A global application software AI default model automatic election and unconscious unified scheduling method

Abstract

This invention belongs to the field of software service scheduling and artificial intelligence service management technology, and discloses a method for automatic election and seamless unified scheduling of default AI models for application software across the entire domain. This invention classifies and manages AI models according to functional categories, setting a unique default running instance for each type of intelligent service; it implements automatic initialization of default identifiers for newly added models, mutual exclusion updates of default states for models of the same category, and batch adjustment of default configurations through database logic; the business layer adopts a seamless scheduling design, where business functions only match the corresponding default model through service classification, without binding fixed interfaces and parameters; a default model locking protection mechanism is set up to prevent the deletion of default models in the global scheduling state, ensuring the continuous and stable operation of AI services; batch data processing is achieved based on table-valued parameters, adapting to batch configuration and maintenance scenarios; the overall solution is universally applicable, without industry or business limitations. This invention solves the problems of hard-coded binding of AI services in traditional software, cumbersome model switching and modification, conflicts between multiple parallel models, and poor service stability, effectively reducing the cost of software iteration and upgrades, and is suitable for all application software products that require long-term access to artificial intelligence services.

Description

Technical Field

[0001] This invention belongs to the fields of software architecture design, artificial intelligence service scheduling and general business system integration technology, and specifically relates to a method for automatic selection, classification management and seamless unified scheduling of AI default models for universal application software. Background Technology

[0002] Currently, most application software integrates AI services using a fixed binding method. During the development phase, a single interface address and model parameters are fixed. When changing service providers, upgrading model versions, or adjusting service nodes later, the program code must be modified and recompiled and released, resulting in extremely low upgrade efficiency.

[0003] In scenarios where multiple models are deployed in parallel, the lack of unified scheduling rules can easily lead to confusion in calling logic and functional conflicts when multiple AI models of the same type coexist. The system lacks an automatic initialization mechanism. When deploying a brand new category for the first time, the default parameters need to be manually configured, making the deployment process cumbersome. The lack of necessary protection logic could lead to the accidental deletion of the default model that is being scheduled and used, which would directly cause the entire AI function to be paralyzed. Existing scheduling solutions are mostly customized and cannot be reused across projects and industries, making it difficult to form a standardized AI service scheduling system. Summary of the Invention

[0004] This invention constructs an integrated AI service scheduling system that features categorized management, unique constraints, automatic election, and seamless scheduling.

[0005] By classifying and managing AI services, we can achieve a fine-grained division of AI services, with intelligent models of different functions being grouped independently so that they do not interfere with each other; Set a globally unique default constraint and rely on database logic to ensure that default models of the same category are mutually exclusive, thus preventing conflicts between multiple instances. Configure an automatic election mechanism so that the default state is automatically activated when the first model is added to the blank category, simplifying the initial deployment process; Supports batch configuration management, adapts to scenarios involving batch adjustments of multiple data sets, and improves operational efficiency; Add a service protection mechanism to lock the running default model and prevent service interruption due to accidental operation; The business layer is decoupled, focusing only on the required AI service types, and default configurations are uniformly distributed by the database to achieve seamless scheduling. Detailed Implementation

[0006] The system categorizes all AI models into different service classes according to their functions and manages each type of intelligent capability independently. When a new model is added to a blank category for the first time, the system automatically determines that there is no existing data in the category and automatically marks the model as the global default scheduling object. After multiple candidate models are successively entered under the same category, the administrator enters the default configuration interface and selects multiple target models to be enabled. Batch configuration commands are passed to the database via table-valued parameters. The stored procedure first clears all old default identifiers for the category, and then completes the binding of the new default model. During daily business operations, the business module only passes in the service category name, and the dedicated read storage procedure automatically filters the interface and configuration information of the corresponding default model; When an operator performs a deletion operation, the system automatically checks the default state and directly intercepts the model that is providing global services. All default configuration adjustments are automatically logged for easy traceability and fault analysis during later maintenance. Beneficial effects

[0007] Seamless service switching means that changing AI service providers or upgrading models requires no changes to business code, significantly reducing maintenance and iteration costs. Automatic initialization configuration; blank categories automatically generate default models, simplifying software deployment and launch processes. The unique mutual exclusion constraint completely solves the calling conflict problem caused by the coexistence of multiple models of the same type; The security protection is reliable, and the default core model is locked to avoid accidental operation that could cause the entire AI function to be paralyzed. Its universal and standardized design allows for wide compatibility with various software, and it possesses excellent reusability and scalability.

Claims

1. A method for automatic election and seamless unified scheduling of default AI models in global application software, characterized in that, include: (1) All AI models are classified independently according to their functions and uses, forming a multi-dimensional intelligent service classification system; (2) Set a unique default constraint for each service category, and only one data item is allowed to be marked as the global default scheduling state within the same category; (3) When adding a new AI model, the corresponding category of existing data is automatically detected. If there is no model for a category, the current item is automatically set as the default model. (4) Provides batch configuration function, supports multiple selection of multiple model data, and batch processing is completed by passing table value parameters to the database in batch; (5) When switching the default model, first clear all the original default labels of the same category, and then assign the default state to the target model to ensure mutual exclusion and uniqueness. (6) Add default model protection logic to intercept deletion operation commands when the target data is in the default scheduling state; (7) The business side uses the service category as the only input parameter, calls the dedicated read storage procedure, and automatically matches the corresponding default model to complete the seamless call.

2. The method according to claim 1, characterized in that: The AI ​​service switch can be completed through backend configuration only, without modifying business code or redeploying the program, achieving a seamless business switch.

3. The method according to claim 1, characterized in that: All default model change operations are automatically logged, including the operator and operation time, which facilitates operation and maintenance management and problem troubleshooting.