AutoRAG and Awesome-LLM-Rag
AutoRAG is an evaluation and optimization framework that can be used to improve RAG systems, while Awesome-LLM-Rag is a curated list of papers and resources related to RAG, making them complements where the list provides knowledge to better utilize or understand the framework.
About AutoRAG
Marker-Inc-Korea/AutoRAG
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
Provides end-to-end RAG pipeline optimization through YAML-driven configuration, encompassing document parsing, semantic chunking, and QA dataset generation with support for multiple parsing/chunking strategies simultaneously. Uses grid-search and metric-driven evaluation across retriever-generator combinations to identify optimal module configurations, with results tracked in a dashboard for deployment-ready pipeline export. Integrates with LlamaIndex, LangChain, and local embedding models, supporting both cloud APIs (OpenAI) and GPU-accelerated inference for custom models.
About Awesome-LLM-Rag
yangchou19/Awesome-LLM-Rag
A curated list of awesome papers and resources for Retrieval-Augmented Generation (RAG) in Large Language Models(LLM).
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