MauroAndretta/WikiRag
WikiRag is a Retrieval-Augmented Generation (RAG) system designed for question answering, it reduces hallucination thanks to the RAG architecture. It leverages Wikipedia content as a knowledge base.
This tool helps researchers, students, and curious individuals quickly get answers to factual questions by searching Wikipedia and, if needed, the broader web. You input a question in natural language, and it provides a concise, accurate answer, leveraging a vast knowledge base to avoid common AI inaccuracies. Anyone who frequently needs to extract specific, reliable information from Wikipedia will find this useful.
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Use this if you need to quickly find accurate answers to specific questions based on Wikipedia's content, with the added benefit of web search for broader context.
Not ideal if you need to summarize or analyze highly specialized documents, proprietary data, or content that is not publicly available on Wikipedia or the general web.
Stars
10
Forks
2
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Aug 27, 2024
Commits (30d)
0
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