The Best RAG Technique Yet? Anthropic’s Contextual Retrieval Explained!
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Top Comments (10)
Sending my best to the little one in the background!
For anyone wondering, I did try these methods (contextual retrieval + reranking) with a local model on my laptop. It does work great the rag part but it takes a while to import new documents due to chunking, generating summaries and generating embeddings. Re-ranking on a local model is surprisingly fast and really good with the right model. If you're building an application using rag, I'd suggest you make adding docs the very first step in the on-boarding to your application because you can then do all of the chunking etc in the background. The user might be expecting real-time drag->drop->ask question workflow but it wont work like that unless you're using models in the cloud. Also, remember to chunk, summarize and gen embeddings simultaneously, not one chunk after another as of course that'll take longer for your end-user.
Best wishes for the kid in the background
I think the baby in the background disagrees :p
🎉baby voices were cute!
Thanks very interesting. Many ideas came to my head for improving RAG with enhancing chunk
Thought it was my baby, but it was yours in the background 😂😂
Thanks for the easy to understand explanation
Great explanation 🎉
Superb explanation
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Top Comments (10)
Sending my best to the little one in the background!
For anyone wondering, I did try these methods (contextual retrieval + reranking) with a local model on my laptop. It does work great the rag part but it takes a while to import new documents due to chunking, generating summaries and generating embeddings. Re-ranking on a local model is surprisingly fast and really good with the right model. If you're building an application using rag, I'd suggest you make adding docs the very first step in the on-boarding to your application because you can then do all of the chunking etc in the background. The user might be expecting real-time drag->drop->ask question workflow but it wont work like that unless you're using models in the cloud. Also, remember to chunk, summarize and gen embeddings simultaneously, not one chunk after another as of course that'll take longer for your end-user.
Best wishes for the kid in the background
I think the baby in the background disagrees :p
🎉baby voices were cute!
Thanks very interesting. Many ideas came to my head for improving RAG with enhancing chunk
Thought it was my baby, but it was yours in the background 😂😂
Thanks for the easy to understand explanation
Great explanation 🎉
Superb explanation