I recorded a step-by-step tutorial about how to test RAG applications. It's 50 minutes, and I tried to make it as simple to understand as possible. For those of you who find these long tutorials helpful, what should I cover next?

In case you prefer to watch the video in YouTube, here is the link:

An in-depth session on agents will be great.

It’s on my list, for sure. I’ve been distracted with other cool stuff… there’s just too much!

How about a series on LangChain? 1) An intro/overview tutorial, 2) a session on LangSmith, and 3) a session on LangServe. You could also do a separate session on building agents with LangChain. 😀

a suggestion for future tutorial: combining RAG with function calling and chain of prompts to apply user request on real data to provide a chart or to shape a query or a json accordingly would be cool. to see how we can combine ai capabilities with functions to make cool outcomes

Thanks , it's very helpful ....would love more content like this

cloud rag using open source LLM has an api to post data to it and also send prompts to get responds from the data.

Is It possibile to cover also how to manage multiple formats of input data, (JSON, CSV,...) and then how to expose the RAG output data, i.e. building an interface (streamlit interface,...)

Agents and chain tools 🤔

CI/CD for RAG using local LLMs