Reranking Microservice¶

The Reranking Microservice, fueled by reranking models, stands as a straightforward yet immensely potent tool for semantic search. When provided with a query and a collection of documents, reranking swiftly indexes the documents based on their semantic relevance to the query, arranging them from most to least pertinent. This microservice significantly enhances overall accuracy. In a text retrieval system, either a dense embedding model or a sparse lexical search index is often employed to retrieve relevant text documents based on the input. However, a reranking model can further refine this process by rearranging potential candidates into a final, optimized order.

Flow Chart

🛠️ Features¶

rerank on retrieved documents: Perform reranking on the given documents using reranking models together with query.

⚙️ Implementation¶

Utilizing Reranking with fastRAG¶

For additional information, please refer to this README

Utilizing Reranking with Mosec¶

For additional information, please refer to this README

Utilizing Reranking with TEI¶

For additional information, please refer to this README

Utilizing Reranking with VideoQnA¶

For additional information, please refer to this README