Web Gateway RAG Reference Selection for Accurate AI Queries
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Solution Overview
Problem
Traditional AI models rely solely on pre-trained data, limiting their ability to provide up-to-date and context-specific information, and implementing Retrieval Augmented Generation (RAG) poses challenges in integrating with various interfaces, managing data sources, and identifying relevant references for accurate responses.
Innovation Solution
A web gateway system that integrates with AI models, stores data sources as RAG references, and uses metadata and advanced analysis to determine relevant data sources for generating optimal responses, acting as an intermediary between interfaces and AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional AI models rely solely on pre-trained data, then the model structure remains simple, but the accuracy and context-specific information capability deteriorates
Solution Approach 1:
The patent introduces a web gateway as an intermediary component between the AI model and external data sources. The web gateway receives AI queries, retrieves relevant information from multiple data sources, and presents processed information to the AI model. This mediator approach enables the system to access up-to-date and context-specific information without modifying the core AI model structure, thus improving reliability while maintaining manageable complexity.
Solution Approach 2:
The system is segmented into distinct functional components: the AI model, the web gateway, and multiple external data sources. The web gateway is further divided into specialized modules for query processing, data retrieval, and information synthesis. This segmentation allows each component to be optimized independently, enabling the system to achieve high accuracy through coordinated specialization without overwhelming overall complexity.
2Loss of information
If RAG integrates with various interfaces and manages multiple data sources, then the information completeness improves, but the system complexity increases
Solution Approach 1:
The web gateway is designed as a universal interface that can connect to and manage multiple different data sources including databases, APIs, and file systems. It implements a standardized query processing mechanism that works across diverse data sources, enabling the system to access comprehensive information from various interfaces without requiring separate integration logic for each source, thus improving information completeness while controlling system complexity through standardization.
3Reliability
If the web gateway uses advanced analysis to identify relevant references, then the response accuracy improves, but the processing time increases
Solution Approach 1:
The web gateway performs preliminary actions by pre-processing queries, pre-fetching potentially relevant data, and pre-establishing connections to data sources before the AI model requires responses. It maintains cached information and pre-computed indexes that can be quickly accessed during query processing, thereby reducing the time penalty associated with advanced analysis while maintaining high response accuracy.
Data Source
AI summary
A method and system for performing retrieval augmented generation (RAG) for artificial intelligence (AI) queries through a web gateway is disclosed. The method includes interconnecting an interface and the web gateway, wherein the web gateway is configured to receive a command set from the interface and communicate the command set to an AI model. The web gateway stores a collection of RAG references containing a set of data sources, each associated with metadata. The method further includes identifying a subset of RAG references relevant to the command set using the metadata, transmitting the command set and the subset of RAG references to the AI model, and receiving a response from the AI model. The system includes a data store, a communication link with an interface, and a processor for executing instructions to perform the method steps.