rag-all-techniques and advanced-rag
About rag-all-techniques
liu673/rag-all-techniques
Implementation of all RAG techniques in a simpler way（以简单的方式实现所有 RAG 技术）
This project provides practical, framework-agnostic implementations of various advanced Retrieval Augmented Generation (RAG) techniques. It takes unstructured text data, applies different methods for breaking it down and enriching it, and then uses a large language model to generate improved, contextually relevant answers to user queries. This is for AI practitioners, researchers, or anyone building custom question-answering systems who wants to understand and experiment with core RAG components.
About advanced-rag
guyernest/advanced-rag
Jupyter Notebooks for Mastering LLM with Advanced RAG Course
This project helps developers and data scientists build more accurate and robust AI chatbots and question-answering systems using their own documents. It provides practical examples and solutions for feeding internal documents and data into Large Language Models (LLMs) to get precise answers, handling issues like long documents or specialized jargon. The end result is an AI system that provides more relevant and reliable responses based on your specific information.
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