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How to Use PostgreSQL for Retrieval-Augmented Generation (RAG)

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Manage episode 469856167 series 3648424
Content provided by Business Compass LLC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Business Compass LLC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

How to Use PostgreSQL for Retrieval-Augmented Generation (RAG)

https://businesscompassllc.com/genai

Retrieval-augmented generation (RAG) is a powerful technique for enhancing Large Language Models (LLMs) by retrieving relevant documents from a database to generate more context-aware responses. PostgreSQL, an advanced open-source relational database, is a great choice for implementing RAG because it supports full-text search, vector similarity search (via extensions like pgvector), and scalability. This article will guide you through using PostgreSQL for RAG and integrating it with LLMs to create AI-powered applications.

  continue reading

37 episodes

Artwork
iconShare
 
Manage episode 469856167 series 3648424
Content provided by Business Compass LLC. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Business Compass LLC or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

How to Use PostgreSQL for Retrieval-Augmented Generation (RAG)

https://businesscompassllc.com/genai

Retrieval-augmented generation (RAG) is a powerful technique for enhancing Large Language Models (LLMs) by retrieving relevant documents from a database to generate more context-aware responses. PostgreSQL, an advanced open-source relational database, is a great choice for implementing RAG because it supports full-text search, vector similarity search (via extensions like pgvector), and scalability. This article will guide you through using PostgreSQL for RAG and integrating it with LLMs to create AI-powered applications.

  continue reading

37 episodes

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