Intro and demo to RAG with Azure OpenAI
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- Опубликовано: 6 фев 2025
- Retrieval Augmented Generation (RAG) is a technique used to feed more accurate and up to date data to LLM models like ChatGPT. That is because LLM models have two important limitations. They are trained on a massive amount of data, but they not trained on all data available on the internet. In addition to that, they are not trained on customer private data. So the question is how can we feed LLM models with this lacking data so we make sure its answers are accurate and correct.
Well, this is what RAG will do.
More details in this video.
Disclaimer: This video is part of my upcoming course on Udemy. Watch the updates here: www.udemy.com/...
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This is a great video, love the overview diagram, code walkthrough and clear explanation!
I am enrolling in your Udemy course, this is exactly what I am looking for a project to create RAG with my company documents. Thank you a lot!
Finally a demo that works. Thanks Houssem.
Really really good step through
Great video, Houssem! One of the best tutorial on that topic!
very good and fresh summary - very good starting point with detaisl implementaiton details
Thanks a lot! Really got content in short time!
Do you have mor information on which toolset can be used to simplify the data loading process or how to load document types such as pdf in a simple way?
Thank you, very good demo!
Nice! Do you have a reference for RAG that uses Azure Cosmos DB for MongoDB (vCore)?
Do you have a course for that?
Can you plese confirm if this is equivalent to AWS Bedrock now? Bedrock also provides inbuilt functionality to apply chunking from a list of chunking methods, porcessing document using multi-model if data has tables and images etc. All that is part of AWS Bedrock Knowledge base functionality now.
Im having trouble accessing extra body/dataSources on the javascript client. Any ideas why? It says the extra param does not exist.
Good job !
What will your new course cover?
Can we do this for free in azure ai studio????
Thank you!
Hi, how can I use that if I do not have only markdown files?