Retrieval-Augmented Generation (RAG) Systems
36 repos
Libraries, frameworks, and applications for building retrieval-augmented generation systems that combine large language models with external knowledge retrieval. This cluster encompasses RAG pipeline implementations, embedding models, vector indexing, and end-to-end applications that ground LLM responses in retrieved documents. Most repos are Python-based tools for assembling RAG components, with a few supporting implementations in Rust for performance-critical indexing and retrieval layers.
Python · 25
Jupyter Notebook · 4
Rust · 3
Go · 2
C# · 1
TypeScript · 1
retrieval-augmented-generation ·333,282
rag ·304,181
llm ·199,650
ai ·178,169
ai-agents ·153,850
agentic-ai ·152,064
context-engineering ·152,039
vector-database ·113,775
large-language-models ·110,668
agentic-search ·90,017
