DataScienceUIBK/Rankify

RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking.

Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

Retrieval and Retrieval-augmented LLMs

A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data

A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.

🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL

A Python framework for performing information retrieval experiments, building on http://terrier.org/

Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.

Generic rag framework to apply the power of LLMs on any given dataset