correcting the service execution result to obtain a service correction result includes:

[0059] Confirming the abnormal similar case group of the executable confidence level in the case library, and obtaining the abnormal execution result group corresponding to the abnormal similar case group;

[0060] Inputting the abnormal execution result group and the business execution result into the large language model to obtain a risk point group, wherein the risk point group includes multiple risk points;

[0061] Generate a manual task order based on the risk point group, use the manual task order to make manual corrections, and obtain the business correction results.

[0062] To achieve the above-mentioned object, the present invention further provides a device for rapid abstract modeling of business applications, comprising:

[0063] A business application construction module is configured to receive an application modeling instruction, determine the business to be modeled and the original business data based on the application modeling instruction, determine the business application field of the business to be modeled, and obtain a business abstract application library based on the business application field, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is provided with a parameter interface;

[0064] a dedicated parameter setting module, configured to divide the business to be modeled into business groups to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface; construct a valid business application group based on the business abstract application library and the unit business group, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library; determine the application scenario of the business to be modeled, and based on the application scenario, perform dedicated parameter setting on the valid business application group to obtain a target business application group;

[0065] The language model analysis module is used to orchestrate business scenario application models based on the target business application group, perform business automation processing based on the original business data and the business scenario application model, obtain business execution results, and perform intelligent analysis on the business execution results based on the pre-built case library to obtain the executable confidence level, wherein the intelligent analysis refers to analysis using a large language model;

[0066] An execution result correction module is used to manually correct the business execution result if the executable confidence is not greater than the confidence threshold, obtain a business correction result, and record the business correction result as an executable result; if the executable confidence is greater than the confidence threshold, record the business execution result as an executable result, merge case data based on the original business data and the executable result to obtain the current case, and add the current case to the case library.

[0067] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0068] a memory storing at least one instruction; and

[0069] The processor executes the instructions stored in the memory to implement the above-mentioned method for rapid abstract modeling of business applications.

[0070] In order to solve the above problems, the present invention also provides a computer-readable storage medium, which stores at least one instruction. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned method for rapid abstract modeling of business applications.

[0071] In order to solve the problems described in the background technology, the present invention first determines the business application field and obtains the corresponding business abstract application library. These business abstract applications have standardized parameter interfaces and can be easily combined and called, which greatly improves the efficiency and flexibility of modeling. By dividing the complex business to be modeled into multiple relatively independent unit businesses, each unit business is made clearer, easier to understand and process. At the same time, setting a parameter interface for each unit business can ensure that the data interaction and collaborative work between each unit business are smoother. Then, an effective business application group is constructed to realize the personalized and scenario-based application of the business abstract application library. According to the specific needs of the business to be modeled, suitable public business applications can be extracted from the library, and proprietary business applications can be developed for special needs. This not only makes full use of the existing business abstract application resources and avoids repeated development, but also meets the unique requirements of the business to be modeled, improves the efficiency and flexibility of the business, and ensures the integrity and accuracy of the business process. By setting exclusive parameters for the effective business application group, the business application can be more in line with the specific application scenario requirements, improving The invention can improve the pertinence and practicality of business applications, ensure that business processes can be effectively executed in different environments and conditions, and then arrange business scenario application models to ensure that each business application can work together, realize the automation and intelligent processing of business processes, improve the efficiency and quality of business execution, and also facilitate the subsequent optimization and adjustment of business processes. By using the business scenario application model to automatically process the original business data, it can quickly and efficiently complete complex business processes, greatly improving the speed and efficiency of business processing. Furthermore, the invention also introduces a large language model and a case library for intelligent analysis to obtain executable confidence, which helps to judge the credibility and rationality of the business execution results and timely discover potential problems and risks. When the executable confidence is low, manual correction is performed, which can ensure that the final business results meet actual needs and business specifications. Finally, the current case is added to the case library, which can continuously enrich the content and diversity of the case library, so that the case library more comprehensively and accurately reflects various business scenarios and processing methods, which further improves the accuracy and reliability of intelligent analysis. Therefore, the invention can improve the intelligence and flexibility of business processing and improve the efficiency of business processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A flowchart of a method for rapid abstract modeling of business applications provided by one embodiment of the present invention;

[0073] Figure 2 A functional module diagram of a device for rapid abstract modeling of business applications provided by an embodiment of the present invention;

[0074] Figure 3A schematic diagram of the structure of an electronic device for implementing the method for rapid abstract modeling of business applications provided by an embodiment of the present invention.

[0075] Description of reference numerals:

[0076] 1. Electronic device; 10. Processor; 11. Memory; 12. Bus.

[0077] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0078] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0079] The present embodiment provides a method for rapid abstract modeling of business applications. The method can be executed by at least one of a server, a terminal, or other electronic device capable of executing the method provided by the present embodiment. In other words, the method can be executed by software or hardware installed on a terminal or server device, where the software can be a blockchain platform. The server can include, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0080] Reference Figure 1 FIG. 1 is a flow chart of a method for rapid abstract modeling of business applications provided by an embodiment of the present invention. In this embodiment, the method for rapid abstract modeling of business applications includes:

[0081] S1. Receive an application modeling instruction, and determine the business to be modeled and original business data based on the application modeling instruction.

[0082] It is understood that the application modeling instruction refers to a human-initiated instruction to model a specific business, and the business to be modeled refers to the specific business specified in the application modeling instruction. The raw business data refers to the initial data set related to the business to be modeled provided by the user, including business operation records, transaction flow, file content, or raw information returned by external system interfaces.

[0083] For example, the original business data is: the account transaction details table (CSV format) of Department B of a bank in the third quarter of 2023 and the associated customer information database table.

[0084] S2. Determine the business application domain of the business to be modeled, and obtain a business abstract application library based on the business application domain, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is set with a parameter interface.

[0085] It is clear that the business application field refers to the application field involved in the business to be modeled. For example, if the business to be modeled is "account reconciliation of a company in Part B in the third quarter of 2023", then the business application field is "account reconciliation". The business abstract application library refers to an artificially constructed application database that can execute all possible businesses in the business application field, wherein the business abstract application refers to a program or plug-in that can execute a certain business in the business application field. The parameter interface refers to a standardized protocol for data interaction between the business abstract application and the external system or process node. The parameter interface includes: a parameter input interface and a parameter output interface, wherein the parameter input interface refers to the interface corresponding to the data that needs to be input before executing the business abstract application, for example: receiving a string parameter of the file path, and the parameter output interface refers to the interface corresponding to the data output after executing the business abstract application.

[0086] In detail, the acquisition of a business abstract application library based on the business application field includes:

[0087] Constructing a business application process of the business application field, wherein the business application process includes a plurality of business process nodes;

[0088] Extracting business process nodes in sequence from a plurality of business process nodes of a business application process, defining node interfaces of the business process nodes, and obtaining programmable business nodes, wherein the node interfaces include: an input parameter interface and an output parameter interface;

[0089] Performing application development on the programmable service node to obtain a service abstract application, wherein the application development includes language programming;

[0090] The business abstract applications are aggregated to obtain a business abstract application library.

[0091] It should be explained that the business application process refers to the step process for completing the tasks specified in the business application field. The business application process is formulated by relevant R&D personnel and includes multiple business process nodes, where a business process node refers to an action that needs to be completed in the business application process.

[0092] For example, a business application process is "account reconciliation", and its business process nodes include: Node 1: Upload accounting files, where the input interface of Node 1 is: file path, and the output interface is: parsed accounting data; Node 2: Verify transaction compliance, where the input interface of Node 2 is: accounting data, and the output interface is: compliance mark; Node 3: Generate reconciliation report, where the input interface of Node 3 is: compliance mark, and the output interface is: PDF report path.

[0093] Furthermore, the node interface refers to the data transmission specification between the business process node and the upstream and downstream nodes or systems, and the node interface includes: an input parameter interface and an output parameter interface, wherein the input parameter interface refers to the entry for receiving the processing results of the previous node or external input data, and the output parameter interface refers to the exit for transmitting the processing results of the current node to the subsequent node. The programmable business node refers to the business process node obtained after the definition of the node interface. The detailed process of defining the node interface of the business process node in the above steps is: defining the format of the input data (such as JSONSchema) and the structure of the output data (such as database table fields) through the API. The purpose of defining the node interface of the business process node mentioned in the above steps is to achieve standardization and modularization of business process nodes, ensure seamless connection of data between different nodes, and reduce development complexity.

[0094] It is clear that the business abstract application refers to a programmable business node that has undergone application development. Application development for a programmable business node refers to implementing the data processing logic defined in the node interface through a programming language. The implementation path for this application development is to write a script or service to convert the data of the input parameter interface into the expected result of the output parameter interface. The purpose of application development for a programmable business node here is that the programmable business node defines the node interface, but the implementation path between the input parameter interface and the output parameter interface is not determined, that is, the specific actions corresponding to the programmable business node have not yet been set. Therefore, through application development, it is possible to convert the abstract interface definition into a specific business logic execution unit, such as developing a "file parsing" plug-in to implement the function of extracting accounting data from a CSV file.

[0095] Importantly, the business abstraction applications provided by this solution can be independently developed and deployed online.

[0096] S3. Divide the business to be modeled into business units to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface.

[0097] It is understandable that the unit business refers to the business to be modeled after division, wherein the purpose of business division of the business to be modeled is: since the business to be modeled is a complete business process, which includes multiple actions that need to be executed, the business division here is to turn the completed business into actions that can be executed individually. The implementation of these individual actions can be completed through the business abstract applications established in the business abstract application library, thereby avoiding the repeated establishment of business applications for different businesses. When it is necessary to call the business application corresponding to a certain action, it is only necessary to extract the corresponding business application from the business abstract application library. By inserting the business applications extracted for each action into each other, the complete business to be modeled can be modeled.

[0098] Furthermore, the method of dividing the unit business groups is: first determine the implementation step process of the business to be modeled, and then extract each individual action in the implementation step process, and these individual actions constitute the unit business groups.

[0099] S4. Based on the business abstract application library and the unit business group, construct a valid business application group, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications come from the business abstract application library.

[0100] It should be explained that the effective business application group refers to a combination of business applications that can execute the business of each unit in the unit business group, and the effective business applications include public business applications and proprietary business applications, among which public business applications are business abstract applications that can be extracted from the business abstract application library. It can be seen from the above that the applications in the business abstract application library are constructed according to the processes of the corresponding fields, but not all implementation processes of the businesses in the field are exactly the same as the processes of constructing the business abstract application library. There may be some differences in actions between them, and proprietary business applications are artificially constructed applications with different actions between the unit business group and the business abstract application library. For example, a business to be modeled is: to check the accounts of a company in March and mark the accounts for reimbursement. Then, the business to be modeled not only contains account checking, but also contains the marking of specific accounts. Then, the application that implements the marking of specific accounts is a proprietary business application.

[0101] Specifically, the construction of an effective business application group based on the business abstract application library and the unit business group includes:

[0102] Extracting unit businesses in the unit business group in sequence and determining flow data of the unit businesses, wherein the flow data includes: input data and output data;

[0103] Based on the flow data, determine whether there is a business abstract application matching the unit's business in the business abstract application library;

[0104] If there is a business abstract application matching the unit's business in the business abstract application library, extract the public business application from the business abstract application library;

[0105] If there is no business abstract application matching the unit business in the business abstract application library, then construct a proprietary business application for the unit business;

[0106] The public business applications or proprietary business applications are aggregated to obtain a valid business application group.

[0107] It can be understood that the flow data refers to the data involved in the execution of the unit business, and the flow data includes: input data and output data, wherein the input data refers to the data that needs to be input before executing the unit business, and the output data refers to the data obtained after executing the unit business. The flow data matches the parameter interface in the business abstract application (that is, the input data is the same as the parameter input interface, and the output data is the same as the parameter output interface).

[0108] For example, the flow data is "customer ID number" and "transaction amount". If the parameter input interface of a business abstract application requires "string type customer ID" and "floating point type transaction amount", the two match; if the parameter interface requires "integer type customer number", the flow data does not match the parameter interface.

[0109] Furthermore, the public business application is a business abstract application in the business abstract application library that matches the unit business, and the proprietary business application is an artificially constructed business application for the unit business that does not have a matching business abstract application. The method of constructing the proprietary business application is the same as the method of constructing the business abstract application in the business abstract application library. Please refer to the content in Example S2.

[0110] Specifically, the step of determining whether there is a business abstract application matching the unit business in the business abstract application library includes:

[0111] Extracting business abstract applications from the business abstract application library in sequence, identifying the business node interface of the business abstract application, and determining whether the unit business matches the business abstract application based on the flow data and the business node interface;

[0112] If it is confirmed that the unit business does not match the business abstract application, the business abstract application is recorded as a non-matching application;

[0113] Aggregate the non-matching applications to obtain a non-matching application set;

[0114] If the number of non-matching applications in the non-matching application set is equal to the number of business abstract applications in the business abstract application library, then there is no business abstract application matching the unit business in the business abstract application library;

[0115] Otherwise, there is a business abstract application matching the unit business in the business abstract application library.

[0116] It is understood that the service node interface refers to the parameter interface of the service abstraction application. If the parameter input interface and parameter output interface corresponding to the service node interface are identical to the input data and output data in the flow data, the unit service can be considered to match the service abstraction application. If the parameter input interface and parameter output interface corresponding to the service node interface are not identical to the input data and output data in the flow data, the unit service can be considered to not match the service abstraction application.

[0117] Furthermore, when the number of non-matching applications in the non-matching application set is equal to the number of business abstract applications in the business abstract application library, it means that the unit business does not match all business abstract applications in the business abstract application library, that is, there is no business abstract application in the business abstract application library that matches the unit business; conversely, there is a business abstract application in the business abstract application library that matches the unit business.

[0118] S5. Determine the application scenario of the business to be modeled, and based on the application scenario, perform exclusive parameter setting on the valid business application group to obtain the target business application group.

[0119] It should be noted that the application scenario refers to the usage scenario of the business to be modeled, which is determined in real time by the operator. For example, if the business to be modeled is account reconciliation, and this account reconciliation is to reconcile the accounts of Department B of Company A in March, then Company A, March, and Department B are the application scenarios here. The target business application group refers to the valid business application group after the dedicated parameters are set.

[0120] Furthermore, the execution-specific parameter setting refers to the need to set different configuration parameters for the effective business application group for different application scenarios, wherein the configuration parameters refer to dynamic variables related to the application scenario, such as: time range (such as "Q3 2023"), department code (such as "Department B"), and account type (such as "accounts receivable").

[0121] Specifically, the method of performing exclusive parameter setting on the valid business application group based on the application scenario to obtain the target business application group includes:

[0122] Extracting valid business applications in the valid business application group in sequence, and confirming configuration options in the valid business applications;

[0123] Obtaining exclusive configuration parameters for the application scenario, and using the exclusive configuration parameters to update configuration options in the valid business application to obtain the target business application;

[0124] Summarize the target business applications to obtain a target business application group.

[0125] It is understandable that the configuration options refer to adjustable variables or conditions in the business abstract application, such as the account reconciliation range, and the exclusive configuration parameters refer to the numerical parameters involved in the application scenario.

[0126] For example, if a valid business application is an application for account reconciliation, then there will be a reconciliation scope in the valid business application, and the reconciliation scope is a configuration option. If the application scenario is "account reconciliation of Department B of Company A in March", then in this application scenario, the reconciliation scope should be March, that is, the reconciliation scope in the valid business application needs to be set to March.

[0127] S6. Based on the target business application group, orchestrate the business scenario application model.

[0128] It should be explained that the business scenario application model refers to the model resulting from the combination and orchestration of the target business applications in the target business application group. Because the target business applications within the target business application group represent only a single action, orchestrating the target business application group involves combining the actions corresponding to these applications so that the resulting model can complete the business being modeled.

[0129] Specifically, the process of arranging a business scenario application model based on a target business application group includes:

[0130] Determining a target business process of the business to be modeled, wherein the target business process includes a plurality of target business nodes, and each target business node corresponds to a target business application in a target business application group;

[0131] Based on the target business process, determining the application connection relationship of each target business application in the target business application group to obtain an application connection relationship group, wherein the application connection relationship group includes: a series relationship and a parallel relationship;

[0132] According to the application connection relationship group, each target business application in the target business application group is integrated to obtain a business scenario application model, wherein the integration method includes: API interface call.

[0133] It is understood that the target business process refers to the action flow for executing the business to be modeled, and the target business node refers to a specific action in the action flow. The application connection relationship refers to the connection relationship between the target business applications in the business scenario application model. Among them, a series relationship means that two target business applications have a chronological order when they are executed, and a parallel relationship means that two target business applications have the same execution order when they are executed.

[0134] For example, for the account reconciliation business, the business includes several actions: uploading files, verifying transactions and adjusting accounts. Among them, the order of executing these actions is: uploading files, verifying transactions and adjusting accounts, and the application connection relationships between them are all serial relationships. Then, according to the application connection relationship group, each target business application in the target business application group is integrated as follows: uploading files, verifying transactions and adjusting accounts are connected in series. After the series connection is completed, the business scenario application model is obtained, and the series connection method includes API interface calls.

[0135] S7. Perform business automation processing based on the original business data and business scenario application model to obtain business execution results.

[0136] It can be understood that business automation processing means: inputting the original business data into the business scenario application model, and the target business application group completed by the connection in the business scenario application model processes the original business data in sequence, and the business execution result is obtained after the processing is completed.

[0137] S8. Perform intelligent analysis on the business execution results based on the pre-built case library to obtain executable confidence, wherein the intelligent analysis refers to analysis using a large language model.

[0138] It is understood that the case library refers to a manually constructed collection of a large number of cases acquired over time. The executable confidence level is a numerical value that quantifies the credibility of the business execution results. The greater the executable confidence level, the more reliable the business execution results. When the executable confidence level exceeds a preset confidence threshold, the business will be processed according to the business execution results. Otherwise, manual intervention is required to modify the business execution results.

[0139] Specifically, the business execution results are intelligently analyzed based on the pre-built case library to obtain the executable confidence level, including:

[0140] Based on the business application field, search for case collections in the case library. Case collections in the same field include multiple cases in the same field, and cases in the same field are cases in the business application field.

[0141] Extracting cases in the same field from the case set in the same field in sequence, determining a case business application group of the cases in the same field, and obtaining case configuration parameters corresponding to each case business application in the case business application group to obtain a case configuration parameter group;

[0142] Determine case input data for the case in the same field;

[0143] Based on the case input data and case configuration parameter group, similarity analysis is performed on cases in the same field and the business to be modeled to obtain business similarity;

[0144] If the business similarity is greater than a preset similarity threshold, the business similarity is recorded as a valid business similarity;

[0145] Summarize the effective business similarities to obtain an effective business similarity group;

[0146] If the valid business similarity group is a preset empty set, the executable confidence is recorded as 0;

[0147] If the valid business similarity group is not an empty set, extracting a similar case group corresponding to the valid business similarity group from the case set in the same field;

[0148] Use similar case groups to evaluate business execution results and obtain executable confidence.

[0149] It can be understood that the case set in the same field refers to a collection of cases in the case library with the same business field and business application field. The case business application group refers to the target business application group in the case in the same field. The case configuration parameter group refers to the combination of exclusive configuration parameters of each case business application in the case business application group. The case input data refers to the data input when the case in the same field was previously executed, and the data corresponds to the above-mentioned original business data. The business similarity refers to a numerical value that quantifies the similarity between the case in the same field and the business to be modeled. The greater the business similarity, the greater the similarity between the case in the same field and the business to be modeled. Among them, performing similarity analysis on the case in the same field and the business to be modeled refers to: calculating the Euclidean geometric distance between the case input data and the case configuration parameter group and the business input data and the exclusive configuration parameter group, and using the Euclidean geometric distance as the business similarity. The similarity threshold refers to an artificially set constant. The similarity case group refers to a combination of cases in the same field corresponding to the valid business similarity group.

[0150] Specifically, the use of similar case groups to evaluate business execution results and obtain executable confidence includes:

[0151] Sequentially extract similar cases from the similar case group and obtain case execution results of the similar cases;

[0152] Use the large language model to evaluate the similarity between case execution results and business execution results to obtain action similarity;

[0153] The action similarities are summarized to obtain an action similarity group, and the executable confidence is calculated based on the action similarity group and the effective business similarity group, where the executable confidence is expressed as:

[0154]

[0155] in, Indicates the confidence level of execution. Indicates the number of action similarities in the action similarity group or the number of valid business similarities in the valid business similarity group. and Respectively represent the first The similarity of effective business and Effective business similarity, Indicates the first Action similarity.

[0156] It should be explained that the case execution result refers to the business execution result of a similar case. The large language model refers to a pre-trained model based on the Transformer architecture (such as GPT-4). The action similarity refers to a numerical value that quantifies the similarity between the case execution result and the business execution result. The greater the action similarity, the higher the similarity between the case execution result and the business execution result. The use of the pre-acquired large language model to evaluate the similarity of the case execution result and the business execution result refers to: converting the case execution result and the current business execution result into natural language descriptions, then using the large language model to extract the semantic vectors of the two, and finally calculating the cosine similarity between the semantic vectors as the action similarity.

[0157] S9. If the executable confidence is not greater than the confidence threshold, manually correct the business execution result to obtain a business correction result, and record the business correction result as an executable result.

[0158] It is clear that the business correction result refers to the business execution result after manual correction.

[0159] In detail, manually correcting the business execution result to obtain the business correction result includes:

[0160] Confirming the abnormal similar case group of the executable confidence level in the case library, and obtaining the abnormal execution result group corresponding to the abnormal similar case group;

[0161] Inputting the abnormal execution result group and the business execution result into the large language model to obtain a risk point group, wherein the risk point group includes multiple risk points;

[0162] Generate a manual task order based on the risk point group, use the manual task order to make manual corrections, and obtain the business correction results.

[0163] It is clear that the abnormal similar case group refers to a similar case group when the executable confidence is not greater than the confidence threshold. The abnormal execution result group refers to a combination of business execution results corresponding to the abnormal similar case group. The risk point refers to a potential problem that may cause errors in the business execution results, for example: "The account adjustment amount exceeds 20% of the historical average". The large language model can identify abnormal patterns and generate risk prompts described in natural language, for example: "An abnormal adjustment amount is detected", so the difference between the abnormal execution result group and the business execution result can be identified through the large language model, thereby obtaining a risk point group. The manual task order refers to a business execution result that includes a risk point group. The manual correction refers to the modification of the risk point group in the manual task order by a professional.

[0164] S10: If the executable confidence is greater than the confidence threshold, the business execution result is recorded as an executable result.

[0165] It is understandable that if the executable confidence is greater than the confidence threshold, the business execution result can be directly executed without human intervention.

[0166] S11. Based on the original business data and the executable results, case data is merged to obtain the current case, and the current case is added to the case library to complete the rapid abstract modeling of the business application.

[0167] It should be explained that the current case represents the currently processed business to be modeled. This case can be represented by a speed configuration parameter set consisting of the original business data, executable results, and exclusive configuration parameters. Adding the current case to the case library can further enrich the case library and improve the accuracy of subsequent business processing.

[0168] Furthermore, this solution uses a completely independent sandbox space to provide users with a lab environment. This lab environment allows users to conduct temporary experiments on orchestrated application models to verify the effectiveness of the orchestration and the correctness of the parameters. The sandbox data space is completely isolated from the production line and can be cleaned up at any time. Furthermore, this solution also features an independent log tracking module that records every step of the automated execution of business scenario application models and makes them available for user query.

[0169] In order to solve the problems described in the background technology, the present invention first determines the business application field and obtains the corresponding business abstract application library. These business abstract applications have standardized parameter interfaces and can be easily combined and called, which greatly improves the efficiency and flexibility of modeling. By dividing the complex business to be modeled into multiple relatively independent unit businesses, each unit business is made clearer, easier to understand and process. At the same time, setting a parameter interface for each unit business can ensure that the data interaction and collaborative work between each unit business are smoother. Then, an effective business application group is constructed to realize the personalized and scenario-based application of the business abstract application library. According to the specific needs of the business to be modeled, suitable public business applications can be extracted from the library, and proprietary business applications can be developed for special needs. This not only makes full use of the existing business abstract application resources and avoids repeated development, but also meets the unique requirements of the business to be modeled, improves the efficiency and flexibility of the business, and ensures the integrity and accuracy of the business process. By setting exclusive parameters for the effective business application group, the business application can be more in line with the specific application scenario requirements, improving The invention can improve the pertinence and practicality of business applications, ensure that business processes can be effectively executed in different environments and conditions, and then arrange business scenario application models to ensure that each business application can work together, realize the automation and intelligent processing of business processes, improve the efficiency and quality of business execution, and also facilitate the subsequent optimization and adjustment of business processes. By using the business scenario application model to automatically process the original business data, it can quickly and efficiently complete complex business processes, greatly improving the speed and efficiency of business processing. Furthermore, the invention also introduces a large language model and a case library for intelligent analysis to obtain executable confidence, which helps to judge the credibility and rationality of the business execution results and timely discover potential problems and risks. When the executable confidence is low, manual correction is performed, which can ensure that the final business results meet actual needs and business specifications. Finally, the current case is added to the case library, which can continuously enrich the content and diversity of the case library, so that the case library more comprehensively and accurately reflects various business scenarios and processing methods, which further improves the accuracy and reliability of intelligent analysis. Therefore, the invention can improve the intelligence and flexibility of business processing and improve the efficiency of business processing.

[0170] like Figure 2 FIG. 1 is a functional module diagram of a device for rapid abstract modeling of business applications provided by an embodiment of the present invention.

[0171] The business application rapid abstract modeling device 100 described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the business application rapid abstract modeling device 100 may include a business application construction module 101, a dedicated parameter setting module 102, a language model analysis module 103, and an execution result correction module 104. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function, and is stored in the electronic device's memory.

[0172] The business application construction module 101 is configured to receive an application modeling instruction, determine the business to be modeled and the original business data based on the application modeling instruction, determine the business application field of the business to be modeled, and obtain a business abstract application library based on the business application field, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is provided with a parameter interface;

[0173] The dedicated parameter setting module 102 is used to divide the business to be modeled into business groups to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is set with a parameter interface; construct a valid business application group based on the business abstract application library and the unit business group; wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library; determine the application scenario of the business to be modeled, and perform dedicated parameter setting on the valid business application group based on the application scenario to obtain a target business application group;

[0174] The language model analysis module 103 is used to compile a business scenario application model based on the target business application group, perform business automation processing based on the original business data and the business scenario application model, obtain business execution results, and perform intelligent analysis on the business execution results based on a pre-built case library to obtain executable confidence, wherein the intelligent analysis refers to analysis using a large language model;

[0175] The execution result correction module 104 is used to manually correct the business execution result if the executable confidence is not greater than the confidence threshold, obtain a business correction result, and record the business correction result as an executable result; if the executable confidence is greater than the confidence threshold, record the business execution result as an executable result, merge case data based on the original business data and the executable result to obtain the current case, and add the current case to the case library.

[0176] In detail, each module in the business application rapid abstract modeling device 100 in the embodiment of the present invention adopts the same method as above when in use. Figure 1The technical means are the same as the business application rapid abstract modeling method described in, and can produce the same technical effects, so I will not go into details here.

[0177] like Figure 3 FIG. 1 is a schematic diagram of the structure of an electronic device for implementing a method for rapid abstract modeling of business applications provided by an embodiment of the present invention.

[0178] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a business application rapid abstract modeling method program.

[0179] The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 1. Furthermore, the memory 11 includes both the internal storage unit of the electronic device 1 and an external storage device. The memory 11 can be used not only to store application software installed on the electronic device 1 and various types of data, such as the code of the business application rapid abstract modeling method program, but also to temporarily store data that has been output or is about to be output.

[0180] In some embodiments, the processor 10 may be comprised of an integrated circuit, such as a single packaged integrated circuit or a combination of multiple packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (control unit) of the electronic device, connecting the various components of the electronic device using various interfaces and circuits. It executes programs or modules (such as a program for a rapid abstract modeling method for business applications) stored in the memory 11 and accesses data stored in the memory 11 to perform various functions and process data.

[0181] The bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0182] Figure 3 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 3 The structure shown does not constitute a limitation on the electronic device 1 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0183] For example, although not shown, the electronic device 1 may further include a power supply (e.g., a battery) to power various components. Preferably, the power supply may be logically connected to the at least one processor 10 via a power management device, thereby enabling functions such as charge management, discharge management, and power consumption management via the power management device. The power supply may further include any components such as one or more DC or AC power supplies, a recharging device, a power failure detection circuit, a power converter or inverter, and a power status indicator. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not further described here.

[0184] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0185] Optionally, the electronic device 1 may further include a user interface, which may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display may also be appropriately referred to as a display screen or a display unit, and is used to display information processed by the electronic device 1 and to display a visual user interface.

[0186] The business application rapid abstract modeling method program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve the following:

[0187] Receive application modeling instructions, and determine the business to be modeled and original business data based on the application modeling instructions;

[0188] Determine the business application domain of the business to be modeled, and obtain a business abstract application library based on the business application domain, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is set with a parameter interface;

[0189] Dividing the business to be modeled into business units to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface;

[0190] Based on the business abstract application library and the unit business group, a valid business application group is constructed, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library;

[0191] Determine the application scenario of the business to be modeled, and based on the application scenario, perform exclusive parameter setting on the valid business application group to obtain the target business application group;

[0192] Orchestrate business scenario application models based on target business application groups;

[0193] Perform business automation processing based on original business data and business scenario application models to obtain business execution results;

[0194] Based on a pre-built case library, intelligent analysis is performed on the business execution results to obtain an executable confidence level, wherein the intelligent analysis refers to analysis using a large language model;

[0195] If the executable confidence is not greater than the confidence threshold, manually correcting the business execution result to obtain a business correction result, and recording the business correction result as an executable result;

[0196] If the confidence level of the business execution is greater than the confidence threshold, the business execution result is recorded as an executable result;

[0197] Based on the original business data and the executable results, case data is merged to obtain the current case, and the current case is added to the case library to complete the rapid abstract modeling of the business application.

[0198] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figures 1 to 3 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0199] Furthermore, if the modules / units integrated into the electronic device 1 are implemented as software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. The computer-readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0200] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor of an electronic device, the computer program can implement:

[0201] Receive application modeling instructions, and determine the business to be modeled and original business data based on the application modeling instructions;

[0202] Determine the business application domain of the business to be modeled, and obtain a business abstract application library based on the business application domain, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is set with a parameter interface;

[0203] Dividing the business to be modeled into business units to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface;

[0204] Based on the business abstract application library and the unit business group, a valid business application group is constructed, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library;

[0205] Determine the application scenario of the business to be modeled, and based on the application scenario, perform exclusive parameter setting on the valid business application group to obtain the target business application group;

[0206] Orchestrate business scenario application models based on target business application groups;

[0207] Perform business automation processing based on original business data and business scenario application models to obtain business execution results;

[0208] Based on a pre-built case library, intelligent analysis is performed on the business execution results to obtain an executable confidence level, wherein the intelligent analysis refers to analysis using a large language model;

[0209] If the executable confidence is not greater than the confidence threshold, manually correcting the business execution result to obtain a business correction result, and recording the business correction result as an executable result;

[0210] If the confidence level of the business execution is greater than the confidence threshold, the business execution result is recorded as an executable result;

[0211] Based on the original business data and the executable results, case data is merged to obtain the current case, and the current case is added to the case library to complete the rapid abstract modeling of the business application.

[0212] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, and actual implementation may have other division methods.

[0213] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0214] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0215] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0216] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for rapid abstract modeling of business applications, characterized in that: The method comprises: Receive application modeling instructions, and determine the business to be modeled and original business data based on the application modeling instructions; Determine the business application domain of the business to be modeled, and obtain a business abstract application library based on the business application domain, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is set with a parameter interface; Dividing the business to be modeled into business units to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface; Based on the business abstract application library and the unit business group, a valid business application group is constructed, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library; Determine the application scenario of the business to be modeled, and based on the application scenario, perform exclusive parameter setting on the valid business application group to obtain the target business application group; Orchestrate business scenario application models based on target business application groups; Perform business automation processing based on original business data and business scenario application models to obtain business execution results; Based on a pre-built case library, intelligent analysis is performed on the business execution results to obtain an executable confidence level, wherein the intelligent analysis refers to analysis using a large language model; If the executable confidence is not greater than the confidence threshold, manually correcting the business execution result to obtain a business correction result, and recording the business correction result as an executable result; If the confidence level of the business execution is greater than the confidence threshold, the business execution result is recorded as an executable result; Based on the original business data and the executable results, case data is merged to obtain the current case, and the current case is added to the case library to complete the rapid abstract modeling of the business application.

2. The method for rapid abstract modeling of business applications according to claim 1, characterized in that: The obtaining of the business abstract application library based on the business application field includes: Constructing a business application process of the business application field, wherein the business application process includes a plurality of business process nodes; Extracting business process nodes in sequence from a plurality of business process nodes of a business application process, defining node interfaces of the business process nodes, and obtaining programmable business nodes, wherein the node interfaces include: an input parameter interface and an output parameter interface; Performing application development on the programmable service node to obtain a service abstract application, wherein the application development includes language programming; The business abstract applications are aggregated to obtain a business abstract application library.

3. The method for rapid abstract modeling of business applications according to claim 2, wherein: The construction of a valid business application group based on the business abstract application library and the unit business group includes: Extracting unit businesses in the unit business group in sequence and determining flow data of the unit businesses, wherein the flow data includes: input data and output data; Based on the flow data, determine whether there is a business abstract application matching the unit's business in the business abstract application library; If there is a business abstract application matching the unit's business in the business abstract application library, extract the public business application from the business abstract application library; If there is no business abstract application matching the unit business in the business abstract application library, then construct a proprietary business application for the unit business; The public business applications or proprietary business applications are aggregated to obtain a valid business application group.

4. The method for rapid abstract modeling of business applications according to claim 3, wherein: The determining whether there is a business abstract application matching the unit business in the business abstract application library includes: Extracting business abstract applications from the business abstract application library in sequence, identifying the business node interface of the business abstract application, and determining whether the unit business matches the business abstract application based on the flow data and the business node interface; If it is confirmed that the unit business does not match the business abstract application, the business abstract application is recorded as a non-matching application; Aggregate the non-matching applications to obtain a non-matching application set; If the number of non-matching applications in the non-matching application set is equal to the number of business abstract applications in the business abstract application library, then there is no business abstract application matching the unit business in the business abstract application library; Otherwise, there is a business abstract application matching the unit business in the business abstract application library.

5. The method for rapid abstract modeling of business applications according to claim 4, characterized in that: The method of performing exclusive parameter setting on the valid business application group based on the application scenario to obtain the target business application group includes: Extracting valid business applications in the valid business application group in sequence, and confirming configuration options in the valid business applications; Obtaining exclusive configuration parameters for the application scenario, and using the exclusive configuration parameters to update configuration options in the valid business application to obtain the target business application; Summarize the target business applications to obtain a target business application group.

6. The method for rapid abstract modeling of business applications according to claim 5, characterized in that: The process of arranging the business scenario application model based on the target business application group includes: Determining a target business process of the business to be modeled, wherein the target business process includes a plurality of target business nodes, and each target business node corresponds to a target business application in a target business application group; Based on the target business process, determining the application connection relationship of each target business application in the target business application group to obtain an application connection relationship group, wherein the application connection relationship group includes: a series relationship and a parallel relationship; According to the application connection relationship group, each target business application in the target business application group is integrated to obtain a business scenario application model, wherein the integration method includes: API interface call.

7. The method for rapid abstract modeling of business applications according to claim 6, wherein: The intelligent analysis of the business execution results based on the pre-built case library to obtain the executable confidence level includes: Based on the business application field, search for case collections in the case library. Case collections in the same field include multiple cases in the same field, and cases in the same field are cases in the business application field. Extracting cases in the same field from the case set in the same field in sequence, determining a case business application group of the cases in the same field, and obtaining case configuration parameters corresponding to each case business application in the case business application group to obtain a case configuration parameter group; Determine case input data for the case in the same field; Based on the case input data and case configuration parameter group, similarity analysis is performed on cases in the same field and the business to be modeled to obtain business similarity; If the business similarity is greater than a preset similarity threshold, the business similarity is recorded as a valid business similarity; Summarize the effective business similarities to obtain an effective business similarity group; If the valid business similarity group is a preset empty set, the executable confidence is recorded as 0; If the valid business similarity group is not an empty set, extracting a similar case group corresponding to the valid business similarity group from the case set in the same field; Use similar case groups to evaluate business execution results and obtain executable confidence.

8. The method for rapid abstract modeling of business applications according to claim 7, characterized in that: The use of similar case groups to evaluate business execution results and obtain executable confidence includes: Sequentially extract similar cases from the similar case group and obtain case execution results of the similar cases; Use the large language model to evaluate the similarity between case execution results and business execution results to obtain action similarity; The action similarities are summarized to obtain an action similarity group, and the executable confidence is calculated based on the action similarity group and the effective business similarity group, where the executable confidence is expressed as: in, Indicates the confidence level of execution. Indicates the number of action similarities in the action similarity group or the number of valid business similarities in the valid business similarity group. and Respectively represent the first The similarity of effective business and Effective business similarity, Indicates the first Action similarity.

9. The method for rapid abstract modeling of business applications according to claim 8, characterized in that: Manually correcting the business execution result to obtain a business correction result includes: Confirming the abnormal similar case group of the executable confidence level in the case library, and obtaining the abnormal execution result group corresponding to the abnormal similar case group; Inputting the abnormal execution result group and the business execution result into the large language model to obtain a risk point group, wherein the risk point group includes multiple risk points; Generate a manual task order based on the risk point group, use the manual task order to make manual corrections, and obtain the business correction results.

10. A device for rapid abstract modeling of business applications, characterized in that: The device comprises: A business application construction module is configured to receive an application modeling instruction, determine the business to be modeled and the original business data based on the application modeling instruction, determine the business application field of the business to be modeled, and obtain a business abstract application library based on the business application field, wherein the business abstract application library includes multiple business abstract applications, and each business abstract application is provided with a parameter interface; a dedicated parameter setting module, configured to divide the business to be modeled into business groups to obtain unit business groups, wherein the unit business group includes multiple unit businesses, and each unit business is provided with a parameter interface; construct a valid business application group based on the business abstract application library and the unit business group, wherein the valid business application group includes multiple valid business applications, and the valid business applications include: public business applications and proprietary business applications, and the public business applications are from the business abstract application library; determine the application scenario of the business to be modeled, and based on the application scenario, perform dedicated parameter setting on the valid business application group to obtain a target business application group; The language model analysis module is used to orchestrate business scenario application models based on the target business application group, perform business automation processing based on the original business data and the business scenario application model, obtain business execution results, and perform intelligent analysis on the business execution results based on the pre-built case library to obtain the executable confidence level, wherein the intelligent analysis refers to analysis using a large language model; An execution result correction module is used to manually correct the business execution result if the executable confidence is not greater than the confidence threshold, obtain a business correction result, and record the business correction result as an executable result; if the executable confidence is greater than the confidence threshold, record the business execution result as an executable result, merge case data based on the original business data and the executable result to obtain the current case, and add the current case to the case library.

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