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Retrieval Augmented Generation (RAG) is a way for an LLM to use information from a large corpus of documents.
may be useful or not, no promises
https://docs.openwebui.com/tutorial/rag
https://python.langchain.com/v0.2/docs/tutorials/rag/
https://python.langchain.com/v0.2/docs/tutorials/local_rag/
https://www.reddit.com/r/LangChain/comments/1cyjfap/best_stack_for_rag/
https://docs.llamaindex.ai/en/stable/getting_started/concepts/#retrieval-augmented-generation-rag
https://x.com/jerryjliu0/status/1811871559117865256
https://www.useready.com/blog/rag-wars-llama-index-vs-langchain-showdown
https://x.com/baptadn/status/1813232789946253703
https://x.com/baptadn/status/1813610429907914915
Abhinav Kimothi on LinkedIn: Retrieval Augmented Generation - A Simple Introduction | 30 comments
Introduction to Retrieval Augmented Generation, organized by ACM, with Abhinav Kimothi