Self-reflective RAG with LangGraph: Self-RAG and CRAG

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Self-reflection can greatly enhance RAG, enabling correction of poor quality retrieval or generations. Several recent RAG papers focus on this theme, but implementing the ideas can be tricky. Here, we show that LangGraph can be easily used for "flow engineering" of self-reflective RAG pipelines. We provide cookbooks for implementing ideas from two interesting papers, Self-RAG and C-RAG.

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LangChain

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Very Clear and informative . Thank you

ramzirebai

This is cool 🤯
And I love that you guys are putting out all these educational videos - thank you!

preston_is_on_youtube

great video Lance! The way you diagrammed the flow made it easy to understand the concepts.

donb

Thanks Lance for more one great tutorial! Really useful and easy to follow.

advfuk

Lance, you are great! Thank you for your splendid video!

gyttqmx

Thank you. This video was informative. Your explanation was clear. For me personally the examples that us local LLMs are interesting. Thanks once again.

UGMurthy

Excellent breakdown! This video really helped me grasp the concepts, and it's one of the first Langchain videos that clicked for me. While Harrison's brilliance is undeniable, Lance, you're truly a great teacher.I love your approach of using diagrams to break down complex code into easily understandable logic. It really enhances the learning experience!

girijeshthodupunuri

Great tutorial. Keep up the great work!

jim

Really great video! Keep 'em coming

JoshuaMcQueen

Thank you for breaking this down!

Is there a way to do cyclical/iterative agents when one produces an answer and the other checks the answer, and if not correct/satisfied with it, sends it back to the first agent to produce a better answer?

jzam

Thanks for that ! Do you have a video that helps build an ui associated for prompting ?

MLA

Great video! I have a question about recent RAG papers which talking about RAG paradigms such as advanced RAG and modular RAG. Could we say that using LangGraph have we applying modular rag? I’m not sure in which paradigm fall self rag and crag.
Thanks!!

carloszelabueno

is thsi still effective with conversational memory?

seansullivan

What are other possibly ways to utilize this on a local database? I mean, if there are no relevant docs what it can do?

LordPBA

Do you have any resources for deploying this type of solution on AWS/GCP?

corybilyeu

Hi, I have one question here related to the Retrieval Evaluator. Let's suppose we are not allowed to do a web search. Can we again play around with chunking and different retrieval methods?

anshubhatia

How to deploy langgraph using langserve, can you please help me do it?

siddharthchauhan

Very interesting, I assume this would have very long response times?

GREENDAYROKS

at around 13 minutes, based on your story i would assume that it wouldnt run web search as there are at least a few documents that are relevant, but as i understand even if 1 of the retrieved documents isnt relevant it will do a web search?

janwillemaltink

Lance - isn't the workflow you outline here a DAG? The LangGraph docs are very explicit about not using LangGraph for DAGs - can you help us understand this nuance?

"The main use is for adding cycles to your LLM application. Crucially, this is NOT a DAG framework. If you want to build a DAG, you should just use LangChain Expression Language."

wjysbhz

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