Fixing RAG with GraphRAG

  Рет қаралды 2,494

Vivek Haldar

Vivek Haldar

Күн бұрын

arxiv.org/abs/2404.16130
0:00 Introduction to RAG and its Limitations
1:08 Sense-Making and Graph-Based Approaches to RAG
2:27 Overview of the Graph RAG Pipeline
4:19 Extracting Concepts and Relationships from Documents
5:07 Summarizing Graph Elements and Clustering into Communities
6:32 Answering Queries with Graph RAG
8:58 Evaluating Graph RAG: Datasets and Question Generation
10:42 Comparing Graph RAG to Traditional RAG
12:25 Qualitative Example: Graph RAG vs. Traditional RAG
13:20 Quantitative Results: Graph RAG Outperforms Traditional RAG
14:14 Conclusion and Future Direction of RAG
Previous video explaining basics of RAG: • Search with LLMs and v...
vivekhaldar.com
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Пікірлер: 10
@rafikyahia7100
@rafikyahia7100 9 күн бұрын
Excellent content summarizing cutting edge approaches, thank you!
@awakenwithoutcoffee
@awakenwithoutcoffee 17 сағат бұрын
great presentation Vivek. Some questions: - is graphRAG production ready ? if not, would it be difficult to upgrade RAG methods once we are in production ? - is there a RAG provider/stack that you prefer ? (datastax, pinecone, weaviate + a bunch of others who are all competing for attention) - what are your thoughts on LangChain vs LangGraph ?
@jordycollingwood
@jordycollingwood 13 күн бұрын
Really great explanation, I’m currently struggling to decide on my own KG structure for a 2000 medical pdf corpus, so this was very helpful
@awakenwithoutcoffee
@awakenwithoutcoffee 17 сағат бұрын
same here brother. There are so many techniques, everyday I learn something new which is both good and terrifying ha. What stack are you thinking of using ? We are researching DataStax, Pinecone, Weaviate and are learning to build agents with LangGraph.
@sasha297603ha
@sasha297603ha Ай бұрын
Very interesting paper, thanks for covering!
@brandonheaton6197
@brandonheaton6197 Күн бұрын
can you pontificate on the combination of upcoming transformer inference ASICs with deep agentic workflows employing GraphRAG style strategies? Seems like we will be close to our personal assistants writing a PhD thesis in the background whenever we ask a question. SOHU is reporting 500,000 tokens per second with Llama3 70B....
@wanfuse
@wanfuse 7 күн бұрын
wouldn't it cut to the chase to train an llm on your own data? theres your graph use one of these OpenAI's GPT-3/4 Hugging Face Transformers (e.g., GPT-2, GPT-3 via third-party providers) Google's T5 (Text-to-Text Transfer Transformer) Meta's BART and BlenderBot Anthropic's Claude every week update the llm summarization is the death of real data, better off one level of summarization? Just a thought!
@mccleod6235
@mccleod6235 7 күн бұрын
Maybe you don't want to send all your valuable business data to third party companies.
@wanfuse
@wanfuse 7 күн бұрын
@@mccleod6235 thats true but its not necessary, there are models that are open source you can train air gapped from a jetson
@bohnohboh676
@bohnohboh676 4 күн бұрын
"every week update the llm" yeah no way unless you have tons of cash, compute, and time
@wanfuse
@wanfuse 4 күн бұрын
maybe maybe not, let you know! your probably right, will see if my idea pans out
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