sparse-retrieval

SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.

A Python Search Engine for Humans 🥸

Unified Learned Sparse Retrieval Framework

🚀 Engram-PEFT: An unofficial implementation of DeepSeek Engram. Inject high-capacity conditional memory into LLMs via sparse retrieval PEFT without increasing inference FLOPs / DeepSeek Engram 架构的非官方实现。通过参数高效微调 (PEFT) 为大语言模型注入超大规模条件记忆，支持稀疏更新且不增加推理开销。

SPRINT Toolkit helps you evaluate diverse neural sparse models easily using a single click on any IR dataset.

Fast search index for SPLADE sparse retrieval models implemented in Python using Numpy and Numba

Lite weight wrapper for the independent implementation of SPLADE++ models for search & retrieval pipelines. Models and Library created by Prithivi Da, For PRs and Collaboration checkout the readme.

Semantic search in one SQLite file. No model, no server at query time.

Provides a minimal PyTorch implementation of SPLADE

Optimised BAAI/bge-m3 serving with dense + sparse + ColBERT embeddings, async dynamic batching and pipeline GPU inference

SPLADE (Sparse Lexical AnD Expansion) model fine-tuned for Portuguese text retrieval. Based on BERTimbau and trained on Portuguese question-answering datasets.

Python code to train SPLADE sparse retrieval models based on BERT-Tiny (4M) and BERT-Mini (11M) by distilling a Cross-Encoder on the MSMARCO dataset

AI-native long-term memory for Hermes Agent with AES-256-GCM encryption at rest, dense HNSW ANN, sparse and exact-text recall, metadata/range filters, and MinHash dedup, backed by an embedded or multi-client server columnar SQL database with 35 language bindings.

JEV-inspired typed runtime decisions over long-horizon PSG: reusable overnight encoding, sparse retrieval, and Choice/Noul/Score probabilities.

miniCOIL EN-ES: bilingual English/Spanish sparse retrieval (BM25 + learned concept blocks)

A local RAG assistant that will answer LLM security questions using retrieved OWASP documentation

Benchmarked RAG pipeline over 150 arXiv ML papers — compares BGE, MiniLM, MPNet, and BM25 across chunk sizes with MRR, Faithfulness, and Answer Relevance metrics. Powered by FAISS and Gemini.

This is the GitHub repository for the paper "A Systematic Cross-domain Evaluation of Document Retrievers".

OctoVector AI is a high-performance RAG system that combines dense and sparse retrieval with fusion and cross-encoder reranking to deliver precise, context-aware answers.

Demo for SenTrEv python package