This helped me a lt sorting some concepts in my brain. You have a huge talent for explaining things simply. It's clear that you have real hands-on experience. keep it up! 🥂
As a person who is developing an internal RAG application, multiquerying/rephrasing seems useless for one who understands the system, but I've found that users, especially new GenAI users, love it as it lowers the entrybarrier for usage. "Remember the stand user could be anyone"
For multiquery i totally agree (that why I put it into D tier). But rephrasing is not useless. How do you handle follow up questions without rephrasing in a RAG System?
@@codingcrashcourses8533 it is very early days, im primarily an SCADA engineer and this is a side project at work, so it dosen't handle multiple queries at the time. The project scope is iterating through BID/NOBID questions for every tender we plan to bid on, and then use some LDA magic to sort chunks into project roles to minimize wasted time reading through materials
Hey man, love yor vids!! I am trying to build my own RAG application and with my background in backend/data engineering I think I'll be able to come up with a pretty good RAG system. My big problem is building I nice front end, any plans on doing a tutorial (or udemy course) on building professional front ends to go with a RAG application?
No sorry I don´t plan on that. There are tons of tutorials on building frontends from people who are much better at that than I am. I would learn that somewhere else and than you will be good enough to come up with solutions for that on your own ;-).
You’ve helped me a lot by explaining all these topics related to RAG so well :) . Keep it up, you're a pro, man! I have a question: How is it possible to keep a Langchain course updated knowing that almost every week new things come out in the documentation or others become outdated? You are the best :D
Thank you! It´s actually not possible, especially since I a have a full time job and a life beside my job and this channel. I currently work on an LCEL Deep dive update for my first course. My courses do not cover EVERYTHING too, I think good courses are not bloated and don´t cover every single edge case or in the LangChain World the integration of 1000 different VEctorstores or AI models.
I hope you're doing well! I’ve been really excited about your LangGraph course and was wondering if you could provide an estimated release date. I’m looking forward to diving into it! Thanks so much!
Hello! Sorry for the late response, there is currently a lot of spam on my channel. My estimation is the beginning of november, since I will have one week holiday then
Great Video ! Which vector store would you recommend to use? I was using supabase, but I will use azure OpenAI, so I’m not sure if change to an azure vector store
what would rate 4o-minis chunking capabilities, what about distilling some of 4o's chunking to a smaller opensource model wonder if that would work and make a lot cheaper
Interesting question, but I honestly can´t answer it. I never ran into issues with my normal PgVector and I doubt the current similarity search approach is suited to support that many docs that hnsw indexing or not really matters. But I am not 100% sure about that.
You see anything different? Change my mind in the comments ;-)
This helped me a lt sorting some concepts in my brain. You have a huge talent for explaining things simply. It's clear that you have real hands-on experience. keep it up! 🥂
Thank you :]
As a person who is developing an internal RAG application, multiquerying/rephrasing seems useless for one who understands the system, but I've found that users, especially new GenAI users, love it as it lowers the entrybarrier for usage.
"Remember the stand user could be anyone"
For multiquery i totally agree (that why I put it into D tier). But rephrasing is not useless. How do you handle follow up questions without rephrasing in a RAG System?
@@codingcrashcourses8533 it is very early days, im primarily an SCADA engineer and this is a side project at work, so it dosen't handle multiple queries at the time.
The project scope is iterating through BID/NOBID questions for every tender we plan to bid on, and then use some LDA magic to sort chunks into project roles to minimize wasted time reading through materials
Thank You ! A good and very timely review !!!!
Hey man, love yor vids!! I am trying to build my own RAG application and with my background in backend/data engineering I think I'll be able to come up with a pretty good RAG system. My big problem is building I nice front end, any plans on doing a tutorial (or udemy course) on building professional front ends to go with a RAG application?
No sorry I don´t plan on that. There are tons of tutorials on building frontends from people who are much better at that than I am. I would learn that somewhere else and than you will be good enough to come up with solutions for that on your own ;-).
You’ve helped me a lot by explaining all these topics related to RAG so well :) . Keep it up, you're a pro, man! I have a question: How is it possible to keep a Langchain course updated knowing that almost every week new things come out in the documentation or others become outdated? You are the best :D
Thank you! It´s actually not possible, especially since I a have a full time job and a life beside my job and this channel. I currently work on an LCEL Deep dive update for my first course. My courses do not cover EVERYTHING too, I think good courses are not bloated and don´t cover every single edge case or in the LangChain World the integration of 1000 different VEctorstores or AI models.
Thankyou soo much, I really needed this video. It just cleared so much confussions.
@@arslanabid2245 thank you for that comment:)
I hope you're doing well! I’ve been really excited about your LangGraph course and was wondering if you could provide an estimated release date. I’m looking forward to diving into it!
Thanks so much!
Hello! Sorry for the late response, there is currently a lot of spam on my channel. My estimation is the beginning of november, since I will have one week holiday then
Thank you - I will try your courses -)
thought you are already subscribed? ;)
Incredible content! Danke!
Danke für den comment :)
Great Video ! Which vector store would you recommend to use? I was using supabase, but I will use azure OpenAI, so I’m not sure if change to an azure vector store
You can use Azure AI Search which is fine. I use PgVector as a container there, since it makes me independent from the cloudprovider.
@@codingcrashcourses8533 thank you very much :D
What about technique like query decomposition?
Better than something like Multiquery! But I have not experimented too much with it.
what would rate 4o-minis chunking capabilities, what about distilling some of 4o's chunking to a smaller opensource model wonder if that would work and make a lot cheaper
since small models would require like exponential (or quadratically?) less vram and compute to make the chunks i think it would be a lot cheaper
So it is better to use llm to for intent classification and entities extraction instead of using tool like RASA?
Maybe - wd actually got rid of rasa:)
You mentioned gpt4o is a great semantic chunker, please can you share the notebook for the same
That´s something I covered in-depth in my udemy course, where I build a custom chunker on top of the LangChain interface.
@@codingcrashcourses8533 please make a free video here on youtube about that topic (gpt4o as a great semantic chunker) 😁😁❤❤
with the new hnsw indexing, supabase pg vector seems better than pinecone and for scalability too , or am i missing something ?
Interesting question, but I honestly can´t answer it. I never ran into issues with my normal PgVector and I doubt the current similarity search approach is suited to support that many docs that hnsw indexing or not really matters. But I am not 100% sure about that.
Hi, I am a big fan of your youtube videos. Wanted to ask if you offer any consultation / project dev services?
Sorry, I only make youtube videos and courses, no consulting or active development.
S:
rawdata, chat model
A:
document chunking,
prompt enginnering
GuardraiIs
B:
embedding model
agent RAG
rephrasing
tool calling
document compression
C :
vector store
reranking
D:
base routing
Multiquery Retrieval
RAPTOR
graphRAG
finetuning
graph rag like trying to apply NP hard problem to production, should be F tier..
The software I used had nothing below D ;-)
Well informative video. But I will recommend some good images, instead of shitty AI generated images which are unreadable.....
Get your point