Building a Fast, Typo-Tolerant AI Search Engine
Blog post from Upstash
The text outlines the process of building a fast and typo-tolerant AI search engine using JStack, a tech stack for high-performance Next.js applications. It elaborates on key steps such as collecting user search queries with React state and a debouncing mechanism, sending these queries to a backend via JStack's API, and retrieving relevant documents from a hybrid vector index using Upstash's Vector Hybrid Index. Additionally, it discusses optional re-ranking and weighting of documents for enhanced search relevance, although this is deemed more relevant for enterprise-level applications. The search engine employs a combination of full-text and semantic search to deliver intuitive results, and it is implemented with a simple React component that handles user input and displays search results. The author notes the ease of implementation and effectiveness of this approach for personal websites and small-to-medium product catalogs, though they suggest that custom re-ranking and synonym support could further enhance search quality.