The dawn of Generative AI makes possible new kinds of capabilities for the applications we build. LLMs can answer the user’s questions with an incr...
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Hi @rogiia, thanks for mentioning all the common problems or pitfalls. I'm experiencing it right now as I'm working to build a custom RAG system. Could you share any blog/article on a more advanced RAG pipeline to avoid these common pitfalls?
Hi Rahul, thank you for your comment. To know more about common pitfalls in RAG and how are other people solving them, I would really recommend reading the paper "Retrieval Augmented Generation for Large Language Models: A Survery". Here's a link to it: arxiv.org/pdf/2312.10997.pdf.
I'm also working on covering more Advanced RAG techniques myself, so keep in tune, I'll be releasing them shortly.
Thank you @rogiia, for sharing the paper. Also, I would love to connect with you sometime to chat more about this!
Feel free to contact me at rogeroriwd@gmail.com
Thank your for this article. I found it quite informative.
Could you share your full LLM prompt? It looks like you shared a screenshot but the prompt was cut short.
Thanks.
Thank you for your feedback!
After your comment I went and checked the link to the Colab notebook and it was broken. The link is now fixed. You can go to the Colab notebook and not only check out the prompts, you can also execute them and see the result.
Link to the Colab notebook: colab.research.google.com/drive/1m...
This article excellently highlights the transformative potential of RAG in enhancing LLM-based applications.
By leveraging RAG's ability to integrate real-time data with generative capabilities, organizations can not only provide precise, context-aware responses but also drastically reduce hallucination risks, paving the way for more reliable and intelligent user interactions.
Thank you Joseph! I'm working on some more Advanced RAG tips and techniques, so keep in tune!
I tried myself in colab with Gemini pro and Gemini embeddings three days back some errors in embedding but your code provide me the front end portion of embedding ,it help to connect my gemini pro chat model to questions . Thank you
Hi Roger Oriol,
Top, very nice !
Thanks for sharing
Thank you so much for this article.
This is very good for Beginner like to understand RAG and build something. 💖
I'm glad you found my article of use. Feel free to ask me questions if they come up as you learn.
This is awesome ,the whole RAG in a nutshell. Nice work 👍
Thank you for your comment Nikita! I'm glad the article was informative to you
It was helpful for the bigginer level. Kindly write more articles on that topic like same way with more diagrams.
Thank you
Thank you for your feedback! I'm currently working on more Advanced RAG tips and techniques. They will not be as beginner friendly as this article, but I'll make sure they are of use to both beginners and experts in the field.