SaaS station building platform system integrated with AIGC function and building method of SaaS station building platform system

Abstract

The invention discloses an SaaS website building platform system integrated with an AIGC function and a building method of the SaaS website building platform system, and relates to the technical field of website building. Comprising a demand analysis and architecture design module, a multi-modal AIGC engine module, a distributed calculation and real-time generation module, a modular design and data security module, a user interaction and editing module, a system test and optimization module and a deployment and online module. Diversified requirements are met; distributed calculation and real-time generation are carried out, and high-concurrency and low-delay content generation is ensured through a distributed architecture and a GPU acceleration technology; modular design and data security are achieved, a micro-service architecture is adopted, independent deployment and expansion of functional modules are supported, and meanwhile data security is guaranteed; user interaction and intelligent recommendation provide a visual interaction interface and an intelligent recommendation function, and improve user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of website construction, and particularly relates to a SaaS website construction platform system integrating AIGC function and a construction method thereof. Background Art

[0002] The SaaS (Software as a Service) website construction platform system is a website construction tool based on cloud computing. Users can access and use it simply through a browser without the need to download or install software. Such platforms usually provide modular functions to help users quickly build and manage websites, and are applicable to various scenarios such as enterprises, individuals, and e-commerce.

[0003] According to the application publication number: CN117873456A - A modular website construction management system, which records that "through an independent working operation mode, each module can work independently. Even if a single group of modules fails, it does not affect the operation of the entire system. When each group of modules reaches full load, the system will automatically start another group of modules, so as to ensure that the output of the system always matches the actual demand, ensure the efficient operation of each module and save resources, and improve efficiency". From this, those skilled in the art know that each module in the reference patent works independently and cannot achieve the load balancing of the entire system, which affects the high efficiency of the system operation; not only that, the data security of the system is not well managed and controlled, thus affecting the reliability of the system operation.

[0004] In summary, it is necessary to design a SaaS website construction platform system integrating AIGC function and a construction method thereof. Summary of the Invention

[0005] In order to overcome the above deficiencies, the present invention provides a SaaS website construction platform system integrating AIGC function and a construction method thereof.

[0006] The present invention achieves the above object through the following technical solutions:

[0007] A SaaS website construction platform system integrating AIGC function, comprising

[0008] A requirements analysis and architecture design module, which is used to clarify user requirements and system goals, and design a modular and extensible system architecture.

[0009] A multi-modal AIGC engine module, which is used to integrate the multi-modal content generation capabilities of text, image, video, and code to meet diverse requirements;

[0010] A distributed computing and real-time generation module, which is used to achieve high-concurrency and low-latency content generation through a distributed architecture and high-performance computing resources.

[0011] Modular Design and Data Security Module, which uses modular design to ensure system scalability and flexibility while guaranteeing data security;

[0012] User Interaction and Editing Module, which provides an intuitive interaction interface and supports users to edit and preview generated content in real time;

[0013] System Testing and Optimization Module, which monitors the system running status and optimizes resource utilization and user experience;

[0014] Deployment and Go-live Module, which deploys the system to the production environment to ensure high availability and scalability. Preferably, the Requirement Analysis and Architecture Design Module includes a User Requirement Research Module, a System Goal Definition Module, a System Architecture Design Module, and a Technology Selection Module. The User Requirement Research Module is used to collect the functional requirements of potential users for the website building platform through methods such as questionnaires and user interviews. The System Goal Definition Module is used to determine the core goals of the platform (such as rapid website building, intelligent content generation, multi-device compatibility, etc.) and formulate key performance indicators (such as generation latency ≤ 1 second, supporting 1000 concurrent users, etc.). The System Architecture Design Module is used to adopt a microservices architecture, split the system into independent functional modules (such as AIGC engine, user interaction, data security, etc.) and design the communication protocols between modules (such as RESTAPI, gRPC). The Technology Selection Module is used to select a suitable technology stack (such as React front-end, Node.js back-end, Kubernetes deployment) and determine the integration method of the AIGC model (such as OpenAI API, HuggingFace model). Preferably, the Multimodal AIGC Engine Module includes a Text Generation Module, an Image Generation Module, a Video Generation Module, a Code Generation Module, and a Multimodal Fusion Algorithm Module. The Text Generation Module is used to generate high-quality natural language text, such as website copywriting, SEO-optimized content. The Image Generation Module is used to generate high-quality images, such as website pictures, icons, backgrounds. The Video Generation Module is used to generate high-quality videos, such as promotional videos, dynamic content. The Code Generation Module is used to generate high-quality front-end code or functional plugins, such as HTML, CSS, JavaScript, etc. The Multimodal Fusion Algorithm Module is used to fuse and optimize content of different modalities, such as combining text with images to generate content with both pictures and texts.

[0015] Preferably, the Distributed Computing and Real-time Generation Module includes a Task Scheduling Module, a GPU Acceleration Module, and an Edge Computing Module. The Task Scheduling Module is used to dynamically allocate computing resources to ensure the efficient execution of generation tasks. The GPU Acceleration Module is used to accelerate content generation using a GPU cluster to reduce latency. The Edge Computing Module is used to process user requests near the edge nodes to improve the response speed.

[0016] Preferably, the modular design and data security module includes a modular architecture module, a data encryption module, and an access control module. The modular architecture module is based on a microservices architecture and supports the independent deployment and expansion of functional modules. The data encryption module is used to encrypt and store user data during transmission. The access control module manages user access based on roles and permissions to ensure data privacy.

[0017] Preferably, the user interaction and editing module includes a drag-and-drop editor module, a real-time preview module, and an intelligent recommendation module. The drag-and-drop editor module supports users in adjusting the layout and content by dragging. The real-time preview module is used to generate instant rendering of the content and supports multi-device adaptation. The intelligent recommendation module recommends templates, content, or functional modules according to user needs.

[0018] Preferably, the system testing and optimization module includes a performance monitoring module, a user feedback module, and a data analysis module. The performance monitoring module is used to monitor the system performance in real time, detect and solve problems in a timely manner. The user feedback module is used to collect user feedback and drive function optimization and iteration. The data analysis module is used to analyze user behavior and data, and optimize the generation model and recommendation algorithm.

[0019] Preferably, the deployment and go-live module includes a cloud platform deployment module, a go-live preparation module, and a user support and maintenance module. The cloud platform deployment module is used to deploy the system to a cloud platform (such as AWS, Azure), utilize load balancing and auto-scaling functions, and configure monitoring tools (such as Prometheus, Grafana) to monitor the system running status in real time. The go-live preparation module is used to conduct final tests to ensure system stability and performance and formulate a go-live plan to ensure a smooth transition. The user support and maintenance module is used to provide user documentation and training to help users get started quickly, and establish an operations and maintenance team to solve user problems and system failures in a timely manner.

[0020] A construction method for a SaaS website building platform integrating AIGC functions as described above includes the following steps

[0021] S1. Requirement analysis and architecture design;

[0022] S2. Integration of multi-modal AIGC engines;

[0023] S3. Implementation of distributed computing and real-time generation;

[0024] S4. Modular design and data security implementation;

[0025] S5. Development of the user interaction and editing module;

[0026] S6. System testing and optimization;

[0027] S7, Deployment and Go-live.

[0028] Preferably, the requirements analysis and architecture design include the following steps:

[0029] S11, User requirement research. Through methods such as questionnaire surveys and user interviews, collect the functional requirements of potential users for the website building platform (such as multi-modal content generation, real-time editing, SEO optimization, etc.) and analyze the functions of competing products to clarify the differential advantages;

[0030] S12, System goal definition. Determine the core goals of the platform (such as rapid website building, intelligent content generation, multi-device compatibility, etc.) and formulate key performance indicators (such as generation latency ≤ 1 second, supporting 1000 concurrent users, etc.);

[0031] S13, System architecture design. Adopt a microservices architecture, split the system into independent functional modules (such as AIGC engine, user interaction, data security, etc.) and design the communication protocols between modules (such as RESTAPI, gRPC);

[0032] S14, Technology selection. Select a suitable technology stack (such as React front-end, Node.js back-end, Kubernetes deployment) and determine the integration method of the AIGC model (such as OpenAI API, HuggingFace model);

[0033] The integration of the multi-modal AIGC engine includes the following steps:

[0034] S21, Model selection and evaluation. Select a suitable multi-modal model (such as GPT-4 text generation, DALL·E image generation, Runway video generation) and evaluate the performance of the model (such as generation quality, response speed, resource consumption);

[0035] S22, API integration and encapsulation. Integrate the selected model through API calls, encapsulate it into a unified interface layer, and implement the multi-modal switching function to support users to select the generation type (such as text, image, video);

[0036] S23, Model optimization and fine-tuning. According to user feedback and generation results, fine-tune the model (such as transfer learning, incremental learning), and optimize the model parameters (such as temperature, resolution, frame rate) to improve the generation quality;

[0037] S24, Performance testing. Conduct high-concurrency tests to ensure the stability of the model in a multi-user scenario, and optimize the model call frequency and resource allocation to reduce latency and costs;

[0038] The implementation of distributed computing and real-time generation includes the following steps:

[0039] S31. Build a distributed architecture, deploy a Kubernetes cluster, support dynamic scheduling and expansion of computing resources, and configure GPU nodes to accelerate content generation tasks;

[0040] S32. Task scheduling and load balancing, implement task scheduling algorithms (such as RoundRobin, Min-Min), ensure load balancing, and monitor node loads to dynamically adjust task allocation;

[0041] S33. Deploy edge computing nodes, deploy edge nodes at geographical locations close to users to reduce generation latency, and implement a task migration strategy to select the best computing node based on a latency threshold;

[0042] S34. Real-time rendering and interaction, integrate real-time rendering technologies (such as WebGL, Three.js), support real-time preview of generated content, and implement an interactive editing function that allows users to make adjustments during the generation process;

[0043] The modular design and data security implementation include the following steps:

[0044] S41. Implement a modular architecture, split the system into independent functional modules (such as AIGC engine, user management, data security), and deploy each module using containerization technologies (such as Docker) to ensure independence and scalability;

[0045] S42. Data encryption and storage, implement a data encryption algorithm (such as AES-256), encrypt and store user data during transmission, and configure a secure storage solution (such as AWS S3, Azure Blob Storage);

[0046] S43. Access control and permission management, implement role-based access control (RBAC), manage user permissions (such as administrator, ordinary user), and configure access policies to ensure the security of sensitive data;

[0047] S44. Security monitoring and response, deploy security monitoring tools (such as IDS, SIEM), detect system anomalies in real time, and formulate an emergency response strategy to promptly address security threats;

[0048] The development of the user interaction and editing module includes the following steps:

[0049] S51. Interaction interface design, design an intuitive user interface that supports drag-and-drop operations and real-time preview, and implement multi-device adaptation to ensure compatibility on PCs, mobile phones, and tablets;

[0050] S52. Implement the intelligent recommendation function. Based on collaborative filtering and knowledge graph technologies, implement the intelligent recommendation function, and recommend relevant templates, content, or functional modules according to user needs;

[0051] S53. Develop the real-time editing function. Implement the real-time rendering and editing functions, support users to adjust the generated content, and integrate multi-language support to meet internationalization requirements;

[0052] S54. Optimize the user experience. Collect user feedback, optimize the interface design and interaction process, and conduct A / B tests to select the best design scheme;

[0053] The system testing and optimization include the following steps:

[0054] S61. Function testing. Conduct function testing on each module to ensure compliance with requirements, and fix the problems found in the testing to optimize the system functions;

[0055] S62. Performance testing. Conduct high-concurrency testing to evaluate the system's performance under pressure, and optimize resource allocation and task scheduling to improve the system performance;

[0056] S63. User testing. Invite target users to conduct testing, collect feedback opinions, and optimize the generation quality and interaction experience according to user feedback;

[0057] S64. Continuous optimization. Establish a continuous integration and continuous delivery (CI / CD) process to support rapid iteration, and continuously optimize the AIGC model and system functions according to user data and generation results;

[0058] The deployment and launch include the following steps:

[0059] S71. Cloud platform deployment. Deploy the system to a cloud platform (such as AWS, Azure), utilize load balancing and auto-scaling functions, and configure monitoring tools (such as Prometheus, Grafana) to monitor the system running status in real time;

[0060] S72. Launch preparation. Conduct final testing to ensure system stability and performance, and formulate a launch plan to ensure a smooth transition;

[0061] S73. User support and maintenance. Provide user documentation and training to help users get started quickly, and establish an operation and maintenance team to solve user problems and system failures in a timely manner.

[0062] The beneficial effects of the present invention are: In the SaaS website building platform system integrating AIGC functions and its construction method,

[0063] 1. Integration of multi-modal AIGC engines to achieve the generation of multi-modal content such as text, images, videos, and code, meeting diverse requirements;

[0064] 2. Distributed computing and real-time generation. Through a distributed architecture and GPU acceleration technology, high-concurrency and low-latency content generation are ensured;

[0065] 3. Modular design and data security. Adopting a microservices architecture, it supports the independent deployment and expansion of functional modules while ensuring data security;

[0066] 4. User interaction and intelligent recommendation. Providing an intuitive interaction interface and intelligent recommendation functions to enhance the user experience;

[0067] 5. Data security and privacy protection. Ensuring the security and privacy of user data, in compliance with relevant regulatory requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The present invention will be described by way of examples and with reference to the accompanying drawings, where:

[0069] Figure 1 is a step diagram of the construction method of the present invention;

[0070] Figure 2 is a step diagram of the requirement analysis and architecture design of the present invention;

[0071] Figure 3 is a step diagram of the integration of the multi-modal AIGC engine of the present invention;

[0072] Figure 4 is a step diagram of the implementation of distributed computing and real-time generation of the present invention;

[0073] Figure 5 is a step diagram of the implementation of modular design and data security of the present invention;

[0074] Figure 6 is a step diagram of the development of the user interaction and editing module of the present invention;

[0075] Figure 7 is a step diagram of the system testing and optimization of the present invention;

[0076] Figure 8 is a step diagram of the deployment and going live of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0077] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, and therefore only showing the components related to the present invention.

[0078] As Figures 1 - 8As shown, a SaaS website building platform system integrating AIGC functions includes

[0079] A requirements analysis and architecture design module, which is used to clarify user requirements and system goals, and design a modular and scalable system architecture

[0080] A multi-modal AIGC engine module, which is used to integrate the multi-modal content generation capabilities of text, image, video, and code to meet diverse needs;

[0081] A distributed computing and real-time generation module, which is used to achieve high-concurrency and low-latency content generation through a distributed architecture and high-performance computing resources;

[0082] A modular design and data security module, which is used to adopt a modular design to ensure the scalability and flexibility of the system while ensuring data security;

[0083] A user interaction and editing module, which is used to provide an intuitive interaction interface and support users to edit and preview generated content in real time;

[0084] A system testing and optimization module, which is used to monitor the running status of the system and optimize resource utilization and user experience;

[0085] Deployment and Go-live Module, which is used to deploy the system to the production environment to ensure high availability and scalability. Specifically, the Requirement Analysis and Architecture Design Module includes a User Requirement Research Module, a System Goal Definition Module, a System Architecture Design Module, and a Technology Selection Module. The User Requirement Research Module is used to collect the functional requirements of potential users for the website building platform through methods such as questionnaire surveys and user interviews. The System Goal Definition Module is used to determine the core goals of the platform (such as rapid website building, intelligent content generation, multi-device compatibility, etc.) and formulate key performance indicators (such as generation latency ≤ 1 second, supporting 1000 concurrent users, etc.). The System Architecture Design Module is used to adopt a microservices architecture, split the system into independent functional modules (such as AIGC Engine, User Interaction, Data Security, etc.) and design the communication protocols between the modules (such as REST API, gRPC). The Technology Selection Module is used to select a suitable technology stack (such as React front-end, Node.js back-end, Kubernetes deployment) and determine the integration method of the AIGC model (such as OpenAI API, HuggingFace model). Specifically, the Multimodal AIGC Engine Module includes a Text Generation Module, an Image Generation Module, a Video Generation Module, a Code Generation Module, and a Multimodal Fusion Algorithm Module. The Text Generation Module is used to generate high-quality natural language text, such as website copywriting, SEO optimization content. The Image Generation Module is used to generate high-quality images, such as website pictures, icons, backgrounds. The Video Generation Module is used to generate high-quality videos, such as promotional videos, dynamic content. The Code Generation Module is used to generate high-quality front-end code or functional plugins, such as HTML, CSS, JavaScript, etc. The Multimodal Fusion Algorithm Module is used to fuse and optimize content of different modalities, such as combining text with images to generate illustrated content.

[0086] Specifically, the Distributed Computing and Real-time Generation Module includes a Task Scheduling Module, a GPU Acceleration Module, and an Edge Computing Module. The Task Scheduling Module is used to dynamically allocate computing resources to ensure the efficient execution of generation tasks. The GPU Acceleration Module is used to accelerate content generation using a GPU cluster to reduce latency. The Edge Computing Module is used to process user requests nearby through edge nodes to improve the response speed.

[0087] Specifically, the Modular Design and Data Security Module includes a Modular Architecture Module, a Data Encryption Module, and an Access Control Module. The Modular Architecture Module is based on the microservices architecture and supports the independent deployment and extension of functional modules. The Data Encryption Module is used to encrypt the storage and transmission of user data. The Access Control Module manages user access based on roles and permissions to ensure data privacy.

[0088] Specifically, the user interaction and editing module includes a drag-and-drop editor module, a real-time preview module, and an intelligent recommendation module. The drag-and-drop editor module is used to support users in adjusting the layout and content by dragging. The real-time preview module is used to generate instant rendering of the content and support multi-device adaptation. The intelligent recommendation module is used to recommend templates, content, or functional modules according to user needs.

[0089] Specifically, the system testing and optimization module includes a performance monitoring module, a user feedback module, and a data analysis module. The performance monitoring module is used to monitor the system performance in real time, discover and solve problems in a timely manner. The user feedback module is used to collect user feedback and drive function optimization and iteration. The data analysis module is used to analyze user behavior and data, and optimize the generation model and recommendation algorithm.

[0090] Specifically, the deployment and go-live module includes a cloud platform deployment module, a go-live preparation module, and a user support and maintenance module. The cloud platform deployment module is used to deploy the system to a cloud platform (such as AWS, Azure), utilize load balancing and auto-scaling functions, and configure monitoring tools (such as Prometheus, Grafana) to monitor the running status of the system in real time. The go-live preparation module is used to conduct final testing to ensure system stability and performance and formulate a go-live plan to ensure a smooth transition. The user support and maintenance module is used to provide user documentation and training to help users get started quickly, and establish an operation and maintenance team to solve user problems and system failures in a timely manner.

[0091] A construction method of an SaaS website building platform integrating AIGC functions as described above includes the following steps

[0092] S1. Requirement analysis and architecture design;

[0093] S2. Integration of multi-modal AIGC engines;

[0094] S3. Implementation of distributed computing and real-time generation;

[0095] S4. Modular design and implementation of data security;

[0096] S5. Development of the user interaction and editing module;

[0097] S6. System testing and optimization;

[0098] S7. Deployment and go-live.

[0099] Specifically, the requirement analysis and architecture design include the following steps:

[0100] S11. Conduct user needs research. Through methods such as questionnaire surveys and user interviews, collect the functional requirements of potential users for the website building platform (such as multi-modal content generation, real-time editing, SEO optimization, etc.) and analyze the functions of competing products to clarify the differential advantages.

[0101] S12. Define the system goals. Determine the core goals of the platform (such as rapid website building, intelligent content generation, multi-device compatibility, etc.) and formulate key performance indicators (such as generation latency ≤ 1 second, supporting 1000 concurrent users, etc.).

[0102] S13. Design the system architecture. Adopt a microservices architecture, split the system into independent functional modules (such as AIGC engine, user interaction, data security, etc.) and design the communication protocols between modules (such as RESTAPI, gRPC).

[0103] S14. Select technologies. Choose a suitable technology stack (such as React for the front end, Node.js for the back end, Kubernetes for deployment) and determine the integration method of the AIGC model (such as OpenAI API, HuggingFace model).

[0104] The integration of the multi-modal AIGC engine includes the following steps:

[0105] S21. Select and evaluate models. Select suitable multi-modal models (such as GPT-4 for text generation, DALL·E for image generation, Runway for video generation) and evaluate the performance of the models (such as generation quality, response speed, resource consumption).

[0106] S22. Integrate and encapsulate the API. Integrate the selected model through API calls, encapsulate it into a unified interface layer, and implement the multi-modal switching function to support users to select the generation type (such as text, image, video).

[0107] S23. Optimize and fine-tune the model. According to user feedback and generation results, fine-tune the model (such as transfer learning, incremental learning), and optimize the model parameters (such as temperature, resolution, frame rate) to improve the generation quality.

[0108] S24. Conduct performance testing. Conduct high-concurrency testing to ensure the stability of the model in a multi-user scenario, and optimize the model call frequency and resource allocation to reduce latency and costs.

[0109] The implementation of distributed computing and real-time generation includes the following steps:

[0110] S31. Build a distributed architecture. Deploy a Kubernetes cluster to support dynamic scheduling and expansion of computing resources and configure GPU nodes to accelerate content generation tasks.

[0111] S32. Task scheduling and load balancing, implementing task scheduling algorithms (such as RoundRobin, Min-Min), ensuring load balancing, and monitoring node loads to dynamically adjust task allocation;

[0112] S33. Edge computing node deployment, deploying edge nodes at geographical locations close to users to reduce generation latency, and implementing a task migration strategy to select the best computing node based on a latency threshold;

[0113] S34. Real-time rendering and interaction, integrating real-time rendering technologies (such as WebGL, Three.js), supporting real-time previews of generated content, and implementing an interactive editing function that allows users to make adjustments during the generation process;

[0114] The modular design and data security implementation include the following steps:

[0115] S41. Modular architecture implementation, splitting the system into independent functional modules (such as AIGC engine, user management, data security), and deploying each module using containerization technologies (such as Docker) to ensure independence and scalability;

[0116] S42. Data encryption and storage, implementing data encryption algorithms (such as AES-256) to encrypt and store user data during transmission, and configuring a secure storage solution (such as AWS S3, Azure Blob Storage);

[0117] S43. Access control and permission management, implementing role-based access control (RBAC) to manage user permissions (such as administrator, regular user), and configuring access policies to ensure the security of sensitive data;

[0118] S44. Security monitoring and response, deploying security monitoring tools (such as IDS, SIEM) to detect system anomalies in real time, and formulating an emergency response strategy to promptly address security threats;

[0119] The development of the user interaction and editing module includes the following steps:

[0120] S51. Interaction interface design, designing an intuitive user interface that supports drag-and-drop operations and real-time previews, and implementing multi-device adaptation to ensure compatibility on PCs, mobile phones, and tablets;

[0121] S52. Implementation of intelligent recommendation functions, implementing intelligent recommendation functions based on collaborative filtering and knowledge graph technologies, and recommending relevant templates, content, or functional modules according to user needs;

[0122] S53. Develop real-time editing functions to achieve real-time rendering and editing capabilities, support users in adjusting the generated content, and integrate multi-language support to meet internationalization requirements;

[0123] S54. Optimize the user experience, collect user feedback, optimize the interface design and interaction process, and conduct A / B tests to select the best design solution;

[0124] The system testing and optimization include the following steps:

[0125] S61. Function testing: Conduct function testing on each module to ensure compliance with requirements, fix issues found during testing, and optimize system functions;

[0126] S62. Performance testing: Conduct high-concurrency testing to evaluate the system's performance under pressure, and optimize resource allocation and task scheduling to improve system performance;

[0127] S63. User testing: Invite target users to conduct tests, collect feedback, and optimize the generation quality and interaction experience based on user feedback;

[0128] S64. Continuous optimization: Establish a continuous integration and continuous delivery (CI / CD) process to support rapid iteration, and continuously optimize the AIGC model and system functions based on user data and generation results;

[0129] The deployment and go-live include the following steps:

[0130] S71. Cloud platform deployment: Deploy the system to a cloud platform (such as AWS, Azure), utilize load balancing and auto-scaling functions, and configure monitoring tools (such as Prometheus, Grafana) to monitor the system's running status in real time;

[0131] S72. Go-live preparation: Conduct final testing to ensure system stability and performance, and formulate a go-live plan to ensure a smooth transition;

[0132] S73. User support and maintenance: Provide user documentation and training to help users get started quickly, and establish an operations and maintenance team to promptly address user issues and system failures.

[0133] Example 1: Enterprise official website construction

[0134] 1. Requirement analysis and architecture design:

[0135] - User requirements: The enterprise needs to display company information, products, and services, and support multiple languages.

[0136] - System goals: Quickly generate an enterprise official website and support SEO optimization.

[0137] - Technology Selection: Choose React for the front end, Node.js for the back end, and Kubernetes for deployment.

[0138] 2. Integration of Multimodal AIGC Engine:

[0139] - Model Selection: Integrate GPT-4 to generate copywriting and DALL·E to generate images.

[0140] - API Encapsulation: Implement a unified interface to support users in selecting the generation type.

[0141] 3. Distributed Computing and Real-time Generation:

[0142] - Architecture Setup: Deploy a Kubernetes cluster and configure GPU nodes.

[0143] - Task Scheduling: Implement the RoundRobin algorithm to ensure load balancing.

[0144] 4. Modular Design and Data Security:

[0145] - Modular Architecture: Split into user management, AIGC engine, and data security modules.

[0146] - Data Encryption: Use AES-256 for encrypting and transmitting user data in storage.

[0147] 5. User Interaction and Editing:

[0148] - Interaction Interface: Design a drag-and-drop editor to support real-time preview.

[0149] - Intelligent Recommendation: Recommend relevant templates and content according to enterprise needs.

[0150] 6. System Testing and Optimization:

[0151] - Function Testing: Test functions such as copywriting generation and image generation.

[0152] - Performance Testing: Conduct high-concurrency tests and optimize resource allocation.

[0153] 7. Deployment and Go Live:

[0154] - Cloud Platform Deployment: Deploy the system to AWS and configure load balancing.

[0155] - User Support: Provide enterprise user documentation and training.

[0156] Example 2: Building an E-commerce Platform

[0157] 1. Requirement Analysis and Architecture Design:

[0158] - User Requirements: The e-commerce platform needs to support product management, order processing, and payment functions.

[0159] - System Goals: Quickly generate an e-commerce website that supports multiple payment methods.

[0160] - Technology Selection: Choose Vue for the front end, Spring Boot for the back end, and Docker for deployment.

[0161] 2. Integration of Multimodal AIGC Engine:

[0162] - Model Selection: Integrate GPT-4 to generate product descriptions and StableDiffusion to generate product images. - API Encapsulation: Implement a unified interface to support users in selecting the generation type.

[0163] 3. Distributed Computing and Real-Time Generation:

[0164] - Architecture Setup: Deploy a Kubernetes cluster and configure GPU nodes.

[0165] - Task Scheduling: Implement the Min-Min algorithm to ensure load balancing.

[0166] 4. Modular Design and Data Security:

[0167] - Modular Architecture: Split into product management, order processing, and payment modules.

[0168] - Data Encryption: Use RSA encryption to store and transmit user data.

[0169] 5. User Interaction and Editing:

[0170] - Interaction Interface: Design a drag-and-drop editor that supports real-time preview.

[0171] - Intelligent Recommendation: Recommend relevant templates and content based on product categories.

[0172] 6. System Testing and Optimization:

[0173] - Function Testing: Test functions such as product description generation and order processing.

[0174] - Performance Testing: Conduct high-concurrency tests and optimize resource allocation.

[0175] 7. Deployment and Go Live:

[0176] - Cloud Platform Deployment: Deploy the system to Azure and configure load balancing.

[0177] - User Support: Provide e-commerce user documentation and training.

[0178] Example 3: Building a Personal Blog

[0179] 1. Requirement Analysis and Architecture Design:

[0180] - User requirements: An individual needs to display blog articles and support SEO optimization.

[0181] - System goals: Quickly generate a personal blog and support multi-device compatibility.

[0182] - Technology selection: Choose Angular for the front end, Django for the back end, and Kubernetes for deployment.

[0183] 2. Integration of multimodal AIGC engine:

[0184] - Model selection: Integrate GPT-4 to generate blog articles and DALL·E to generate cover images.

[0185] - API encapsulation: Implement a unified interface to support users to select the generation type.

[0186] 3. Distributed computing and real-time generation:

[0187] - Architecture setup: Deploy a Kubernetes cluster and configure GPU nodes.

[0188] - Task scheduling: Implement the RoundRobin algorithm to ensure load balancing.

[0189] 4. Modular design and data security:

[0190] - Modular architecture: Split into user management, AIGC engine, and data security modules.

[0191] - Data encryption: Use AES-256 to encrypt and transmit user data.

[0192] 5. User interaction and editing:

[0193] - Interaction interface: Design a drag-and-drop editor to support real-time preview.

[0194] - Intelligent recommendation: Recommend relevant templates and content based on the blog theme.

[0195] 6. System testing and optimization:

[0196] - Function testing: Test functions such as blog article generation and cover image generation.

[0197] - Performance testing: Conduct high-concurrency testing and optimize resource allocation.

[0198] 7. Deployment and launch:

[0199] - Cloud platform deployment: Deploy the system to Google Cloud and configure load balancing.

[0200] - User support: Provide personal user documentation and training.

[0201] In summary, this patent has the following advantages:

[0202] 1. Model optimization: Continuously optimize the AIGC model based on user feedback and generated results to support generation in more modalities.

[0203] 2. Performance improvement: Optimize the distributed computing architecture to reduce generation latency; introduce more efficient GPU acceleration technology.

[0204] 3. User experience: Enhance the interactive editing function to support more customization options; provide a more intelligent recommendation algorithm to improve user satisfaction.

[0205] 4. Data security: Introduce blockchain technology to ensure content copyright and data security; strengthen access control and permission management to prevent data leakage.

[0206] 5. Ecosystem expansion: Open API interfaces to support third-party developers to access AIGC functions; build a developer community to enrich the platform ecosystem.

[0207] Based on the inspiration of the present invention, through the above description, relevant staff can completely make various changes and modifications without departing from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A SaaS website building platform system integrated with AIGC function, characterized in that: including a requirements analysis and architecture design module for clarifying user requirements and system goals, and designing a modular and extensible system architecture; a multi-modal AIGC engine module for integrating the multi-modal content generation capabilities of text, image, video, and code to meet diverse requirements; a distributed computing and real-time generation module for achieving high-concurrency and low-latency content generation through a distributed architecture and high-performance computing resources; a modular design and data security module for adopting a modular design to ensure the scalability and flexibility of the system while guaranteeing data security; a user interaction and editing module for providing an intuitive interaction interface to support users in real-time editing and previewing of generated content; a system testing and optimization module for monitoring the system running status and optimizing resource utilization and user experience; a deployment and go-live module for deploying the system to the production environment to ensure high availability and scalability.

2. The SaaS website building platform system integrating AIGC function according to claim 1, wherein: The requirements analysis and architecture design module includes a user requirements research module, a system goal definition module, a system architecture design module, and a technology selection module. The user requirements research module is used to collect the functional requirements of potential users for the website building platform through methods such as questionnaires and user interviews. The system goal definition module is used to determine the core goals of the platform and formulate key performance indicators. The system architecture design module is used to adopt a microservices architecture to split the system into independent functional modules and design the communication protocol between the modules. The technology selection module is used to select a suitable technology stack and determine the integration method of the AIGC model.

3. The SaaS website building platform system integrating AIGC function according to claim 1, characterized in that: The multi-modal AIGC engine module includes a text generation module, an image generation module, a video generation module, a code generation module, and a multi-modal fusion algorithm module. The text generation module is used to generate high-quality natural language text. The image generation module is used to generate high-quality images. The video generation module is used to generate high-quality videos. The code generation module is used to generate high-quality front-end code or functional plugins. The multi-modal fusion algorithm module is used to fuse and optimize content of different modalities.

4. The SaaS website building platform system integrating AIGC function according to claim 1, characterized in that: The distributed computing and real-time generation module includes a task scheduling module, a GPU acceleration module, and an edge computing module. The task scheduling module is used to dynamically allocate computing resources to ensure the efficient execution of generation tasks. The GPU acceleration module is used to utilize a GPU cluster to accelerate content generation and reduce latency. The edge computing module is used to process user requests nearby through edge nodes to improve the response speed.

5. The SaaS website building platform system integrating AIGC function according to claim 1, characterized in that: The modular design and data security module includes a modular architecture module, a data encryption module, and an access control module. The modular architecture module is based on a microservices architecture and supports the independent deployment and extension of functional modules. The data encryption module is used to encrypt the storage and transmission of user data. The access control module manages user access based on roles and permissions to ensure data privacy.

6. The SaaS website building platform system integrating AIGC function according to claim 1, characterized in that: The user interaction and editing module includes a drag-and-drop editor module, a real-time preview module, and an intelligent recommendation module. The drag-and-drop editor module is used to support users in adjusting the layout and content by dragging. The real-time preview module is used to instantaneously render the generated content and support multi-device adaptation. The intelligent recommendation module is used to recommend templates, content, or functional modules according to user requirements.

7. The SaaS website building platform system integrating AIGC function according to claim 1, characterized in that: The system testing and optimization module includes a performance monitoring module, a user feedback module, and a data analysis module. The performance monitoring module is used to monitor the system performance in real time, discover and solve problems in a timely manner. The user feedback module is used to collect user feedback, drive function optimization and iteration. The data analysis module is used to analyze user behavior and data, and optimize the generation model and recommendation algorithm.

8. The SaaS website building platform system integrating AIGC functions according to claim 1, characterized in that: The deployment and go-live module includes a cloud platform deployment module, a go-live preparation module, and a user support and maintenance module. The cloud platform deployment module is used to deploy the system to the cloud platform, utilize load balancing and auto-scaling functions, and configure monitoring tools to monitor the system running status in real time. The go-live preparation module is used to conduct final tests, ensure system stability and performance, and formulate a go-live plan to ensure a smooth transition. The user support and maintenance module is used to provide user documentation and training to help users get started quickly, and establish an operation and maintenance team to solve user problems and system failures in a timely manner.

9. A method for constructing a SaaS website building platform integrating AIGC functions according to any one of claims 1-8, characterized in that: It includes the following steps S1. Requirement analysis and architecture design; S2. Multi-modal AIGC engine integration; S3. Distributed computing and real-time generation implementation; S4. Modular design and data security implementation; S5. User interaction and editing module development; S6. System testing and optimization; S7. Deployment and go-live. The construction method of the SaaS website building platform integrating AIGC function according to claim 9, characterized in that: The requirement analysis and architecture design include the following steps: S11. User requirement research. Through methods such as questionnaire surveys and user interviews, collect the functional requirements of potential users for the website building platform, analyze the functions of competing products, and clarify the differential advantages; S12. System goal definition. Determine the core goals of the platform and formulate key performance indicators; S13. System architecture design. Adopt a microservices architecture, split the system into independent functional modules, and design the communication protocol between modules; S14. Technology selection. Select a suitable technology stack and determine the integration method of the AIGC model; The multi-modal AIGC engine integration includes the following steps: S21. Model selection and evaluation. Select a suitable multi-modal model and evaluate the performance of the model; S22. API integration and encapsulation. Integrate the selected model through API calls, encapsulate it into a unified interface layer, and implement the multi-modal switching function to support users to select the generation type; S23. Model optimization and fine-tuning. According to user feedback and generation results, fine-tune the model and optimize the model parameters to improve the generation quality; S24. Performance testing. Conduct high-concurrency tests to ensure the stability of the model in a multi-user scenario, and optimize the model call frequency and resource allocation to reduce latency and cost; The distributed computing and real-time generation implementation includes the following steps: S31. Distributed architecture construction. Deploy a Kubernetes cluster to support dynamic scheduling and expansion of computing resources, and configure GPU nodes to accelerate content generation tasks; S32. Task scheduling and load balancing. Implement a task scheduling algorithm to ensure load balancing, and monitor the node load to dynamically adjust task allocation; S33. Edge computing node deployment. Deploy edge nodes at locations close to users to reduce generation latency, and implement a task migration strategy to select the best computing node according to the latency threshold; S34. Real-time rendering and interaction, integrating real-time rendering technology, supporting real-time preview of generated content, and implementing interactive editing functions, allowing users to make adjustments during the generation process; The modular design and data security implementation include the following steps: S41. Modular architecture implementation, splitting the system into independent functional modules and deploying each module using containerization technology to ensure independence and scalability; S42. Data encryption and storage, implementing data encryption algorithms to encrypt and store user data during transmission, and configuring a secure storage solution; S43. Access control and permission management, implementing role-based access control to manage user permissions and configuring access policies to ensure the security of sensitive data; S44. Security monitoring and response, deploying security monitoring tools to detect system anomalies in real time and formulating emergency response strategies to promptly address security threats; The development of the user interaction and editing module includes the following steps: S51. Interaction interface design, designing an intuitive user interface that supports drag-and-drop operations and real-time preview, and achieving multi-device adaptation to ensure compatibility on PCs, mobile phones, and tablets; S52. Implementation of intelligent recommendation functions, based on collaborative filtering and knowledge graph technologies, implementing intelligent recommendation functions and recommending relevant templates, content, or functional modules according to user needs; S53. Development of real-time editing functions, implementing real-time rendering and editing functions, supporting users to adjust the generated content, and integrating multi-language support to meet internationalization requirements; S54. User experience optimization, collecting user feedback, optimizing the interface design and interaction process, and conducting A / B tests to select the best design solution; The system testing and optimization include the following steps: S61. Function testing, conducting function testing on each module to ensure compliance with requirements, and fixing problems found during testing to optimize system functions; S62. Performance testing, conducting high-concurrency testing to evaluate the system's performance under pressure, and optimizing resource allocation and task scheduling to improve system performance; S63. User testing, inviting target users to conduct tests, collecting feedback, and optimizing the generation quality and interaction experience according to user feedback; S64. Continuous optimization, establishing a continuous integration and continuous delivery (CI / CD) process to support rapid iteration, and continuously optimizing the AIGC model and system functions based on user data and generation results; The deployment and go-live include the following steps: S71. Cloud platform deployment, deploying the system to the cloud platform, leveraging load balancing and auto-scaling functions, and configuring monitoring tools to monitor the system's running status in real time; S72. Go-live preparation, conducting final tests to ensure system stability and performance, and formulating a go-live plan to ensure a smooth transition; S73. User support and maintenance, providing user documentation and training to help users get started quickly, and establishing an operations and maintenance team to promptly address user problems and system failures.

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