Langchain-based intelligent interactive Agent system and implementation method

Abstract

The invention discloses an intelligent interactive Agent system based on Langchain and an implementation method, and relates to the technical field of natural language processing and artificial intelligence. Comprising the steps of 1, establishing an intelligent interactive Agent system by using an interface and an integrated tool provided by a Langchain framework, 2, managing calling of various tool modules and services through a central scheduling module, and dynamically registering and unbinding the tool modules by using the interface provided by the Langchain framework, and 3, processing user input by using a large language model through a process management module, and establishing an intelligent interactive Agent system. 4, a series of tool modules are integrated through the integrated tool management module, the tool modules comprise a text search tool, a weather query tool and a video information acquisition tool, each tool module works independently or is in linkage with other tool modules, and the tool modules are connected with the integrated tool management module. And 5, managing a user interaction interface through a front-end management module, supporting a user to query and control in a natural language, displaying a processing progress and a processing result in real time, and providing feedback and help information.

Description

Technical Field

[0001] The present invention discloses a Langchain-based intelligent interactive Agent system and an implementation method, and relates to the technical fields of natural language processing and artificial intelligence. Background Art

[0002] With the rapid development of big data and artificial intelligence technologies, intelligent agent systems are becoming increasingly widely used in all walks of life. These systems greatly improve work efficiency and accuracy by automating complex information retrieval, data analysis, and daily task management. However, although existing intelligent agent technologies have made certain progress, there are still some significant limitations and challenges.

[0003] Many current intelligent agent systems still rely on predefined rules and limited processing logic, which makes them perform poorly when faced with non-standard problems or cross-domain tasks. In addition, these systems often lack effective mechanisms to integrate and utilize data from different sources, limiting the breadth and depth of their applications.

[0004] In addition, some intelligent agent systems have begun to use machine learning models to improve processing efficiency, but there is still much room for improvement in real-time data processing and efficient response. Especially in scenarios with large amounts of data and complex queries, the system's response time and data processing capabilities become bottlenecks that limit user experience. Summary of the invention

[0005] In view of the problems of the prior art, the present invention provides an intelligent interactive Agent system based on Langchain and an implementation method, which realizes efficient data processing and information services by dynamically integrating and calling multiple tools, such as search engines, databases, weather queries, etc. It adopts a modular design to support users to customize and expand Agent functions according to actual needs.

[0006] The specific scheme proposed by the present invention is:

[0007] The present invention provides a method for implementing an intelligent interactive Agent system based on Langchain, comprising:

[0008] Step 1: Use the interfaces and integration tools provided by the Langchain framework to establish an intelligent interactive Agent system, which includes a central scheduling module, a process management module, an integrated tool management module, and a front-end management module.

[0009] Step 2: The central scheduling module is responsible for managing the calls of various tool modules and services, and uses the interface provided by the Langchain framework to dynamically register and unbind tool modules.

[0010] Step 3: The process management module uses the large language model to process user input and, combined with contextual information, decides which tool modules or services to call to process data and respond to user queries.

[0011] Step 4: Integrate a series of tool modules through the integrated tool management module. The tool modules include text search tools, weather query tools, and video information acquisition tools. Each tool module works independently or in conjunction with other tool modules to complete the task together.

[0012] Step 5: Manage the user interaction interface through the front-end management module, support users to query and control in natural language, display processing progress and results in real time, and provide feedback and help information.

[0013] Furthermore, in step 2 of the implementation method of the Langchain-based intelligent interactive Agent system, a task dependency parsing and priority processing mechanism is established through a central scheduling module. When the intelligent interactive Agent system processes task dependencies, the execution order of tasks is reasonably arranged. At the same time, through the error handling and recovery mechanism, errors that may occur during execution are managed, and error recording, user notification, task retry or rollback are performed to ensure the stable operation of the intelligent interactive Agent system.

[0014] Furthermore, in step 3 of the implementation method of the intelligent interactive agent system based on Langchain, the query or command inputted from the user interaction interface is sent to the large language model through the process management module, and the semantic intent and key information of the text are parsed by the large language model.

[0015] Based on the analysis results, identify the core requirements and decompose the query or command corresponding operations into a series of manageable subtasks, arrange the execution order and dependencies for each subtask, and generate a detailed task execution plan.

[0016] According to the specific requirements of the subtask, select the most appropriate tool module or service registered in the intelligent interactive agent system for calling.

[0017] After each subtask is completed, collect their outputs, perform data synthesis and integration processing,

[0018] Use machine learning methods to analyze historical data and user feedback, and continuously optimize task decomposition algorithms, resource scheduling strategies, and tool module selection logic.

[0019] Furthermore, in step 4 of the implementation method of the Langchain-based intelligent interactive Agent system, a unified tool interface specification is defined by integrating the tool management module, including the implementation method and properties.

[0020] Register the tool module. When the intelligent interactive agent system is started or running, the new tool module is dynamically registered into the system. The registration information includes the name, version, interface definition, and dependency of the tool module.

[0021] Provide a visual configuration interface for each tool, through which the operating parameters of the tool can be modified. The configuration information is stored in the central configuration library for easy management and auditing, and the configuration parameters entered by the user are verified.

[0022] Perform performance monitoring on tool modules, record the number of calls, execution time, and success rate of each tool module, regularly evaluate monitoring data, identify performance bottlenecks or failure modes, and automatically optimize the configuration of tool modules based on monitoring data.

[0023] Furthermore, in step 5 of the implementation method of the Langchain-based intelligent interactive Agent system, the front-end management module is used to manage the layout of the user interaction interface, and the user interaction interface includes a query input area, an information display area, a tool control panel and a system feedback area.

[0024] The query input area supports text input and voice input modes, and the information display area displays output in text, chart, and video formats.

[0025] The integrated online help system provides a variety of help resources such as operation guides, FAQs and video tutorials. The help content covers all functional modules, which is convenient for users to check at any time. It also dynamically provides relevant help information based on the user's current interface status and operation history.

[0026] The present invention also provides an intelligent interactive Agent system based on Langchain, including a central scheduling module, a process management module, an integrated tool management module and a front-end management module.

[0027] The central scheduling module is responsible for managing the calls of various tool modules and services, and uses the interface provided by the Langchain framework to dynamically register and unbind tool modules.

[0028] The process management module uses a large language model to process user input and, combined with contextual information, decides which tool modules or services to call to process data and respond to user queries.

[0029] The integrated tool management module integrates a series of tool modules, including text search tools, weather query tools, and video information acquisition tools. Each tool module works independently or in conjunction with other tool modules to complete tasks together.

[0030] The front-end management module manages the user interaction interface, supports users to query and control in natural language, displays processing progress and results in real time, and provides feedback and help information.

[0031] Furthermore, the central scheduling module of the intelligent interactive Agent system based on Langchain establishes a task dependency parsing and priority processing mechanism. When the intelligent interactive Agent system processes task dependencies, it reasonably arranges the execution order of tasks. At the same time, through the error handling and recovery mechanism, it manages the errors that may occur during the execution, performs error recording, user notification, task retry or rollback, and ensures the stable operation of the intelligent interactive Agent system.

[0032] Furthermore, the process management module of the Langchain-based intelligent interactive agent system sends the query or command input from the user interaction interface to the large language model, and uses the large language model to parse the semantic intent and key information of the text.

[0033] Based on the analysis results, identify the core requirements and decompose the query or command corresponding operations into a series of manageable subtasks, arrange the execution order and dependencies for each subtask, and generate a detailed task execution plan.

[0034] According to the specific requirements of the subtask, select the most appropriate tool module or service registered in the intelligent interactive agent system for calling.

[0035] After each subtask is completed, collect their outputs, perform data synthesis and integration processing,

[0036] Use machine learning methods to analyze historical data and user feedback, and continuously optimize task decomposition algorithms, resource scheduling strategies, and tool module selection logic.

[0037] Furthermore, the integrated tool management module of the Langchain-based intelligent interactive agent system defines a unified tool interface specification, including implementation methods and properties.

[0038] Register the tool module. When the intelligent interactive agent system is started or running, the new tool module is dynamically registered into the system. The registration information includes the name, version, interface definition, and dependency of the tool module.

[0039] Provide a visual configuration interface for each tool, through which the operating parameters of the tool can be modified. The configuration information is stored in the central configuration library for easy management and auditing, and the configuration parameters entered by the user are verified.

[0040] Perform performance monitoring on tool modules, record the number of calls, execution time, and success rate of each tool module, regularly evaluate monitoring data, identify performance bottlenecks or failure modes, and automatically optimize the configuration of tool modules based on monitoring data.

[0041] Furthermore, the front-end management module of the Langchain-based intelligent interactive Agent system manages and layouts the user interaction interface, which includes a query input area, an information display area, a tool control panel and a system feedback area.

[0042] The query input area supports text input and voice input modes, and the information display area displays output in text, chart, and video formats.

[0043] The integrated online help system provides a variety of help resources such as operation guides, FAQs and video tutorials. The help content covers all functional modules, which is convenient for users to check at any time. It also dynamically provides relevant help information based on the user's current interface status and operation history.

[0044] The benefits of the method of the present invention are:

[0045] Make the system flexible and extensible: The system adopts a modular design concept, allowing independent tool modules to be easily added or replaced without affecting existing functions. This design enables the system to quickly adapt to new business needs or technical changes; by implementing a dynamic tool registration and management mechanism, the system can integrate new tools and services at runtime and provide continuous functional expansion support.

[0046] Improve data processing efficiency and accuracy: The intelligent scheduler in the system can dynamically allocate computing resources and optimize the order of task execution according to the complexity and priority of the task, thereby greatly improving processing efficiency; using advanced natural language processing technology and large language models, the system can accurately understand and process user requests, reduce error rates, and improve data processing accuracy.

[0047] Enhanced user interaction experience: By designing an easy-to-use graphical user interface, the system simplifies complex operations, allowing users to interact in an intuitive way and lowering the usage threshold; the system provides real-time feedback and dynamic interaction functions, which enhances the user's operating experience, allowing users to instantly see the operation results and system status, and improves user satisfaction.

[0048] Optimized resource utilization and cost-effectiveness: Intelligent resource management and task scheduling not only improve the system's operating efficiency, but also optimize the use of hardware resources and reduce operating costs; the system's high degree of automation and intelligence reduces the need for manual intervention, reducing labor costs and operational errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic flow chart of the method of the present invention.

[0050] Figure 2 It is a schematic diagram of the tool integration framework of the present invention. DETAILED DESCRIPTION

[0051] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0052] Example 1

[0053] The present invention provides a method for implementing an intelligent interactive Agent system based on Langchain, comprising:

[0054] Step 1: Use the interfaces and integration tools provided by the Langchain framework to establish an intelligent interactive Agent system, which includes a central scheduling module, a process management module, an integrated tool management module, and a front-end management module.

[0055] Step 2: The central scheduling module is responsible for managing the calls of various tool modules and services, and uses the interface provided by the Langchain framework to dynamically register and unbind tool modules.

[0056] In step 2, the central scheduling module can schedule the pre-processing module to clean, format and integrate the incoming raw data, ensuring that the data meets the basic processing requirements before being input into the application layer, such as data type unification and missing value processing.

[0057] The central scheduling module is used to parse user requests, schedule task execution, manage resource allocation, etc. The central scheduling module intelligently allocates system resources and optimizes task execution efficiency according to the type, priority and resource requirements of the task; and based on the Langchain framework, the tools and services in the system are modularized according to different functions. Each module has independent functions and interfaces, which can be dynamically loaded and unloaded through configuration, and registered with the central scheduler to ensure that it can be scheduled.

[0058] At the same time, a task dependency parsing and priority processing mechanism is established through the central scheduling module. When the intelligent interactive Agent system processes task dependencies, the execution order of tasks is reasonably arranged. At the same time, through the error handling and recovery mechanism, errors that may occur during execution are managed, and error records, user notifications, task retries or rollbacks are performed to ensure the stable operation of the intelligent interactive Agent system.

[0059] Step 3: The process management module uses a large language model to process user input and, combined with contextual information, decides which tool modules or services to call to process data and respond to user queries.

[0060] Step 4: Integrate a series of tool modules through the integrated tool management module. The tool modules include text search tools, weather query tools, and video information acquisition tools. Each tool module works independently or in conjunction with other tool modules to complete the task together.

[0061] Step 5: Manage the user interaction interface through the front-end management module, support users to query and control in natural language, display processing progress and results in real time, and provide feedback and help information.

[0062] Example 2

[0063] Based on Example 1, step 3 is suitable for understanding user needs, intelligently scheduling tasks, performing specific operations, and providing feedback.

[0064] The query or command input from the user interface is sent to the large language model through the process management module, and the large language model is used to parse the semantic intent and key information of the text.

[0065] Based on the analysis results, the core requirements are identified and the query or command operations are decomposed into a series of manageable subtasks. The execution order and dependencies are arranged for each subtask, and a detailed task execution plan is generated. The plan takes into account the data dependencies, resource requirements and priorities between tasks to ensure efficient and reasonable resource allocation.

[0066] Through the process management module, according to the specific needs of the subtask, the most appropriate tool module or service registered in the intelligent interactive agent system is selected for calling. For example, data query may use database access tools, while data visualization may call chart generation tools. For tasks that can be processed in parallel, the system performs intelligent scheduling based on resource availability to shorten the overall response time. At the same time, the resource consumption of each task is monitored, and resource allocation is dynamically adjusted to avoid resource conflicts and bottlenecks.

[0067] After each subtask is completed, the process management module collects the outputs of each task, performs data synthesis and integration, and can further include resolving data conflicts, format conversion, and information aggregation. According to the nature of the task and the needs of the user, the processing results are organized into easy-to-understand formats, such as report documents, charts, or direct replies. The generated output is presented to the user through the user interface, and interactive options are provided to collect user feedback. Based on the feedback, the system further optimizes the processing flow and tool configuration to improve user satisfaction and system performance.

[0068] Through the process management module, we use machine learning methods to analyze historical data and user feedback, and continuously optimize the task decomposition algorithm, resource scheduling strategy, and tool module selection logic.

[0069] Example 3

[0070] Based on Example 2, step 4 is applicable to the key components of the intelligent Agent system, which encapsulates external tools or services into independent modules, defines a unified calling interface and data exchange format, and ensures that the system can flexibly expand new functions and improve the efficiency of existing functions.

[0071] The unified tool interface specification is defined through the integrated tool management module, including the implementation methods and properties, such as execution entry, configuration parameters and output format. This specification ensures that all tools can be smoothly integrated and called in the Agent system; each tool is encapsulated as an independent module with its own configuration files and dependency libraries. The modular design allows each tool to be updated and maintained independently without affecting other parts of the system.

[0072] The tool module registration is performed through the integrated tool management module. When the intelligent interactive agent system is started or running, the new tool module is dynamically registered into the system. The registration information includes the name, version, interface definition, and dependency of the tool module. The dynamic loading and unloading function of the development tool allows the system administrator to add new tools or remove old tools without restarting the system. This function can be realized based on advanced class loading technology and runtime programming technology.

[0073] Provide a visual configuration interface for each tool, through which the operating parameters of the tool can be modified. The configuration information is stored in the central configuration library for easy management and auditing, and the configuration parameters entered by the user are verified to ensure the correctness and security of the parameters. When the tool configuration changes, the system automatically notifies the affected tasks to readjust the execution strategy.

[0074] Perform performance monitoring on tool modules, record the number of calls, execution time, and success rate of each tool module, regularly evaluate monitoring data, identify performance bottlenecks or failure modes, and automatically optimize the configuration of tool modules based on monitoring data, such as adjusting concurrency levels, modifying timeout settings, etc. In addition, the system can automatically select the best tool combination to perform specific tasks based on the performance of the tools.

[0075] Example 4

[0076] Based on Example 3, a friendly user interaction interface is provided in step 5, which supports users to query and control in natural language, displays processing progress and results in real time, and provides feedback and help information. Through real-time data processing and dynamic feedback mechanism, the user's interactive experience and the overall performance of the system are greatly improved. In addition, through the comprehensive help system, even novice users can quickly master the use of the system, effectively reducing the learning cost.

[0077] The front-end management module is used to manage the layout of the user interaction interface, which includes the query input area, information display area, tool control panel and system feedback area. Such a layout can help users quickly understand the operation mode and content organization of the interface; the responsive design principle is adopted to ensure that the interface can maintain a good user experience on different devices, such as desktops, tablets, and mobile phones. Interface elements such as buttons, input boxes and display panels need to be automatically adjusted according to the screen size.

[0078] The query input area supports text input and voice input modes, and the information display area displays output in text, chart, and video formats. For example, the query input area supports multiple modes such as text input and voice input; the information display area can display output in multiple formats such as text, chart, and video; and implements dynamic interaction logic, such as input suggestions, real-time search result preview, drag and drop functions, etc., to improve the interactivity of the interface and user convenience.

[0079] The integrated online help system provides a variety of help resources such as operation guides, FAQs and video tutorials. The help content covers all functional modules, which is convenient for users to check at any time. It also dynamically provides relevant help information based on the user's current interface status and operation history. For example, when a user stays in a complex functional module for too long, the operation guide of the module will automatically pop up.

[0080] Example 2

[0081] The present invention also provides an intelligent interactive Agent system based on Langchain, including a central scheduling module, a process management module, an integrated tool management module and a front-end management module.

[0082] The central scheduling module is responsible for managing the calls of various tool modules and services, and uses the interface provided by the Langchain framework to dynamically register and unbind tool modules.

[0083] The process management module uses a large language model to process user input and, combined with contextual information, decides which tool modules or services to call to process data and respond to user queries.

[0084] The integrated tool management module integrates a series of tool modules, including text search tools, weather query tools, and video information acquisition tools. Each tool module works independently or in conjunction with other tool modules to complete tasks together.

[0085] The front-end management module manages the user interaction interface, supports users to query and control in natural language, displays processing progress and results in real time, and provides feedback and help information.

[0086] As the information interaction and execution process between the modules of the above-mentioned system are based on the same concept as the embodiment of the method of the present invention, the specific contents can be found in the description of the embodiment of the method of the present invention and will not be repeated here.

[0087] Likewise, the benefits of the system of the present invention are:

[0088] Make the system flexible and extensible: The system adopts a modular design concept, allowing independent tool modules to be easily added or replaced without affecting existing functions. This design enables the system to quickly adapt to new business needs or technical changes; by implementing a dynamic tool registration and management mechanism, the system can integrate new tools and services at runtime and provide continuous functional expansion support.

[0089] Improve data processing efficiency and accuracy: The intelligent scheduler in the system can dynamically allocate computing resources and optimize the order of task execution according to the complexity and priority of the task, thereby greatly improving processing efficiency; using advanced natural language processing technology and large language models, the system can accurately understand and process user requests, reduce error rates, and improve data processing accuracy.

[0090] Enhanced user interaction experience: By designing an easy-to-use graphical user interface, the system simplifies complex operations, allowing users to interact in an intuitive way and lowering the usage threshold; the system provides real-time feedback and dynamic interaction functions, which enhances the user's operating experience, allowing users to instantly see the operation results and system status, and improves user satisfaction.

[0091] Optimized resource utilization and cost-effectiveness: Intelligent resource management and task scheduling not only improve the system's operating efficiency, but also optimize the use of hardware resources and reduce operating costs; the system's high degree of automation and intelligence reduces the need for manual intervention, reducing labor costs and operational errors.

[0092] It should be noted that not all steps and modules in the above-mentioned processes and system structures are necessary, and some steps or modules can be ignored according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The system structure described in the above-mentioned embodiments can be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or some components in multiple independent devices may be implemented together.

[0093] The above-described embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or changes made by those skilled in the art based on the present invention are within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. A method for implementing an intelligent interactive agent system based on Langchain, characterized by: include: Step 1: Use the interfaces and integration tools provided by the Langchain framework to establish an intelligent interactive Agent system, which includes a central scheduling module, a process management module, an integrated tool management module, and a front-end management module. Step 2: The central scheduling module is responsible for managing the calls of various tool modules and services, and uses the interface provided by the Langchain framework to dynamically register and unbind tool modules. Step 3: The process management module uses the large language model to process user input and, combined with contextual information, decides which tool modules or services to call to process data and respond to user queries. Step 4: Integrate a series of tool modules through the integrated tool management module. The tool modules include text search tools, weather query tools, and video information acquisition tools. Each tool module works independently or in conjunction with other tool modules to complete the task together. Step 5: Manage the user interaction interface through the front-end management module, support users to query and control in natural language, display processing progress and results in real time, and provide feedback and help information.

2. According to claim 1, a method for implementing an intelligent interactive Agent system based on Langchain is characterized in that In step 2, the task dependency parsing and priority processing mechanism is established through the central scheduling module. When the intelligent interactive Agent system processes task dependencies, the execution order of tasks is reasonably arranged. At the same time, through the error handling and recovery mechanism, errors that may occur during execution are managed, and error records, user notifications, task retries or rollbacks are performed to ensure the stable operation of the intelligent interactive Agent system.

3. According to claim 1, the method for implementing the Langchain-based intelligent interactive Agent system is characterized by: In step 3, the query or command input by the user interface is sent to the large language model through the process management module, and the large language model is used to parse the semantic intent and key information of the text. Based on the analysis results, identify the core requirements and decompose the query or command corresponding operations into a series of manageable subtasks, arrange the execution order and dependencies for each subtask, and generate a detailed task execution plan. According to the specific requirements of the subtask, select the most appropriate tool module or service registered in the intelligent interactive agent system for calling. After each subtask is completed, collect their outputs, perform data synthesis and integration processing, Use machine learning methods to analyze historical data and user feedback, and continuously optimize task decomposition algorithms, resource scheduling strategies, and tool module selection logic.

4. According to claim 1, the method for implementing the Langchain-based intelligent interactive Agent system is characterized by: In step 4, a unified tool interface specification is defined through the integrated tool management module, including the implementation methods and properties. Register the tool module. When the intelligent interactive agent system is started or running, the new tool module is dynamically registered into the system. The registration information includes the name, version, interface definition, and dependency of the tool module. Provide a visual configuration interface for each tool, through which the operating parameters of the tool can be modified. The configuration information is stored in the central configuration library for easy management and auditing, and the configuration parameters entered by the user are verified. Perform performance monitoring on tool modules, record the number of calls, execution time, and success rate of each tool module, regularly evaluate monitoring data, identify performance bottlenecks or failure modes, and automatically optimize the configuration of tool modules based on monitoring data.

5. According to claim 1, the method for implementing the Langchain-based intelligent interactive Agent system is characterized by: In step 5, the front-end management module is used to manage and layout the user interaction interface, which includes a query input area, an information display area, a tool control panel, and a system feedback area. The query input area supports text input and voice input modes, and the information display area displays output in text, chart, and video formats. The integrated online help system provides a variety of help resources such as operation guides, FAQs and video tutorials. The help content covers all functional modules, which is convenient for users to check at any time. It also dynamically provides relevant help information based on the user's current interface status and operation history.

6. An intelligent interactive agent system based on Langchain, characterized by Including central scheduling module, process management module, integrated tool management module and front-end management module, The central scheduling module is responsible for managing the calls of various tool modules and services, and uses the interface provided by the Langchain framework to dynamically register and unbind tool modules. The process management module uses a large language model to process user input and, combined with contextual information, decides which tool modules or services to call to process data and respond to user queries. The integrated tool management module integrates a series of tool modules, including text search tools, weather query tools, and video information acquisition tools. Each tool module works independently or in conjunction with other tool modules to complete tasks together. The front-end management module manages the user interaction interface, supports users to query and control in natural language, displays processing progress and results in real time, and provides feedback and help information.

7. According to claim 6, the intelligent interactive Agent system based on Langchain is characterized by: The central scheduling module establishes a task dependency parsing and priority processing mechanism. When the intelligent interactive Agent system processes task dependencies, it reasonably arranges the execution order of tasks. At the same time, through the error handling and recovery mechanism, it manages the errors that may occur during execution, performs error recording, user notification, task retry or rollback, and ensures the stable operation of the intelligent interactive Agent system.

8. According to claim 6, the intelligent interactive Agent system based on Langchain is characterized by: The process management module sends the query or command input from the user interface to the large language model, and uses the large language model to parse the semantic intent and key information of the text. Based on the analysis results, identify the core requirements and decompose the query or command corresponding operations into a series of manageable subtasks, arrange the execution order and dependencies for each subtask, and generate a detailed task execution plan. According to the specific requirements of the subtask, select the most appropriate tool module or service registered in the intelligent interactive agent system for calling. After each subtask is completed, collect their outputs, perform data synthesis and integration processing, Use machine learning methods to analyze historical data and user feedback, and continuously optimize task decomposition algorithms, resource scheduling strategies, and tool module selection logic.

9. According to claim 6, the intelligent interactive Agent system based on Langchain is characterized in that The integrated tool management module defines a unified tool interface specification, including implementation methods and properties. Register the tool module. When the intelligent interactive agent system is started or running, the new tool module is dynamically registered into the system. The registration information includes the name, version, interface definition, and dependency of the tool module. Provide a visual configuration interface for each tool, through which the operating parameters of the tool can be modified. The configuration information is stored in the central configuration library for easy management and auditing, and the configuration parameters entered by the user are verified. Perform performance monitoring on tool modules, record the number of calls, execution time, and success rate of each tool module, regularly evaluate monitoring data, identify performance bottlenecks or failure modes, and automatically optimize the configuration of tool modules based on monitoring data.

10. According to claim 6, a Langchain-based intelligent interactive Agent system is characterized in that the front-end management module manages the layout of the user interaction interface, and the user interaction interface includes a query input area, an information display area, a tool control panel and a system feedback area. The query input area supports text input and voice input modes, and the information display area displays output in text, chart, and video formats. The integrated online help system provides a variety of help resources such as operation guides, FAQs and video tutorials. The help content covers all functional modules, which is convenient for users to check at any time. It also dynamically provides relevant help information based on the user's current interface status and operation history.

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