Open SourceRAG1k
rerankers
One tiny Python API for every reranking model and method.
rerankers is a lightweight library from AnswerDotAI that provides a single unified interface over many reranking approaches: cross-encoders, ColBERT-style late interaction, T5-based rerankers, LLM rerankers, and hosted reranking APIs. It lets you swap reranker implementations behind one consistent call, so improving RAG relevance does not require rewriting integration code. It is notable for standardizing the otherwise fragmented reranking ecosystem.
Repository
AnswerDotAI/rerankersLanguage
PythonWhat you'd build with it
- Adding a reranking stage to a RAG pipeline to reorder retrieved chunks for better answer quality
- A/B testing different reranker models behind one API without changing surrounding code
- Combining cheap vector recall with a stronger cross-encoder or LLM reranker for two-stage retrieval
Tags
rerankingretrievalrag