Retrieval-Augmented Generation (RAG) Systems

57 repos across 5 sub-areas

Libraries, frameworks, and implementations for building retrieval-augmented generation systems that combine large language models with external knowledge retrieval. The cluster spans foundational RAG architectures (MiniRAG, LightRAG, R2R), semantic search approaches (SearchLM, SubgraphRAG), and agent-based variants that integrate retrieval with agentic AI workflows. Most repos are Python-based tools and frameworks for developers implementing RAG pipelines at various scales of complexity.