Bidirectional data transfer platform based on large model and processing method

Abstract

The invention relates to the technical field of data circulation, in particular to a data bidirectional circulation platform based on a large model and a processing method. The system is composed of a task, a multifunctional agent, a tool set and a data set. The processing flow comprises data circulation and data circulation analysis. According to the invention, the data circulation process is more portable and intelligent, the operation convenience and usability are improved, and rapid circulation of the data is realized; and meanwhile, a user is supported to intuitively master the current and historical conditions of data circulation resources at any time, the specific working process and working condition of circulation are effectively displayed, and the purpose of auxiliary decision making is achieved.

Description

Technical Field

[0001] The present invention relates to the field of data flow technology, and in particular to a large model-based bidirectional data flow platform and a processing method. Background Art

[0002] At present, data elements have become new production factors, and the circulation of data between different owners has become a common way of production and living. Whether it is the sharing and exchange of government data between higher and lower levels of the government, or the sharing and openness of data between state-owned enterprises and small and medium-sized enterprises based on production, marketing, procurement, and delivery, it can greatly promote economic and social activities and government management and governance. The current data circulation platform relies more on the traditional expert system development model, and the response process needs to be set in advance through programming languages. Summary of the invention

[0003] The present invention provides a large model-based data bidirectional flow platform and processing method, which can overcome certain or some defects of the prior art.

[0004] According to a large model-based two-way data flow platform of the present invention, the platform mainly includes tasks, multifunctional intelligent agents, tool sets and data sets.

[0005] As a preferred option, a two-way data flow platform based on a large model can realize directory management services, data exchange applications, user authority identification, automatic approval of suppliers, automatic data matching and docking, automatic generation of data reports, generation of data flow visualization charts and data flow assistants.

[0006] A method for processing a large-model-based bidirectional data flow platform according to the present invention includes a processing flow including data flow and data flow analysis.

[0007] Preferably, the data flow includes the following steps:

[0008] S11. The data applicant initiates the application;

[0009] S12, the data two-way circulation platform based on the big model receives the demand and forms the work task;

[0010] S13, output the results according to the reasoning principle of the data flow management agent;

[0011] S14. Output the final result.

[0012] Preferably, the data flow analysis includes the following steps:

[0013] S21. Users initiate data analysis needs on the platform in an interactive dialogue manner;

[0014] S22, the platform receives the demand and forms a work task, which is processed by the task receiving agent;

[0015] S23, the agent inputs the task into the application assistant component of the platform large model; calls the trained application model for reasoning;

[0016] S24. Call the tools required for the task to assist in completing the task as needed;

[0017] S25. The intelligent agent outputs results based on the reasoning results of the large model, including generating reports, realizing automatic data docking, and changing data.

[0018] Preferably, the application initiated by the data applicant includes: using an interactive dialogue method, and clearly specifying the required data subject, content, type, frequency, and connection method.

[0019] Preferably, the large-model-based two-way data flow platform receives demands and forms work tasks, including: the data flow management agent performs reasoning based on the trained model to obtain the work tasks.

[0020] Preferably, the reasoning principles of the data flow management agent include:

[0021] S131. Based on the existing answers, the data requirements are automatically clarified into data sharing levels and types;

[0022] S132. If it is fully shared, analyze whether the data connection mode is satisfied; if satisfied, push the data application agent; otherwise, transfer the data demand to the data supply agent for review;

[0023] S133. If the supply agent cannot provide a result, it will be transferred to manual processing, and shared opinions will be given, and an updated data docking method will be provided.

[0024] Preferably, the tools required to invoke the task include API calls, database queries, and resources for providing additional information and execution capabilities.

[0025] Preferably, the flow modes output by the data flow management agent include: data exchange based on database; data exchange based on service integration; data exchange based on large file transfer.

[0026] Compared with the existing technology, the present invention makes the data transfer process more convenient and intelligent, improves the convenience and ease of operation, and realizes the rapid transfer of data. At the same time, it supports users to intuitively grasp the current and historical status of data transfer resources at any time, effectively displays the specific workflow and working status of the transfer, and achieves the purpose of auxiliary decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention is an overall architecture diagram of an embodiment of a big model-based data bidirectional flow platform and processing method. DETAILED DESCRIPTION

[0028] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0029] Example

[0030] like Figure 1 As shown, this embodiment provides a data bidirectional flow platform and processing method based on a large model.

[0031] See Figure 1 , a data bidirectional flow platform based on a large model in this embodiment, the platform mainly includes tasks, multifunctional intelligent agents, tool sets and data sets.

[0032] Among them, the two-way data flow platform based on the big model can realize directory management services, data exchange applications, user authority identification, automatic approval of suppliers, automatic matching and docking of data, automatic generation of data reports, generation of data flow visualization charts and data flow assistants.

[0033] The present embodiment provides a large model-based data bidirectional flow platform processing method, including a processing flow including data flow and data flow analysis.

[0034] The data flow includes the following steps:

[0035] S11. The data applicant initiates the application;

[0036] S12, the data two-way circulation platform based on the big model receives the demand and forms the work task;

[0037] S13, output the results according to the reasoning principle of the data flow management agent;

[0038] S14. Output the final result.

[0039] The data flow analysis includes the following steps:

[0040] S21. Users initiate data analysis needs on the platform in an interactive dialogue manner;

[0041] S22, the platform receives the demand and forms a work task, which is processed by the task receiving agent;

[0042] S23, the agent inputs the task into the application assistant component of the platform large model; calls the trained application model for reasoning;

[0043] S24. Call the tools required for the task to assist in completing the task as needed;

[0044] S25. The intelligent agent outputs results based on the reasoning results of the large model, including generating reports, realizing automatic data docking, and changing data.

[0045] The above-mentioned application initiated by the data applicant includes: adopting an interactive dialogue method and clearly specifying the required data subject, content, type, frequency, and connection method.

[0046] The above-mentioned large-model-based two-way data flow platform receives demands and forms work tasks, including: the data flow management agent performs reasoning based on the trained model to obtain work tasks.

[0047] The above-mentioned data flow management agent reasoning principles include:

[0048] S131. Based on the existing answers, the data requirements are automatically clarified into data sharing levels and types;

[0049] S132. If it is fully shared, analyze whether the data connection mode is satisfied; if satisfied, push the data application agent; otherwise, transfer the data demand to the data supply agent for review;

[0050] S133. If the supply agent cannot provide a result, it will be transferred to manual processing, and shared opinions will be given, and an updated data docking method will be provided.

[0051] Among them, the tools required to call the task include API calls, database queries, and resources used to provide additional information and execution capabilities.

[0052] Among them, the flow modes of the output of the data flow management intelligent body include: data exchange based on database; data exchange based on service integration; data exchange based on large file transfer.

[0053] The data transfer process of this embodiment is more convenient and intelligent, which improves the convenience and ease of operation and realizes the rapid transfer of data. At the same time, it supports users to intuitively grasp the current and historical status of data transfer resources at any time, effectively displays the specific workflow and working status of the transfer, and achieves the purpose of auxiliary decision-making.

[0054] It is easy to understand that those skilled in the art can combine, split, reorganize, etc. the embodiments of the present application to obtain other embodiments based on one or several embodiments provided in the present application, and these embodiments do not exceed the protection scope of the present application.

[0055] The present invention and its implementation methods are described schematically above, and the description is not restrictive. The embodiments shown in the embodiments are only part of the implementation methods of the present invention, and the actual structure is not limited thereto. Therefore, if a person skilled in the art is inspired by the embodiments and designs a structure and an implementation method similar to the technical solution without creativity without departing from the purpose of the invention, they should all fall within the protection scope of the present invention.

Claims

1. A two-way data transfer platform based on a large model, characterized in that: The platform mainly includes tasks, multifunctional agents, toolsets and data sets.

2. According to the big model-based two-way data transfer platform of claim 1, it is characterized in that: The big model-based two-way data flow platform can realize directory management services, data exchange applications, user authority identification, automatic approval of suppliers, automatic data matching and docking, automatic generation of data reports, generation of data flow visualization charts and data flow assistants.

3. A data bidirectional flow platform processing method based on a large model, characterized in that: Including processing procedures including data flow and data flow analysis.

4. According to the method for processing a large-model-based bidirectional data transfer platform according to claim 1, it is characterized in that: The data flow includes the following steps: S11. The data applicant initiates the application; S12, the data two-way circulation platform based on the big model receives the demand and forms the work task; S13, output the results according to the reasoning principle of the data flow management agent; S14. Output the final result.

5. According to the method for processing a large-model-based bidirectional data transfer platform according to claim 1, it is characterized in that: Data flow analysis includes the following steps: S21. Users initiate data analysis needs on the platform in an interactive dialogue manner; S22, the platform receives the demand and forms a work task, which is processed by the task receiving agent; S23, the agent inputs the task into the application assistant component of the platform large model; calls the trained application model for reasoning; S24. Call the tools required for the task to assist in completing the task as needed; S25. The intelligent agent outputs results based on the reasoning results of the large model, including generating reports, realizing automatic data docking, and changing data.

6. A method for processing a large-model-based bidirectional data transfer platform according to claim 4, characterized in that: The application initiated by the data applicant includes: adopting an interactive dialogue method and clearly specifying the required data subject, content, type, frequency, and connection method.

7. A method for processing a large-model-based bidirectional data transfer platform according to claim 4, characterized in that: The large-model-based two-way data flow platform receives demands and forms work tasks, including: the data flow management agent performs reasoning based on the trained model to obtain the work tasks.

8. The method for processing a large-model-based bidirectional data transfer platform according to claim 4, characterized in that: The reasoning principles of the data flow management agent include: S131. Based on the existing answers, the data requirements are automatically clarified into data sharing levels and types; S132. If it is fully shared, analyze whether the data connection mode is satisfied; if satisfied, push the data application agent; otherwise, transfer the data demand to the data supply agent for review; S133. If the supply agent cannot provide a result, it will be transferred to manual processing, and shared opinions will be given, and an updated data docking method will be provided.

9. The method for processing a large-model-based bidirectional data transfer platform according to claim 5, characterized in that: The tools required to invoke tasks include API calls, database queries, and resources that provide additional information and execution capabilities.

10. The method for processing a large-model-based bidirectional data transfer platform according to claim 5, characterized in that: The data flow management agent outputs flow modes including: data exchange based on database; data exchange based on service integration; data exchange based on large file transfer.

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