Posts tagged with #postgres

#postgres#search#database#rails#ruby

Postgres Full-Text Search vs. Embeddings: A Practical Guide

Most teams reach for embeddings before they need them, wiring up pgvector when Postgres’s full-text search would have done the job. If your users are just looking for “caching” and expect to find “Rails caching strategies,” full-text search is fast, precise, and already built in. Where embeddings shine is when meaning matters more than exact words, like an e-commerce query for “summer outfit” that should return linen shirts and beach dresses. The key isn’t choosing one tool over the other, but knowing when Postgres alone is enough and when a hybrid approach gives you the semantic nuance users actually need.
#ai#rails#rag#postgres#ruby

How I Built a RAG System in Rails Using Nomic Embeddings and OpenAI

RAG doesn’t have to mean heavyweight infrastructure. In this post, I show how I wired up a lean Retrieval-Augmented Generation pipeline inside a Rails app using Nomic for embeddings, PgVector for search, and OpenAI for generation. The result is a flexible system: open-source at the embedding layer, powerful where it counts, and simple enough to extend without vendor lock-in.
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