Intelligent agent automatic generation method and system based on large language model

Abstract

The invention provides an intelligent agent automatic generation method and system based on a large language model. The method comprises the steps that a page is created according to a component requirement and a page requirement input by a user, a component is generated, and configuration parameters are set; analyzing the interface document through a large language model, generating page components according to the component knowledge base, and binding and combining the page components, configuration information of the components and interaction behaviors through a translator; initializing a configuration interaction behavior; configuring behavior conditions of the interaction behaviors, selecting data sources of the components, and modularly rendering a system page according to configuration information of the page components; generating a page layout according to the generation mode of the combined page of the business requirements and the input natural language and the page generation mode, and binding the interactive behavior information to generate a system page; and customizing the storage mode of the intelligent agent. The method depends on a memory unit mechanism, is driven by a large model, assembles personalized application pages according to requirements and automatically executes task requirements, and has a higher-level automatic generation technology.

Description

Technical Field

[0001] The present invention relates to the technical field of generative intelligent agents and large language models, and in particular to a method and system for automatically generating an intelligent agent based on a large language model. Background Art

[0002] With the rapid development of enterprise digitalization and the wave of digital transformation, enterprises have an increasing demand for rapid iteration and efficient development. Enterprise digital development platforms have rapidly emerged, which not only reduces development costs but also simplifies the development process, giving non-technical personnel unprecedented thinking space and creativity, and quickly responding to market changes. It has promoted enterprise digitalization to a new peak era. Therefore, under the current model, enterprise digitalization and AI technology have emerged. However, in the existing technology of enterprise platform digitalization, the process of building visual application pages through dragging and dropping is not simple enough, and business logic is difficult to adapt automatically. It can only configure components or page behaviors, and there are still certain problems in the configuration of various interactive behavior logics.

[0003] In order to solve the above problems, this application proposes a method and system for automatically generating intelligent agents based on a large language model, constructs a visual application page in the form of drag and drop, and automatically generates intelligent agents in combination with natural language. It continuously iterates and stores each step of the constructed behavior configuration information to form a rich knowledge base, allowing the enterprise digital development platform to complete the setting of various interactive behavior logics through the automatic generation capability of natural language configuration. Summary of the invention

[0004] The present invention proposes the following technical solutions to address one or more technical deficiencies in the above-mentioned prior art.

[0005] Based on the first aspect of the present invention, a method for automatically generating an intelligent agent based on a large language model is proposed, comprising:

[0006] S1: Create a page and automatically generate components according to the component requirements and page requirements input by the user, obtain component configuration information and set configuration parameters, and then store the component configuration information in the component knowledge base;

[0007] S2: parsing the interface document through a large language model, generating page components according to the component knowledge base, and binding and combining the page components, the configuration information of the components and the interactive behaviors through a translator;

[0008] S3: Initialize the configuration of the interactive behavior, including customizing logical expressions and regular expressions;

[0009] S4: configuring the behavior conditions of the interactive behavior and selecting the data source of the component, and performing modular rendering on the system page according to the configuration information of the page component;

[0010] S5: combining the page generation mode according to the business requirements, automatically generating the page layout according to the input natural language and the page generation mode, and binding the interactive behavior information to generate the system page;

[0011] S6: Customize the storage mode of the agent.

[0012] Storing component configuration information in the knowledge base can continuously generate automation logic and expand the knowledge base.

[0013] Furthermore, the components include a page component, a drag and drop component, and a create page component;

[0014] The automatic generation of components includes creating the layout, style and properties of the components.

[0015] Furthermore, the configuration information of the components includes the addition and modification of page fields, and the interaction behaviors between components;

[0016] The configuration information of the page component includes component name, component type, component data and component fields.

[0017] Automatically generating page layout configuration information through natural language allows users to customize page configuration plans and generate a variety of page templates.

[0018] Furthermore, the page components are elements that make up the page layout, and render the data of the page by accessing data services from different sources.

[0019] Furthermore, the step S2 also includes binding the page component to an API interface and a data service, specifically including:

[0020] S201: Acquire data configuration information of a data service agent and a data model agent and generate a source of the data configuration information;

[0021] S202: Acquire the data configuration information, select a data service through natural language, and generate the data source of the component;

[0022] S203: generating the component field according to the data source of the component;

[0023] S204: Generate a page component by combining the data source of the component, the component and the component field.

[0024] Furthermore, the modular rendering of the system page according to the configuration information of the page component specifically includes: the page component generates a combination of the configuration information of the component and the configuration information of the page layout through natural language, creates a page through natural language, and renders the page layout and the interaction behavior between the page components according to the custom set page function requirement expression, regular expressions and comparison operators.

[0025] By customizing the conditional settings of interactive behaviors and selecting appropriate component data sources for modular rendering, not only can development costs be reduced, but development efficiency is also improved, and a diverse combination of page component layouts can be achieved.

[0026] Furthermore, the storage mode specifically outputs the configuration information of the component through natural language, uses the name of the component configuration as the component name of the component, uses the data source of the component as the component data, uses the page layout configuration template to perform page layout rendering, renders the component data according to the data service configuration, and binds the interactive behavior between the component and the page according to the interactive behavior information, and then stores the interactive behavior information and the component configuration information.

[0027] The knowledge base storage mode is used to store relevant configuration information generated by different configuration schemes, and the page templates and knowledge base are continuously enriched, so that users can quickly build their own enterprise digital intelligent applications.

[0028] Furthermore, the storage mode of the intelligent agent specifically includes a component generation storage mode, a page generation storage mode, a component data binding configuration information storage mode, a page component layout mode and a page rendering layout mode.

[0029] Based on the second aspect of the present invention, a system for automatically generating an intelligent agent based on a large language model is also proposed, comprising:

[0030] Component module: creates pages and automatically generates components according to component requirements and page requirements input by users, obtains component configuration information and sets configuration parameters, and then stores the component configuration information in the component knowledge base;

[0031] Binding module: parsing the interface document through a large language model, generating page components according to the component knowledge base, and binding and combining the page components, the configuration information of the components and the interactive behaviors through a translator;

[0032] Initialization configuration module: Initialization configuration of the interaction behavior, including custom setting of logical expressions and regular expressions;

[0033] Rendering module: configures the behavior conditions of the interactive behavior and selects the data source of the component, and performs modular rendering of the system page according to the configuration information of the page component;

[0034] Generation module: combines page generation modes according to business requirements, automatically generates page layout according to input natural language and the page generation mode, and binds interactive behavior information to generate system pages;

[0035] Storage module: Customize the storage mode of the agent.

[0036] Based on the third aspect of the present invention, a computer program product is also proposed, comprising a computer program, wherein when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0037] The technical effect of the present invention is that: the present invention proposes a method and system for automatically generating intelligent entities based on a large language model, which relies on the automatic generation capability of natural language, continuously iterates the interactive behavior configuration information and forms a rich component knowledge base, which reduces the development cost while shortening the development cycle and improving the development efficiency. Users can build their own enterprise digital intelligent applications in real time, automatically create application pages according to different needs of users, and realize diversified combinations of page components. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Other features, objects and advantages of the present application will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings.

[0039] Figure 1 It is an overall flow chart of a method for automatically generating an intelligent agent based on a large language model provided according to an embodiment of the present invention.

[0040] Figure 2 It is a specific flow chart of binding API interface and data service of page components of an intelligent agent automatic generation method based on a large language model provided according to an embodiment of the present invention.

[0041] Figure 3 It is a framework diagram of an intelligent agent automatic generation system based on a large language model provided according to an embodiment of the present invention.

[0042] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0043] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings.

[0044] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] Figure 1 1 is a general flow chart of a method for automatically generating an intelligent agent based on a large language model according to an embodiment of the present invention, comprising the following steps:

[0046] S1: Create a page and automatically generate components according to the component requirements and page requirements input by the user, obtain component configuration information and set configuration parameters, and then store the component configuration information in the component knowledge base;

[0047] S2: parsing the interface document through a large language model, generating page components according to the component knowledge base, and binding and combining the page components, the configuration information of the components and the interactive behaviors through a translator;

[0048] S3: Initialize the configuration of the interactive behavior, including customizing logical expressions and regular expressions;

[0049] S4: configuring the behavior conditions of the interactive behavior and selecting the data source of the component, and performing modular rendering on the system page according to the configuration information of the page component;

[0050] S5: combining the page generation mode according to the business requirements, automatically generating the page layout according to the input natural language and the page generation mode, and binding the interactive behavior information to generate the system page;

[0051] S6: Customize the storage mode of the agent.

[0052] It should be noted that storing the configuration information of the components in the component knowledge base can enable the knowledge base to be continuously expanded and the automation logic to be continuously generated.

[0053] It should be noted that the components include page components, drag and drop components and create page components;

[0054] The automatic generation of components includes creating the layout, style and properties of the components.

[0055] It should be noted that the configuration information of the components includes the addition and modification of page fields, and the interaction between components;

[0056] The configuration information of the page component includes component name, component type, component data and component fields.

[0057] In a specific embodiment, MySQL, Impala, Dor IS, HTTP services and ES browser are used as data sources accessed by page components.

[0058] In a specific embodiment, the data accessed by the page component comes from the collaboration of other systems, and the system from which the data comes serves as an intelligent entity of the data service.

[0059] In a specific embodiment, the user can customize the data configuration information, set the conditions of the data configuration information and other interactive behaviors, adjust the conditions according to business needs, and then automatically update the page components bound to the data service.

[0060] It should be noted that after the natural language generation data is configured for visualization and the interactive behavior is configured, the conditions of the interactive behavior are set, and then the data source of the component is selected, and modular data rendering is performed in the generated system page.

[0061] It should be noted that the page components are elements that make up the page layout, and the data of the page is rendered by accessing data services from different sources.

[0062] It should be noted that the step S2 also includes binding the page component to the API interface and data service, such as Figure 2 As shown, specifically including:

[0063] S201: Acquire data configuration information of a data service agent and a data model agent and generate a source of the data configuration information;

[0064] S202: Acquire the data configuration information, select a data service through natural language, and generate the data source of the component;

[0065] S203: generating the component field according to the data source of the component;

[0066] S204: Generate a page component by combining the data source of the component, the component and the component field.

[0067] In a specific embodiment, data source configuration information is generated according to natural language as the data output field of the component, which facilitates the control of the component layer information, as well as user management and adjustment of the sequence and layout style of page components.

[0068] It should be noted that the modular rendering of the system page according to the configuration information of the page component specifically includes: the page component generates a combination of the configuration information of the component and the configuration information of the page layout through natural language, creates a page through natural language, and renders the page layout and the interaction between the page components according to the custom set page function requirement expression, regular expressions and comparison operators.

[0069] It should be noted that the storage mode specifically outputs the configuration information of the component through natural language, uses the name of the component configuration as the component name of the component, uses the data source of the component as the component data, uses the page layout configuration template to perform page layout rendering, renders the component data according to the data service configuration, and binds the interactive behavior between the component and the page according to the interactive behavior information, and then stores the interactive behavior information and the component configuration information.

[0070] It should be noted that the storage mode of the intelligent agent specifically includes a component generation storage mode, a page generation storage mode, a component data binding configuration information storage mode, a page component layout mode and a page rendering layout mode.

[0071] It should be noted that an intelligent agent refers to a system that can perceive the environment, make decisions and take actions. It can adjust its behavior according to changes in the environment, has autonomy, adaptability, interactivity and learning ability, makes decisions independently and does not rely on external instructions; it can adjust its behavior according to environmental changes and maintain effectiveness; it can communicate and cooperate with the environment and other intelligent agents, extract useful information from massive data through learning algorithms and data analysis, form its own knowledge base, and optimize the decision-making process through continuous experience accumulation to improve the efficiency of task completion.

[0072] In a specific embodiment, the logical interaction behavior of the component is automatically generated and configured according to natural language, and the page component module and the page automatically generate related configuration information to store and generate configuration information. When the natural language recognizes the relevant configuration information, the interaction behavior is triggered, and further judged whether the interaction behavior and the component configuration information are consistent according to the regular expression and the conditions of the interaction behavior. If the interaction behavior is consistent with the component configuration information, the component will be automatically configured according to the corresponding configuration information. Otherwise, if the interaction behavior does not conform to the component configuration information, the component will not be configured.

[0073] It should be noted that using the present invention to create different intelligent entities can deeply integrate different systems and services, form a cooperative ecosystem between different systems and flexibly combine and generate page modes according to business needs.

[0074] It should be noted that the present invention automatically generates component configuration information, page layout information and interactive behavior information through natural language automatic generation capabilities, thereby simplifying the development process of enterprise digital application pages, shortening the development cycle of application pages, and realizing diversified combinations of page component layouts. In addition, page layout configuration information is generated through natural language for users to customize and select configuration plans, providing more page templates for application pages.

[0075] Figure 3 A framework diagram of an intelligent agent automatic generation system based on a large language model is shown, which specifically includes a component module a, a binding module b, an initialization configuration module c, a rendering module d, a generation module e and a storage module f.

[0076] In a specific embodiment, the component module a is configured to: create a page and automatically generate a component according to the component requirements and page requirements input by the user, obtain component configuration information and set configuration parameters, and then store the component configuration information in a component knowledge base.

[0077] In a specific embodiment, the binding module b is configured to: parse the interface document through a large language model, generate page components according to the component knowledge base, and bind and combine the page components, the configuration information and interactive behaviors of the components through a translator.

[0078] In a specific embodiment, the initialization configuration module c is configured to: perform initialization configuration on the interactive behavior, including customizing logical expressions and regular expressions.

[0079] In a specific embodiment, the rendering module d is configured to: configure the behavior conditions of the interactive behavior and select the data source of the component, and modularly render the system page according to the configuration information of the page component.

[0080] In a specific embodiment, the generation module e is configured to: combine page generation modes according to business needs, automatically generate page layout according to the input natural language and the page generation mode, and bind interactive behavior information to generate a system page.

[0081] In a specific embodiment, the storage module f is configured as: a storage mode of a custom agent.

[0082] It should be noted that the intelligent agent refers to a system that can autonomously perceive the environment, make decisions and execute actions. It has autonomy, interactivity, responsiveness and adaptability. By adding the ability to plan, think, remember and use tools, it can autonomously complete complex tasks.

[0083] It should be noted that the large language model is a deep learning model that learns language patterns, semantics and grammar through a large amount of text data in the field of natural language processing to understand and generate human language.

[0084] It should be noted that, in the present invention, the realization of the intelligent agent relies on a large language model, which enables the intelligent agent to understand and process complex environmental information and make reasonable decisions.

[0085] Reference below Figure 4 , which shows a schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0086] like Figure 4 As shown, the computer system includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage part 408 into a random access memory (RAM) 403. Various programs and data required for system operation are also stored in the RAM 403. The CPU 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0087] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.

[0088] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above functions defined in the method of the present application are executed. It should be noted that the computer-readable storage medium of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, - but not limited to - a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wireline, optical cable, RF, etc., or any suitable combination of the foregoing.

[0089] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0090] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0091] The modules involved in the embodiments of the present application may be implemented by software or hardware.

[0092] As another aspect, the present application also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment; or it may exist independently without being assembled into the electronic device. The above computer-readable storage medium carries one or more programs. When the above one or more programs are executed by the electronic device, the electronic device: creates a page according to the component requirements and page requirements input by the user, generates components and sets configuration parameters; parses the interface document through a large language model, generates page components according to the component knowledge base, and binds and combines page components, component configuration information and interactive behaviors through a translator; initializes and configures interactive behaviors; configures the behavioral conditions of the interactive behaviors and selects the data source of the components, and modularly renders the system page according to the configuration information of the page components; combines the generation mode of the page according to business needs, generates the page layout according to the input natural language and page generation mode, and binds the interactive behavior information to generate the system page; customizes the storage mode of the intelligent body.

[0093] Finally, it should be noted that the above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above invention concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A method for automatically generating an intelligent agent based on a large language model, characterized in that: include: S1: Create a page and automatically generate components according to the component requirements and page requirements input by the user, obtain component configuration information and set configuration parameters, and then store the component configuration information in the component knowledge base; S2: parsing the interface document through a large language model, generating page components according to the component knowledge base, and binding and combining the page components, the configuration information of the components and the interactive behaviors through a translator; S3: Initialize the configuration of the interactive behavior, including customizing logical expressions and regular expressions; S4: configuring the behavior conditions of the interactive behavior and selecting the data source of the component, and performing modular rendering on the system page according to the configuration information of the page component; S5: combining the page generation mode according to the business requirements, automatically generating the page layout according to the input natural language and the page generation mode, and binding the interactive behavior information to generate the system page; S6: Customize the storage mode of the agent.

2. The method according to claim 1, characterized in that The components include page components, drag and drop components and create page components; The automatic generation of components includes creating the layout, style and properties of the components.

3. The method according to claim 1, characterized in that The configuration information of the components includes the addition and modification of page fields, and the interaction between components; The configuration information of the page component includes component name, component type, component data and component fields.

4. The method according to claim 1, characterized in that The page components are elements that make up the page layout, and render the page data by accessing data services from different sources.

5. The method according to claim 1, characterized in that: The step S2 also includes binding the page component to an API interface and a data service, specifically including: S201: Acquire data configuration information of a data service agent and a data model agent and generate a source of the data configuration information; S202: Acquire the data configuration information, select a data service through natural language, and generate the data source of the component; S203: generating the component field according to the data source of the component; S204: Generate a page component by combining the data source of the component, the component and the component field.

6. The method according to claim 1, characterized in that The modular rendering of the system page according to the configuration information of the page component specifically includes: the page component generates a combination of the configuration information of the component and the configuration information of the page layout through natural language, creates a page through natural language, and renders the page layout and the interaction behavior between the page components according to the custom set page function requirement expression, regular expressions and comparison operators.

7. The method according to claim 1, characterized in that The storage mode specifically outputs the configuration information of the component through natural language, uses the name of the component configuration as the component name of the component, uses the data source of the component as the component data, uses the page layout configuration template to perform page layout typesetting and rendering, renders the component data according to the data service configuration, and binds the interactive behavior between the component and the page according to the interactive behavior information, and then stores the interactive behavior information and the component configuration information.

8. The method according to claim 1, characterized in that The storage mode of the intelligent agent specifically includes a component generation storage mode, a page generation storage mode, a component data binding configuration information storage mode, a page component layout mode and a page rendering layout mode.

9. An agent automatic generation system based on a large language model, characterized in that: include: Component module: creates pages and automatically generates components according to component requirements and page requirements input by users, obtains component configuration information and sets configuration parameters, and then stores the component configuration information in the component knowledge base; Binding module: parsing the interface document through a large language model, generating page components according to the component knowledge base, and binding and combining the page components, the configuration information of the components and the interactive behaviors through a translator; Initialization configuration module: Initialization configuration of the interaction behavior, including custom setting of logical expressions and regular expressions; Rendering module: configures the behavior conditions of the interactive behavior and selects the data source of the component, and performs modular rendering of the system page according to the configuration information of the page component; Generation module: combines page generation modes according to business requirements, automatically generates page layout according to input natural language and the page generation mode, and binds interactive behavior information to generate system pages; Storage module: Customize the storage mode of the agent.

10. A computer program product, comprising a computer program, characterized in that The computer program implements the steps of the method according to any one of claims 1 to 8 when executed by a processor.

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