RAG with a Neo4j Knowledge Graph: How it Works and How to Set It Up
28,101
Published 2023-12-18
We’ll cover:
What is RAG?
How does RAG with a Neo4j Knowledge Graph work?
What are the benefits of using RAG & Neo4j?
How can I set up RAG with Neo4j using a Llama2 model and the GenAI Stack?
Links:
GenAI Walkthrough: neo4j.com/developer-blog/genai-app-how-to-build/
Neo4j & GenAI: neo4j.com/generativeai/
Github Repo: github.com/docker/genai-stack
RAG Blogs: neo4j.com/developer-blog/tagged/retrieval-augmente…
LLM Blogs: neo4j.com/developer-blog/tagged/llm/
@philippbrunenberg www.philipp-brunenberg.de/
00:00 Introduction
00:29 What is RAG?
02:09 The Neo4j Vector Store
03:03 Augmenting LLM answers with RAG
04:50 Using the GenAI-Stack
06:37 GenAI-Stack Configuration
08:08 The compose file
09:47 Loading data into Neo4j
11:59 Using the chat frontend
15:30 Conclusion
#neo4j #graphdatabase #knowledgegraph #langchain #genai #rag #ollama
All Comments (21)
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Thank you for publishing this type of content. This is absolutely amazing!
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Great whirlwind tour to present a concrete understading of RAG with knowledge graphs in Neo4j. Thanks. Looking forward to exploring this channel more to learn more about RAG/KGs/GenAIStack etc.
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Loved this video and the pace!
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This was really useful., also the presentor did an amazing job. But it was too short. I wish to see a longer more tutorial like version of it too. Or to have links to relevant knowledge and tutorials.
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Thank you for the deep explanation
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Thanks for this robust example.
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Excellent video. Thank you.
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Brilliant, thank you!
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Thank you ❤
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Thank you so much
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Thanks for sharing the video @neo4j. By the way, both responses provided in the video were inaccurate. Why wasn't the correct answer generated? 🤔
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It would be really useful to do this video adding how to convert the unstructured data to KG and the use it on a RAG. Step by step it's what makes people use Neo4j more. Thank you!
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About how long can we expect the StackOverflow loader to import using the settings in the video to run?
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It is still not clear whether at the final stage what input do you provide to LLM to get the final question: - Original Question text - Text extracted from the KG nodes/edges - SO, you do not provide text associated with the best K answers resulted form initial generation of embeddings from the user prompt? ...and how to you compose the text extracted from the nodes? What is the technique?
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Great video! What would be the minimum recommended system specs for this to work?
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Great video, I have Windows and ollama is not for windows yet. Can I run the docker under wsl2?
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Amazing! Planning on integrating this with my neo4j db which has 1 billion relationships, might be pushing the limits a bit 🤣🤣
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How does this compare to what MS is doing in the GraphRAG paper, it seems like MS was really jazzed on using the LLM, GPT4, (in some way it wasn't clear) to create the relationships, the edges/weights etc, and this was the secret sauce, I assume this is different from what Neo4j is doing, but could you expand?
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Is there any loader ready to insert own data (csv or else - not pdf) instead of stackOverflow?
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This is only demo of some commercial product? Can I use it within company to build some service?
