RAG on PostgreSQL

RAG (Retrieval Augmented Generation) is the most common approach used to get LLMs to answer questions grounded in a particular domain's data. Discover the many ways you can build RAG applications on top of Azure Database for PostgreSQL Flexible Servers. We'll start by using the pgvector extension for vector similarity search. Then we'll explore the new azure_ai extension which provides built-in functions for embeddings, summarization, sentiment analysis, and more. Finally, we'll demo the new azure_local_ai extension to efficiently run pre-trained models on our database server, which can be a great fit for RAG applications that require custom embedding models. Presented by Joshua Johnson, Principal TPM on Azure PostgreSQL, and Pamela Fox, Developer Advocate for Python ** Part of RAGHack, a free global hackathon to develop RAG applications. Join at https://aka.ms/raghack ** 📌 Check out the RAGHack 2024 series here! https://aka.ms/RAGHack2024 #microsoftreactor #raghack [eventID:23331]

RAG on PostgreSQL

Microsoft Reactor

RAG on PostgreSQL

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Microsoft Reactor

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RAG on Azure SQL Server

Why Build Enterprise RAG with Postgres?

Building a RAG application with GitHub Models and Postgres FROM SCRATCH

PostgreSQL - Performance updates, Elastic Clusters (Citus) & AI controls in Azure

Build high-performance RAG using just PostgreSQL (Full Tutorial)

RAG with AI Search and .NET

Azure DevOps Tutorial for Beginners | CI/CD with Azure Pipelines

Intro and demo to RAG with Azure OpenAI

PostgreSQL Tutorial for Beginners

Reliable, fully local RAG agents with LLaMA3.2-3b

Enable GenAI in your applications with .NET 9 and Semantic Kernel

True Multimodal RAG - Audio/Image/Video/Text

PGVector: Turn PostgreSQL Into A Vector Database

Postgres pgvector Extension - Vector Database with PostgreSQL / Langchain Integration

Beyond the Hype: A Realistic Look at Large Language Models • Jodie Burchell • GOTO 2024

RAFT (RAG + Fine-tuning) in Azure AI Studio

Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search

Hybrid Search RAG With Langchain And Pinecone Vector DB

Model Context Protocol (MCP), clearly explained (why it matters)

Python Web Apps: Databases & ORMs