Full-text tutorial (requires MLExpert Pro): https://www.mlexpert.io/bootcamp/advanced-rag-with-llama-3-in-langchain

that's great; llama-parse is sweet. Please make a video showing how to use a knowledge graph index in conjunction with the vector DB!

thanks mate ! subscribed, keep up the good work !!!

is there any method to correct that mistake about calculating profits?

i think RetrievalQA class is deprecated. What about updating it to use the create_retrieval_chain

Thank you for your amazing works. Is there any method to improve the runtime of advanced RAG (maybe generate answer in realtime)?

Great material! My I ask you what model and hardware config are you using to get those performances? Thank youu

what is the distance used here ? the cosine ?

Thank you for the tutorial very useful and easy to follow, can you please add the UI for this RAG application  so that normal user can interact.

i am unable to pickle this model
how can i do so?

за пореден път - отличен материал!

an error occurred?
how can i get in touch with you?

How to use ms doc docx with the same code . Any one suggets or point to code. Everything remains same except the input is docx.

tanks