Papa's Got a Brand New RAG

In this article, the author discusses how Postgres extensions can act as middleware, allowing databases to handle tasks like retrieving relevant information from a text corpus and feeding it into a large language model.

  1. Postgres extensions make it possible for the database to act as a kind of middleware, tying together external services like sentence transformers and large language models in a standardized way.
  2. The author demonstrates how the pg_vectorize extension can be used to create a Retrieval Augmented Generation (RAG) application entirely within Postgres, without the need for additional application code.
  3. This approach allows the entire process to remain within the database, avoiding the need to move vectors or results in and out of the application layer.

Remember this guy? AI is all anyone talks about these days, isn't it? Even when it comes to databases like Postgres, devs are finding new and innovative ways to leverage LLMs in everyday use cases. Can you really blame them though? This is an exciting new technology that will transform how we work and potentially society as a whole once it finally matures. We even covered building a crude RAG app a few short weeks ago. Technology moves fast though—especially when it comes to AI—and the techniques we use will inevitably evolve accordingly. So let's rebuild our crude RAG app using a more modern approach that handles much of the work for us!

Read the full article: https://postgr.es/p/6tL