Searching is a fundamental concept in software, aimed at finding relevant information in a large dataset. Let's see how Spring AI, PGVector, and Ollama can work together to implement semantic search in our applications.

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Learn to implement a semantic search application using Spring AI, PGVector, and Ollama. This tutorial covers the basics of semantic search, including key concepts like word embeddings, semantic similarity, and cosine similarity. You'll set up a Spring Boot project, configure it for PGVector, and enhance it with an Ollama LLM for more context-aware responses. Example code for ingesting book data and performing searches highlights practical implementation steps.

Implementing Semantic Search Using Spring AI and PGVector