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Building a RAG AI Agent using Azure Redis

Microsoft Reactor
125K subscribers

Welcome & Code of Conduct

0:00

Speaker Introductions

1:02

Overview of Today’s Session

1:49

What is an AI Agent?

2:13

Exact Question Answering Agent Explained

4:37

Why Azure Managed Redis Matters

7:28

Redis as a Knowledge Base for AI

10:15

Azure Managed Redis Overview

11:03

Common Use Cases for Redis

13:06

Redis in AI and Vector Search

16:06

Redis Search Capabilities

19:00

Unlocking Search with Redis

21:03

Vector Search Demo Setup

24:44

Loading Data and Creating Embeddings

26:22

Querying Redis with Python

29:05

Vector Search Results Explained

32:01

NET Integration and Libraries

33:01

Exact QA Agent Architecture

35:51

Live Demo: Exact QA Agent in Action

37:56

Observability with .NET Aspire

41:04

Easy Deployment with Azure Developer CLI

44:49

Code Walkthrough: Agent and Plugin

48:11

Real-World Use Case: Customer Service

52:22

Adding AI Chat UI with Aspire

55:13

Recap and Technologies Used

57:55

Open Q&A

58:22

Running Locally and Python Support

59:57

Final Thanks and Wrap-Up

1:00:53
Building a RAG AI Agent using Azure Redis
Use Azure Managed Redis to build a performant and consistent Agent application. We will look into Azure AI Foundry, Azure PaaS agent platform services, and the latest Azure Managed Redis with its feature enhancements. The sample showcases .NET Aspire and Azure integrations secured with Entra ID. Check it out! Chapters: 00:00 - Welcome & Code of Conduct 01:02 - Speaker Introductions 01:49 - Overview of Today’s Session 02:13 - What is an AI Agent? 04:37 - Exact Question Answering Agent Explained 07:28 - Why Azure Managed Redis Matters 10:15 - Redis as a Knowledge Base for AI 11:03 - Azure Managed Redis Overview 13:06 - Common Use Cases for Redis 16:06 - Redis in AI and Vector Search 19:00 - Redis Search Capabilities 21:03 - Unlocking Search with Redis 24:44 - Vector Search Demo Setup 26:22 - Loading Data and Creating Embeddings 29:05 - Querying Redis with Python 32:01 - Vector Search Results Explained 33:01 - .NET Integration and Libraries 35:51 - Exact QA Agent Architecture 37:56 - Live Demo: Exact QA Agent in Action 41:04 - Observability with .NET Aspire 44:49 - Easy Deployment with Azure Developer CLI 48:11 - Code Walkthrough: Agent and Plugin 52:22 - Real-World Use Case: Customer Service 55:13 - Adding AI Chat UI with Aspire 57:55 - Recap and Technologies Used 58:22 - Open Q&A 59:57 - Running Locally and Python Support 1:00:53 - Final Thanks and Wrap-Up #learnconnectbuild #MicrosoftReactor [eventID:25536]

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Microsoft Reactor

125K subscribers