farhad-dalirani/Collection-LLM-RAG
Collection-LLM-RAG is a Retrieval-Augmented Generation (RAG) application designed to explore collections of web articles and PDF files, such as conference papers.
This tool helps researchers, analysts, or anyone working with dense information quickly get answers from large collections of web articles or PDF files, like conference papers or internal documentation. You provide a set of documents, organize them into custom collections, and then ask questions in plain language. The tool returns accurate, context-specific answers grounded in your provided sources, helping you avoid misinformation and saving time searching through countless pages.
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Use this if you need to extract specific information or insights from a defined body of knowledge, like a set of research papers, legal documents, or industry reports, without relying solely on general internet searches or the static knowledge of a general-purpose AI.
Not ideal if your primary need is general knowledge retrieval from the entire internet, or if you prefer a simpler search engine interface without the ability to upload and query custom document collections.
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Language
Python
License
MIT
Category
Last pushed
Feb 27, 2025
Commits (30d)
0
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