Document generation component system based on modular design

Abstract

The invention relates to the technical field of document generation, and discloses a document generation component system based on modular design. The document generation component system comprises a document demand analysis module, a module selection and evaluation module, a module loading and scheduling module and a performance optimization and feedback module. The invention discloses a modular design-based document generation component method. The method comprises the following steps of: receiving and analyzing document requirements, and determining required functional modules; evaluating module resource consumption, priority and efficiency gain, and selecting an optimal module for loading; dynamically loading the modules and unloading unnecessary modules; monitoring a document generation process in real time, feeding back a generation state and optimizing a loading strategy; and adjusting a loading sequence according to feedback, and optimizing resource allocation. The document generation component system based on modular design is adopted, module selection and scheduling are performed in combination with an optimization algorithm and a game theory model, the intelligent module loading and unloading process is achieved, unnecessary resource consumption and performance bottlenecks are avoided, and the generation efficiency and the utilization rate of system resources are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of document generation, and specifically provides a document generation component system based on modular design. Background Art

[0002] In the current field of document generation, traditional document generation systems usually adopt a fixed module design. During the document generation process, various modules are often statically loaded, that is, regardless of the actual requirements of the document, the system will load and execute in a preset manner. This method can work properly during the generation of simple documents, but when the document complexity increases, especially when dealing with tasks such as a large amount of data processing or chart generation, the system often faces problems such as excessive resource consumption and performance degradation.

[0003] Traditional document generation systems usually lack flexibility in module selection. Since the loading order and selection of modules are usually statically set, the system cannot dynamically select the functional modules to be loaded according to the different actual requirements of the document. This leads to the possible loading of many unnecessary modules during the document generation process, or the omission of the loading of some key modules, affecting the efficiency and quality of document generation.

[0004] In addition, the document generation systems in the prior art often do not effectively evaluate and optimize resource consumption and priorities. The loading and unloading of modules are usually fixed, without a real-time feedback mechanism. Especially during the generation of complex documents, some modules may occupy a large amount of resources due to large amounts of calculations or high data processing complexity, while other modules may not effectively release computing resources due to lighter generation tasks. This problem is difficult to solve in existing systems, resulting in resource waste and performance bottlenecks, affecting the fluency of the entire document generation process; moreover, traditional systems usually lack in-depth analysis of document requirements and complexity. Many systems rely on manual or preset rules to define the document type and required functional modules. This method not only reduces the adaptability and intelligence of the system, but also makes it difficult for the system to flexibly respond to different generation requirements brought about by changes in document content. The system can only select modules according to the set templates or fixed logic, and cannot dynamically adjust the loading order and type of modules according to the complexity and generation requirements of the actual document content. Therefore, those skilled in the art have proposed a document generation component system based on modular design to solve the above problems. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a document generation component system based on modular design, which solves problems such as resource waste and lack of flexibility in the prior art.

[0006] To achieve the above object, the present invention is realized by the following technical solutions: A document generation component system based on modular design, comprising: A document requirement analysis module, configured to analyze the type and generation requirements of the document to be generated, and determine the functional modules required in the document generation process; A module selection and evaluation module, configured to evaluate the resource consumption, priority, and generation efficiency of each module according to the analysis result of the document requirement analysis module, and adopt an optimal module loading strategy to select the modules to be loaded; A module loading and scheduling module, configured to dynamically load and unload the selected modules according to the output of the module selection and evaluation module, and perform module scheduling according to the usage of resources; A performance optimization and feedback module, configured to monitor the generation status after module loading, adjust the loading strategy in real time, optimize the module loading and unloading process, and ensure the high efficiency of document generation.

[0007] Preferably, the document requirement analysis module includes: A document type recognition unit, configured to analyze the type, content structure, and generation requirements of the document; A document complexity evaluation unit, configured to evaluate the complexity of the document, and determine the module types and functions required in the document generation process.

[0008] Preferably, the document type recognition unit further includes: A document structure analysis unit, configured to analyze the text type, data requirements, and formatting requirements of the document.

[0009] Preferably, the module selection and evaluation module includes: An optimal module loading strategy unit, configured to evaluate the loading schemes of each module based on optimization theory; A game theory evaluation unit, configured to calculate the Nash equilibrium solution of each module according to the game theory model, so as to determine the optimal module loading scheme; An information gain evaluation unit, configured to calculate the contribution of each module to document generation based on entropy and information gain in information theory, and preferentially load the module with the largest contribution.

[0010] Preferably, the game theory evaluation unit further includes: A module benefit calculation unit, configured to calculate the benefit after each module is loaded.

[0011] Preferably, the benefit calculation formula of the module benefit calculation unit is: u i (x 1 ,x 2 ,...,x n )=e i xi -r i x i ; Where: u i is the benefit of module i, representing the overall benefit brought by module i during the document generation process; e i is the efficiency gain of module i, representing the contribution of module i to the document generation efficiency; r i is the resource consumption of module i, representing the resources consumed when loading module i; x i is the decision variable for whether module i is loaded. x i = 1 means the module is loaded, x i = 0 means the module is not loaded.

[0012] Preferably, the module loading and scheduling module is used for: The dynamic loading unit is used to load the selected module according to the output of the module selection and evaluation module; The module unloading mechanism unit unloads the no-longer-needed modules during the document generation process according to the real-time generation requirements and resource usage conditions; The resource allocation optimization unit dynamically allocates computing resources through an optimization algorithm, avoids resource conflicts between modules, and ensures load balancing.

[0013] Preferably, the performance optimization and feedback module includes: The real-time monitoring unit is used to monitor the execution status, resource consumption situation, and document generation progress of each module; The feedback mechanism unit is used to adjust the module loading strategy according to the real-time monitoring results, optimize the loading order, and ensure the optimal utilization of system resources.

[0014] Preferably, the resource allocation optimization unit performs resource allocation by using the following optimization formula: Where: x i ∈ {0, 1} represents whether module i is loaded. x i = 1 means the module is loaded, x i = 0 means the module is not loaded; r i is the resource consumption of module i, representing the resources consumed when loading module i; p i is the priority of module i, representing the importance of this module for the document generation task; e i is the ability of module i to improve the document generation efficiency, representing the contribution of module i to improving the document generation efficiency; n represents the total number of modules.

[0015] A document generation component method based on modular design includes the following steps: S1. Receive the requirements of the document to be generated, analyze the document type and generation requirements, and determine the functional modules to be loaded; S2. Based on the resource consumption, priority, and efficiency gain of the module for the document requirements assessment, select the optimal module for loading; S3. According to the module selection result, dynamically load the module, and unload unnecessary modules according to the real-time resource usage; S4. Monitor the document generation process in real time, feedback the generation status, and optimize the module loading strategy according to the resource allocation and generation progress; S5. Adjust the module loading order according to the feedback result to optimize the allocation of system resources.

[0016] The present invention provides a document generation component system based on modular design. It has the following beneficial effects: 1. The present invention adopts a document generation component system based on modular design, combines the optimization algorithm and game theory model for module selection and scheduling, and achieves an intelligent module loading and unloading process; compared with the prior art of statically loading modules, the present invention avoids unnecessary resource consumption and performance bottlenecks by dynamically adjusting the module loading order, and greatly improves the generation efficiency and the utilization rate of system resources.

[0017] 2. By monitoring the execution status of each module in the document generation process in real time, the present invention provides real-time feedback and optimizes the module loading strategy, realizing the precise allocation of resources; different from the traditional manual configuration of module loading, the present invention can dynamically adjust the loading order according to the generation progress and resource consumption, ensuring that high-priority modules are executed first, thus effectively avoiding resource waste and system overload.

[0018] 3. The present invention adopts a document requirement analysis module to deeply analyze the document type and complexity, and selects the most suitable module for loading according to the requirements; compared with the prior art of loading modules through fixed templates or manual configuration, the intelligent analysis method of the present invention can flexibly adjust the module configuration according to the actual requirements of different documents, improving the flexibility and adaptability of the document generation process.

[0019] 4. The module loading and scheduling module of the present invention uses a feedback mechanism and a resource allocation optimization algorithm to dynamically adjust the timing of module loading and resource allocation, enabling the system to avoid resource conflicts and excessive consumption while efficiently executing document generation; compared with the prior art of static resource configuration, the dynamic adjustment scheme of the present invention greatly improves the stability and reliability of the system under high load. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the system architecture of the present invention; Figure 2Schematic diagram of the document requirement analysis module of the present invention; Figure 3 Schematic diagram of the document type recognition unit of the present invention; Figure 4 Schematic diagram of the module selection and evaluation module of the present invention; Figure 5 Schematic diagram of the game theory evaluation unit of the present invention; Figure 6 Schematic diagram of the module loading and scheduling module of the present invention; Figure 7 Schematic diagram of the performance optimization and feedback module of the present invention; Figure 8 Schematic diagram of the method flow of the present invention. Detailed implementation manners

[0021] Next, in combination with the accompanying drawings of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Please refer to the attached Figure 1 - attached Figure 7 , the embodiment of the present invention provides a document generation component system based on modular design, including: A document requirement analysis module, which is used to analyze the type and generation requirements of the document to be generated, and determine the functional modules required in the document generation process; Specifically, the document requirement analysis module plays a crucial role in the entire system; it is the starting point of the document generation component system based on modular design, and is used to analyze the type and generation requirements of the document to be generated. The output result of this module directly affects the subsequent module selection, loading, and optimization strategies. Therefore, ensuring the accurate analysis of document requirements is the key to the efficient operation of the system. According to the specific content and structure of the document, the document requirement analysis module can accurately identify the functional modules to be loaded, and provide guidance for the subsequent module loading and scheduling; through the analysis of the document type and complexity, this module accurately provides the required module set, laying a foundation for the entire document generation process.

[0023] The document requirement analysis module includes two core units: a document type recognition unit and a document complexity evaluation unit.

[0024] The document type recognition unit first analyzes the document to be generated. Generally, the document type can be recognized by performing natural language processing (NLP) analysis on the document content. Through text classification algorithms, the system can identify whether the document belongs to types such as reports, contracts, papers, advertisements, etc. According to the different document types, the system will selectively choose different functional modules. For example, if the document type is a "report", the system may need to select data analysis modules, chart generation modules, etc.; for a "contract" type document, functional modules such as legal clause analysis and formatting need to be selected.

[0025] The document type recognition unit uses text classification techniques to parse the document content. Text classification techniques include rule-based methods and machine learning-based methods. Machine learning methods such as support vector machines (SVM) and Naive Bayes classifiers can predict the type of the input document through pre-trained models. When performing document type analysis, these techniques can combine key information in the document (such as keywords, phrases, structural patterns, etc.) to make accurate classifications.

[0026] The document complexity assessment unit further conducts in-depth analysis on the structure and content of the document to evaluate the document complexity. The main task of the document complexity assessment unit is to judge the document complexity based on the document's hierarchical structure, text length, number of data tables, and the presence of a large number of complex charts. If the document contains a large number of data processing requirements (such as data tables, calculation tasks, etc.), then this module will evaluate the document as a high-complexity document and require loading more computing and data processing modules.

[0027] The complexity assessment unit uses a rule-based model or a deep learning-based model to perform complexity assessment. Through the rule engine, the system can automatically evaluate the complexity level of the document based on the document's structure. For example, if the document contains multiple data tables and complex mathematical calculation formulas, the system will evaluate it as a high-complexity document and load the necessary data processing modules. In practical applications, this assessment method can dynamically adjust the complexity of document generation according to changes in the document content, thereby determining which specific modules to load.

[0028] In addition, the document complexity assessment unit can also judge the document complexity by detecting special requirements in the document (such as chart generation, inserting large images, formula calculation, etc.). The complex requirements in the document directly affect the selection of subsequent modules. The system needs to rationally allocate resources according to the document complexity to ensure that system resources are not wasted and at the same time ensure the efficiency of document generation.

[0029] The complexity assessment unit can also calculate a complexity score to evaluate the processing requirements of the document. This score is based on various structural features in the document, comprehensively considering factors such as the number of words, the number of paragraphs, the number of data tables and charts in the document, etc., and outputs a numerical score, which is used to guide the subsequent module selection.

[0030] For example, if the complexity score is high, the system will automatically select some advanced data processing modules, such as data analysis modules, chart generation modules, etc., to ensure that all business requirements can be met when generating the document. When the complexity score is low, the system will reduce the loading of complex modules and preferentially select simple text generation modules to reduce resource consumption.

[0031] The key role of the document requirement analysis module is to accurately identify the type and complexity of the document, ensuring that the system can load the most suitable functional modules for the current document. By this method, the document generation component system can flexibly adjust module loading according to actual requirements, improving efficiency and reducing resource waste.

[0032] Through the accurate analysis of the document type and complexity, the system can load corresponding functional modules according to different types and complexities of documents; moreover, based on the document analysis, the system can avoid loading unnecessary modules, reducing resource waste; furthermore, different types and complexities of documents can be efficiently generated through different modules, enhancing the adaptability and scalability of the system.

[0033] The module selection and evaluation module is used to evaluate the resource consumption, priority, and generation efficiency of each module according to the analysis results of the document requirement analysis module, and adopt the optimal module loading strategy to select the modules to be loaded; Specifically, the module selection and evaluation module plays a decision-making support role in the entire document generation process; the main task of this module is to select appropriate functional modules based on the results output by the document requirement analysis module and evaluate them. Based on the document type, complexity, and required functions, the module selection and evaluation module evaluates the resource consumption, priority, and generation efficiency of each module through optimization algorithms, game theory models, and information theory analysis, and finally selects the most suitable module to be loaded. The selection of modules directly affects the efficiency of document generation and resource allocation. Therefore, this module occupies a core position in the entire system.

[0034] In the aforementioned document requirement analysis module, a document requirement description has been generated according to the document type and complexity. As input, the module selection and evaluation module will deeply evaluate each module based on these descriptions. According to these requirements, this module can intelligently select the most suitable functional module for the current document and make reasonable scheduling according to its performance in resource consumption, priority, and efficiency gain.

[0035] The module selection and evaluation module includes three core units: the optimal module loading strategy unit, the game theory evaluation unit, and the information gain evaluation unit.

[0036] The optimal module loading strategy unit evaluates the resource consumption, priority, and generation efficiency of each module according to the optimization theory, and selects the optimal module loading scheme based on these parameters. First, the system preliminarily evaluates parameters such as the performance, resource requirements, and execution time of each module, and combines the complexity of the actual generated document to propose a series of feasible module loading schemes.

[0037] Generally, module loading needs to meet the optimization of resource use and avoid high-resource-consuming modules competing with other modules for limited computing resources. Therefore, the optimization algorithm will consider the priority among modules and the ultimate goal of document generation. For example, if a certain module contributes much more to document generation than other modules, the system will load this module first and postpone the loading of modules with lower resource consumption.

[0038] The optimal module loading strategy unit will follow the formula: where: x i ∈{0,1} indicates whether module i is loaded. When x i =1, the module is loaded; when x i =0, the module is not loaded; r i is the resource consumption of module i, representing the resources consumed when loading module i; p i is the priority of module i, indicating the importance of this module for the document generation task; e i is the ability of module i to improve the document generation efficiency, representing the contribution of module i to improving the document generation efficiency; n represents the total number of modules.

[0039] Comprehensively evaluate the resource consumption r i , priority p i , and efficiency gain e i of each module i, and select appropriate modules for loading. Here, x i ∈{0,1} is the decision variable indicating whether the module is loaded. When x i =1, the module is loaded; when x i =0, the module is not loaded. The system selects the optimal module configuration by continuously optimizing the value of the objective function f(x).

[0040] The game theory evaluation unit further optimizes the module selection process by introducing the concept of Nash equilibrium in game theory. In this unit, the system regards each module as a participant, and the goal of the participant is to maximize its own benefit. The benefit of the module can be measured by the difference between its generation efficiency gain and resource consumption.

[0041] The benefit function of the module is expressed as: u i (x 1 , x 2 ,..., x n ) = e i x i -r i x i ; Where: u i is the benefit of module i, representing the overall benefit brought by module i during the document generation process; e i is the efficiency gain of module i, representing the contribution of module i to the document generation efficiency; r i is the resource consumption of module i, representing the resources consumed when loading module i; x i is the decision variable of whether to load module i. x i = 1 means the module is loaded, and x i = 0 means the module is not loaded.

[0042] Each module will make its own loading decision based on the current states of other modules to ensure the optimal allocation of resources.

[0043] The game theory evaluation unit ensures the reasonable allocation of computing resources among multiple modules by solving the Nash equilibrium of all modules, thus avoiding resource contention among modules. The benefit of each module is calculated under the condition of considering whether other modules are loaded or not. Only when the benefits of all modules cannot be improved by changing their own loading states will the equilibrium state of the game be reached.

[0044] The information gain evaluation unit further optimizes the loading decision of modules by calculating the contribution degree of each module. The system evaluates the contribution of each module to document generation based on the entropy and information gain principles in information theory, and preferentially selects those modules that can significantly improve the document generation efficiency. The calculation formula for information gain is: IG = H(Y) - H(Y|X); Where: IG represents the information gain, measuring the contribution of the module to the document generation task; H(Y) is the initial entropy of the document generation task, representing the initial uncertainty of document generation before loading any module; H(Y|X) is the conditional entropy given the module is loaded, representing the remaining uncertainty of the document generation task after loading a specific module.

[0045] The information gain IG measures the improvement of the system efficiency after the module is loaded. The loading decision of the module will be based on the magnitude of the information gain, and the module that contributes the most to the generation process will be preferentially loaded.

[0046] The information gain evaluation unit also comprehensively considers the interactions and collaboration methods between modules to further refine the module loading order and priority. For example, if there are data dependencies between certain modules, the system will ensure that these modules are loaded in the correct order to avoid calculation errors or resource waste caused by incorrect dependency relationships.

[0047] Through the comprehensive application of the optimal module loading strategy, game theory evaluation, and information gain, the module selection and evaluation module can intelligently select the optimal module loading scheme. This comprehensive evaluation method can not only improve the efficiency of document generation but also ensure the optimal use of system resources and avoid the loading of invalid modules and redundant calculations.

[0048] Through the comprehensive application of optimization algorithms, game theory, and information gain, the decision-making of module selection is more accurate, avoiding unnecessary module loading. Moreover, the game theory model ensures fair and efficient resource allocation between modules, avoiding resource conflicts and duplicate calculations. Additionally, the information gain evaluation unit ensures that the modules loaded by the system can maximize the document generation efficiency and reduce redundant work.

[0049] The module loading and scheduling module is used to dynamically load and unload the selected modules according to the output of the module selection and evaluation module and perform module scheduling based on the resource usage situation. Specifically, in the entire document generation component system based on modular design, the core task of the module loading and scheduling module is to intelligently load the required modules according to the output results of the aforementioned module selection and evaluation module and perform reasonable scheduling based on the resource usage situation. This module directly affects the resource usage efficiency and execution speed of the document generation process. Therefore, its design and implementation are crucial. The module loading and scheduling module is not only responsible for loading appropriate modules at different stages but also needs to manage the unloading and resource allocation of modules in real time during the document generation process to ensure that the system does not experience resource conflicts or performance bottlenecks while executing efficiently.

[0050] The document generation system needs to dynamically load different functional modules and perform scheduling based on the real-time resource usage situation. The design of the module loading and scheduling module considers two aspects: one is how to accurately load modules according to the output results of the module selection and evaluation module; the other is how to timely unload unnecessary modules according to the document generation progress and resource requirements to optimize the system's resource allocation. This process is achieved through a dynamic loading and unloading mechanism to ensure the efficiency of the document generation process.

[0051] The module loading and scheduling module includes three main units: the dynamic loading unit, the module unloading mechanism unit, and the resource allocation optimization unit.

[0052] The dynamic loading unit dynamically loads the selected module according to the module selection and the output of the evaluation module. The goal of dynamic loading is to accurately load the required module into the system based on system resources and document generation requirements. The loading of each module is based on the evaluation results output by the aforementioned module selection and evaluation module. Specifically, the loaded module will be determined according to factors such as the type of document, generation requirements, and module priority. For example, if a certain module is crucial for document generation, it will be loaded first; if a certain module has high resource consumption and low generation requirements, its loading will be postponed or its execution will be delayed.

[0053] The dynamic loading unit will screen out those functional modules that meet the current document requirements from the modules selected by the module selection and evaluation module and load them into the document generation system. These modules may include text processing modules, data processing modules, formatting modules, etc. During the loading process, the system will dynamically calculate resource consumption and generation time to ensure that the loaded modules can complete their work in the shortest time without affecting the overall operation efficiency of the system.

[0054] The module unloading mechanism unit is responsible for unloading unnecessary modules during document generation according to real-time generation requirements and resource usage. When a certain stage of document generation is completed, the system will remove the unnecessary modules from the memory in a timely manner through the unloading mechanism. The basis for unloading is the progress of document generation and the actual usage of each module. If some modules have completed their tasks during generation and will not affect the generation of subsequent stages, the system will automatically unload these modules to release resources for other modules to use.

[0055] For example, when document generation enters the formatting stage, the text generation module may have completed its work. At this time, the system can unload this module. The unloading mechanism monitors the execution status of each module in real time to determine whether it is still active or necessary. Through this dynamic unloading method, the system avoids modules that occupy computing resources for a long time and effectively improves resource utilization efficiency.

[0056] The resource allocation optimization unit dynamically adjusts the allocation of computing resources through an optimization algorithm to ensure that there are no conflicts in resource usage between modules. In some embodiments, the resource allocation optimization unit uses an algorithm to dynamically calculate the resource requirements of each module to ensure that computing resources are reasonably allocated to each module, avoiding some modules consuming excessive resources and causing resource shortages for other modules.

[0057] For example, if a certain module has high resource consumption, the system will automatically allocate more computing resources to this module to ensure its smooth execution. In addition, the system will also adjust the resource allocation in real time according to the execution situation of the module. If a certain module has completed its task and released resources, the system will reallocate these released resources to other running modules to ensure the efficiency and smoothness of the entire document generation process.

[0058] The resource allocation optimization unit optimizes the resource allocation through the following formula: where: x i ∈{0, 1} indicates whether module i is loaded. When x i = 1, the module is loaded; when x i = 0, the module is not loaded; r i is the resource consumption of module i, representing the resources consumed when loading module i; p i is the priority of module i, representing the importance of this module to the document generation task; e i is the ability of module i to improve the document generation efficiency, representing the contribution of module i to improving the document generation efficiency; n represents the total number of modules.

[0059] Through this formula, the system can evaluate the weight of each module in resource allocation and selectively load high-priority and high-benefit modules in case of resource shortage.

[0060] The resource allocation optimization unit also further optimizes the resource allocation by monitoring the real-time data of module execution (such as execution time, memory consumption, etc.). If a certain module shows high resource consumption during execution, the system will immediately make adjustments and reallocate computing resources to avoid resource conflicts between modules. In this way, the system can maximize the generation efficiency while maintaining the efficient use of computing resources.

[0061] The dynamic loading and unloading mechanism ensures that only necessary modules are loaded at the appropriate time, avoiding unnecessary modules from consuming system resources; and, through intelligent scheduling and resource optimization algorithms, the system can dynamically adjust the resource allocation to ensure that there is no resource contention between modules, greatly improving the resource utilization efficiency of the system; moreover, dynamically unloading unnecessary modules can release computing resources in a timely manner during the document generation process, improving the overall response speed of the system.

[0062] The performance optimization and feedback module is used to monitor the generation status after module loading, adjust the loading strategy in real time, and optimize the module loading and unloading process.

[0063] Specifically, in the entire document generation component system, the performance optimization and feedback module plays a crucial role in monitoring and adjustment; the main task of this module is to track each stage of the document generation process in real time and dynamically optimize the system based on real-time feedback. By monitoring the execution status, resource consumption, and document generation progress of the module, the system can promptly identify potential bottlenecks and adjust the module loading order and resource allocation strategy according to this feedback information, thus ensuring the efficient operation of the document generation process. The performance optimization and feedback module can not only optimize resource allocation but also ensure the stability and response speed of the system during operation.

[0064] The performance optimization and feedback module includes two core units: the real-time monitoring unit and the feedback mechanism unit.

[0065] The real-time monitoring unit is responsible for monitoring the execution status and resource usage of each module during the document generation process. During the document generation process, the execution status of each module may change. For example, when a certain module finishes execution or is in an idle state, the real-time monitoring unit will record these changes and feedback them to the feedback mechanism unit. Through real-time monitoring, the system can accurately understand the operation of each module and judge whether it is necessary to adjust the resource allocation or loading strategy based on this data.

[0066] The real-time monitoring unit forms a detailed monitoring report by collecting data such as the execution time, memory consumption, and CPU usage rate of the module. These reports provide the real-time operation of the module during the generation process. The system can adjust the loading order and resource allocation of subsequent modules based on this information. The real-time monitoring unit can not only record the operation status of the system but also provide the performance trend of the system, thus helping the system make reasonable optimization decisions during the document generation process.

[0067] The feedback mechanism unit dynamically adjusts the module loading order and resource allocation strategy based on the monitoring data provided by the real-time monitoring unit. In some cases, some modules may slow down the processing speed due to resource competition or heavy generation tasks. At this time, the feedback mechanism unit will promptly adjust the loading order and allocate resources to the modules that need to be processed first. For example, if a certain module occupies a large amount of resources due to complex calculation tasks, the system can make a temporary adjustment and delay the loading of other less urgent modules to ensure the smooth execution of the core module.

[0068] The feedback mechanism unit will also optimize the module loading timing based on the real-time monitoring data. For example, if the system detects that a certain module has completed a large amount of calculation tasks and no longer requires a large amount of calculation resources, the system will unload it and release the resources for other modules to use. At the same time, the system can optimize the module loading order according to the feedback data so that high-priority tasks can be executed first, avoiding low-priority modules from slowing down the overall generation progress.

[0069] The feedback mechanism unit dynamically adjusts the module loading strategy using an optimization algorithm by calculating the resource consumption and execution status of the computing module. This algorithm takes into account the requirements of the current document generation, the available system resources, and the dependencies between modules. For modules with high resource consumption, the system will adjust the resource allocation according to the feedback results to ensure that these modules can complete tasks in the shortest time. By continuously adjusting the resource allocation, the system can avoid excessive resource occupation to the greatest extent, thus avoiding the occurrence of performance bottlenecks.

[0070] The feedback mechanism unit can also adjust the system workload according to the progress of document generation. If the system is approaching the completion stage of document generation and the remaining tasks are relatively simple, the feedback mechanism unit can decide to temporarily suspend or delay the loading of those modules that are not urgently needed. The system can dynamically adjust the resource allocation according to the complexity of the document content to ensure that each stage of document generation can receive appropriate resource support.

[0071] Through real-time monitoring and feedback, the system can flexibly respond to resource requirements at different stages, avoiding unnecessary resource waste; moreover, by adjusting the loading order according to real-time data, it ensures that high-priority modules are processed first, improving the efficiency of document generation; furthermore, by adjusting the module loading timing and resource allocation, the system can maintain load balance throughout the document generation process, avoiding performance bottlenecks.

[0072] A method for document generation components based on modular design described below can be mutually referred to with a system for document generation components based on modular design described above.

[0073] Please refer to the appendix Figure 8 , a method for document generation components based on modular design, includes the following steps: S1. Receive the document requirements to be generated, analyze the document type and generation requirements, and determine the functional modules to be loaded; S2. Based on the document requirements, evaluate the resource consumption, priority, and efficiency gain of the modules, and select the optimal modules for loading; S3. Dynamically load the modules according to the module selection results, and unload unnecessary modules according to the real-time resource usage; S4. Real-time monitor the document generation process, feedback the generation status, and optimize the module loading strategy according to the resource allocation and generation progress; S5. Adjust the module loading order according to the feedback results to optimize the system resource allocation.

[0074] Specifically, in S1, the system receives the document requirements to be generated, analyzes the document type and generation requirements, and determines the functional modules to be loaded. In this step, the system receives the document requirements to be generated and conducts a preliminary analysis of the document. First, the system identifies the document type, such as reports, contracts, papers, or advertisements. Then, the system analyzes the generation requirements of the document, including functional requirements such as text generation, data processing, formatting, and chart generation. By analyzing the structure, content, and format requirements of the document, the system determines the functional modules to be loaded.

[0075] In S2, based on the resource consumption, priority, and efficiency gain of the document requirement evaluation module, the optimal module is selected for loading. After the document requirements are clear, the system evaluates the resource consumption, priority, and efficiency gain of each candidate module. Resource consumption includes metrics such as memory, CPU time, and I / O. Priority indicates the criticality of the module for document generation, and efficiency gain refers to the contribution of the module to improving the speed and quality of document generation. Based on these evaluations, the system selects the optimal module for loading. The selection criteria can include preferentially loading high-priority modules or selecting the module that most significantly improves the document generation efficiency.

[0076] In S3, according to the module selection result, the module is dynamically loaded, and unnecessary modules are unloaded based on the real-time resource usage situation. In this step, the system dynamically loads the module according to the previous module selection result. When the document generation enters different stages, the system selects and loads the corresponding module according to the requirements. At the same time, the system monitors the resource usage situation in real time. If some modules are no longer needed or have completed their tasks, the system will release the resources occupied by these modules in a timely manner through the unloading mechanism to avoid waste of resources.

[0077] In S4, the document generation process is monitored in real time, the generation status is fed back, and the module loading strategy is optimized according to the resource allocation and generation progress. In this step, the system monitors the execution status of each module in the document generation process in real time, tracks the progress of the generation task, and the resource consumption. The monitoring data includes the execution time, memory occupancy, and computing resource usage of each module. Based on these monitoring results, the system will give feedback and adjust the subsequent module loading strategy. If some modules execute too slowly, the system may preferentially allocate resources to these modules; if the resource consumption of some modules is too large, the system will adjust the loading order or postpone the loading.

[0078] S5. Adjust the module loading order according to the feedback results to optimize the allocation of system resources: Based on the real-time feedback results, the system will adjust the module loading order according to the progress of document generation and the actual requirements of the modules. For example, in the early stage of document generation, if the generation tasks of some modules are more complex, the system will load these modules first to ensure that they can complete the tasks in time. At the same time, the system will re-evaluate the resource requirements of each module and adjust the allocation of computing resources to ensure system load balancing.

[0079] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A document generation component system based on modular design, characterized in that: include: Document requirement analysis module, used to analyze the type and generation requirements of the document to be generated, and determine the functional modules required for the document generation process; The module selection and evaluation module is used to evaluate the resource consumption, priority and generation efficiency of each module based on the analysis results of the document requirement analysis module, and select the modules that need to be loaded by adopting the optimal module loading strategy; The module loading and scheduling module is used to dynamically load and unload selected modules according to the output of the module selection and evaluation module, and to schedule modules according to resource usage; The performance optimization and feedback module is used to monitor the generation status of the module after loading, adjust the loading strategy in real time, and optimize the loading and unloading process of the module.

2. A document generation component system based on modular design according to claim 1, characterized in that: The document requirement analysis module includes: Document type identification unit, used to analyze the document type, content structure and generation requirements; The document complexity assessment unit is used to assess the complexity of the document and determine the module types and functions required in the document generation process.

3. A document generation component system based on modular design according to claim 2, characterized in that: The document type identification unit further comprises: The document structure analysis unit is used to analyze the text type, data requirements and formatting requirements of the document.

4. A document generation component system based on modular design according to claim 1, characterized in that: The module selection and evaluation module includes: The optimal module loading strategy unit is used to evaluate the loading scheme of each module based on the optimization theory; A game theory evaluation unit is used to calculate the Nash equilibrium solution of each module according to the game theory model, so as to determine the optimal module loading solution; The information gain evaluation unit is used to calculate the contribution of each module to document generation based on entropy and information gain in information theory, and preferentially load the module with the greatest contribution.

5. A document generation component system based on modular design according to claim 4, characterized in that: The game theory evaluation unit further comprises: The module benefit calculation unit is used to calculate the benefit of each module after loading.

6. A document generation component system based on modular design according to claim 5, characterized in that: The benefit calculation formula of the module benefit calculation unit is: you i (x1,x2,...,x n )=e i x i -r i x i ; Where: u i is the benefit of module i, which indicates the overall benefit brought by module i in the document generation process; e i is the efficiency gain of module i, indicating the contribution of module i to the document generation efficiency; r i is the resource consumption of module i, indicating the resources consumed when loading module i; x i is the decision variable for whether module i is loaded, x i =1 module loading, x i =0 The module is not loaded.

7. A document generation component system based on modular design according to claim 1, characterized in that: The module loading and scheduling module is used to: A dynamic loading unit for loading the selected module based on the output of the module selection and evaluation module; The module uninstallation mechanism unit uninstalls modules that are no longer needed during document generation based on real-time generation requirements and resource usage; The resource allocation optimization unit dynamically allocates computing resources through optimization algorithms to avoid resource conflicts between modules and ensure load balancing.

8. A document generation component system based on modular design according to claim 1, characterized in that: The performance optimization and feedback module includes: Real-time monitoring unit, used to monitor the execution status, resource consumption and document generation progress of each module; The feedback mechanism unit is used to adjust the module loading strategy according to the real-time monitoring results, optimize the loading sequence, and ensure the optimal use of system resources.

9. A document generation component system based on modular design according to claim 6, characterized in that: The resource allocation optimization unit performs resource allocation by using the following optimization formula: Where: x i ∈{0,1} indicates whether module i is loaded, x i =1 module loading, x i =0 module is not loaded; r i is the resource consumption of module i, indicating the resources consumed when loading module i; p i is the priority of module i, indicating the importance of the module to the document generation task; i is the ability of module i to improve the efficiency of document generation, indicating the contribution of module i to improving the efficiency of document generation; n represents the total number of modules.

10. A document generation component method based on modular design, applied to a document generation component system based on modular design as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Receive the document requirements to be generated, analyze the document type and generation requirements, and determine the functional modules to be loaded; S2, evaluate the resource consumption, priority and efficiency gain of the modules based on the document requirements, and select the optimal module to load; S3, dynamically load modules according to the module selection result, and unload unnecessary modules according to the real-time resource usage; S4, monitor the document generation process in real time, feedback the generation status, and optimize the module loading strategy according to resource allocation and generation progress; S5. Adjust the module loading order according to the feedback results and optimize the allocation of system resources.

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