LLM Agents and RAG Systems
15 repos
Libraries, frameworks, and tutorials for building AI agents and retrieval-augmented generation (RAG) systems powered by large language models. The cluster spans practical implementations (ReMe, PixelRAG, ragent), educational materials and starter projects (hello-agents, tutorials), and foundational frameworks (ai-assistant-framework, happy-llm) that combine agentic reasoning with information retrieval. Most repos are in Python with supporting Jupyter notebooks and TypeScript, reflecting both research-oriented and production-ready tooling in this rapidly evolving area.
Python · 7
Jupyter Notebook · 2
TypeScript · 2
C++ · 1
Java · 1
CSS · 1
rag ·277,734
agent ·277,734
llm ·210,132
ai ·81,556
tutorial ·78,432
multimodal ·64,874
large-language-models ·54,939
mcp ·52,466
multi-agent ·47,488
agent-memory ·45,706
