Generative AI API Merging via AST Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods lack efficient ways to merge and optimize multiple application programming interfaces (APIs), manage legacy APIs, and map discontinued API calls to new APIs, leading to suboptimal performance and increased complexity in software development.
Innovation Solution
The use of generative AI and deep learning algorithms, such as abstract syntax tree (AST) and generative pre-trained transformer (GPT), to analyze and merge APIs based on user requirements, extract metadata, and deploy new APIs using smart contracts on blockchain protocols, optimizing API repositories and deprecating obsolete APIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple legacy APIs are called to provide functionality, then existing functionality is maintained, but performance is suboptimal and system complexity increases
Solution Approach 1:
The patent merges multiple legacy APIs into a single optimized API by analyzing their functionalities through AI algorithms. The system extracts metadata from multiple APIs, compares their operations, and creates a unified API that combines the strengths of all legacy APIs while eliminating redundant calls, thereby improving performance while maintaining reliability.
Solution Approach 2:
The generated API is designed to be universal, handling multiple functions that were previously distributed across separate legacy APIs. The single API can perform all operations that the multiple legacy APIs could perform, making it multi-functional and improving system efficiency.
2Adaptability or versatility
If multiple legacy APIs are maintained, then backward compatibility is preserved, but management complexity and storage requirements increase
Solution Approach 1:
The patent extracts essential functionality from multiple legacy APIs and consolidates it into a single new API. By taking out the core operational elements from each legacy API and重组 them into a unified structure, the system reduces management complexity while preserving the necessary functionality and compatibility.
Solution Approach 2:
The system acts as an intermediary between legacy APIs and new applications. It provides a translation layer that maps calls to the unified API back to the appropriate legacy API implementations, maintaining backward compatibility without requiring direct management of multiple legacy API definitions.
3Adaptability or versatility
If API repositories are continuously updated with new APIs, then functionality is enhanced, but tracking and optimization become difficult
Solution Approach 1:
The patent implements a feedback mechanism where the AI system continuously analyzes API performance data, usage patterns, and operational metrics. This feedback is used to automatically optimize the API repository by identifying which APIs are most effective and should be prioritized for generation, making the tracking and optimization process automated and data-driven.
Solution Approach 2:
The system performs self-optimization by automatically analyzing its own performance data and adjusting API generation priorities without external intervention. The AI algorithms self-evaluate which APIs need to be generated based on current system state and performance metrics, reducing the manual tracking and measurement burden.
Data Source
AI summary
An intelligent technical procedure to merge two or more application programming interfaces (APIs) leveraging generative AI is disclosed. API metadata is extracted from two or more APIs (e.g., name of API, endpoints, request/response formats (JSON or XLM), authentication mechanism (API keys, OAuth, or JWT tokens), rate limits, error codes, error messages, version scheme and API documentation etc.) to formulate and generate new API based on user prompt. Using Abstract Syntax tree (AST) advance deep learning generative AI algorithms like Generative pre-trained transformer (GPT) or the like, the method can merge and construct new API based on user's requirement prompt. Method leverages smart contracts to test new generated API and deploy API in desired environment based on blockchain consent protocol to manage API.