FlexRAG and RAGLAB

FlexRAG
59
Established
RAGLAB
43
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 14/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 17/25
Stars: 235
Forks: 22
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 310
Forks: 35
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
No risk flags
Stale 6m No Package No Dependents

About FlexRAG

ictnlp/FlexRAG

FlexRAG: A RAG Framework for Information Retrieval and Generation.

This is a tool for AI researchers and developers who are building Retrieval-Augmented Generation (RAG) systems. It helps quickly reproduce, develop, and evaluate RAG systems, taking various data types like text, images, and web content as input and producing enhanced generative AI models. It's designed for those who need to experiment with different RAG approaches and share their findings efficiently.

AI research NLP engineering generative AI development information retrieval systems machine learning experimentation

About RAGLAB

fate-ubw/RAGLAB

[EMNLP 2024: Demo Oral] RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation

This project helps researchers and developers evaluate and compare different Retrieval-Augmented Generation (RAG) algorithms for large language models. It takes in various RAG algorithms and benchmark datasets, then outputs comprehensive evaluation results. It is ideal for AI researchers, NLP scientists, and machine learning engineers who need to understand, reproduce, and extend state-of-the-art RAG techniques.

AI research NLP development Generative AI Language model evaluation Information retrieval

Related comparisons

FlexRAG and RAG_Techniques FlexRAG and fed-rag FlexRAG and FlashRAG FlexRAG and RAGHub FlexRAG and MiniRAG FlexRAG and TrustRAG

Scores updated daily from GitHub, PyPI, and npm data. How scores work