LLM Applications and RAG Systems
39 repos
Python-based frameworks, libraries, and practical guides for building production applications with large language models, retrieval-augmented generation (RAG), and AI agents. The cluster emphasizes applied AI engineering over foundational model research, covering end-to-end patterns for integrating LLMs into real systems, prompt engineering, agent orchestration, and knowledge retrieval pipelines. Repos range from hands-on tutorials and reference implementations to reusable agent frameworks and LLM app templates.
Python · 29
Jupyter Notebook · 4
TypeScript · 3
Shell · 2
JavaScript · 1
rag ·586,937
agents ·533,220
llm ·328,335
llms ·315,512
python ·296,405
ai ·242,477
ai-agents ·166,378
genai ·161,426
memory ·158,077
framework ·133,831
