AnswerDotAI/rerankers

Health v2 · maintenance only

Adoption not part of the score

1629 stars · 104 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A lightweight, dependency-free Python library providing a unified API for using all common reranking and cross-encoder models. It lets developers swap between different reranking architectures (cross-encoders, LLM-based rankers, ColBERT, API rerankers) with a single handful of calls.

Use cases

• rerank search results with a cross-encoder
• add a reranker to my RAG pipeline
• compare different reranking models with one API
• use RankGPT or ColBERT rerankers in Python
• reorder retrieved documents by relevance to a query
• unified interface for reranking models

When to choose

• you want to experiment with or swap reranking models without rewriting pipeline code
• you need a minimal-dependency library that fits into existing retrieval pipelines
• you want support for many reranker architectures including LLM-based, late-interaction, and API rerankers

When to avoid

• you need a single highly-optimized reranker with advanced tuning options specific to one architecture
• you need production-grade guarantees - the project describes itself as beta
• your stack is not Python

Facets

library · maturity active

machine-learning nlp search-engine rag machine-learning python cross-platform reranking cross-encoder unified-api information-retrieval lightweight natural-language-processing search retrieval-augmented-generation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="AnswerDotAI/rerankers")