arjbingly/grag
GRAG is a simple python package that provides an easy end-to-end solution for implementing Retrieval Augmented Generation (RAG). The package offers an easy way for running various LLMs locally, Thanks to LlamaCpp and also supports vector stores like Chroma and DeepLake.
No commits in the last 6 months. Available on PyPI.
Stars
15
Forks
1
Language
Python
License
AGPL-3.0
Category
Last pushed
May 11, 2024
Monthly downloads
13
Commits (30d)
0
Dependencies
19
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/arjbingly/grag"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ictnlp/FlexRAG
FlexRAG: A RAG Framework for Information Retrieval and Generation.
VectorInstitute/fed-rag
A framework for fine-tuning retrieval-augmented generation (RAG) systems.
NirDiamant/RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG)...
RUC-NLPIR/FlashRAG
⚡FlashRAG: A Python Toolkit for Efficient RAG Research (WWW2025 Resource)
gomate-community/TrustRAG
TrustRAG:The RAG Framework within Reliable input,Trusted output