Azure Cache for Redis Community Standup – OpenAI Embeddings and Vector Search with Redis

In this month’s community standup, we’ll walk through how to use Azure Cache for Redis Enterprise to store and compare embeddings vectors produced by Azure OpenAI Service. We’ll also use LangChain to make development even easier. Our end goal: a movie recommendation engine using semantic natural text queries!

Chapters:00:00 Welcome to the Azure Cache Redis Community Standup00:18 On today’s stream” Azure Cache Redis and OpenAI01:39 Today’s demo:AI-powered movie recommendation app02:25 Embeddings06:28 Our workflow07:36 Dataset from Kaggle08:44 Ingest and clean data with Pandas09:52 Generate Embeddings through Azure OpenAI11:23 Get a vector DB – Azure Cache for Redis14:44 Run queries16:32 Demo19:52 Add a UI with Streamlit21:00 Deploy to Azure Container Apps22:10 Demo25:59 Vector Similarity Search Use Cases30:53 Additional Cache SKUs31:35 Learn more and Get started33:02 Thank you and Connect

Community Links: https://www.theurlist.com/redis-and-openai

Featuring: Kyle Teegarden

#Redis #Langchain #OpenAI

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