Reranking Python Packages

mteb

MTEB: Massive Text Embedding Benchmark

flashrank

Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.

mxbai-rerank

Crispy reranking models by Mixedbread

qwen3-embed

Lightweight Qwen3 text embedding and reranking via ONNX Runtime and GGUF

knowledge-rag

Drop docs, search instantly from Claude Code — 12 MCP tools, 20 format parsers, hybrid search + reranking. Zero servers, zero API keys, 100% local.

byaldi

Use late-interaction multi-modal models such as ColPali in just a few lines of code.

vera-ai

Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ranges, and symbol metadata. Built in Rust.

mixedbread-ai

mixedbread ai python sdk

rankops

Rank fusion and reranking

raglite

🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL

ranksmith

A fast-fail Python package for LLM-based document reranking with Azure OpenAI, RankGPT, PRP, and TourRank-r.

chunkrank

Model-aware text chunking and answer re-ranking for LLM pipelines. Automatically adapts chunk size to tokenizer and context window, then consolidates and ranks answers across chunks.

symrank

🐍📦 High-performance cosine similarity ranking for Retrieval-Augmented Generation (RAG) pipelines.

lemonade-python-sdk

A clean interface for interacting with the Lemonade LLM server

langformers

🚀 Unified NLP Pipelines for Language Models

pyllmsearch

Querying local documents, powered by LLM

langchain-localai

Langchain integration package with LocalAI. It provides embeddings and reranker support

rankify

🔥 Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation 🔥. Our toolkit integrates 40 pre-retrieved benchmark datasets and supports 7+ retrieval techniques, 24+ state-of-the-art Reranking models, and multiple RAG methods.

rankflow

Visualize and evaluate rank evolution across retrieval steps - rankflow plots, retrieval metrics, and pipeline comparison for RAG.

ferrex

Local-first MCP memory server for AI agents

useb

Heterogenous, Task- and Domain-Specific Benchmark for Unsupervised Sentence Embeddings used in the TSDAE paper.