retrieval

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read

OpenKB: Open LLM Knowledge Base

SimpleMem: Efficient Lifelong Memory for LLM Agents — Text & Multimodal

MTEB: State-of-the-art evaluation of embeddings across languages and modalities

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

Open-source inference server and production cluster for all the models your agent needs.

User Profile-Based Long-Term Memory for AI Chatbot Applications.

Apache Lucene.NET is an open-source full-text search library written in C#, ported from the Apache Lucene project.

A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

Fast BM25 search in Python, powered by Numpy and Numba

The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis

Open CLI for integrating AI search, recommendation, and conversational retrieval into agent systems and business systems

An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"

Rust library for generating vector embeddings and reranking locally!

Parsing-free RAG supported by VLMs

Epsilla is a high performance Vector Database Management System

SGPT: GPT Sentence Embeddings for Semantic Search

Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.

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

[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"

Grounded search engine (i.e. with source reference) based on LLM / ChatGPT / OpenAI API. It supports web search, file content search etc.

Generative Representational Instruction Tuning

🔥 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.

The retrieval layer for production AI systems. Lightning-fast (<10ms) search without vector databases. Built for browser, edge, on-device, and cloud.

Easy-to-Use RAG Framework; CCF AIOps International Challenge 2024 Top3 Solution; CCF AIOps 国际挑战赛 2024 季军方案

~97% token reduction for AI coding sessions — zero deps, 33 languages, MCP server

Use ArXiv ChatGuru to talk to research papers. This app uses LangChain, OpenAI, Streamlit, and Redis as a vector database/semantic cache.

Retrieve, Read and LinK: Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget (ACL 2024)