Intelligent assistant cooperation platform based on large language model and AI Agent

Abstract

The invention relates to the technical field of artificial intelligence, in particular to an intelligent assistant cooperation platform based on a large language model and an AI Agent. Comprising a multi-Agent cooperation mechanism module, a function integration and extension module, a self-adaptive adjustment mechanism module, a high-efficiency data processing module, an intelligent content creation module, a short video creation sub-module and an interactive user interface module, the multi-Agent cooperation mechanism module supports cooperation and interaction among a plurality of AI Agents, task processing is achieved through role specialization and task delegation, and the interaction of the AI Agents is achieved. Each Agent can automatically allocate and execute tasks according to own speciality and task requirements; the platform comprises a plurality of Agent modules with independent functions and task processing capability, and data exchange and task coordination are carried out among the Agent modules through a communication protocol. The method has the advantages that the cooperation efficiency is high, efficient cooperation work among multiple intelligent assistants is achieved through role specialization and task delegation by means of a multi-Agent cooperation mechanism, and the cooperation efficiency is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and specifically to an intelligent assistant collaboration platform based on a large language model and AI Agent. Background Art

[0002] With the rapid development of artificial intelligence (AI) technology, AI agents have been widely used in numerous fields. Through learning and interaction, AI agents can automatically complete complex tasks and provide intelligent decision-making and predictions. However, in the field of intelligent assistants, there are many pressing issues that need to be addressed, such as:

[0003] Low collaboration efficiency: Most existing intelligent assistants operate independently and lack effective collaboration mechanisms, making it difficult to achieve efficient collaboration between multiple assistants.

[0004] Single function: The function is relatively single and cannot meet the diverse needs of enterprises and individual users;

[0005] Poor adaptability: Existing intelligent assistants lack adaptability to different usage scenarios and needs, and have difficulty automatically adjusting their behavior.

[0006] Limited data processing capabilities: Existing intelligent assistants are inefficient when processing large-scale, complex data and have difficulty extracting valuable information quickly and accurately.

[0007] Low content creation efficiency: In terms of content creation, such as document summarization, PPT generation, and short video creation, there is a lack of efficient support tools, which cannot meet users' needs for quickly generating high-quality content. Summary of the Invention

[0008] The purpose of the present invention is to solve the problems in the above-mentioned background technology and provide an intelligent assistant collaboration platform based on a large language model and AI Agent, which is characterized by including a multi-agent collaboration mechanism module, a function integration and expansion module, an adaptive adjustment mechanism module, an efficient data processing module, an intelligent content creation module, a short video creation sub-module, and an interactive user interface module. The multi-agent collaboration mechanism module supports collaboration and interaction between multiple AI Agents, realizes task processing through role specialization and task delegation, and each Agent can automatically allocate and execute tasks according to its own expertise and task requirements; the platform includes multiple Agent modules with independent functions and task processing capabilities, and each Agent module exchanges data and coordinates tasks through a communication protocol;

[0009] The function integration and expansion module integrates multiple functional modules such as document processing, schedule management, short video creation, document editing, data analysis, etc. to meet diverse needs. It also supports users to add new functional modules through plug-ins or API interfaces according to their own needs. It adopts a modular design, and each functional module can run and expand independently;

[0010] The adaptive adjustment mechanism module enables the platform to automatically adjust the agent's behavior and task allocation according to environmental changes and user needs. The platform is equipped with an environmental monitoring module to collect environmental data in real time and feed it back to the agent. The agent automatically adjusts its task processing strategy and behavior mode according to changes in environmental data.

[0011] The efficient data processing module uses distributed computing and parallel processing technologies to improve data processing efficiency and ensures fast data reading and processing by optimizing data storage and management methods. The platform sets up a distributed computing framework to distribute data processing tasks to multiple computing nodes for parallel execution. At the same time, it uses efficient data storage and indexing technologies to improve data reading and writing speed and query efficiency.

[0012] The intelligent content creation module includes:

[0013] The submodule that automatically summarizes documents and generates PPTs integrates an AI document processing module that can automatically read and analyze user-uploaded documents, extract key information, and generate PPT outlines. It uses natural language processing technology to convert document content into structured PPT content. The platform is equipped with a document processing module that supports uploading and processing multiple document formats, and can automatically extract key information and generate PPT outlines.

[0014] The short video creation submodule supports automated tasks related to short video creation, including automatic topic selection, automatic copywriting, and automatic video publishing. It uses AI to analyze hot topics and trends to provide short video topics and generate copy, and supports scheduled video publishing to mainstream social media platforms. The platform is equipped with a short video creation module that includes topic analysis, copywriting, and video publishing functions, supporting one-click generation and publishing of short videos.

[0015] The interactive user interface module is designed with an interactive user interface, through which users can input data, adjust parameters, view task progress and results to achieve human-computer collaborative decision-making; the user interface includes a data input module, a parameter adjustment module, a task progress display module and a result display module.

[0016] Preferably, in the multi-agent collaboration mechanism module, the communication protocol is a custom protocol or an existing general communication protocol, which is used to ensure accurate and efficient data transmission and task coordination between agent modules.

[0017] Preferably, in the functional integration and expansion module, the newly added functional modules can realize data sharing and interaction with the existing functional modules after being connected to the platform, and jointly serve the user needs.

[0018] Preferably, in the adaptive adjustment mechanism module, the data collected by the environment monitoring module includes but is not limited to network status, user operation habit data, and external system data interface status data.

[0019] Preferably, in the efficient data processing module, the distributed computing framework adopts one or more combinations of distributed computing frameworks such as MapReduce and Spark, and the data storage adopts one or more combinations of technologies such as distributed file system and column storage.

[0020] Preferably, in the intelligent content creation module, the sub-module that automatically summarizes documents and generates PPTs has targeted information extraction and outline generation strategies for different types of documents; the short video creation sub-module comprehensively considers multi-platform data and user portrait data when analyzing hot topics and trends.

[0021] Preferably, in the interactive user interface module, the data input module supports multiple input methods such as voice input and text input, and the task progress display module displays the task execution status in multiple forms such as visual charts and progress bars.

[0022] The beneficial effects of the present invention are:

[0023] High collaboration efficiency: Through role specialization and task delegation, and with the help of a multi-agent collaboration mechanism, efficient collaboration between multiple intelligent assistants is achieved, significantly improving collaboration efficiency.

[0024] Diverse functions: It integrates multiple functional modules and supports function expansion to meet the diverse needs of enterprises and individual users;

[0025] Strong adaptability: Through the adaptive adjustment mechanism, it can quickly adapt to new data and environmental changes, improving the robustness and adaptability of the system;

[0026] Strong data processing capabilities: Distributed computing and parallel processing technologies are used to improve data processing efficiency and ensure fast data reading and processing;

[0027] High content creation efficiency: Supports automatic summary of documents to generate PPT and short video creation related automation work, greatly improving content creation efficiency;

[0028] Good interactivity: Design an interactive user interface to achieve human-computer collaborative decision-making and improve the system's practicality and user experience.

[0029] Obviously, based on the above contents of the present invention, according to common technical knowledge and customary means in this field, without departing from the above basic technical ideas of the present invention, other various forms of modifications, replacements or changes can be made.

[0030] The following further describes the above content of the present invention in detail through specific embodiments in the form of examples. However, this should not be construed as limiting the scope of the above subject matter of the present invention to the following examples. All technologies implemented based on the above content of the present invention fall within the scope of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of the structure of the intelligent assistant collaboration platform of the present invention. DETAILED DESCRIPTION

[0032] The present invention is described below with specific examples, which are not intended to limit the present invention.

[0033] An intelligent assistant collaboration platform based on a large language model and AI Agent, including a multi-agent collaboration mechanism module, a function integration and expansion module, an adaptive adjustment mechanism module, an efficient data processing module, an intelligent content creation module, a short video creation sub-module, an interactive user interface module, a multi-agent collaboration mechanism module, and supports multiple AI The collaboration and interaction between agents realizes task processing through role specialization and task delegation. Each agent can automatically allocate and execute tasks according to its own expertise and task requirements. The platform contains multiple agent modules with independent functions and task processing capabilities. Each agent module exchanges data and coordinates tasks through communication protocols. The function integration and extension module integrates multiple functional modules such as document processing, schedule management, short video creation, document editing, data analysis, etc. to meet diverse needs, and supports users to add new functional modules through plug-ins or API interfaces according to their own needs. With modular design, each functional module can run and expand independently. The adaptive adjustment mechanism module can automatically adjust the agent's behavior and task allocation according to environmental changes and user needs. The platform is equipped with an environmental monitoring module to collect environmental data in real time and feed it back to the agent. The agent automatically adjusts the task processing strategy and behavior mode according to changes in environmental data. The efficient data processing module uses distributed computing and parallel processing technology to improve data processing efficiency and ensures fast data reading and processing by optimizing data storage and management methods. The platform sets up distributed The computing framework distributes data processing tasks to multiple computing nodes for parallel execution, while using efficient data storage and indexing technologies to improve data reading and writing speeds and query efficiency. The intelligent content creation module includes: a sub-module for automatically summarizing documents and generating PPTs, an integrated AI document processing module that can automatically read and analyze user-uploaded documents, extract key information, and generate PPT outlines, and use natural language processing technology to convert document content into structured PPT content. The platform is equipped with a document processing module that supports uploading and processing multiple document formats, and can automatically extract key information and generate PPT outlines. The short video creation sub-module supports automation related to short video creation, including automatic topic selection, automatic copywriting, and automatic video publishing. It uses AI to analyze hot topics and trends to provide short video topics and generate copy, and supports scheduled video publishing to mainstream social media platforms. The platform has a short video creation module that includes topic analysis, copy generation, and video publishing functions, supporting one-click generation and publishing of short videos. The interactive user interface module is designed with an interactive user interface through which users can input data, adjust parameters, and view task progress and results to achieve human-computer collaborative decision-making.The user interface includes a data input module, a parameter adjustment module, a task progress display module, and a result display module. In the multi-agent collaboration mechanism module, the communication protocol is either a custom protocol or an existing general communication protocol, ensuring accurate and efficient data transmission and task coordination between agent modules. In the function integration and expansion module, newly added functional modules, after being connected to the platform, can share and interact with existing functional modules to jointly serve user needs. In the adaptive adjustment mechanism module, the data collected by the environmental monitoring module includes, but is not limited to, network status, user operation habits, and external system data interface status data. In the efficient data processing module, the distributed computing framework uses one or more combinations of distributed computing frameworks such as MapReduce and Spark, and data storage uses one or more combinations of technologies such as distributed file systems and columnar storage. In the intelligent content creation module, the submodule that automatically summarizes documents and generates PPTs has targeted information extraction and outline generation strategies for different document types. The short video creation submodule comprehensively considers multi-platform data and user profile data when analyzing hot topics and trends. In the interactive user interface module, the data input module supports multiple input methods such as voice input and text input. The task progress display module displays task execution status in various forms, such as visual charts and progress bars.

[0034] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0035] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention specification under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.

[0036] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent assistant collaboration platform based on a large language model and AI Agent, characterized by: The platform includes a multi-agent collaboration mechanism module, a function integration and expansion module, an adaptive adjustment mechanism module, an efficient data processing module, an intelligent content creation module, a short video creation sub-module, and an interactive user interface module. The multi-agent collaboration mechanism module supports collaboration and interaction between multiple AI agents, and realizes task processing through role specialization and task delegation. Each agent can automatically allocate and execute tasks based on its own expertise and task requirements. The platform contains multiple agent modules with independent functions and task processing capabilities. The agent modules exchange data and coordinate tasks through communication protocols. The function integration and expansion module integrates multiple functional modules such as document processing, schedule management, short video creation, document editing, data analysis, etc. to meet diverse needs. It also supports users to add new functional modules through plug-ins or API interfaces according to their own needs. It adopts a modular design, and each functional module can run and expand independently; The adaptive adjustment mechanism module enables the platform to automatically adjust the agent's behavior and task allocation according to environmental changes and user needs. The platform is equipped with an environmental monitoring module to collect environmental data in real time and feed it back to the agent. The agent automatically adjusts its task processing strategy and behavior mode according to changes in environmental data. The efficient data processing module uses distributed computing and parallel processing technologies to improve data processing efficiency and ensures fast data reading and processing by optimizing data storage and management methods. The platform sets up a distributed computing framework to distribute data processing tasks to multiple computing nodes for parallel execution. At the same time, it uses efficient data storage and indexing technologies to improve data reading and writing speed and query efficiency. The intelligent content creation module includes: The submodule that automatically summarizes documents and generates PPTs integrates an AI document processing module that can automatically read and analyze user-uploaded documents, extract key information, and generate PPT outlines. It uses natural language processing technology to convert document content into structured PPT content. The platform is equipped with a document processing module that supports uploading and processing multiple document formats, and can automatically extract key information and generate PPT outlines. The short video creation submodule supports automated tasks related to short video creation, including automatic topic selection, automatic copywriting, and automatic video publishing. It uses AI to analyze hot topics and trends to provide short video topics and generate copy, and supports scheduled video publishing to mainstream social media platforms. The platform is equipped with a short video creation module that includes topic analysis, copywriting, and video publishing functions, supporting one-click generation and publishing of short videos. The interactive user interface module is designed with an interactive user interface, through which users can input data, adjust parameters, view task progress and results to achieve human-computer collaborative decision-making; the user interface includes a data input module, a parameter adjustment module, a task progress display module and a result display module.

2. The intelligent assistant collaboration platform based on a large language model and AI Agent according to claim 1, characterized in that: In the multi-agent collaboration mechanism module, the communication protocol is a custom protocol or an existing general communication protocol, which is used to ensure accurate and efficient data transmission and task coordination between agent modules.

3. The intelligent assistant collaboration platform based on a large language model and AI Agent according to claim 1, characterized in that: In the functional integration and expansion module, the newly added functional modules can realize data sharing and interaction with the existing functional modules after being connected to the platform, and jointly serve the user needs.

4. The intelligent assistant collaboration platform based on a large language model and AI Agent according to claim 1, characterized in that: In the adaptive adjustment mechanism module, the data collected by the environment monitoring module includes but is not limited to network status, user operation habit data, and external system data interface status data.

5. The intelligent assistant collaboration platform based on a large language model and AI Agent according to claim 1, characterized in that: In the efficient data processing module, the distributed computing framework adopts one or more combinations of distributed computing frameworks such as MapReduce and Spark, and the data storage adopts one or more combinations of technologies such as distributed file system and column storage.

6. The intelligent assistant collaboration platform based on a large language model and AI Agent according to claim 1, characterized in that: In the intelligent content creation module, the sub-module that automatically summarizes documents and generates PPTs has targeted information extraction and outline generation strategies for different types of documents; the short video creation sub-module comprehensively considers multi-platform data and user portrait data when analyzing hot topics and trends.

7. The intelligent assistant collaboration platform based on a large language model and AI Agent according to claim 1, characterized in that: In the interactive user interface module, the data input module supports multiple input methods such as voice input and text input, and the task progress display module displays the task execution status in multiple forms such as visual charts and progress bars.

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