AI/ML Toolkit
2.5k 2026-04-18
athina-ai/rag-cookbooks
A comprehensive repository offering practical implementations and evaluation guidance for advanced and agentic Retrieval-Augmented Generation (RAG) techniques.
Core Features
Implementations of advanced and agentic RAG techniques.
Guidance on RAG system evaluation, including integration with Athina AI.
Covers foundational Naive RAG and progresses to complex methods.
Includes research papers and references for deeper understanding.
Detailed Introduction
Large Language Models (LLMs) often struggle with private or recent information and can 'hallucinate'. Retrieval-Augmented Generation (RAG) addresses this by integrating external, reliable data. This repository serves as a vital resource for researchers and developers, providing ready-to-use implementations of advanced and agentic RAG techniques. It simplifies the complex process of building and evaluating RAG systems from scratch, ensuring LLM responses are accurate, relevant, and up-to-date, thereby accelerating development and research in the field.