MosaicRAG Search Engine Framework

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Authors: Felix Holz, Daniel Scharf, Alexander Nussbaumer
Cited by: 0

Abstract

MosaicRAG is a framework that enables developers of search applications to build their own Retrieval-Augmented Generation (RAG) search engine. MosaicRAG uses search results coming from Mosaic or Chroma and allows to define a sequence of RAG processes (e.g. summarisation, re-ranking, chat) on retrieved search results. Such sequences can be stored as search engines for further use. Together with Mosaic it can be used as an out-of-the-box search application or as an underlying technology to create more complex applications based on the index data retrieved from the Open Web Index (OWI) of the OpenWebSearch.EU project. Mosaic is a generic search application that makes index slices searchable that have been retrieved from the Open Web Index of the OpenWebSearch.eu project. Index slices are small or medium sized indices containing web documents related to a certain topic or for a particular purpose. These slices contain various metadata, such as geo-coordinates, topics, and genres of the web documents. More information can be found on https://doi.org/10.5281/zenodo.13790237 The software package (two zip files) contains all source files, as well as build and start scripts. A readme file describes the package, installation, and usage in detail.

Fields of Study & Subjects

Information Retrieval and Search Behavior Topic Modeling Recommender Systems and Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
25 February 2026
Language
EN