AI Configuration File Validation Under Deployment Constraints
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Solution Overview
Problem
Generating and validating configuration files for complex software systems is time-consuming and error-prone, requiring manual intervention and repeated iterations, especially in modern environments where minor deviations can lead to system failures, security vulnerabilities, or degraded performance.
Innovation Solution
An AI-driven system that integrates a pre-trained AI model to generate configuration files based on queries, subjecting them to filtering processes to ensure compliance with formatting standards and organizational policies, iteratively refining the files until they meet all constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual generation and validation of configuration files is performed, then flexibility and control are maintained, but time consumption and error rates increase
Solution Approach 1:
The system enables self-service automation where the configuration file generation and validation processes are performed automatically by the computer system without requiring manual intervention. The processor executes instructions to generate configuration files, validate them against constraints, and iteratively refine them, allowing the system to serve itself in completing tasks that previously required human operators.
Solution Approach 2:
The patent replaces manual mechanical processes with automated computational processes. Instead of manually creating and validating configuration files through human operators, the system uses a processor executing AI/ML models to generate, validate, and refine configuration files automatically, substituting human mechanical work with automated computational mechanisms.
2Productivity
If automated AI generation is implemented, then productivity and speed are improved, but compliance with constraints and standards may deteriorate
Solution Approach 1:
The system implements feedback mechanisms where generated configuration files are automatically validated against predefined constraints and standards. When validation fails, the system receives feedback about specific constraint violations and iteratively refines the configuration files by generating new versions that address the identified issues, continuing this loop until compliance is achieved.
Solution Approach 2:
The system performs preliminary validation and constraint checking before finalizing configuration files. By预先 establishing validation rules and constraints, and checking generated files against these criteria in advance, the system ensures compliance is built into the generation process itself rather than being a post-hoc correction.
3Manufacturing precision
If iterative refinement processes are used, then accuracy and compliance are improved, but complexity of the system increases
Solution Approach 1:
The system segments the configuration file generation and validation process into distinct modular components: generation phase, validation phase, and refinement phase. Each phase is handled by separate functional modules that can be independently executed and managed, reducing overall system complexity while enabling iterative refinement through structured segmentation of tasks.
Data Source
AI summary
Please replace the original Abstract as filed with the below amended Abstract.An example operation may include one or more of storing a set of configuration files of a software system within a database, receiving a query associated with the software system via a graphical user interface (GUI) of a software application, executing an artificial intelligence (AI) model on the query and the set of configuration files to generate a configuration file that matches the query, determining a set of constraints associated with at least one of the software system and the configuration file, determining that the configuration file matches the set of constraints based on execution of a filter on the configuration file and the set of constraints, and in response to a determination that the configuration file matches the set of constraints, deploying the software system based on the configuration file. The example operation may further include an AI agent that performs an action based on the configuration file.