faerber-lab/RAGentA
Repository for the SIGIR LiveRAG challenge: "RAGentA: Multi-Agent Retrieval-Augmented Generation for Attributed Question Answering"
This tool helps researchers, analysts, or anyone needing reliable information from large document collections. You input a question and a collection of documents, and it generates a trustworthy answer with citations, ensuring factual accuracy and relevance. It's designed for users who need to confidently extract precise information from extensive textual data.
No commits in the last 6 months.
Use this if you need to generate highly accurate and thoroughly cited answers to complex questions by drawing information from a large set of documents, ensuring the answer is fully grounded in the provided text.
Not ideal if you need a simple chatbot for general knowledge queries or if your primary goal is creative text generation rather than factual answer extraction from specific sources.
Stars
19
Forks
1
Language
Python
License
BSD-3-Clause
Category
Last pushed
Jul 10, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/faerber-lab/RAGentA"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepsense-ai/ragbits
Building blocks for rapid development of GenAI applications
infiniflow/ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses...
GiovanniPasq/agentic-rag-for-dummies
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
truefoundry/cognita
RAG (Retrieval Augmented Generation) Framework for building modular, open source applications...
vectara/py-vectara-agentic
A python library for creating AI assistants with Vectara, using Agentic RAG