bRAG-langchain and RAG_local_tutorial
One tool provides a comprehensive toolkit for building RAG applications, while the other offers simple, local tutorials, making them complementary where the latter can introduce concepts reinforced and expanded upon by the former.
About bRAG-langchain
bragai/bRAG-langchain
Everything you need to know to build your own RAG application
This project provides comprehensive guides and boilerplate code for building Retrieval-Augmented Generation (RAG) applications. It takes your various documents and a user's question, then processes them to deliver accurate and contextually relevant answers. Developers, machine learning engineers, and data scientists looking to implement or enhance RAG systems will find this useful.
About RAG_local_tutorial
sergiopaniego/RAG_local_tutorial
Simple RAG tutorials that can be run locally or using Google Colab (only Pro version).
This project offers practical guides for extracting specific details from various types of content using a local Large Language Model. You can input files like PDFs, YouTube videos, audio recordings, or even entire GitHub repositories. The output is a clear, concise summary or specific information derived from your input, making it useful for researchers, analysts, or anyone needing to quickly digest information from diverse sources.
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