bRAG-langchain and Learn_RAG_from_Scratch_LLM
These are complementary learning resources where the first provides a comprehensive production-ready RAG implementation framework, while the second offers a beginner-focused tutorial for understanding RAG fundamentals from scratch before applying them with the more advanced tooling.
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 Learn_RAG_from_Scratch_LLM
simranjeet97/Learn_RAG_from_Scratch_LLM
Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python
This project helps developers integrate large language models (LLMs) with custom data sources. It guides you through creating a system that can answer questions using information beyond its initial training, taking your documents or text as input and producing contextually accurate responses. Developers looking to build custom AI assistants or sophisticated search tools would find this useful.
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