Chat With Knowledge Graph Data | Improved RAG

Graph RAG is an Knowledge-enabled RAG approach to retrieve information from Knowledge Graph on given task.
☎️ Do you need any career or technical help? Book a call with me: calendly.com/m...
*******************
LET'S CONNECT!
*******************
Join Discord Channel: / discord
✅ You can contact me at:
LinkedIn: / mohammad-ghodratigohar
Email: [e-mail]
Twitter: / mg_cafe01
🔔 Subscribe for more cloud computing, data, and AI analytics videos
by clicking on the subscribe button so you don't miss anything.
#RAG #Graph#Chat_with_data #GPT4

[@rafikyahia7100]

Thanks for the insight, very helpful!

[@sandeepsasikumar701]

Could you pls do a video on vector plus knowledge graph rag?

[@juliaroberts9602]

Thank you for the informative video! I tried to search for the code in the discord reference section but was not able to find it. I would greatly appreciate if you could post the link to the source code or if you could give the label/title it’s posted with? Thanks and keep up there great work!

[@MG_cafe]

Thanks so much! All links and sources codes ( for even this video) is now added to discord channel, under 'Reference' Section. Please try again as I jsut added there :)

[@lauther_27]

Nice video bro, but there is something that I have not clear and is for the fisrt RAG structure, when querying we vectorize the task and make vector search to the embedded graph relationships descriptions right? So in that way we retrieve and give this as context to the LLM. Sorry I'm new at this and learning something new everyday, thanks!

[@034_mayankparashar9]

Hi! How can i summarize my whole graph ,it is not working using chain.invoke as i asked to summarize the graph or tried multiple user queries for summarization

[@qazwsxedcrfvtgb8877]

You'll have to make the context window bigger not sure how to do it

[@thesimplicitylifestyle]

Thanks guys! Very helpful! 😎🤖