Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face

TL;DR

Spacerini is a versatile, open-source tool that simplifies the creation and deployment of interactive search engines by integrating Pyserini and Hugging Face, making advanced IR models accessible to a broader audience.

Contribution

It introduces a plug-and-play framework that combines Pyserini and Hugging Face, enabling easy construction and deployment of state-of-the-art search engines for diverse users.

Findings

Demonstrated 13 different search engines for various use cases.

Facilitated qualitative analysis of training corpora.

Enhanced accessibility of advanced IR models.

Abstract

We present Spacerini, a tool that integrates the Pyserini toolkit for reproducible information retrieval research with Hugging Face to enable the seamless construction and deployment of interactive search engines. Spacerini makes state-of-the-art sparse and dense retrieval models more accessible to non-IR practitioners while minimizing deployment effort. This is useful for NLP researchers who want to better understand and validate their research by performing qualitative analyses of training corpora, for IR researchers who want to demonstrate new retrieval models integrated into the growing Pyserini ecosystem, and for third parties reproducing the work of other researchers. Spacerini is open source and includes utilities for loading, preprocessing, indexing, and deploying search engines locally and remotely. We demonstrate a portfolio of 13 search engines created with Spacerini for different use cases.