Proxy API System Enriches Messages with Semantic Annotations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing API systems face challenges in effective communication due to outdated interfaces, poorly documented messaging structures, and incorrect API requests, leading to resource wastage and disparate interpretations between requesting and providing systems.
Innovation Solution
A proxy API system intercepts and enriches API messages with semantic information and reference data, providing additional context to improve interpretation and reduce resource consumption by centralizing message processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If each providing system implements its own response parsing and actuation system to process API requests, then the system can independently process requests, but excessive consumption of resources such as wasted time, computational resources, and manpower occurs
Solution Approach 1:
The patent merges the response parsing and actuation functions into a centralized service that multiple providing systems share. Instead of each system implementing its own parsing logic, they all communicate with a single centralized service that handles message interpretation and routing, eliminating redundant computational work across the distributed system.
Solution Approach 2:
The centralized response parsing service provides universal functionality that serves multiple providing systems. This single service performs the multi-functional role of parsing different API message formats, interpreting responses, and routing them appropriately, replacing the need for each individual system to have its own specialized parsing implementation.
2Productivity
If a requesting system directly uses an API with difficult-to-parse messaging structures or poorly-documented APIs, then the system can communicate with the providing system, but extensive testing by the requesting system is required
Solution Approach 1:
The patent introduces an intermediary component that sits between the requesting system and the providing system. This intermediary translates difficult-to-parse messaging structures into easily interpretable formats and handles poorly-documented APIs by providing its own documentation and interface specifications, eliminating the need for extensive testing by requesting systems.
Solution Approach 2:
The intermediary performs preliminary actions by pre-processing and validating API messages before they reach the requesting system. It pre-translates complex messaging structures, pre-validators responses against expected formats, and pre-handles errors, so that requesting systems receive already-processed, easy-to-use data without needing to perform extensive testing.
3Ease of manufacture
If developer interpretations of API documentation are used to configure requesting systems, then the system can be configured without extensive resources, but incorrect interpretations lead to incorrect API requests
Solution Approach 1:
The patent enables the system to serve itself by automatically generating accurate API request configurations through machine learning models. Instead of relying on human developers to interpret documentation, the system uses trained models that automatically understand API specifications and generate correct request configurations, making the configuration process both easy and reliable.
Solution Approach 2:
The system implements feedback mechanisms where the centralized response parsing service provides information back to the requesting system about the correctness and effectiveness of API requests. This feedback loop allows the machine learning models to learn from actual API interactions and continuously improve request accuracy, ensuring that initial configurations are correct while maintaining the ability to self-correct.
Data Source
AI summary
A proxy API system intercepts and enriches API messages such as an API request or API response. The proxy API system enriches an API message by incorporating additional semantic meaning into the API message. More specifically, the proxy API system extracts features from a message and applies the features to a trained model. The trained model identifies annotations that are relevant for labeling the API message. Additionally, the proxy API system identifies reference data corresponding to the API message data and annotations to provide additional data related to content of the API message, such as additional detail about a data item in the message such as additional fields related to that item. The proxy API system enriches the API request or API response with the annotations and reference data.